food bank research

• Open access
• Published: 22 April 2021

The impact of novel and traditional food bank approaches on food insecurity: a longitudinal study in Ottawa, Canada

• Anita Rizvi 1 ,
• Rania Wasfi 1 , 2 ,
• Aganeta Enns 1 &
• Elizabeth Kristjansson 1  

BMC Public Health volume  21 , Article number:  771 ( 2021 ) Cite this article

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A Correction to this article was published on 19 May 2021

This article has been updated

Food insecurity is strongly associated with poor mental and physical health, especially with chronic diseases. Food banks have become the primary long-term solution to addressing food insecurity. Traditionally, food banks provide assistance in the form of pre-packed hampers based on the food supplies on hand, such that the food items often do not meet the recipients’ cultural, religious or medical requirements. Recently, new approaches have been implemented by food banks, including choice models of food selection, additional onsite programming, and integrating food banks within Community Resource Centres.

This study examined changes in food security and physical and mental health, at four time points over 18 months at eleven food banks in Ottawa, Ontario, Canada. The participants – people who accessed these food banks – were surveyed using the Household Food Security Survey Module (HFSSM) and the Short-Form Health Survey Version 2 (SF-12). Statistical analyses included: pairwise paired t-tests between the mean perceived physical and mental health scores across the four waves of data collection, and longitudinal mixed effects regression models to understand how food security changed over time.

The majority of people who were food insecure at baseline remained food insecure at the 18-month follow-up, although there was a small downward trend in the proportion of people in the severely food insecure category. Conversely, there was a small but significant increase in the mean perceived mental health score at the 18-month follow-up compared to baseline. We found significant reductions in food insecurity for people who accessed food banks that offered a Choice model of food distribution and food banks that were integrated within Community Resource Centres.

Conclusions

Food banks offer some relief of food insecurity but they don’t eliminate the problem. In this study, reductions in food insecurity were associated with food banks that offered a Choice model and those that were integrated within a Community Resource Centre. There was a slight improvement in perceived mental health at the 18-month time point; however, moderately and severely food insecure participants still had much lower perceived mental health than the general population.

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Introduction

Household food insecurity, defined as the inadequate or insecure access to food due to financial constraints, is a growing health problem in Canada that adversely affects mental, physical, and social health, and strains our healthcare system [ 1 , 2 ]. The magnitude of the problem is alarming considering that in 2017–2018, one in eight households in Canada faced food insecurity, which translates into nearly 4.4 million people, including more than 1.2 million children. The number of people living in food-insecure households in 2017–2018 constitutes the highest rate since national monitoring began in 2007 [ 2 ].

Past research has highlighted the many negative health consequences associated with food insecurity [ 3 , 4 , 5 ], including a multitude of chronic conditions, such as arthritis, back problems, hypertension, diabetes, and cardiovascular disease [ 6 , 7 , 8 , 9 ]. Additionally, adults with mobility impairments are inordinately affected by food insecurity [ 10 ]. Food insecurity likewise has an enduring effect on children’s wellbeing, with studies linking the exposure to food insecurity at an early age with increased risk of developing asthma, depression, and suicidal ideation in adolescence and early adulthood [ 11 , 12 , 13 ].

Food insecurity has been associated with nutritional vulnerability. In Canada, adults in food-insecure households reported lower dietary intake of energy, macronutrients and micronutrients in comparison to their food secure counterparts; adolescents who were food insecure also reported some nutritional deficits [ 14 ]. People living in food insecure households reported limited social support and poorer social cohesion in their neighbourhoods [ 15 , 16 ] compared to food secure households.

Food banks emerged in Canada in the early 1980’s as a short-term measure to ameliorate a surge in food insecurity due to job losses after a downturn in the oil industry and the subsequent economic recession [ 17 ]. The number of visits to Canadian food banks has been climbing since then, with 1,084,386 visits reported across the Canadian Food Bank Network in March 2019 [ 18 , 19 ]. In the absence of comprehensive government policies, food banks have continued to propagate, and these agencies are now the first line of response to the issue of hunger and food insecurity in Canada [ 20 ].

With respect to terminology, food banks in Canada serve the functions of both “food pantries” – the local not-for-profit agencies that provide food assistance, in the form of unprepared grocery items, directly to people in need – as well as the central warehouses which are referred to as food banks in the United States, and which distribute food to various types of front-line food programs [ 21 ]. It should be noted that the terms “food bank” and “food pantry” may carry different meanings in an international context, for example, the term “food pantry” in the United Kingdom refers to a “membership scheme” which allows members to obtain a limited number of food items, typically redistributed surplus stock from supermarkets, for a nominal weekly fee [ 22 ]. Food banks in Canada offer food assistance free of charge, but the frequency of visits is usually limited, typically to once per month, with the goal of providing a few days’ worth of groceries during each visit. In this paper, we use the term “food bank” to refer specifically to local agencies that provide unprepared food items at no cost directly to individuals, with one exception being the Ottawa Food Bank (OFB) organization, which operates a central warehouse facility that serves member agencies in the Ottawa area.

Each food bank that participated in this study serves a specific geographic area of Ottawa. To receive assistance, people do not need referrals from other agencies; however, the food banks may require people to provide documents during their first visit to verify their identity, address, and income. Proof of address may need to be presented at subsequent visits to confirm residence within the area that a food bank serves.

Despite the escalation of food bank use in recent decades, food banks have limited capacity to alleviate the needs of those who seek assistance [ 23 ]. Furthermore, although conventional food bank models may be linked with short-term improvement in household food security and health [ 24 ], these agencies have a limited capacity to offer food of adequate quality and variety due to their reliance on donations [ 23 ]. Furthermore, people report experiencing stigma, embarrassment, frustration and shame when accessing a food bank, because they often receive food that is left over/unsold, high in sugar and fat, and past the best-before date [ 25 , 26 ].

Change is taking place in the ways that food banks provide food assistance [ 27 ]. Contemporary approaches to improving services include increasing the quality and choice of food provisions, establishing safe and welcoming spaces, and providing greater integration with health care and health promotion [ 20 ]. Recent studies have examined the potential benefits of Choice models [ 28 , 29 , 30 ], in which people visiting food banks can select food items from displays, as in a grocery store, instead of receiving pre-packed hampers. Research is also emerging on food banks which offer an array of services such as nutrition education, life-skills training, and health and social support services, in addition to food assistance [ 31 , 32 , 33 , 34 , 35 ]; however, the existing research documents a significant heterogeneity in the types of supplementary services offered.

Although the number of food banks in Canada has been proliferating for more than four decades, there is a dearth of studies describing and evaluating both traditional strategies as well as the newer, more novel approaches [ 27 , 29 , 36 , 37 ]. To help fill this gap, we collaborated with the Ottawa Food Bank (OFB) to plan and carry out this study, which was conducted in collaboration with eleven community food banks within the OFB network.

There is also a gap in the literature regarding the health of people who access food banks, which are a specific sub-population of food insecure people in general. Studies have found that less than one quarter of people in food insecure households in Canada rely on food banks, and that the people who do access food banks are not a representative subset of the food insecure population, having substantially lower incomes and higher rates of receiving social assistance benefits than food insecure people who do not access food banks [ 38 , 39 ]. We found five quantitative studies that examined the health of people who relied on food banks in Europe and North America [ 24 , 40 , 41 , 42 , 43 ]; however, none of these studies were of a longitudinal nature with participants who accessed food banks on a long-term basis. All the other literature we reviewed on household food insecurity and health relied on data from cross-sectional population surveys.

The main aim of this study is to model changes in food insecurity over time and identify their associations with different types of food bank approaches offered in Ottawa. We also report on food bank use and examine change in physical and mental health over the 18-month period.

Study design

This observational prospective study was conducted from November 2017 until December 2019 and involved repeated surveys of the same cohort of participants over four time points. A baseline survey and three follow-up surveys were conducted at intervals of approximately 6 months, such that there was a total span of approximately 18 months between the baseline survey and the final survey for each participant. (The complete surveys are included in a companion article by Enns [ 44 ]).

This study was originally planned to last 2 years, with a fourth follow-up survey at the 24-month time-point; however, due to significant attrition and many surveys from participants being returned incomplete, we chose to end the study after the 18-month follow up, which still provided an adequate sample size to yield statistically meaningful results (details are provided in the Sample Size and Attrition section below). The decision to omit the 24-month time point was also based on receiving feedback from some participants who expressed annoyance over being contacted repeatedly for the follow-up surveys. We determined that an 18-month follow-up would still contribute novel longitudinal evidence as this time period is longer than any previous longitudinal studies of food bank access and trajectories of food insecurity.

Participants and setting

The participants in this study were people who accessed community food banks in Ottawa, Ontario, Canada. Eleven of twenty-six community food banks within the Ottawa Food Bank (OFB) network were included in this study. The eleven food banks were identified and recruited in collaboration with the OFB, which is the central collection and distribution hub of the network. Partners at the OFB distributed an email to community food bank coordinators within their network that included study information and an invitation to directly contact a member of the University of Ottawa research team (by phone or email) if they were interested in taking part and facilitating data collection at their food bank. The research team member who received correspondence from interested food bank coordinators then invited coordinators to in-person meetings to provide further study information, answer questions, and gather information on food bank operations. Each food bank that participated in this study serves a specific geographic area of Ottawa and provides food to 400 or more people per month.

The participants were recruited in the food bank waiting areas. People were approached and given information about the study, and if they were interested in participating, they were asked to read a consent form. People who were 18 years of age or older and comfortable conversing in English or French were eligible to participate. Those people who provided signed consent were then given several options for completing the initial baseline survey: (i) filling out a paper version, (ii) completing an electronic version on a tablet, (iii) completing the survey in private with a research assistant who would read the questions out, or (iv) completing an online version at home, using the Internet URL provided in a handout.

The six-, twelve- and eighteen-month follow-up surveys were completed over the phone, or by email with a link to access an online version, or by regular mail using a printed paper version which could be returned in a supplied, postage-paid envelope.

As an incentive to join the study, participants in the baseline survey were invited to enter a draw for one of eight $50 grocery store gift cards at the time of consenting to take part in the study. Participants who indicated that they would like to enter the draw were also asked for their preferred contact method and information and were assigned a random ID number. At the end of the baseline data collection periods, IDs were entered into a random number generator to select the eight winners, who received the gift cards by mail. Everyone who participated in the six-month follow-up survey received a $5 grocery store gift card by mail, and everyone who participated in the twelve- and eighteen-month follow-ups received a $10 grocery store gift card by mail for each survey. The amount was increased from $5 to $10 to encourage retention due to the significant attrition which was observed at the six-month follow-up.

Survey questionnaire design

The survey questionnaire sought to measure the participants’ demographics, duration and frequency of food bank access, level of food insecurity, and self-reported physical health and mental health.

Food security was measured using the Household Food Security Survey Module (HFSSM), an 18-item measure used in national population health surveys in Canada and includes questions on household food security situations over a 12-month period. The HFSSM is based on the Core Food Security Module developed by the United States Department of Agriculture to be a benchmark measure of household food security, which has been used and validated widely in North America [ 45 ].

Perceived mental and physical health were measured using the 12-item version of the Short-Form Health Survey Version 2 (SF-12) [ 46 ]. The SF-12 is a widely used measure of self-reported health. It has demonstrated good reliability and validity among diverse populations [ 47 ]. The SF-12v2 has also been shown to be a valid outcome indicator among marginalized or vulnerable populations [ 47 , 48 ]. The Physical and Mental Health Composite Scores (PCS and MCS) are continuous variables measured on a scale from 0 to 100, where 0 indicates poor perceived health, and 100 indicates excellent perceived health.

Statistical analysis

We assessed descriptive statistics to demonstrate demographic characteristics of the study sample. We report the means and standard deviations of participants’ age  and perceived physical and mental health scores at the four waves of data collection. We also summarized the proportions of people with different gender identities, education; monthly income; marital status; whether participants were born in Canada or abroad; their ethnicity; marital status and whether or not they live with dependents.

To measure change in physical and mental health across the four waves of data collection, we performed pairwise paired t-tests between the scores of the physical and mental health of the within-subject factor (i.e., across waves of data collection). P -values were adjusted using the Bonferroni multiple testing correction method [ 49 ].

To examine food bank use in each of the four waves of data collection, we asked about and reported frequency of use of food banks in the 3 months preceding each survey.

Modelling food insecurity

We conducted longitudinal mixed effects regression models [ 50 ] to understand how food security changed during the four waves of data collection and to understand their associations with different types of food bank approaches offered in Ottawa. Participants were nested within the four time points of data collection.

Main outcome measure

We used both categorical and continuous scales as each of them serve a particular purpose in our analysis.

As explained in detail by Carlson et al. [ 51 ] and Bickel et al. [ 45 ], the Food Security Scale is a continuous linear scale, developed to measure the degree of severity of food insecurity/hunger experienced by a household in terms of a single numerical value on a ten-point scale (i.e., from 1 to 10, where 1 indicates food secure and 10 indicates severely food insecure). We used this scale in the regression models to show the precise change in food security levels, and associations with novel and traditional food bank approaches.

We also decided to show food security as a categorical variable for descriptive purposes, providing a small set of categories, each one representing a meaningful range of severity of food insecurity. Thus, scores were categorized as: 0 = food secure, 1 = marginal food insecurity, 2 = moderate food insecurity, or 3 = severe food insecurity. Categories were created using established criteria for scoring the HFSSM [ 51 ]; the cuts offs were developed by Bickel et al. [ 45 ].

Main variables of interest

The main variables of interest (the independent variables / IVs) were the food banking models used in the eleven participating food banks:

Food bank type : integrated within a Community Resource Centre (CRC IV): a dichotomous variable: 0 = not CRC, 1 = is a CRC.

Choice distribution model (Choice IV): a dichotomous variable: 0 = Hamper model, 1 = Choice model.

Additional onsite programming (Programs IV): a dichotomous variable: 0 = no, 1 = yes.

We conducted a Chi-squared test between the CRC and Choice models as well as the CRC and Program models to examine their independence.

Six of the eleven food banks offered additional onsite programming, which included food-related programs such as community kitchens, as well as support for finding employment or affordable housing, or applying for social assistance.

Three of the food banks were situated within Community Resource Centres (CRCs) which provide wraparound services, so that emergency food assistance, community programs, and health and social services were all offered in one place. In comparison, the additional onsite programming model is limited to helping people to find and access such services elsewhere, as the food bank itself is not integrated within a CRC.

Four of the food banks offered food assistance via a choice or ‘grocery shopping’ model, whereas the other seven provided food supplies in the form of a food hamper, with some offering choice of certain items by way of a food options list. In the choice model as referred to in this paper, people are invited to walk around a food display area, typically with a volunteer, and choose food items that they and their family need and want. Choice model food banks may place limits on the number of food items collected per person and per food category.

Food bank characteristics were not mutually exclusive and food banks could possess more than one approach. However, based on the results of our contingency analysis (shown further below) and the aim of this study, each food banking approach was analysed separately.

Individual covariates included in the analyses were: age at baseline, gender, monthly household income, having dependents in the household or not, ethnicity, whether born in Canada or not, married/living with a partner or not, perceived physical health and perceived mental health.

Sample size and attrition

We used the Generalized Linear Mixed Model Power and Sample Size (GLIMMPSE) software ( https://glimmpse.samplesizeshop.org ) to estimate the sufficient sample size needed to model food security score, using a multi-level mixed effect model with repeated measures across four waves of data collection. The sufficient sample size estimated to detect a target power of 0.8 with a Type I error rate of 0.05 was 229 participants. Our sample size used in the analysis was 369 participants with 1040 observations across the 4 waves of data collection, which was sufficient to detect a meaningful effect.

Seven hundred and thirty participants were recruited in total at baseline. Participants who did not respond to at least two of the four data collection waves were excluded from the analysis, resulting in a sample of 401 participants at baseline.

Our colleague Enns [ 44 ] performed a statistical comparison of all the recruited participants and those who completed the six-month follow-up and did not find any significant differences in their demographic characteristics; i.e., the participants who were excluded at baseline or who did not complete the six-month survey were not significantly different from the follow-up participants, in terms of education, gender, ethnicity, being born in Canada, marital status or having dependents.

In the current study, an attrition analysis was conducted for each of the three follow-ups, to understand whether people who did not participate in some waves of data collection dropped out at random or whether significant differences in sample characteristics existed between people who answered the survey and those who were missing in each wave. No significant differences were found between baseline sample characteristics of the group that answered the survey and those who dropped out in each wave of data collection in terms of age p -value (attrition W2 = 0.1073, attrition W3 = 0.2582, attrition W4 = 0.4173), perceived physical health p -value (attrition W2 = 0.5273, attrition W3 = 0.5188, attrition W4 = 0.8808), mental health p -value (attrition W2 = 0.2912, attrition W3 = 0.3114, attrition W4 = 0.8417), and food security level p -value (attrition W2 = 0.7674, attrition W3 = 0.5373, attrition W4 = 0.8808). These results suggest that participants dropped out at random.

In the four waves of data collection for the eighteen-month study, there were: 401 participants who responded with complete data in wave 1; 320 in wave 2; 311 in wave 3; and 271 in wave 4. Some participants skipped a wave, and then returned to answer in a following wave. In total, 189 participants answered all four waves of data collection, 125 participants answered three waves of surveys, and 85 participants answered the two waves of surveys. Across all waves, there were a total of 1303 valid responses, and 301 missing ones.

We imputed missing data only for time-constant variables that were reported by participants in one wave of data collection, but missing in others; for example, if in one wave of data collection a participant did not report their age, gender, education, ethnicity, whether they were born in Canada or not, data was imputed from their answers from another wave. However, for all variables that can change over time – for example food security, income, marital status, perceived mental and physical health – missing data was not imputed.

In longitudinal data analysis using mixed effects regression models, two points in time can be used in the analysis without the need to impute missing data, if the missing data is “missing completely at random”; hence, the analysis provides valid inferences, with no need to impute, delete, or weight [ 50 ].

Data preparation, cleaning and analyses were conducted in Stata 13.1 and R Studio 4.0.1.

Descriptive statistics

Sample characteristics in each wave of data collection.

At baseline, 401 participants answered a set of demographic questions. As shown in Table  1 , the majority of the sample at baseline were: born in Canada (68.8%), white (53.4%), women (50.9%), not married nor living with a partner (64.3%), with no dependents (52.1%), and had some (i.e., not completed) college education or less (61.8%). Around 79.8% of participants’ household income in the month preceding the baseline survey was less than $2400 (i.e., less than $28,800 per year). Missing data for each variable is indicated in Table 1 . Across all waves of data collection, the largest share of participants in each demographic category was found to be: women; people born in Canada; not married nor living with a partner; with no dependents; and who had less than a college degree.

Food security

As show in Fig.  1 below, when comparing the overall change in food security from the first wave of data collection to the last wave, the proportion of people who were food secure increased, and the proportion of people that were severely food insecure decreased. Over the eighteen-month time span, there was an increase of seven percentage points (from 11 to 18%) in the proportion of participants in the food secure category, an increase of five percentage points (from 34 to 39%) in the moderately food insecure category, whereas there was an overall decrease of 14 percentage points (from 39 to 25%) in the severely food insecure category.

Proportion of Participants in Each Wave by Food Security Level

Frequency of food Bank use in the previous 3 months

Overall, the percentage of people who visited food banks three or more times in the preceding 3 months decreased over time. In the first wave of data collection, 52.1% of people who used the food banks used them three or more times in the previous 3 months, compared to 50.5% in wave 2, 42.4% in wave 3, and 40.6% in wave 4.

In the first wave of data collection, the majority of participants (52.1%) used food banks three or more times in the preceding 3 months, followed by those who visited the food banks once (23.2%) or twice (20.4%). The largest proportion of participants visited the food banks three or more times in all waves of data collection, compared to the proportions of participants that made either one or two visits in the preceding 3 months.

Perceived physical and mental health

The mean perceived physical health scores ranged from 45.2 (SD 9.76) in wave 1 to 43.5 (SD 11.2) in wave 4, while the mean perceived mental health scores ranged from 40.2 (SD 11.3) in wave 1 to 41.6 (SD 11.9) in wave 4 (Table 1 ).

No significant difference between the mean perceived physical and mental health by waves of data collection were detected, with the exception of a slight increase of 1.4 in the mean perceived mental health score between wave 1 and wave 4 ( p  < 0.001).

Descriptive statistics by levels of food security

Table  2 summarizes the demographic characteristics of participants over the four waves of data collection for each food security category. As shown in the table, participants who accessed the food banks were between the ages of 18 and 80 years old. There was an age gradient in food security: the mean age at baseline of people who were severely food insecure (42.2 years, SD 12.0) was 5 years lower than those who were food secure (47.2 years, SD 14.9). Across all four waves of data collection, there were 688 responses from women and 511 from men. Across food insecurity categories, the largest difference between men (35.4%) and women (57.6%) was in the moderately food insecure category.

Overall, out of 1111 responses on household income, 931 responses (83.8%) indicated an income of CAN$1799 or less per month. As well, an income gradient was found between people in different food security categories: among participants who were severely food insecure, only 5.1% had a monthly household income of CAN$2400 or more, compared to 10.9% of participants who were food secure.

There was a significant relationship between food security level and average perceived physical and mental health: those with higher levels of food security had higher levels of perceived health (Table 2 ). The mean physical health scores ranged from 47.2 for those who were food secure, to 42.5 for those who were severely food insecure. Similarly, the mean mental health scores ranged from 48.8 to 35.8 for the same categories.

Contingency analysis

The Chi-squared test between CRC and Choice model was not significant ( p -value = 0.7), which indicates that the variables are correlated. The same finding ( p -value = 0.63) was found between the CRC and additional programming models, indicating that these variables are also correlated. As a result, we did not put the three variables in one model to predict food security scores, but instead tested each variable separately.

Longitudinal regression models

We modeled the trajectory of the food security index, a continuous variable from one to ten where one is the most food secure, and ten is the most insecure. The results are summarized in Table  3 .

The mixed effect regression model (a growth curve model/trajectory model) revealed that with every year increase in age at baseline, the food security score decreased by 0.03 units (i.e., food insecurity decreased with age). Being a woman was related to a decrease of 0.38 units in the food insecurity score compared to being a man. Being not born in Canada was related to 0.57 units decrease in the food insecurity score. Increased income was related to a decrease in food insecurity: having a monthly income of $1800 or more was related to 0.42 units of decreased food insecurity. Every 10 points increase in the physical health index was related to 0.4 units in decreased food insecurity; similarly, every 10 points increase in mental health index, was related to 0.5 units in decreased food insecurity.

After the first wave of data collection, food insecurity decreased over time by 0.78 units in wave 2, 0.98 units in wave 3, and 1.09 units in wave 4 (all compared to baseline), as shown in Table 3 .

For participants who went to a food bank connected with a CRC, the food insecurity score was lower by 0.59 units compared to those who went to a regular food bank. For participants who went to a choice-model food bank, the food insecurity score was 0.53 units less than for those who went to hamper-model food banks. Additional onsite programming was not associated with any decrease or increase in food security. Having not accessed a food bank in the preceding 3 months was related to a higher likelihood of being food insecure, with the greatest increase observed for those who were marginally food insecure.

Having a higher age at baseline, being not born in Canada, married or living with a partner, with higher income, and higher perceived physical and mental health scores were associated with less food insecurity. For all other variables, the impact of the variable on the different food insecurity categories was not statistically significant. In the CRC model, the Intraclass correlation (rho) shows that 53% of the variance was explained by between-participants variance, as opposed to 56% in the Choice model, and 51% in the Program model.

In this study, 271 out of 401 participants (67.6%) responded during the final eighteen-month follow-up. Part of the observed attrition could be explained by findings from a large-scale longitudinal study conducted in Vancouver, Canada [ 52 ]. These researchers found that the majority of people who access food banks could be characterized as “short-term, transitional users who visited food banks a handful of times and disengaged after a few weeks or months of use,” and that the 9% who accessed food banks over a long-term accounted for 65% of all food bank visits. Thus, a significant number of the participants in our study at baseline may have only needed food assistance over a short term. We were often unable to contact participants for follow-ups because the contact information they provided was no longer valid (e.g., telephone was out of service and mailing address had changed), so it is impossible to say what changed in their life circumstances and whether they still had a need for food assistance.

As described above in the Methods section, those who participated in the 6-month follow-up were given a $5 grocery store gift card, and for the subsequent follow-ups the amount was increased to $10 to encourage retention due to the 20% attrition seen at 6 months. The increased incentive appears to have been successful since the incremental attrition rates at the 12- and 18-month time points were lower at 2% and 10%, respectively.

In terms of income, which is necessary for purchasing food, the results fit with what we would expect to find, as participants with the lowest income were more heavily represented in the severely food insecure category. Conversely, participants with CAD$1800 or more in monthly income were more heavily represented in the food secure category.

Food insecurity was higher for participants who were not married and not living with a partner. This may be because people who are married or live with a partner share major expenses like rent, and therefore may have more money for food if they both have incomes. As well, if one partner loses some or all of their income, the other partner’s income may ‘cushion’ the economic impact. Lastly, single parents working in the service industry find it problematic to work varied hours for relatively low wages, and also schedule paid childcare, so they may not be able to earn sufficient income to maintain their food security [ 53 ].

In terms of gender, the majority of participants in our study were women (683 total responses in all four waves by women compared to 502 responses by men). The greatest disparity was in the moderately food insecure category, in which there were 38.5% fewer responses from men than from women. Our regression analysis found that food insecurity among women in our study was 0.38 points lower on the 10-point food insecurity scale (where a lower score means less food insecurity).

The higher proportion of women participants in our study may have been due to an unintended gender bias in the recruitment process, or the results above (lower number of men, but with higher food insecurity than women) may also reflect sociocultural attitudes that men should behave stoically and not ask for help except in dire circumstances. A 2012 study in Montréal, Canada involved in-depth interviews with 22 men experiencing poverty, followed by six discussion groups to validate the results, which suggested that “asking for help can be diametrically opposed to traditional masculine roles” and that, when facing a serious problem, men will ask for help only as a last resort [ 54 ].

There were notable differences between the demographics of the participants in this study and those of the general population of Ottawa, based on the 2016 Census figures from Statistics Canada. In terms of education, the census showed that 63.7% of people in Ottawa had a postsecondary certificate, diploma, or degree [ 55 ], compared to 29.4% of the participants in the baseline survey. Our result closely matches that of a 2005 study in Toronto, Canada, which found that 27.4% of people accessing food banks in Toronto had completed college or university [ 56 ]; however, our result is very different from a US study using national data which found that less than 8% of people that received assistance from food pantries between 2002 and 2014 had a college degree (US meaning, similar to university) [ 57 ]. The Toronto study found a drastic increase – from 12% in 1995 to 53% in 2005 – in the percentage of immigrants with some college or university education among immigrants who received assistance from food banks, so the higher numbers of educated people accessing food banks in Canada, versus the United States, may reflect Canadian immigration policy.

We found that participants born in Canada reported significantly higher food insecurity than those who were not born in Canada. This may also be due to Canadian immigration policies, which require people coming to Canada as immigrants to be skilled or well educated or to possess a prescribed amount of liquid assets [ 58 ].

In terms of income, only 3% of the participants at baseline reported a monthly household income of $2400 ($28,800 per year) or more, compared to 86% of all residents in the city of Ottawa having an annual household income of $30,000 or more in 2016 [ 55 ]. Although 17% of the participants in our study did not provide income information, the results still indicate a huge income gap between people who visit food banks and other people in Ottawa.

In terms of ethnicity, 9% of the participants in our study were Indigenous (First nations, Metis, or Inuit), which is almost double the 4.6% of people in all of Ottawa who are Indigenous [ 55 ]. This result echoes the urgent need to address the inequity in food security faced by off-reserve Indigenous people in Canada [ 59 ].

Consistent with previous research that found poorer health was correlated with food insecurity [ 3 , 4 , 5 , 7 ], we found the mean perceived physical and mental health scores to be below the general population mean of 50 points [ 46 ] for all of our participants. Moreover, perceived physical and mental health scores both showed gradients across food insecurity levels, such that health scores decreased as the severity of food insecurity increased. Participants in the food secure category scored closest to 50 points, with means of 47.2 for perceived physical health and 48.8 for perceived mental health, suggesting that their health was close to that of the general population.

While previous research has also found evidence of gradients in mental and physical health according to the severity of food insecurity [ 60 , 61 , 62 , 63 , 64 , 65 ], those studies depended on national health surveys (i.e., the Canadian Community Health Survey, and the National Health and Nutrition Examination Survey in the U.S.) to obtain data on household food insecurity and did not focus specifically on people who access food banks. Other studies have found that less than one quarter of food insecure households in Canada relied on food banks, and that the people who do access food banks were not a representative subset of the food insecure population, having substantially lower incomes and higher rates of receiving social assistance benefits than food insecure people who had not accessed food banks [ 38 , 39 ]. As such, the examination of perceived physical and mental health in the current study relates to a unique subset of the food insecure population. Our finding that the largest proportions of participants across all waves were in the CAD$600–1199 bracket may reflect that many of the participants in our study received modest social assistance benefits as their source of income.

Physical health scores ranged from 47.2 for food secure participants to 42.5 for those who were severely food insecure. Mental health scores were even lower for moderately and severely food insecure participants at 39.6 and 35.8, respectively. Since the standard deviation (SD) of the SF-12 health scores is 10 points, obtaining mean results that are more than one SD below the average of 50 points is concerning. In comparison, another study [ 66 ] with a similar sample size of food insecure adults ( n  = 325) drawn from a population survey in the Lower Mississippi Delta in the United States, obtained mean physical and mental health scores of 45.7 and 46.5, respectively, using the SF-12 scales. The mean physical health score falls within the 47.2–42.5 range obtained in the current study; however, the mean mental health scores that we obtained were much lower (35.8–39.6, versus 46.5 in the US study), so this difference suggests poorer overall mental health for people who rely on food banks, compared to food insecure people in the general population. This is in consonance with previously cited research [ 38 , 39 ], which reported that people who access food banks are not a representative subset of all people who report being food insecure. It is also important to note that the physical health scores did not differ significantly between the four waves of data collection, and that the mental health scores showed a statistically significant, albeit slight improvement.

In this study, we didn’t analyse the associations between different food banking models and physical and mental health; however, due to the increasing prevalence of food banks using novel approaches to providing food assistance, we believe that future research to examine possible associations with health is certainly warranted.

The longitudinal reduction in food insecurity that we observed with food banks integrated in a Community Resource Centre is consistent with the findings of our colleague Enns [ 44 ] at the 6-month time point. The initial reduction in the mean food insecurity score was the most pronounced: 0.79 points out of 10 after 6 months, compared to a decrease of 0.99 points at 12 months and 1.09 points at 18 months (all compared to baseline). Although the consecutive decreases in the food insecurity scores seem to indicate further improvements at 12 and 18 months, the differences were not statistically significant, so larger studies would be needed to confirm if, in fact, there is a continued reduction in food security over time for those who access CRC-type food banks. In any case, the overall reduction in food insecurity that we observed for people who access CRC-type food banks is encouraging because they are also able to access the health and social services offered by CRCs when they visit the Centre for food assistance.

We also found a small but significant difference in food security according to the food distribution model of the food bank. Across all four waves of data collection, the proportions of participants were lower in the moderately and severely food insecure categories if they accessed food banks using the Choice model, compared to participants who visited food banks offering food hampers. Our regression analysis also showed that when food banks used the Choice model, longitudinal food insecurity was 0.53 less (on the 10-point scale) compared to food banks that used the hamper approach. This adds to the findings of the six-month follow-up by Enns [ 44 ], who reported a significant increase in fruit and vegetable consumption by people who accessed food banks that employed a Choice model of food distribution. The Choice model may be especially beneficial for those who must avoid certain foods for medical reasons (e.g., lactose intolerance, low sugar diets for diabetics, gluten allergy) or for cultural/religious reasons (e.g., avoiding processed foods that contain animal-based ingredients such as gelatin and broth, which are not considered kosher or halal). Studies have also shown that people prefer to choose food items that they need (based on personal or cultural preferences or dietary requirements) and not have to throw away food they dislike or cannot use if they receive a pre-packed box [ 67 , 68 ]. The benefit of the choice approach may therefore be threefold: lower observed levels of food insecurity when the Choice model is offered, lower levels of waste, and conferring more dignity on the consumer. However, one drawback of the Choice model perceived by people who accessed choice food pantries was longer line-ups [ 67 ].

Finally, we believe it is important to consider that the food security level measured in this study is the self-reported level of participants while accessing food banks (whereas most of the reviewed literature provides food insecurity data primarily from people who do not rely on food banks). We found that 63.5% of participants who described themselves as food secure reported that they had visited a food bank two or more times in the previous 3 months (Table 2 ); since food banks provide only a few days’ worth of food, it appears that low levels of food insecurity may be temporarily eased by food banks. On the other hand, a more disconcerting observation is that 47.2% of participants in the severely food insecure category reported this level even after visiting a food bank three or more times in the previous 3 months. Similarly, 50.4% of participants in the moderately food insecure category reported that level after also visiting food banks three or more times in the previous 3 months. From these results we can see that food banks may temporarily alleviate food insecurity for some people, whereas many others remain moderately or severely food insecure.

Because household food insecurity is, by definition, due to financial constraints, our findings lend support to the need for public policy changes, such as increases in social support payments or implementing a guaranteed basic income, which several other studies have proposed [ 69 , 70 , 71 , 72 ]. In Canada and other high-income countries, food insecure people with insufficient incomes currently have to rely on a bureaucratic, costly, and stigmatizing ‘patchwork’ of social assistance programs administered by different levels of government; because of the shortcomings of existing social safety nets, many researchers have advocated specifically for a simplified guaranteed basic income as a more effective solution [ 73 , 74 , 75 , 76 ].

Limitations

There are several possible limitations to the findings of this study. First, since the analysis was restricted to one Canadian city with a high median household income – $86,451 per year in Ottawa in 2016, versus $70,336 across all of Canada [ 55 ] – it may not be representative of other physiographic regions in Canada or other countries.

Furthermore, participation was restricted to a convenience sample of English and French speaking adults; thus, some members of the population may be inadequately represented in the sample. Researchers approached participants to take part in the survey; as a result, there may have been bias due to self-selection of volunteers. Recall, acquiescence response and social desirability biases are all known to influence survey respondents [ 77 , 78 ]. Moreover, the data was collected several times over pre-established observation points in this longitudinal study; hence, we cannot account for circumstances occurring in between those time periods. Finally, although the present study analysed a diverse group of food banking models, it lacked a comparable sample, specifically one that was food insecure but did not access food banks. Without a control group, we cannot be sure that the results were not due to other factors (i.e., unobserved or unmeasured covariates).

This study addresses a gap in the evaluation of contemporary food assistance programs by providing current data on the associations between food insecurity and food banking approaches. This study also adds important evidence on the compromised physical and mental health of food insecure people who rely on food banks for assistance. The key strength of this study is that it helps to fill these gaps by providing longitudinal data, collected over 18 months, on patterns of food insecurity over time, and modelling the impact of different food bank approaches on food insecurity scores.

We found significant reductions in food insecurity for people who accessed food banks that offered a Choice model of food distribution and food banks that were integrated within Community Resource Centres. Although our results show a small improvement in food security overall, it is important to note that generally, most participants still reported moderate or severe food insecurity at the end of the 18-month study, indicating a clear need for an effective long-term solution such as a guaranteed income to provide financial stability for people facing food insecurity in Canada. One positive finding was that the mean perceived mental health score was slightly higher at the 18-month point compared to baseline, possibly due to the small improvement in food security. Since our results found poor self-reported health among the subset of food insecure people who access food banks, additional larger and longitudinal studies that explore and address the unique health concerns of this population are vitally needed.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Change history

19 may 2021.

A Correction to this paper has been published: https://doi.org/10.1186/s12889-021-10981-9

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Acknowledgements

We thank the Maple Leaf Food Security Centre for their generous funding of this project. This project was conducted with the collaboration of the Ottawa Food Bank and with the staff and volunteers of the participating food banks. The authors would like to thank the participants and collaborative food bank partners who dedicated their time to support this study. RW was affiliated with University of Ottawa at the time the analysis was conducted. She is currently affiliated with the Public Health Agency of Canada. The content and views expressed in this article are those of the authors and do not necessarily reflect those of the Government of Canada”.

This work was supported by a Maple Leaf Centre for Action on Food Security Learning Hub grant.

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Conceptualization (AE, EK); Data curation (RW, AE, AR); Formal analysis (RW); Funding acquisition (AE, EK); Investigation (EK, AE, AR); Methodology (AE, EK, RW); Project administration (EK, AR, AE); Resources (AR, AE); Software (RW); Supervision (EK); Validation (all authors); Visualization (AR, RW); Roles/Writing - original draft (AR, RW); Writing - review & editing (all authors). The authors read and approved the final manuscript.

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The original version of this article was revised as it contained a numerical error in the Results section, subheading Descriptive statistics/ Frequency of food Bank use in the previous 3 months in the last sentence of the first paragraph..

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Rizvi, A., Wasfi, R., Enns, A. et al. The impact of novel and traditional food bank approaches on food insecurity: a longitudinal study in Ottawa, Canada. BMC Public Health 21 , 771 (2021). https://doi.org/10.1186/s12889-021-10841-6

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Food pantry access worth billions nationally, study finds

By james dean, cornell chronicle.

A research collaboration between Cornell and the U.S. Department of Agriculture offers the first estimates of the economic value contributed by food pantries, and finds it is substantial – worth up to $1,000 annually to participating families and as much as $28 billion nationwide.

The totals underscore food bank systems’ important role in addressing food insecurity, a role that has grown during the pandemic and recent bouts of inflation, said David R. Just , the Susan Eckert Lynch Professor in Science and Business in the Charles H. Dyson School of Applied Economics and Management, part of the Cornell SC Johnson College of Business and the College of Agriculture and Life Sciences.

“Food pantries make a huge difference to the households they serve, for many representing a substantial portion of their income,” Just said. “This is important information for policymakers considering support for the national or local food banking system, like tax breaks for food donation, direct program support from USDA or other efforts.”

Just is the co-author of " What is Free Food Worth? A Nonmarket Valuation Approach to Estimating the Welfare Effects of Food Pantry Services ,” published Nov. 9 in the American Journal of Agricultural Economics. The lead author is Anne Byrne, Ph.D. ’21, a research agricultural economist at the USDA’s Economic Research Service . The team has collaborated on multiple investigations of private food assistance.

“Private food assistance, especially food banking, has grown in recent decades,” Byrne said. “These organizations have a unique position within the food system and a specific role in food access because they offer quick relief in the form of free groceries to a wide variety of people, typically with minimal administrative hurdles.”

Food banks and pantries served 51 million people in 2021, according to the nonprofit Feeding America . Despite their importance, the researchers said, their economic value to the individuals and households that they serve hasn’t been estimated using rigorous economic methods.

Determining that value is challenging, the researchers said, since food pantries provide food and services at no cost. In addition, the market value of food may not accurately capture its value to people who can’t afford to access markets.

Byrne and Just thought they could get at the question using travel costs, a novel application of a methodology long used to value assets like national parks – where the cost of visiting isn’t primarily an entry fee – based on costs incurred to make the trip. They calculated the cost of travel to and from food pantries as a measure of households’ “willingness to pay” for the food, considering the distance, duration and frequency of their trips.

“We know they would be willing to give up at least this amount for the food they obtain, which enables us to identify demand in terms of price – travel costs – and quantity – visits,” Just said.

The scholars analyzed 13 years of data (2005-17) from a northern Colorado food bank that in 2017 served 10% of Larimer County residents at locations in Fort Collins and Loveland.

The data set included millions of pantry visits representing about 45,000 households – a population with lower incomes and more racial and ethnic minorities than the county overall, according to census data. To calculate travel costs, the researchers used Google maps for walking and driving distances and times, AAA data for vehicle costs, and reported incomes or the Colorado minimum wage to determine the opportunity cost of the time trips required.

The result was an estimated value to families of $40 to $60 per trip to a food pantry, and of $600 to $1,000 per year based on typical annual visit frequencies, with values increasing or decreasing with travel costs.

Extrapolated nationally – based on 389 million visits reported by Feeding America’s 2014 Hunger in America Study – the first-of-their-kind estimates confirm that “food bank services collectively represent a sizeable share of the food landscape,” the researchers wrote. Their estimated value of $19 to $28 billion is more than double the sales by farmers markets in 2020, and a significant fraction of federal food stamp (SNAP) benefits that year worth $74.2 billion, according to the research.

“Without such an estimate it is difficult to know whether food pantries are a worthwhile investment from a public policy perspective,” Just said. “Given the great number of families touched by these services and the significant investment and volunteer hours given, it is important to document and measure the value they are contributing to our economy.”

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Data drives our work.

We conduct research to help member food banks thrive, to measure the effectiveness of food banking and new interventions, and to meaningfully contribute to important global conversations about hunger, food loss and waste, and other critical areas.

Ultimately, our evidence-based approach contributes to hunger alleviation and climate change mitigation by providing expertise, directing resources, sharing knowledge, and developing connections.

GFN research is used to:

• Track food banking globally as well as its contributions to the SDGs
• Measure the efficiency and effectiveness of food banks and their contributions to their communities
• Support Network members in their growth and development
• Guide GFN’s data-driven decision-making
• Advocate—and support Network members’ advocacy efforts—for system-wide changes that address the root causes of hunger, poverty, and food loss and waste

GFN’s research priorities are:

The effectiveness of the food bank model.

Food banking isn’t a “one size fits all” approach, and GFN research tracks the scope, breadth, and reach of food banking worldwide and measures its impact beyond hunger alleviation. Our research explores the diversity in food banking programs and the role of food banks in building stronger, healthier, more equitable communities.

Explore this research:

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Policy Research & Recommendations

GFN’s policy research creates recommendations that lead to wider food access and fewer instances of food loss and waste. A key partner in this work is the Harvard University School of Law Food Law and Policy Clinic. Together, we have developed the Global Food Donation Policy Atlas, which chronicles barriers to food donation worldwide and recommends solutions that reduce those barriers.

Explore the Global Food Donation Policy Atlas:

• Global Food Donation Policy Atlas
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Food Bank Surveys

In addition to global research and recommendations, GFN conducts Network research to understand, inform, and improve food bank operations. This helps scale and accelerate food bank development and also informs GFN’s technical assistance to food banks and outreach to partners.

Our surveys cover a range of topics, including:

• This annual survey provides a comprehensive look at the accomplishments of member food banks, including people served, food and grocery product distributed, and the scope and reach of partner organizations. The results inform all of the work we do, including grantmaking, technical assistance, fundraising, and building public awareness.
• Pulse surveys are conducted regularly to track the changing needs that member food banks are observing in their communities.
• These annual surveys collect anonymous feedback from food bank executive directors on the quality and efficacy of GFN’s services. The surveys guide GFN’s strategic priorities as they relate to member food banks.

The Global Food Donation Policy Atlas—a unique, innovative partnership

The Global Food Donation Policy Atlas is the first collaborative research project to examine the state of worldwide food donation laws and policies and provide country-specific policy recommendations for strengthening food recovery efforts. This research is coupled with technical assistance for GFN members that helps food banks advocate for stronger donation policies in their home country. The Atlas is a partnership between Harvard Law School’s Food Law and Policy Clinic and The Global FoodBanking Network.  

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Research Improves Food Bank Effectiveness, Equity

For Immediate Release

Researchers at North Carolina State University have developed new computer models to improve the ability of food banks to feed as many people as possible, as equitably as possible, while reducing food waste.

Food banks serve as networks, collecting food from many different sources and distributing it to local agencies that then share it with people in need. The researchers, who launched this project eight years ago, quickly realized that there is a great deal of uncertainty in food bank operations. Supply and demand both fluctuate – which researchers anticipated.

“But we found that capacity – the ability of local agencies to collect, transport, store and distribute food – was also variable,” says Julie Ivy, a professor of industrial and systems engineering at NC State and co-author of a paper on the work. “These agencies are often small and rely heavily on volunteers.

“Our goal was to develop models that account for uncertainty in a food bank network’s capacity and can help food banks distribute food efficiently and equitably – ensuring all of the regions served by the food bank are treated fairly – while minimizing food waste.”

“Our work here was conducted with the Food Bank of Central and Eastern North Carolina, but these are challenges that are common to most, if not all, food banks, as well as for national food collection and distribution networks, such as Feeding America,” says Irem Sengul Orgut, a former Ph.D. student at NC State and lead author of the paper. Orgut now works for Lenovo.

For this project, the researchers developed two models, which can be used in conjunction with each other. The first model uses historical data to establish ranges of how much capacity each county has. The model then uses those ranges, in conjunction with each county’s needs, to determine how food supplies should be distributed.

The second model takes into account each county’s need and capacity – or ability to distribute food in a timely way – to try to feed as many people as possible, as equitably as possible, across counties before the food goes bad.

“Some counties have agencies with more volunteers, more refrigerated storage, or better transportation resources, allowing them to distribute more food before it goes bad,” says Reha Uzsoy, a co-author of the paper and Clifton A. Anderson Distinguished Professor in NC State’s Edward P. Fitts Department of Industrial & Systems Engineering. “But if those counties get all the food, it wouldn’t be equitable – other counties would suffer. The second model aims to find the best possible balance of those two factors.”

“We now have these two models, which are pretty complex,” Ivy says. “We’re currently working with the Los Angeles Regional Food Bank and the Food Bank of Central and Eastern North Carolina to find ways to implement the models that are user friendly for food bank staff and volunteers.”

Specifically, the researchers are working with North Carolina A&T University and a company called Performigence to develop software that can be used to expand these models and put them into use. That work is being done with support from the National Science Foundation, under grant number 1718672 , titled PFI:BIC – Flexible, Equitable, Efficient, and Effective Distribution (FEEED).

“This work is relevant to food banks, broadly, but the fundamental issues are also relevant to disaster relief efforts,” Ivy says. “Really, any situation in which there is a scarce resource, a need for equity, and a robust suite of challenges in distributing the resource. As a result, this may also be of interest to disaster relief researchers.”

The paper, “ Robust Optimization Approaches for the Equitable and Effective Distribution of Donated Food ,” is published in the European Journal of Operational Research . The paper was co-authored by Charlie Hale of the Food Bank of Central and Eastern North Carolina. The work was done with support from the National Science Foundation under grants CMMI-1000018 and CMMI-1000828 .

Note to Editors: The study abstract follows.

“Robust Optimization Approaches for the Equitable and Effective Distribution of Donated Food”

Authors : Irem Sengul Orgut, Julie S. Ivy and Reha Uzsoy, North Carolina State University; Charlie Hale, Food Bank of Central and Eastern North Carolina

Published : Feb. 17, European Journal of Operations Research

DOI : 10.1016/j.ejor.2018.02.017

Abstract: Motivated by our eight-year partnership with a local food bank, we present two robust optimization models to support the equitable and effective distribution of donated food over the food bank’s service area. Our first model addresses uncertainty in the amount of donated food counties can effectively receive and distribute, which depends on local factors such as budget and workforce that are unknown to the food bank. Assuming that the capacity of each county varies within a range, the model seeks to maximize total food distribution while enforcing a user-specified level of robustness. Our second model uses robust optimization in a nontraditional manner, treating the upper bound on the level of allowed inequity as an uncertain parameter and limiting total deviation from a perfectly equitable distribution over all counties while maximizing total food shipment. We derive structural properties of both models and develop efficient exact solution algorithms. We illustrate our models using historical data obtained from our food bank partner, summarize the policy implications of our results and examine the impact of uncertainty on outcomes and decision making.

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A systematic literature review of food banks’ supply chain operations with a focus on optimization models

Journal of Humanitarian Logistics and Supply Chain Management

ISSN : 2042-6747

Article publication date: 26 January 2023

Issue publication date: 9 February 2023

Food banks play an increasingly important role in society by mitigating hunger and helping needy people; however, research aimed at improving food bank operations is limited.

Design/methodology/approach

This systematic review used Web of Science and Scopus as search engines, which are extensive databases in Operations Research and Management Science. Ninety-five articles regarding food bank operations were deeply analyzed to contribute to this literature review.

Through a systematic literature review, this paper identifies the challenges faced by food banks from an operations management perspective and positions the scientific contributions proposed to address these challenges.

Originality/value

This study makes three main contributions to the current literature. First, this study provides new researchers with an overview of the key features of food bank operations. Second, this study identifies and classifies the proposed optimization models to support food bank managers with decision-making. Finally, this study discusses the challenges of food bank operations and proposes promising future research avenues.

• Food pantries
• Food distribution
• Food insecurity
• Supply chain
• Nonprofit organizations
• Optimization

Rivera, A.F. , Smith, N.R. and Ruiz, A. (2023), "A systematic literature review of food banks’ supply chain operations with a focus on optimization models", Journal of Humanitarian Logistics and Supply Chain Management , Vol. 13 No. 1, pp. 10-25. https://doi.org/10.1108/JHLSCM-09-2021-0087

Emerald Publishing Limited

Copyright © 2022, Adrian Fernando Rivera, Neale R. Smith and Angel Ruiz.

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Families worldwide struggle to collect enough food with basic nutrition for themselves and their children daily. Around 20% of the world’s population survives with less than US$1.25 a day ( Desai et al. , 2016 ), and more than 10% of the world’s population does not have access to sufficient food. This leads to numerous problems worldwide; disease, poverty, hunger and malnutrition affect many lives ( Reihaneh and Ghoniem, 2018 ).

Poverty and food insecurity have constantly increased worldwide. Food insecurity is a grave issue, particularly in developing nations, defined as “a socioeconomic inability to obtain appropriate quality food in sufficient amounts” ( Trzaskowska et al. , 2020 ). Food insecurity arises when people have restricted access to proper food, hindering a vigorous life ( Davis et al. , 2016 ).

Several nonprofit organizations have been established to reduce food insecurity, playing a progressive part in conveying essential services to defenseless and underserved individuals in society ( Balcik et al. , 2014 ). Food banks are one type of nonprofit organization contributing the most to reducing food insecurity. Food banks are “humanitarian aid organizations that collect, organize and deliver food to nonprofit member agencies and to individuals to help alleviate society’s hunger problem” ( Ataseven et al. , 2018 ). Recently, the number of people suffering from malnourishment is estimated to be at its highest point, and food banks have been vital for the less fortunate ( Tarasuk et al. , 2020 ).

Paradoxically, around 20%–30% of the food produced is wasted annually across the supply chain ( Michelini et al. , 2018 ), leading to two concurrent social issues: food insecurity and food waste. Food banks play a key role in reducing wasted food problems by connecting the abundance in supply with the requests of needy people ( Eisenhandler and Tzur, 2019a ). We refer to Sengul Orgut et al. (2016a ) for a discussion of food bank activities and Schneider (2013) for the political, legal, social and logistical barriers and incentives related to this topic.

Many authors emphasize the importance of the social problems facing food banks. Thompson et al. (2018) report on a qualitative study of the health and well-being challenges of food poverty and food banks. Puddephatt et al. (2020) prove that food insecurity creates health issues. Chen et al. (2018) encourage cash donations by helping people visualize the impact of their contributions. Finally, Waltz et al. (2018) explore barriers to equal food access and current approaches to overcoming social, economic and physical barriers.

In countries with good infrastructure, food banks assist people in need by gathering donations that they later redistribute appropriately and impartially ( Sengul Orgut et al. , 2016a ). Donations are not regular enough to satisfy demand; hence, food banks must deal with the conflict between being equitable (working so that each individual in need has the same likelihood of being served) and being effective (serving the maximum number of people in need). This is a typical problem for nonprofit organizations ( Sengul Orgut et al. , 2016a ; Solak et al. , 2014 ).

to provide essential knowledge for new researchers;

to identify and classify the concrete decisions, pursued objectives and the major operations management problems faced by food banks;

to describe the optimization approaches in the extant literature to address the identified problems; and

to recognize emerging research directions in the field.

To this end, we conducted a systematic literature review on studies related to food bank operation, focusing on optimization models. Unlike Mahmoudi et al. (2022) , who recently reviewed decision support models addressing food aid supply chains, our work differs in the research scope and framework used to classify and position the relevant studies. First, Mahmoudi et al. (2022) reviewed works related to food aid management with no restriction on the organizational structure managing the aid. However, our research focuses exclusively on food banks. By narrowing our research, we observed particularities and objectives in food banks, which are unobserved in food aid distribution networks and worth in-depth analysis. Furthermore, this narrower focus sheds light on how food bank operations differ from humanitarian aid distribution problems. Second, Mahmoudi et al. (2022) classified papers according to the methodology they proposed; those proposing optimization models were further classified into strategic, tactical and operational decision-making problems. In contrast, our analysis adopts a more comprehensive framework grounded on the operations handled by managers at the three stages of the food banks’ supply chain (supply, food banks operations and demand). Given these differences, only 20 references are studied by the reviews. Given that this review contains more than 60 references, we believe that its content differs significantly and complements Mahmoudi et al. (2022) .

The rest of this paper is organized as follows. Section 2 provides the research methodology and describes the criteria for selecting the articles used in this systematic literature review. Section 3 presents and analyses the results. Section 4 includes a discussion and presents directions for further research, whereas Section 5 concludes the paper.

2. Research methodology

This systematic review used the search engines Web of Science and Scopus, which are extensive databases in Operations Research and Management Science (OR/MS). This section describes the criteria used to select the articles, followed by an explanation of the article selection process and the steps to complete the data extraction.

2.1 Databases search

Web of Science: The keywords “foodbank” OR “food bank” OR “food pantries” were searched, as shown.

the expression only appears in the article title, abstract or keywords;

only peer-reviewed articles (excluding book chapters, reviews, notes and editorials); and

regarding the subject area, the following were excluded:

Public environmental, occupational health;

Nutrition dietetics; and

Agricultural economics policy.

Scopus: The keywords {foodbanks} OR {food banks} OR {food pantries} were searched, as shown.

in the subject area, the following were excluded:

Agricultural and biological sciences;

Environmental science; and

Arts and humanities.

A total of 231 articles were found in this database.

We obtained 386 distinct articles from both databases to review. Table 1 summarizes the search criteria.

2.2 Final article selection

include a model or discussion on food bank operations, food banks supply chain or analytics applied to food banks;

include information related to food bank operations;

include information on donations; and

include general information, such as nutritional needs, volunteering and food insecurity.

We also required the papers to be written in English.

A manual selection process was performed on the 386 articles, and we read the title and abstract of each article. If the article met the inclusion criteria above, the paper was downloaded, otherwise it was omitted. Two reviewers were consulted to determine a paper’s relevance when we encountered any uncertainty.

After applying this filter, 86 research articles remained. We checked the content of these papers by reading them fully, keeping only those that fully met the inclusion criteria. This left a total of 52 articles.

The last procedure was to delve into the references cited by the most recent selected articles (we arbitrarily limited ourselves to those published in 2021) to find other articles that might contribute to this literature review.

A total of 9 additional articles were identified from the references, totaling 61 articles. Data retrieved from the databases were exported to Mendeley to continue the data extraction and synthesis.

2.3 Data extraction and analysis

We constructed a table to continue the data extraction, which included the following: title, authors, year of publication, keywords, abstract, summary, problem identification, the main topic and country. This helped us identify papers that included an optimization model contributing to Section 3.3. The rest of the papers were analyzed to contribute to other sections regarding important issues in food bank operations.

A second table was constructed with papers that included optimization models. A deeper analysis was performed for these papers to identify their goals and position the characteristics of the problems they studied concerning the analysis framework proposed in Section 3.3. A total of 18 articles that included optimization models were deeply analyzed.

3. Results and analysis

3.1 statistics.

We examined some facts to establish the importance attributed to food banks. Figure 1 illustrates the total number of articles per year in both databases. The number of related articles published annually is growing, indicating that the interest in this topic from researchers in the OR/MS area has increased. Nevertheless, the highest number of publications per year (19 articles published in 2021) is low compared to other research topics. For instance, one of the most recent systematic literature reviews that focused on mathematical models of humanitarian logistics ( Hezam and Nayeem, 2021 ) reports a rise in published papers from around 100 in 2010 to 200 in 2019.

Figure 2 shows the countries each article addresses, providing an idea of which countries have more food bank related research. Of all publications, 64% were from the UK and the USA; thus, there is a gap in an opportunity to study other countries’ operations to understand the most affected factors.

Finally, Tables 2 and 3 shed some light on where articles on food banks were published, providing complementary information on the publication data. On the one hand, Table 2 reports the journals that published more than three relevant papers, providing their categories according to Clarivate’s Journal Citation Reports. Table 2 confirms that food banks received significant attention from journals in the social sciences, particularly journals in the social issues category.

On the other hand, Table 3 reports the journals in MS/OR that published relevant articles. Overall, articles published in OR/MS journals constitute 26.3% of the papers produced by the database search.

3.2 Food banks’ supply chains and the differences with respect to commercial supply chains

This section introduces food banks’ supply chain operations and discusses their main differences regarding commercial supply chains.

3.2.1 Food banks’ supply chains

A food bank supply chain includes three main actors: donors, food banks and agencies. The term agency is used to describe entities (usually non-for-profit entities) that receive the food and distribute it to individuals.

The flows of food that food banks handle can be organized in various ways, as discussed in the following paragraphs. Figure 3 illustrates some common structures. Donors offer products to food banks on unknown dates and amounts ( Fianu and Davis, 2018 ). In some cases, donations are performed directly at the food bank, the case for network A in Figure 3 ; however, in most cases, the food bank organizes the transportation of donations. In this case, visits to several donors are planned to reduce transport costs, as illustrated by network B . Food banks also receive financial donations that allow them to acquire more goods, particularly supplies that are not commonly donated.

At the depots, food banks verify the donations’ quality, and depending on the agencies’ profile and needs, they assign quantities to be delivered or prepare kits that, once delivered, help cover the needs of an individual or a family for a given period (e.g. a week). Because demand is usually higher than donations, food banks must evaluate methods for being as fair and equitable as possible, simultaneously maximizing the efficiency of the distribution operations.

As per the distribution, the food bank sometimes aids each agency directly (network A ), but agencies are often grouped and visited in routes to maximize transport efficiency (network B ). It is also possible to introduce food distribution points to share the distribution effort between the banks and the agencies (network C ). Finally, it is also possible to organize mixed pickup and delivery routes, as discussed later, visiting donors and agencies (network D ). Although mixed routes improve transport efficiency, they are more challenging to plan and manage.

Donations represent most of the food supplied by food banks. Because supply is generally lower than demand (Gómez-Pantoja et al. , 2020), hard choices must be made daily to decide who receives aid, the types of goods provided and the amount supplied. To this end, optimization models might help design effective food collection and delivery strategies ( Davis et al. , 2014 ).

A large part of food banks’ activities is based on the assistance of volunteers. As do Paço and Agostinho (2012) mention, volunteers are not paid and have highly valued opportunities competing for their time, attention and money; thus, agencies need to understand what motivates volunteers to donate their time to food banks. Furthermore, De Boeck et al. (2017) suggest that working with volunteers with inadequate training in food safety and other relevant knowledge on food logistics may generate bottlenecks and barriers during interactions with food donors and handling perishable food products. Why people volunteer has been studied but remains an unresolved question beyond this study’s scope.

Kim (2015) explains that “one good governance model cannot always be applied to all countries because actors, networks and institutions embedded in unique contexts have their own endogenous properties.” Therefore, structures differing from those described in the previous paragraphs can emerge to cope with specific regional peculiarities. For instance, the food banks in North Korea differ from those observed in occidental countries in several critical aspects, as reported in Table 4 .

Challenging situations usually lead to the emergence of new, better-adapted structures. For instance, Ogazon et al. (2022) discuss how food banks should adapt to cope with the consequences of a sudden event, such as a natural or human-made disaster. The recent COVID-19 pandemic exacerbated the food insecurity problem worldwide, so food banks multiplied their efforts to maintain service and adapt to the challenging situation. Blackmon et al. (2021) describe how, during the COVID-19 outbreak, the BOX program launched by the United States Department of Agriculture (USDA) aimed at purchasing fresh produce, dairy and meat directly from farmers and packaging them into boxes to be delivered directly to agencies and people in need. Thus, food banks became “virtual intermediaries” to coordinate supply and demand between suppliers and agencies.

Therefore, it can be concluded that the structure and governance of food banks are impacted by the region’s social, economic and governmental characteristics. As discussed later, an emerging research stream examines food banks’ growing role in facing extraordinary events, such as natural disasters or other disruptive situations ( Roberts et al. , 2021 ; Ogazon et al. , 2022 ).

3.2.2 Differences between commercial and food bank supply chains

As explained, food bank supply chains can be divided into supply (donors), inventory and distribution management (food banks) and demand (agencies). Commercial supply chains include an additional area: the transformation or manufacturing process (production). Generally, food banks do not perform transformation or conservation of goods; they work as intermediaries to get donations to those in need. Furthermore, four essential aspects distance food banks from commercial supply chains at the distribution and demand levels. First, the uncertainty of incoming food necessitates appropriate levels of internal and external integration ( Ataseven et al. , 2020 ). Second, food banks operate at a time-safe distance, indicating that the early expiration of donated goods limits a food bank’s operating range. Third, dependency on the donated items restricts the choice concerning the types, quantity and nutritional composition of the products offered to beneficiaries, in sharp contrast with the almost unlimited choices offered by commercial supply chains. Finally, because food bank supply chains cannot consider meeting demand as an objective (as supply is continuously lower than demand), the main objective is to distribute donations as impartially as possible in proportion to demand.

Once they collect donations, the food banks aim to distribute food to agencies effectively and equitably. Fairness or equity is one of the distinct topics of decision-making in humanitarian operations and a key issue that impacts all food banks’ operations. The notion of fairness in humanitarian aid distribution has been recently discussed ( Holguín-Veras et al. , 2013 ; Anaya-Arenas et al. , 2014 ; Özdamar and Ertem, 2015 ; Gutjahr and Nolz, 2016 ). While there is no agreement on a definition or metric, Fernandes et al. (2016) proposed a structure as a basis for developing a performance measurement system for humanitarian logistics.

The uncertainty in donations and demand is one of the biggest challenges for food banks’ operational decisions. In contrast, commercial supply chains are mainly concerned with managing time adequately; only the demand side harbors uncertainty, which can often be predictable ( Hindle and Vidgen, 2018 ).

most of the supplies are donations; and

the workforce comprises mainly volunteers, meaning that food banks’ cost structure and improvement opportunities are somewhat different from those in commercial supply chains.

3.3 Analysis of the contributions to food banks’ supply chain operations

We describe the food bank’s supply chain to propose a simple framework to classify and analyze the reviewed papers according to their contributions to the chain’s three building blocks: supply, food banks and demand (see Figure 4 ). The following subsections present the topics contributed by the papers or the decisions discussed for each stage. Finally, we added a fourth stream of contributions that – rooting on the growing business analytics methods and tools – map supply and demand to emphasize the geographical/regional perspective of food assistance networks.

3.3.1 Supply

Uncertainty in the total available supply is one obstacle encountered in food bank operations. Food banks depend on donations, either in the form of goods or cash, made by individual donors, private sector organizations and governmental agencies. Food donations are uncertain in the frequency and the quantity provided, their prediction is challenging ( Alkaabneh et al. , 2021 ), and management constitutes a daily challenge to satisfy the needy population’s demand ( Davis et al. , 2016 ). For instance, Brock and Davis (2015) report that collecting donations from supermarkets is planned without knowing if the food items are available and the quantity is sufficient. This is why initiatives to map the potential existing unused or wasted resources, such as those described in Bech-Larsen et al. (2019) and Hollander et al. (2020) , are vital for maximizing food banks’ supply.

Martins et al. (2019) suggested that donations from private organizations and individuals, key sources of supply for food banks, are more unpredictable than governmental and public funding and donations; they are stable and fundamental for steady operations.

Some challenges derived from the uncertainty of supply extend from the capacity of donors to grant supplies, the diverse number of provisions given, and the reception of spontaneous and sometimes even undesirable donations ( Martins et al. , 2019 ). For these reasons, methods of considering donations differ between authors. Some propose activities to increase donations (donations management), others try to predict the donations received and others consider donations a given parameter.

Donations management : Research into interventions designed to increase or affect contributions to food banks is limited. Farrimond and Leland (2006) confirmed that the location of signs and donation containers next to specific items in supermarkets increases donations of targeted products. Ahire and Pekgün (2018) explained that Harvest Hope Food Bank organizes promotional events and fundraising initiatives to increase food and dollar donations. They propose an integer programming optimization model to plan the optimal number of annual events of each kind to maximize the number of meals served using food and dollar donations.

González-Torre and Coque (2016) studied the potential partnership between marketplaces (significant generators of organic food waste because they sell fresh food) and food banks that might reuse food surpluses. They proposed guidelines to facilitate better management of the food surpluses and estimate the potential volume of organic waste generated by marketplaces that food banks might save.

Regarding individuals’ donations, Bennett et al. (2021) examined the motivations and other factors that encourage individuals (as opposed to businesses) to donate to food banks in the UK.

Donations forecast : Donators usually do not provide accurate information regarding available items or quantities. This can negatively impact inventory management capabilities and cause unnecessary transportation costs. Because of this uncertainty, some authors have proposed models to estimate donations.

Brock and Davis (2015) and Nair et al. (2017) evaluated approximation methods to estimate food availability from various food providers. Brock and Davis (2015) studied food surplus estimation at supermarkets, proposing an artificial intelligence approach based on a multiple layer perceptron artificial neural network (MLP-NN), multiple linear regression and two naive estimates to approximate the average collection amount. The four approximation methods are evaluated in terms of their ability to estimate collection amounts in the next planning period. Their results suggest that the MLP-NN model produces the best approximations. The methods proposed in Nair et al. (2017) can also be used to anticipate a potential donation from a new donor that may appear in the network.

Davis et al. (2016) performed a numerical study to quantify the extent of uncertainty regarding the donor, product and supply chain structure. Several predictive models were developed to estimate in-kind donations, including clustering, exponentially weighted moving average (EWMA) and autoregressive integrated moving average. Their results recommend EWMA as the most accurate forecasting method.

Paul and Davis (2021) proposed a method to identify the supply behavior of donors and cluster them based on the frequency, quantity and type of food donated. Results showed the necessary behavioral attributes to classify donors and the best way to cluster donor data to improve the prediction model, where exponential smoothing provides the best estimations.

Donations modeling : Finally, most papers assume that demand is given as a known parameter or a probabilistic function of known parameters.

Most reviewed models, like Gómez-Pantoja et al. (2020), consider the supply as a given parameter or known constant; however, neglecting uncertainty in donations may or may not be acceptable depending on the considered context. Balcik et al. (2014) , Sengul Orgut et al. (2016b ), Eisenhandler and Tzur (2019a ) and Eisenhandler and Tzur (2019b ) addressed food collection and distribution problems where donation and demand amounts are unknown before collection or delivery. They all proposed deterministic models that assumed that the quantity of available food is known. To validate their deterministic assumption, they perform sensibility analysis on their results. Sengul Orgut et al. (2016b ) suggested that, because each agency must collect goods from the food bank, the supply is more related to the food bank’s specific characteristics, such as the available budget, transportation availability and storage capacity, than to the donations themselves. They performed numerical experiments to assess how the variability in the food banks’ receiving capacities affects the solution produced by the deterministic model. Similarly, Balcik et al. (2014) performed probabilistic sensitivity analyses to assess the effect on the models’ deterministic solutions arising from supply uncertainty.

Marthak et al. (2021) studied the prepositioning of food before the strike of a natural disaster, so donations vary according to the severity of the anticipated event by a fixed adjustment factor estimated from historical data analysis.

Finally, other authors model supply as random variables to capture the donation uncertainty. Fianu and Davis (2018) dealt with a single product, so uncertainty only concerns the available quantities at each donor. Stauffer et al. (2022) considered a set of products, so the uncertainty affects the available quantity of each product. Alkaabneh et al. (2021) also considered several products, modeling their quantity and quality (i.e. their nutritional value) as random exogenous variables beyond the food bank’s control.

In summary, food banks’ supply has received limited attention from research; however, contrary to commercial supply chains where demand is the primary source of variability, donations are highly uncertain and constitute one of the biggest challenges to ensuring a fair distribution of food, as confirmed in the following sections.

3.3.2 Food bank operations

Melo et al. (2009) defined supply chain management to be “the process of planning, implementing and controlling the operations of the supply chain in an efficient way,” whereas Hugos (2011) referred to logistics management as “a portion of SCM, that focuses on activities such as inventory management, distribution and procurement that are usually made on the boundaries of a single organization.” Our analysis of the reviewed papers confirmed that most fit better within the latter definition. Furthermore, while distribution is the dominant topic among the reviewed papers, a few focus on inventory management or, in a broader perspective, resource allocation. Only six papers consider network design, defined as the decisions concerning facilities’ location and capacity selection. From the six papers in network design, three study problems jointly decide the number and location of intermediate distribution sites and how they are fed. These joint decision problems are referred to as location-routing or location-transportation problems.

Finally, from the comparison with commercial supply chains, food banks’ supply chains are strongly concerned with resource allocation or how supplies are assigned to agencies or individuals in need. Indeed, most reviewed papers deal implicitly or explicitly with resource allocation problems. Consequently, before discussing this section’s main topics (network design, inventory management and distribution), the following paragraphs discuss the orientations and objectives guiding resource allocation in food banks’ operations.

3.3.2.1 Objectives guiding food banks’ resource allocation.

Although operations efficiency always remains a significant concern, food bank managers are mainly guided by principles of equity and effectiveness. Several papers focus on the nutritional utility of the delivered food. We now discuss these four concepts and how they are addressed in the reviewed papers.

Efficiency: According to Davis et al. (2014) , “while profit is not their objective, food banks, like other nonprofit organizations, must efficiently use their existing resources to best serve their communities.” To this end, operational costs must be minimized or, in other contexts, kept under budget constraints. Martins et al. (2019) included the fixed cost for supporting agencies and the cost for operating storage areas and handling products at food banks in their economic objective function. Islam and Ivy (2021) and Hasnain et al. (2021) included as operational costs the total cost of food bank operation and the cost of receiving and distributing food, computed using the quantity of distributed food, the distance covered and the per-mile cost. Operational costs may include different expenses depending on the context. For instance, Stauffer et al. (2022) included mobile pantries for food distribution. Their objective function includes their fixed cost of allocation and operating cost; however, most authors focus exclusively on transportation costs. Moreover, the total distance is usually considered a proxy for the transport costs. Works proposing location-transportation problems ( Solak et al. , 2014 ; Davis et al. , 2014 ; Reihaneh and Ghoniem, 2018 ) aim to minimize the number of facilities to distribute food. Then they seek to balance the distance traveled by the food bank’s vehicles to bring the food to drop sites and the distance charity agencies travel to grab the food at those drop points. Marthak et al. (2021) consider the cost related to prepositioning and distribution of food on the arrival of a natural event. These costs depend on the traveled distance and the transported quantity.

Finally, although some authors do not target cost or efficiency metrics as objectives, they either restrict the consumption of resources (e.g. by setting a bound on the length of routes) or impose budget constraints. For instance, Eisenhandler and Tzur (2019a , 2019b ) do not include the vehicle’s travel cost in their models; however, they limit the available budget for transportation. Furthermore, Gómez-Pantoja et al. (2020) impose a limit on the available budget to buy food products.

Equity: Most selected papers intend equity in food distribution as their primary goal. Equity is referred to as distributing goods in proportion to the needs, often estimated as the population living in poverty in an area. Still, reaching an equal distribution of food is challenging because of limited vehicle capacities or the time before the items spoil; hard decisions must be made in these cases. Different methods are used in the literature to address equity, including minimizing the difference between the maximum and minimum values, the variance, the coefficient of variation, the sum of absolute deviations, the maximum deviation or the mean absolute deviation ( Fianu and Davis, 2018 ). Minimizing these objectives can maximize equity, although they usually lead to different solutions. Fianu and Davis (2018) present a model that can assist food banks in distributing uncertain supplies equitably; they measure equity as a function of the pounds distributed per person in poverty (PPIP). They also use a benchmark proposed by their food bank partner, setting the target PPIP to 75 per year. Sengul Orgut et al. (2016b ) and Islam and Ivy (2021) incorporate equity in their models by imposing a user-specified upper bound on the absolute deviation of each agency from perfectly equitable distribution. Perfectly equitable distribution means that food donations are distributed to the agencies so that the total donated food allocated to an agency equals the fraction of the total poverty population assigned to that agency.

Effectiveness: Regarding effectiveness, food banks seek to distribute the greatest quantity of goods while wasting as little as possible. Effectiveness is also essential because waste provokes bad publicity and reduces future donations. Sengul Orgut et al. (2016b ) qualified distribution as effective if the amount of undistributed supply is minimized. This is easy to express in words, but all the issues surrounding food bank operations make this objective difficult to satisfy. Many factors affect food bank operations and considering all of them in one model is impossible. Stauffer et al. (2022) penalized the amount of undistributed food in their objective function. Sengul Orgut et al. (2016b ) minimized the amount of wasted food by ensuring timely delivery of healthy, usable food to the beneficiaries. Sengul et al. (2018) aimed to maximize total food distribution while enforcing a user-specified level of robustness in a context where the amount of donated food that agencies could effectively receive and distribute is uncertain.

Nutritional utility: Food banks play a growing role in food safety, distributing billions of pounds of free food and beverages ( Tarasuk et al. , 2020 ). Ross et al. (2013) investigated the types of food moving through six California food banks to assess the nutritional quality of these foods. They concluded that, although the six participant food banks were moving toward more healthful food than previously, still, further attention and action would be required to continue this trend. Therefore, it is understandable that the research concern works on the quality rather than the quantity of the delivery food. Ortuño and Padilla (2017) aimed to maximize the quantity of energy content (in Kcal) sent daily to the families, subject to volume and weight constraints so that the families feel they receive an equal amount of products. Gómez-Pantoja et al. (2020) proposed a similar approach, separating the needs of each individual into categories. If the set of products assigned to an individual reaches a given minimal quantity for a given category, the individual is satisfied. The problem’s objective is to maximize the total number of satisfied categories. Ogazon et al. (2022) did not consider nutritional utility as an objective; they proposed a set of constraints ensuring that the mix of products delivered to each agency (e.g. sugary drinks) respects proportions that the food bank managers set. Units of food that do not meet these proportions may not be delivered.

Most of the papers consider more than one dimension. Balcik et al. (2014) formulated two objectives under agencies’ demand uncertainty: maximizing equity and minimizing waste. They empirically demonstrated that solving the problem for the waste-minimizing objective achieves near-minimal waste while providing equitable food allocation. Islam and Ivy (2021) studied trade-offs between operation costs (the total cost of branch operation and the cost of receiving and distributing food), effectiveness (the cost of undistributed food) and fairness (maintaining a maximum deviation from perfect equity). Eisenhandler and Tzur (2019a , 2019b ) included an objective function that balances equity and effectiveness adequately. The function multiplies the measure of effectiveness – the total allocation supplied to all agencies by an equity measure – which is one minus the Gini coefficient of the food allocation vector. Alkaabneh et al. (2021) considered measures of the effectiveness of the resource allocation problem faced by food banks. They implicitly considered an equity performance measure, developing a dynamic programming model in which the primary decision is how much of each product to allocate/distribute to each agency.

Hasnain et al. (2021) explored solutions that prioritize effectiveness and equity (besides efficiency), developing a single period, weighted multicriteria optimization model that provides flexibility for decision-makers to capture their preferences over the three criteria of equity, effectiveness and efficiency.

Finally, Martins et al. (2019) proposed a network design model that accounts for all dimensions of sustainability (economic, social and environmental) through three objective functions. They investigated the trade-offs under the three conflicting objectives and suggested strategies to improve the sustainable performance of a food bank network in Portugal.

This analysis demonstrates an interesting evolution in how models’ objectives are formulated and extend away from those proposed in humanitarian logistics. Recent models are more concerned with the utility of the distributed food (i.e. the nutritional value) than the actual quantity. Interestingly, deprivation, a metric receiving significant attention in humanitarian logistics, is not mentioned in any reviewed papers.

The following subsections present the four topics on which food bank operations have been segmented: network design, inventory management and distribution. The analysis is completed with the contributions of analytic models to the field

3.3.2.2 Network design.

Network design concerns the structure of the network and usually encompasses decisions related to the choice and location of facilities and the election of their capacity. We identified only a few papers that addressed network design problems in the context of food banks.

Martins et al. (2019) considered strategic decisions, including opening new food banks and selecting their storage and transport capacities from discrete sizes over a multiperiod planning horizon. In addition, existing food banks may be closed or have their capacities expanded. Islam and Ivy (2021) presented a mixed-integer programming model to identify the efficient assignment of demand zones to banks and the equitable allocation of donated food from the food banks to the demand zones. They empirically studied the interaction between the cost of shipping donations and the cost of undistributed food and proposed a more flexible supply chain structure where food from local and national sources might be shipped directly to the agencies.

Stauffer et al. (2022) also examined the structure of the food bank supply chain, focusing on how the use of mobile pantries for food distribution (i.e. integrating the last link of their food aid supply chain), additional food bank storage capacity and improved partner agency capacity can improve food banks’ performance. They proposed a stochastic two-stage mixed-integer formulation to perform extensive sensitivity analysis on how these factors impact total costs, equity in distribution and minimized disposal, providing managerial insights and guides on the design of food banks networks. Ogazon et al. (2022) dealt with reconfiguring food bank operations on the verge of a sudden event, such as natural disasters, which provoke sudden variations in the demand and the supply, forcing food banks to adjust their operations to satisfy the needs of the affected people. They proposed several reconfiguration strategies and compared their performance empirically to elaborate guidelines on how the food banks should reorganize their responsibilities concerning the day-to-day model.

The rest of the papers on this topic discussed food distribution problems where the network structure is modified by inserting food distribution points so that agencies travel a reasonable distance to collect the food they ordered from these distribution points, aiming to share the distribution effort between the bank and the agencies. To this end, the number and the location of distribution points must be jointly decided with the routes for delivering the food from the bank’s depots. Davis et al. (2014) studied a one warehouse multiperiod problem where routes mixing collections and deliveries at distribution points must be planned so that a given number of collections must be performed and each distribution point is visited once. This single visit must deliver enough food to satisfy the needs of the covered agencies for the planning period. Routes are limited by the drivers’ allowed working time and vehicle capacity. Davis et al. (2014) proposed a two-step approach to tackle this challenging problem. First, they solve a capacitated set covering problem to determine the location of the food distribution points and the agencies’ assignment. Then, a periodic vehicle routing problem with backhauls determines the collection and delivery schedule. Solak et al. (2014) referred to this problem as the vehicle routing with demand allocation problem, proposing a formulation for the problem and two Benders decomposition-based solution procedures. Reihaneh and Ghoniem (2018) proposed a multistart optimization-based heuristic to tackle larger instances.

Table 5 summarizes the main characteristics of the reviewed papers on network design. Column Main problem formalizes the paper’s aim. Columns Supply and Demand report how problems are modeled in the paper (D = deterministic, S = random), whereas column Objective indicates the nature of the problem’s goal (F = equity, E = efficiency/cost, U = utility, W = waste) and column Horizon reports if the problem spans one (single) or several (multi) periods. Columns Modeling and Solving describe the proposed modeling and solving approaches, respectively. Finally, column Application details if the paper addresses a real or a theoretical context and if the numerical experiments were executed on real or randomly generated instances.

Table 5 confirms that our search led to only two papers dealing with “classic” network design (i.e. deciding facilities’ opening and closing and their capacities), whereas three more papers proposed location-routing problems to reduce transportation costs for food banks. Unsurprisingly, all the papers assumed deterministic contexts that sought to maximize efficiency (or minimize costs) and proposed MILPs to formulate their models and approximated (heuristic) methods to solve them efficiently; however, as mentioned in the previous section, Martins et al. (2019) sought to improve the sustainability of the solutions simultaneously.

3.3.2.3 Inventory management.

Although food banks do not perform transformations or long-term food conservation, some papers address short-term inventory management or restrictions related to inventory capacity. The latter can be observed in Sengul Orgut et al. (2016b ), which considered the distribution of donations over one month as a single period problem. Donations received and food distributed during the period were aggregated and restricted by flow conservation equations that set each bank’s total (inventory) capacity. Sengul Orgut et al. (2018) extended the previous problem to incorporate variability in the agencies’ capacities. They produce feasible and near-optimal solutions using robust optimization if agencies’ capacity varies within specified limits. They also introduce a stochastic formulation that treats the equity limit as an uncertain parameter, providing a feasible solution in the presence of small deviations from perfectly equitable distribution.

Conversely, Gómez-Pantoja et al. (2020) and Alkaabneh et al. (2021) addressed multiperiod contexts where inventory levels and policies must be handled explicitly. Gómez-Pantoja et al. (2020) introduced a resource allocation model that considers inventory management and product purchases. The model also considers product-beneficiary compatibility, balanced nutrition and the priority of beneficiaries to decide who is served, what kind of products and how many will be supplied. Alkaabneh et al. (2021) developed a framework for optimizing resource allocation by food banks among the agencies they serve, maximizing the expected utility of agencies over a finite horizon. Contrary to Gómez-Pantoja et al. (2020), which assumed that supplies are known in advance, Alkaabneh et al. (2021) considered uncertainty in supply. To handle the uncertainty of future supplies, they proposed an approximate dynamic programming approach that uses the Monte Carlo simulation to estimate the expected utility value of an assignment policy at each horizon period on which a decision is made. Numerical experiments executed on actual instances demonstrated significant improvement in the allocation process over static policies.

Finally, Marthak et al. (2021) proposed a stochastic programming model that considers prepositioning strategies among food bank facilities in high-risk areas for hurricanes. Some researchers outlined the central work of food banks to build community resilience before, during and after disasters ( Roberts et al. , 2021 ). The model considers the uncertainty associated with a hurricane’s impact on each facility regarding the available supplies, donations received and the expected demand for the facility’s service region.

Table 6 summarizes the reviewed papers’ main characteristics related to inventory management. Compared to Table 6 , papers on inventory management are driven by fairness and utility objectives, which align with their tactical rather than strategic decisional scope.

3.3.2.4 Distribution.

Although most analyzed papers report direct food transport from banks to agencies, others propose alternative approaches, including distribution routes or mixed collection and distribution routes.

Lien et al. (2014) and Balcik et al. (2014) addressed similar versions of a sequential resource allocation problem (SRA-e), which considers equity in its objective while obtaining an effective allocation of scarce resources to reduce waste. The problem seeks to create food collection and distribution routes. Food is collected at the first stops and delivered at subsequent stops in the route (the agencies). Because agencies’ demand is not known in advance, the driver must determine the food to deliver at each stop to meet the agency’s demand and reserve food for the remaining agencies on the route. Assuming that the demand follows continuous probability distributions, Lien et al. (2014) propose a dynamic programming framework that allows them to characterize the optimal allocation policy structure for a given customer sequence. The optimal structure is used to develop a heuristic allocation policy for instances with discrete demand distribution. Balcik et al. (2014) extended the SRA-e to a multiroute setting and incorporated travel time restrictions that limit the length of the potential routes. Given the problem’s computational complexity, they proposed a decomposition-based heuristic encompassing three phases to solve the problem: clustering, sequencing and allocation. The heuristic drastically reduced the computational time producing high-quality solutions.

Eisenhandler and Tzur (2019a , 2019b ) present a similar problem: the food bank must determine which agencies to visit, in what sequence and how much to pick up or deliver to each donor or agency. In this version, the food bank determines how much food should be picked up (delivered) from (to) each supplier (agency), considering the limited capacity of the vehicle. Based on this information, the food bank determines a plan for a single day of activity using a single vehicle to collect and distribute the food to the agencies. This setting requires simultaneous vehicle routing and resource allocation decisions to balance two possibly colliding goals: maximizing the total amount distributed and achieving equity in the allocation. Eisenhandler and Tzur (2019b ) contribute a different formulation for the same problem and a matheuristic solution. Table 7 reports the main characteristics of the reviewed papers related to distribution.

In summary, the extant literature’s contributions to food bank operations cover an extensive range of problems that are, in most if not all the cases, related to real applications. These contributions address various situations regarding geographic scope, managerial objectives, the time horizon covered or the aggregation of needs to be satisfied. Network design problems address situations covering large regions and where the effectiveness drives decisions in food transportation. Inventory-related problems concern food allocation, so food transportation is not considered or is a less relevant element in those models. Fairness and the food quality distributed to beneficiaries influence allocation decisions. Finally, distribution models focus on collecting and distributing food over small or local regions. These problems address supply and demand uncertainty and explicitly capture the real-life limitations affecting transportation decisions, such as truck capacity or driving time restrictions. As explained in the following paragraphs, each family of problems addresses and models the beneficiaries’ needs and the demand in different manners.

3.3.3 Demand

Demand points encompass agencies that include shelters, food pantries and soup kitchens that help deliver goods to needy people. Adequate and equitable distribution is vital for hunger-relief organizations, and because supply is almost always lower than demand ( Balcik et al. , 2014 ), it is of the utmost importance to identify and characterize demand. Other than equity in satisfying needs, several considerations must be addressed. For instance, food banks must ensure the quantity and quality of the supplied food, which is difficult because of the limited control of the supply (Gómez-Pantoja et al. , 2020), or minimize spoilage when distributing food to the furthest agencies ( Solak et al. , 2014 ). Additionally, recent research has shifted focus toward a better, more accurate identification of individuals’ needs and the customization of the food they are provided ( Ortuño and Padilla, 2017 ).

Demand estimation : In most cases, demand is a known deterministic parameter. In some cases, agencies estimate and inform the banks about demand. For instance, Gómez-Pantoja et al. (2020) assumed that the beneficiaries to support and their needs are known. Other authors ( Fianu and Davis, 2018 ; Sengul et al. , 2018) used socioeconomic data related to poverty to estimate food needs in a given area. In particular, Sengul Orgut et al. (2018) estimated demand from poverty data, as referred to in the US Census Bureau (2016).

Estimating demand is critical to avoid or minimize waste in SRA-e ( Balcik et al. , 2014 ), where each truck collects food and then delivers it to the remaining agencies along its route. Because demand at each agency is not known in advance, the volunteer driver must decide the amount of food it delivers at each stop, considering the potential needs of the remaining agencies.

Some authors proposed analytic methods to model and estimate demand. Black and Seto (2020) analyzed an administrative dataset of food bank member usage to provide a descriptive profile of patterns of food bank usage. They applied cluster and regression analyses to identify predictors of the frequency and duration of service usage. They concluded that while many users engaged with food bank services for a short duration with a limited frequency of visits, most visits were made by a small subset of deeply engaged longer-term members, raising important questions concerning the role of food banks and how they can better meet people’s needs.

The volume of food donations is regularly insufficient to meet all demands. Martins et al. (2019) considered the case where an agency applying for first-time food assistance joined a group of agencies waiting to be served. Demand for individual food items may not be fully satisfied, but a certain minimum level of assistance must be guaranteed to all agencies served by a food bank, considering predictable variations.

Demand characterization : Demand satisfaction is not just a matter of delivered quantity but nutritional content. Recent studies focused on the nutritional needs of individuals to define demand or measure their food distribution performance. For instance, Alkaabneh et al. (2021) measured resource allocation plans’ effectiveness based on the nutritional value of the allocation decisions; however, not all families have the same nutritional needs. Thompson et al. (2018) suggested that to estimate the ideal demand of a family, the daily energy necessities, the members that make up the family and the characteristics of each person, such as age, gender, body size and composition, must be considered. Gómez-Pantoja et al. (2020) highlighted the importance of the compatibility between the products and the beneficiaries. They indicated that compatibility involves nutritional aspects (e.g. baby milk will be wasted if it is donated to a family without babies), cultural aspects (e.g. some religions prohibit certain animal products) and logistical aspects (e.g. a product requiring refrigeration will be wasted if it is given to a family with refrigerator).

Another practical issue concerns grouping the available products into packages for distribution. One of food banks’ key and challenging tasks is that receiving heterogeneous supplies must be allocated to personalized kits for beneficiaries. Garthwaite et al. (2015) concluded that considering the profile of each family and their particular needs while creating the personalized kits brings several benefits and enables food banks to have a more significant impact.

Determining how to measure the nutritional value of the food delivered was addressed by Ortuño and Padilla (2017) and Gómez-Pantoja et al. (2020). In their work, Ortuño and Padilla (2017) classified goods according to their nutritional group (vegetables, fruits, grains, dairy, meats, oils) and their energy input (measured in Kcal), depending on the type of food. The minimum energy requirements of each family were determined according to the number of members and their characteristics (age, sex, physical activity, weight and height). Gómez-Pantoja et al. (2020) and Ogazon et al. (2022) also considered several categories of nutrients or products, determining that each individual must receive a minimal amount of each to be considered satisfied. The problem aims to determine the individuals to be served and the mix of products assigned to each of them to maximize the total number of satisfied categories while guaranteeing a minimum diversity in the assignment of products, balanced nutrition and compatibility between products and beneficiaries.

3.3.4 Business analytics: opportunities for improving food banks’ supply chain

The emergent field of business analytics is progressively contributing to all possible activities, including food banks’ supply chains. We identified three papers with research contributions that might contribute to improving food banks’ supply chains. From a strategic perspective, Hindle and Vidgen (2018) developed a business analytics methodology and applied it to an agency organization in the UK. The authors developed a logical model that identified the main activities undertaken by the organization. This model was used to identify leverage points and opportunities for business analytics tools, that is, value areas where analytics can be applied, to create value with relative ease. They recognized that combining geospatial analysis and visualization with open data on poverty provided the greatest opportunity because of its potential to predict where food bank aid would be most needed. Sucharitha and Lee (2020) also attempted to answer if food agencies serve their intended recipients sufficiently or sparsely and if the food agencies provide the optimum coverage of donated foods. They combined data from the Greater Cleveland Food Bank and demographic data provided by the USDA. They then used a probabilistic model as a clustering approach to analyze the whole database to identify regions within each cluster that lack food agencies near families in dire need and vice versa. Similarly, Brinkley (2017) sought to understand the geographic patterns of local food supply chains in an attempt to relocalize food systems by identifying gaps or “structural holes” in the local food network.

4. Discussion and suggested future research directions

Despite the variety of specific research or the practical questions they raise, the analysis of the papers confirms that the research on food banks is proliferating and gaining momentum. In doing so, the research progressively diverges from the general literature in humanitarian logistics. In our opinion, this can be partially explained by the long-term mission of food banks, which contrasts with the event-driven, often urgent nature of most studies in humanitarian logistics. A recent literature review on humanitarian logistics ( Hezam and Nayeem, 2021 ) focuses on disruptive situations, such as disasters and crises, whereas food banks deal with steady situations. Nonetheless, resilience is a new topic in food banks’ supply chains, as pointed out by Blessley and Mudambi (2022) . They performed qualitative analyses on how disruptive events (the 2018 US–China trade war and the 2020 COVID-19 pandemic) affected food banks’ supply chain resilience. The authors explained that food banks responded mainly by adapting storage policies, learning quickly to increase or decrease deliveries according to the food supply, collaborating with external partners, leveraging social capital along the supply chain and encouraging the distribution and consumption of low-demand products.

Black and Seto (2020) indicated that food banks feed a growing part of society, and their impact on public health is being increasingly recognized ( Iafrati, 2018 ). This raises questions on the potential extension of the products and services they might offer to specific populations. From a strategic standpoint, food banks’ impact goes beyond efficiency and, to some extent, equity and should be measured in terms of sustainability; however, among the reviewed papers, only Martins et al. (2019) and Iafrati (2018) addressed the three pillars of sustainability.

Blackmon et al. (2020) demonstrated that the added value of food banks exceeds their actual physical resources (trucks, facilities) when proximity and access to communities matter. This key role and the engagement of food banks in long-term population health explains the development of new and richer objective functions aiming to personalize the specific needs of beneficiaries. Although fairness is still a central issue for food banks, new metrics are being proposed around the idea of “nutritional utility” ( Ortuño and Padilla, 2017 ; Gómez-Pantoja et al. , 2020) in contrast with “deprivation,” an emergent metric in the field of humanitarian logistics ( Holguín-Veras et al. , 2013 ; Gutjahr and Nolz, 2016 ).

Additional research should be dedicated to strategic questions concerning the design of the overall distribution network. Only three reviewed papers address classical network design decisions (e.g. decisions concerning facility locations and their capacity or the network’s structure), and the remaining studies assume all the facilities and their capacities are given. In all the reviewed papers, demand is aggregated at agencies abstracting crucial problems, such as individuals’ access to services, that might be formulated as location or coverage problems. In this sense, Stauffer et al. (2022) suggested that food banks can maximize distribution and equity by integrating distribution to individuals through mobile pantries or sharing distribution operations with partner agencies. New models are required to study the more complex resulting logistic networks. Moreover, combining these new models with the power of emerging analytics tools constitutes a promising research direction that, to our knowledge, has been unexplored in the context of food banks.

Concerning resource management, surprisingly, only one of the reviewed papers ( Blackmon et al. , 2021 ) envisaged using a decision support system to assign volunteers to handle different operations. As pointed out by do Paço and Agostinho (2012) , volunteers are crucial for banks and agencies. Therefore, food banks should aim to maximize their comfort and satisfaction, which adequate work schedules and duty rosters can achieve.

Our last comment is dedicated to supply. Most of the reviewed papers agreed on the importance of supply for food banks, but only a few aim to develop knowledge on managing donations. Only Bech-Larsen et al. (2019) and González-Torre and Coque (2016) examined new potential sources that might redirect food surpluses as donations to food banks. More quantitative studies, such as Brock and Davis (2015) , Davis et al. (2016) and Paul and Davis (2021) , developed models to estimate or forecast donations which, in turn, might help improve demand fulfillment while reducing waste. From a more operational perspective, the reviewed papers said little about purchasing and its leverage for local development. Moshtari et al. (2021) reviewed 51 scholarly articles on procurement in humanitarian operations. Although the differences between humanitarian and food bank operations were established, they raised questions concerning procurement organization, objectives and policies, processes and lack of collaboration among stakeholders that also concern food banks. Similarly, Anaya-Arenas et al. (2018) emphasized how humanitarian organizations, such as Oxfam México, purchase as much aid and supplies as possible from the closest available sources to promote local markets and reactivate commercial activities in the served region. According to the authors, this local sourcing policy may imply higher costs and supply risks; however, it aligns with the sustainable objective of humanitarian organizations. We believe that the same sustainability goals should be emphasized in the context of food banks.

As per the suggested directions for future research, most reviewed papers propose extensions to their formulations or the development of approximated yet efficient methods to solve them. They often suggest extending the proposed experiments to better understand their models’ behavior or perform sensitivity analyses; however, some suggest more general lines of research that might eventually lead to unexplored topics.

Davis et al. (2014) suggested investigating approaches to estimate food availability from donors with different characteristics and generate strategies for inventory management that complement the food bank’s operations. Being able to estimate donations accurately would significantly improve operations.

Gómez-Pantoja et al. (2020) proposed to differentiate and prioritize products according to perishability, which is an essential issue because it leads to the unnecessary waste of food. With this prioritization approach, food banks would improve their operations by having less spoilage and thus be able to deliver more food to people in need.

Solak et al. (2014) recommended exploring methods that allow flexibility when considering food bank operations in different countries. This is easy to say but difficult to implement because of the earlier-addressed limitations; however, most food banks must include some general characteristics in their operations. Therefore, a general model might be elaborated as a base and modified to satisfy each region’s necessities.

Parker et al. (2020) advised exploring other types of collaborations between the banks, including how agencies’ expectations may change over time. Usually, collaborations are not considered because of distance and time restrictions leading to food waste; however, achieving adequate collaboration between agencies can significantly improve food banks’ operations.

In summary, this systematic literature review demonstrated a growing scientific interest in food bank operations, which has inspired various problems and scientific challenges. Moreover, we are convinced that this rising interest will accelerate in the future. Indeed, the crucial role of food banks during the COVID-19 pandemic (Blackmon et al. , 2020) should lead to a significant increase in scientific publications on food banks’ activities and contributions.

5. Conclusions

This study presents a systematic literature review of scholarly articles on food bank operations. The study results show that, from an operations perspective, food banks deal with an extensive range of problems that, although related to issues observed in commercial operations, require the formulation of distinct optimization models. Moreover, some emerging features specific to food banks, such as a significant concern for the delivered food’s nutritional utility and its long-term impact on the populations’ health, seem to differentiate food bank literature from the broader humanitarian logistics literature.

This study makes several contributions to the current literature. First, it provides new researchers with an overview of the food bank supply chain’s features and the challenges faced by food bank operations managers. Additionally, assembling, classifying and comparing the optimization models in this research area helps identify the most relevant characteristics involved in food bank operations, hopefully aiding future works to improve these operations.

Based on this review, we make several recommendations for future research. Work addressing the potential extension of food banks’ role and the set of products and services they offer to specific populations would be valuable additions to the literature and the practice. Furthermore, future models can support the coordination and integration of these services with other programs and services. Individuals’ accessibility to agencies’ services is a crucial matter for food banks, and, in this vein, the merging of optimization models with analytics tools represents a promising research direction. Finally, technology advancements and new business models have brought several opportunities for new potential partnerships of food bank supply chains with their commercial counterparts (i.e. web-based food markets) at various levels or stages of their chains. Also, the proper use of technology can provide tools to avoid waste. In some countries, food retailers and supermarkets use programs that lower expiring products’ prices, thereby reducing waste. The extent to which these technologies can impact the potential amount available for donations is unclear and requires exploration.

This research has limitations. As an emergent and not yet fully established research stream, we observed variability in the scientific terms identifying the topic and its related features. Authors inconsistently use the term “food bank” or related variants (i.e. foodbank) as a keyword or tag to identify their research. For instance, a scoping review on “Moving food Assistance into the Digital Age” ( Martin et al. , 2022 ) does not contain “food bank” in the title, abstract or keywords; however, the paper’s content is enormously relevant for food banks. While the omission of some potential papers does not necessarily undermine the value of this review, it may temper some of our conclusions.

Articles published per year

Articles published by country

Different food banks supply chains reported in the literature

Proposed framework for the analysis of the reviewed papers’ contributions

Article search criteria in the databases

Publications by journals

Articles on food banks published by journals in the OR/MS category

Food bank logistic network model characteristics

Characteristics of reviewed papers on network design

D = Deterministic, S = random, F = equity, E = efficiency/cost, U = utility, W = waste

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Hasnain , T. , Sengul Orgut , I. and Ivy , J.S. ( 2021 ), “ Elicitation of preference among multiple criteria in food distribution by food banks ”, Production and Operations Management , Vol. 30 No. 12 , pp. 4475 - 4500 , doi: 10.1111/poms.13551 .

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Food Bank For New York City regularly conducts research on the extent and demographics of food poverty in New York City, access to government nutrition assistance and income support programs, and the needs of our member network .

Our research helps us to determine and address the need for emergency food, government nutrition assistance, income support, and nutrition education programs throughout the five boroughs, as well as helping to inform policy at the city, state and federal levels.

Food Bank’s Latest Research

New York City’s Meal Gap 2016 Trends Report

The Meal Gap Under the Microscope (Research Brief, 2015)

The Hunger Cliff One Year Later (Research Brief, 2014)

Hunger’s New Normal (Emergency Food Network Report, 2013)

Research Archives

Emergency food network.

Food Bank’s emergency food network reports include the NYC Hunger Safety Net report series, which is designed to track trends in hunger and create research-based solutions to hunger throughout the five boroughs. The reports include findings on the population relying on emergency food programs (EFPs) including soup kitchens and food pantries; the operations, resources and services of EFPs; and residents’ access to food assistance.

NYC Hunger Experience

The NYC Hunger Experience report series tracks annual trends in difficulty affording food among New York City residents. Food Bank For New York City contracts with Marist College Institute for Public Opinion to conduct telephone interviews with a random and representative sample of city residents. Socio-demographic findings identify which populations throughout the five boroughs are having the greatest difficulty affording food throughout the year in order to inform policy solutions and address the problem of food poverty.

Policy Papers

Food Bank’s policy papers include reports, policy briefs, white papers, and strategy documents that use data from our research and other sources to inform public policy at the city, state, and federal levels. These publications are instrumental to our ongoing efforts to raise hunger awareness and spur legislative action to end food poverty.

Hunger in America

Feeding America regularly collaborates with member food banks and food rescue organizations throughout the United States to conduct studies on emergency food programs (EFPs) and the people they serve. Food Bank For New York City participates by conducting interviews with residents accessing EFPs and distributing surveys to the EFP network throughout the five boroughs. The Hunger in America: New York City & State reports draw upon local, state and national findings, as analyzed by Mathematica Policy Research, Inc.

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Mapping hunger at a local level

Three Square Food Bank and Feeding America, the nation’s largest domestic hunger relief organization, released its most recent Map the Meal Gap study in 2023. This study accurately reflects who is truly hungry at the local community level by taking into consideration such factors as the unemployment rate, federal food assistance eligibility rates, and the average cost of a meal. Other key findings include:

• 12.0% – The percentage of the population in Clark County who are food insecure. Three Square’s service area also includes three rural counties: Esmeralda, Lincoln, and Nye. Though the rural population is smaller, the food insecurity rate in each county ranges between 8.8%–13.9% .
• 48.5 million – The number of meals needed each year to close the gap between the need for food and what is currently made available through federal nutrition programs and charitable organizations.
• $3.50 – The average price of a meal in Clark County. Rural communities in Nevada often have an even higher average meal cost than their urban counterparts.

Food insecurity maps 

1$ = 6 meals.

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“Five years ago, my husband was in a car accident. We went from an income to absolutely no paycheck practically overnight. It was devastating. We didn’t know where our next meal was coming from.”   While Evetta worked, her single income was not enough. She began visiting one of Northern Illinois Food Bank’s partners, Wesley’s Table Food Pantry. There, she was able to pick up fresh, nutritious groceries to feed her family, and join a community that felt like family.   “When I came to the pantry to get food, they made me feel like I wasn’t alone. I’m not sure what we would have done without it.”

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Brief research report article, the food bank and food pantries help food insecure participants maintain fruit and vegetable intake during covid-19.

• 1 Department of Nutrition and Food Sciences, The University of Vermont, Burlington, VT, United States
• 2 Food Systems Program, The University of Vermont, Burlington, VT, United States
• 3 Gund Institute for Environment, The University of Vermont, Burlington, VT, United States

Charitable food services, including food banks and pantries, support individual and households' food access, potentially maintaining food security and diet quality during emergencies. During the COVID-19 pandemic, the use of food banks and pantries has increased in the US. Here we examine perceptions of food banks and food pantries and their relationship to food security and fruit and vegetable (FV) intake during the first 6 months of the COVID-19 pandemic, using a statewide representative survey ( n = 600) of residents of Vermont. The utilization of food pantries was more common among food insecure households and households with children. Among food insecure respondents, those who did not use a food pantry were significantly more likely to report consuming less FV during the pandemic. Further, we find respondents who are food insecure and using a food pantry report consuming more FV since the onset of the COVID-19 pandemic. We found that respondents who were both food insecure and reported not using a food pantry were significantly more likely to report both a reduction in fruit consumption ( b = −0.58; p = 0.001) and a reduction in vegetable consumption ( b = −0.415; p = 0.012). These results indicate that these services may support food access and one important dimension of diet quality (FV intake) for at-risk populations during emergencies.

Introduction

The COVID-19 pandemic, associated shutdowns, and social distancing measures designed to slow its spread have profoundly impacted the US food system and food access. According to the Pew Research Center, job disruptions have been widespread; lower-income adults have been hardest hit, with half of their households reporting a job or wage loss due to the pandemic ( 1 ). These disruptions have been disproportionately acute among women, low-income communities, and people of color ( 1 ), which have catalyzed important changes in the food supply chain and food security. Recent research suggests that the food insecurity rates have reached levels unprecedented in recent history ( 2 – 4 ).

With the shift from worksites, schools, and restaurant dining, to greater at-home preparation and consumption, food procurement shifted and, in many cases, overwhelmed grocery stores ( 5 ). Simultaneously, food insecure populations turned to charitable feeding systems (e.g., food banks, pantries) ( 6 ). Demands for charitable food services are reported to have increased from 50 to 140% in the first months of the COVID-19 pandemic ( 7 , 8 ). In the year prior to the pandemic, 18% of Vermonters reported experiencing food insecurity ( 2 ). Food insecurity rose by 32% in the first months following the outbreak ( 2 ). By June 2020, nationwide, more than 82% of food banks reported higher numbers of patrons than they did the year prior ( 9 ). A longitudinal population-level survey conducted in Vermont in March and May 2020 found that demand for charitable food services increased by 68%, from 7.1 to 12.0% ( 10 ). In October 2020, Feeding America reported they were on track to distribute 50% more food when comparing October 2019 and October 2020 ( 11 ).

Health inequalities in the US follow a socioeconomic continuum where low-income, low-resource households disproportionally experience higher levels of food-related health risks ( 12 ). Further, inequalities, lack of transportation, and geographic disparities magnify structural and environmental factors contributing to food insecurity and poor dietary health ( 13 , 14 ). Compared to wealthier households, low-income households cook more meals at home ( 15 ) yet consume fewer fruits and vegetables (FV) ( 16 ) and are more likely not to meet the servings of FV recommended by the Dietary Guidelines for Americans ( 17 ). Nanney et al. ( 18 ) examined 269 food shelves using the HEI-2010 (Healthy Eating Index) and concluded that the majority of available food (89%) “needs improvement” for nutritional adequacy. Further, they found significant seasonal fluctuations with the month and quarter scores in July, August, and September significantly higher than in December.

Charitable food services vary in FV distribution from region to region. Vermont is known for its resilient local food system ( 19 ) and has several agencies, organizations, and programs to help address hunger issues in the state. According to the Hunger in America 2014 ( 13 ) report for Vermont Foodbank, of the 23 meal-based relief agencies analyzed, 42.1% aided clients in accessing local food resources. Further, many sites have introduced client choice ( 20 ) to provide food pantry patrons choice; many additional organizations have been transitioning to a client-choice model. This approach allows clients to take products they want and will use. By incorporating behavioral economic techniques, recent initiatives have shown success in nudging clients to select more fruits, vegetables, and nutrient-dense foods ( 21 ). COVID-19 has presented new challenges for these programs as they work to meet growing food needs while protecting staff, volunteers, and clients' health.

This study aims to understand charitable food programs' role during the first 6 months of the COVID-19 pandemic. Emerging international research suggests that COVID-19 mitigation has negatively impacted diet quality during the pandemic ( 22 ). We explore how FV intake changed among a representative sample of Vermonters and examine the emergency food system's role in maintaining access to FVs during a humanitarian crisis.

Survey Development and Recruitment

The research team, in collaboration with other researchers in the National Food Access and COVID research Team (NFACT) ( 22 ), developed and piloted a survey in March 2020 ( 23 ). After two rounds of data collection in March 2020 and June 2020, additional refinements to the pilot survey included food access, food security, food purchasing, food assistance program participation, dietary intake, perceptions of COVID-19, and individual social distancing behaviors, as well as household and individual sociodemographics ( 24 ). Data collection for this study was conducted in August and September 2020 ( 25 ). We obtained Institutional Review Board approval from the University of Vermont (IRB protocol 00000873). The survey was explicitly designed to measure critical outcomes (e.g., food access, food security, food purchasing, and dietary intake) both before the COVID-19 outbreak (dated as of March 11, 2020, the day the World Health Organization declared a global pandemic) ( 26 ) and since the pandemic began. The survey utilizes validated measures when possible ( Supplementary Table 1 ). The survey was piloted in Vermont, with 25 eligible (18 or older) residents in late March, and validation methods (e.g., Cronbach alpha, factor analysis) were used to test the internal validity of questions with key constructs (alpha > 0.70) ( 2 ).

Sampling Approaches

We deployed our online survey to a panel of respondents recruited by Qualtrics (Provo, UT). We developed a sampling strategy for achieving a general population sample reflecting characteristics of the state including income, race, and ethnicity in Vermont. This sample was achieved by matching sample recruitment quotas to the income, race (specifically White, Black or African American, American Indian and Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, and Two or more races), and ethnicity (Hispanic, non-Hispanic) population profile of Vermont in the American Community Survey (ACS) ( Supplementary Table 2 ) ( 27 ). A total of 600 people ages 18 and over responded to the survey, representing a margin of error (95% confidence level) for the adult population of Vermont ±4% ( 27 ).

Variables of Interest

We explore three self-reported dependent variables in this analysis ( Supplementary Table 1 ). First, we measured food security status using the US Department of Agriculture's 6-item short-form food security module ( 28 ). We asked respondents to reflect on the year before the COVID-19 pandemic to collect pre-pandemic food security status. Further, the traditional 12-month period was modified to ~6 months to measure food security status since the start of the COVID-19 pandemic. Following standard scoring protocol, we summarized responses for each item, and classified respondents who answered one or two items affirmatively as living in food insecure households. Second, we measured current FV intake using the National Cancer Institute's two-item screener, modified to apply to the last month and with some example foods removed to shorten it ( 29 ). Finally, we examined the perceived change in FV consumption since the onset of the COVID-19 pandemic. Independent variables included multiple questions related to current food bank and food pantry use, specific charitable food system participant experiences, and transportation other than their own vehicle; we also captured several household and individual-level demographics ( Table 1 ).

Table 1 . Survey respondents' individual and household demographic characteristics.

Statistical Analysis

To examine differences in household food insecurity during the first 6 months of the COVID-19 pandemic, we created three categories of respondents: (1) households with food security , including households that were food secure before and since the onset of the COVID-19 pandemic and households who were food insecure at some point in the year before the COVID-19 pandemic began but were no longer food insecure during the first 6 months of the pandemic; (2) households with persistent food insecurity , food insecure both at some point in the year before the COVID-19 pandemic began and experiencing food insecurity at some point during the first 6 months of the pandemic; (3) households with new food insecurity , categorized as food secure at all times in the year before the COVID-19 pandemic began, but food insecure at some point since the start of the pandemic. We report statistical significance as anything p < 0.05.

To determine statistically significant differences between groups, we utilized SPSS Version 27 ( 30 ) and Stata Version 16 ( 31 ) to run descriptive statistics, chi-square tests, and multivariable logit models. Specifically, we used chi-square tests to analyze food pantry use related to each item of the food security module. In our multivariable regression models, we use a set of demographic controls including gender, children in the household, respondents over 55, respondents identifying as Black, Indigenous, or People of Color (BIPOC) and/or Hispanic, food security status ( 28 ), households with any job loss or negative change since the start of the pandemic, households making <$50,000 in 2019, and households using transportation for food access other than their own vehicle (e.g., public transportation, ride from a friend) since March 2020. It is important to note that although this survey is representative of Vermont state characteristics on race and ethnicity, the sample size is not sufficient to analyze racial and ethnic groups in a disaggregated format in models. Therefore, we have disaggregated race and ethnicity in all food security statistics in the results but use aggregated race and ethnicity for modeling. We used a multivariable logit model with these demographic controls to predict food pantry use (yes/no) since the start of the COVID-19 pandemic. Then, we use a multinomial logit model with demographic controls to predict a change in FV consumption since COVID-19 (decreased, stayed the same, or increased). Finally, we use a multivariable regression model to predict the current intake of FV, measured on a continuous scale, with demographic controls. All variables and their descriptions are included in Supplementary Table 1 . Coefficients are reported as odds ratios for the logistic regression model only. We used all available data to estimate effect sizes and interactions and assumed any missing data were missing at random.

Demographic Characteristics of Respondents

Our sample reflected the demographic composition of the Vermont population for income, race, and ethnicity distribution. The majority of our respondents identified as female (67.3%), non-Hispanic White, without children in the household, and had a household income below $75,000 ( Table 1 ). Almost half of the respondents (46.2%) experienced a change in employment at some point between March and September 2020. Changes included loss of employment (24.8%), reduced hours or income (34.7%), and furlough (20.3%). Only 5.0% of respondents utilized transportation other than a personal vehicle between March and September 2020 ( Table 1 ).

Food Insecurity Prevalence

Nearly one in three (29.0%) respondent households were food insecure at some point between March and September 2020. Among those experiencing food insecurity since the start of the pandemic ( n = 165), 72.1% also experienced food insecurity at some point in the year before the pandemic; in comparison, 27.9% were newly food insecure ( Table 1 ).

Fruit and Vegetable Consumption

The 2020–2025 Dietary Guidelines for Americans (DGA), released on December 28, 2020, recommend that people needing 2,000 calories per day should include at least 2 cups of fruit and 2.5 cups of vegetables in their daily diets. During the COVID-19 pandemic, 15.5% of respondents met the recommendation for fruit intake, and ~27.7% of respondents met the recommendations for vegetables ( Table 1 ).

Changes in Fruit and Vegetable Consumption During the First 6 Months of COVID-19

Multinomial logit models predicted factors contributing to more, less, or the same FV consumption during the first 6 months of COVID-19 ( p ≤ 0.001, Table 2 ). Respondents who were food insecure and did not use a food pantry since the beginning of the COVID-19 pandemic reported consuming significantly less FV ( b = 2.29; p < 0.001). Further, among respondents who utilized food pantries since the start of the COVID-19 pandemic, both food insecure and food secure participants also reported consuming significantly less FV ( b = 1.72; p < 0.001 and b = 1.174; p = 0.034). Conversely, we found BIPOC/Hispanic respondents were more likely to have increased their FV intake ( b = 0.96; p = 0.026) during the first 6 months of the pandemic as compared to non-Hispanic White respondents. Finally, we found that food insecure respondents who reported utilizing a food pantry reported consuming significantly more FV since the start of the COVID-19 pandemic ( b = 1.138; p = 0.17)

Table 2 . Multinomial logit model predicting change in fruit and vegetable consumption during the first 6 months of the COVID-19 pandemic.

Fruit and Vegetable Consumption During the First 6 Months of COVID-19

Using multivariable regression models, we found that respondents in households with children ( b = 0.29; p = 0.039), those who use a form of transportation other than their own vehicle ( b = 0.63; p = 0.020), and those over 55 years old ( b = 0.27; p = 0.049) reported having higher fruit intake during the first 6 months of the pandemic than respondents from households without children, those who used their own vehicle, and those aged 18–55 years ( Table 3 ). We found that respondents from low-income households ( b = −0.39; p = 0.002) and respondents in food insecure households ( b = −0.57; p = 0.001) were more likely to report consuming less fruit than higher income and food secure households. We found that respondents over 55 years old ( b = 0.34; p = 0.013) reported having higher vegetable intake in the first 6 months of the pandemic compared to younger respondents and those from low-income households ( b = −0.63; p = 0.000). Finally, we found that respondents who were both food insecure and reported not using a food pantry were significantly more likely to report both a reduction in fruit consumption ( b = −0.58; p = 0.001) and a reduction in vegetable consumption (b = 0.415; p = 0.012).

Table 3 . Multivariable regression models predicting fruit and vegetable consumption during the first 6 months of COVID-19.

Pantry Utilization Buffers Aspects of Food Access Among Low-Income Households

Food pantry users were significantly more likely to be food insecure ( p < 0.001) than non-pantry users. While low-income households (earning <$50,000 annually) were more likely to use food pantries, we also found that, for low-income households, using food pantries was associated with greater affirmative responses for each food security item [Chi-squared p < 0.001 for all differences ( Supplementary Figure 1 ; Supplementary Table 3 )]. Expressly, as compared to respondents not using a food pantry, 21% fewer respondents from low-income households who utilized a food pantry since March 2020 agreed that the food they had did not last and they did not have money to get more (20.0%; 41.2%) and that they could afford to eat a balanced meal (20.2%; 40.7%). Among those earning $50,000 annually or less, 60% fewer respondents whose households utilized food pantries agreed that adults in their household had cut the size of their meals or skipped meals because there was not enough money for food as compared to respondents whose households did not utilize food pantries (15.6%; 21.1%). Among the same subset of respondents, four percent fewer respondents whose households utilized a food bank or food pantry reported that they had to eat less (17.0%; 20.8%) or cut the size of their meals or skip meals (17.1%; 21.3%) because there was not enough money for food.

Food Pantry Utilization

About one in seven respondents (14.5%) reported that their household utilized a food bank or food pantry between March and September 2020 ( Table 4 ). Those with increased odds of utilizing these food distribution services were food insecure (OR = 6.55, 95% CI = 3.52, 12.20) and low-income households (OR = 3.85, 95% CI = 2.01, 7.38), and respondents using transportation other than their own vehicle (OR = 4.68, 95% CI = 1.87, 11.70) ( Table 4 ).

Table 4 . Multivariate analysis predicting odds of food pantry use since the start of the COVID-19 pandemic.

Food Pantry Participant Experiences

We found that the vast majority of respondents (85%) who utilized food pantries during the first 6 months of the pandemic ( n = 86) agreed or strongly agreed that food pantries have been helpful ( Supplementary Figure 2 ). Approximately one-third of pantry users indicated concerns, including that pantries run out of food often (35%), have long lines and wait times (34%), and have inconvenient or irregular hours (30%). Other concerns among food pantry users included pantries not having the food their family likes (22%) or good quality food (22%) and not knowing how to prepare food the pantry provides (12%).

To our knowledge, this is the first study to examine the relationship between the charitable food system (food banks, pantries/shelves) and FV consumption during the COVID-19 pandemic. Overall, we find that 14.5% of our respondents utilized a food pantry which mirrors increased demand nationally as evidenced by media outlets' reports ( 7 – 9 ). Among food insecure respondents, we found those who did not use a food pantry were significantly more likely to report consuming less FV during the pandemic. Additionally, we found that respondents who are food insecure and using a food pantry report consuming more FV since the onset of the pandemic. Furthermore, we found that respondents who were both food insecure and reported not using a food pantry were significantly more likely to report both a reduction in fruit consumption and a reduction in vegetable consumption. These results suggest that utilization of food banks and food pantries has a relationship with perceptions of FV access and reported intake.

Although low-income households were more likely to prepare home cooked meals before the COVID-19 pandemic ( 15 ), disparities exist in FV intake across socioeconomic status. Home cooked meals are generally associated with higher FV intake ( 32 ). While most households do not eat enough FV—low-income households and those with food insecurity are especially at risk of low FV intake and limited dietary variety. Higher FV intake is associated with a reduced risk of cardiovascular disease, cancer, co-morbidities, and all-cause mortality ( 33 ). Our results suggest that the food bank/food pantry system may play a role in blunting the adverse effects of a humanitarian crisis like the COVID-19 pandemic by increasing food access for low-income households and thereby mitigating reductions in their overall FV intake.

Although we found an association between food security status and pantry use, Robaina and Martin ( 32 ) demonstrated that our low-income pantry users answered specific statements within the USDA Food Security Module at a significantly lower affirmative rate compared to low-income non-users. We recognize that the USDA defines food security based on Anderson's 1990 Report ( 34 ), where food security is acquired “without resorting to emergency food supplies” ( 34 ). Our findings demonstrate that the food bank/food pantry system may have helped maintain several components of food access and FV intake among food insecure users of this system. Our results suggest that although food bank use does not impact the overall food security rate, food security indicators such as “food did not last” and they “could not afford a balanced meal” are associated with positive outcomes among those using food pantries. Further evidence that use of food banks/food pantries may improve food access includes our findings that 85% of users found food pantries helpful.

As expected, both food insecure and low-income populations are at greater odds of using a food bank/food pantry as compared to food secure and higher income households. We also found the population using any form of transportation other than their own vehicle to be more likely to use a food bank/food pantry, probably due at least in part to the greater reliance on public transportation among low-income persons in the US ( 35 , 36 ). Further, studies suggest associations between unemployment and significantly lower levels of car ownership especially among BIPOC and female head of household families ( 37 ). With state and local social distancing requirements informing distribution, many food pantries have shifted from a super-market-type layout to a drive-up operation where volunteers assembled pre-packaged food boxes and placed them in the patron's vehicle ( 9 ). Patrons who rely on public transportation may experience barriers to this new food distribution model. Future studies should include inquiries into the patrons experience with pre-packaged food box distribution.

Although FV intake did not differ between non-Hispanic White and respondents from racial and ethnic minority populations at the time of our survey, BIPOC/Hispanic respondents were more likely to report a significant increase in FV intake during the first 6 months of the COVID-19 pandemic. This is notable and important since increasing FV intake is a national public health goal, and FV intake tends to be lower among some racial and ethnic groups ( 38 ). The FV intake among BIPOC respondents mirrors findings in France by Marty et al. ( 39 ), who found an increase in FV consumption during the lockdown. However, their subjects also increased their consumption of sugary foods, sodium, and alcoholic beverage, which our study did not capture ( 40 ).

We acknowledge that charitable food services are part of a broader system of food access and food security. The charitable food system is designed as an emergency stop-gap and is valuable in crises like the one presented by the COVID-19 pandemic, but does not replace the central role of federal nutrition assistance programs, which are purposely designed to supplement the diverse needs of the most vulnerable Americans. Researchers ( 41 ) indicate that the chronic reliance on charitable food services can worsen food security for many households and limit access to culturally and medically appropriate foods. An additional important role of the charitable food system is to help link people to other programs in times of need. It remains to be investigated the extent to which this occurred during the COVID-19 pandemic.

Limitations

We note a few limitations. First, although our approach's strength was the use of quota sampling to achieve alignment between the sample and the population of Vermont with respect to race, ethnicity, and income, respondents may have differed in other ways. Prior work has demonstrated differences between participants in online survey research and the general population, including greater participation among women, which we saw in our sample ( 42 , 43 ). Online surveys may lead to response bias and the over-representation of females. Second, self-reported dietary data are subject to recall and response bias ( 44 ). Although the two-item FV intake instrument that we used has adequate reliability, it has low validity for measuring precise intake levels ( 29 ). We used this instrument to compare individuals concerning FV intake rather than estimate actual intake in line with recommendations ( 29 ). Further, our study was conducted in August and September when the availability of local FV is at an annual peak. Research is needed that utilizes a more robust and inclusive measure of dietary intake and dietary quality. Finally, these cross-sectional data do not allow rigorous evaluation of a causal link between food pantry use and food security or FV intake. Future research should address these limitations and consider the longer-term associations between food pantry use, food security, and dietary intake in crisis contexts.

This study documented use and experiences with the charitable food system, including associations with food security and FV intake outcomes, among a statewide sample in Vermont, US, in the first 6 months of the COVID-19 pandemic. We found that food bank/food pantry use significantly increased in Vermont since the start of the COVID-19 pandemic. The results document improved FV intake among low-income households that utilized food pantries as compared with low-income households that did not. Taken together, the results suggest that the charitable food system is an important way in which people can supplement their food budget and maintain food access during a humanitarian crisis. However, it is essential to note that Vermont's resilient food system and support programs may have impacted these results and the seasonal abundance when this survey was conducted. Additional research should be conducted more fully to understand these relationships over time and in greater depth. Increased analysis of the food provided through food pantries serving diverse populations may be important to assess the overall accessibility of healthy, culturally, and medically acceptable foods for at-risk populations. The heightened usage of the charitable food system during the COVID-19 pandemic highlights not only the importance of food pantries but reinforces the need for funding, maintenance, and preparedness of these emergency programs.

Data Availability Statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author.

Ethics Statement

The studies involving human participants were reviewed and approved by Institutional Review Board approval was obtained from the University of Vermont under protocol 00000873. Consent was obtained from all participants prior to data collection. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

FB, KR, EB, and MN wrote the original manuscript, provided data curation, code, codebooks, resources, read, edited, and approved the final manuscript. FB and KR provided conceptualization. FB and MN provided methods and data curation. MN, FB, and EB acquired funding. All authors contributed to the article and approved the submitted version.

Funding for this work was provided by the University of Vermont's College of Agriculture and Life Sciences and Office of the Vice President of Research, the Gund Institute for Environment at the University of Vermont, and the USDA Agricultural Research Service Center for Food Systems Research.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2021.673158/full#supplementary-material

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Keywords: food security, coronavirus, food pantry, emergency food assistance, nutrition security

Citation: Bertmann F, Rogomentich K, Belarmino EH and Niles MT (2021) The Food Bank and Food Pantries Help Food Insecure Participants Maintain Fruit and Vegetable Intake During COVID-19. Front. Nutr. 8:673158. doi: 10.3389/fnut.2021.673158

Received: 26 February 2021; Accepted: 13 July 2021; Published: 06 August 2021.

Reviewed by:

Copyright © 2021 Bertmann, Rogomentich, Belarmino and Niles. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Farryl Bertmann, fbertman@uvm.edu

This article is part of the Research Topic

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The Vandal Food Pantry (VFP) is a donation-based pantry that aims to serve those in our Vandal community who are facing short-term food insecurity. We rely on your kind donations and food drives to keep our pantry stocked.

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