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Introduction.

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Young people and healthy eating: a systematic review of research on barriers and facilitators

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J Shepherd, A Harden, R Rees, G Brunton, J Garcia, S Oliver, A Oakley, Young people and healthy eating: a systematic review of research on barriers and facilitators, Health Education Research , Volume 21, Issue 2, 2006, Pages 239–257, https://doi.org/10.1093/her/cyh060

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A systematic review was conducted to examine the barriers to, and facilitators of, healthy eating among young people (11–16 years). The review focused on the wider determinants of health, examining community- and society-level interventions. Seven outcome evaluations and eight studies of young people's views were included. The effectiveness of the interventions was mixed, with improvements in knowledge and increases in healthy eating but differences according to gender. Barriers to healthy eating included poor school meal provision and ease of access to, relative cheapness of and personal taste preferences for fast food. Facilitators included support from family, wider availability of healthy foods, desire to look after one's appearance and will-power. Friends and teachers were generally not a common source of information. Some of the barriers and facilitators identified by young people had been addressed by soundly evaluated effective interventions, but significant gaps were identified where no evaluated interventions appear to have been published (e.g. better labelling of food products), or where there were no methodologically sound evaluations. Rigorous evaluation is required particularly to assess the effectiveness of increasing the availability of affordable healthy food in the public and private spaces occupied by young people.

Healthy eating contributes to an overall sense of well-being, and is a cornerstone in the prevention of a number of conditions, including heart disease, diabetes, high blood pressure, stroke, cancer, dental caries and asthma. For children and young people, healthy eating is particularly important for healthy growth and cognitive development. Eating behaviours adopted during this period are likely to be maintained into adulthood, underscoring the importance of encouraging healthy eating as early as possible [ 1 ]. Guidelines recommend consumption of at least five portions of fruit and vegetables a day, reduced intakes of saturated fat and salt and increased consumption of complex carbohydrates [ 2, 3 ]. Yet average consumption of fruit and vegetables in the UK is only about three portions a day [ 4 ]. A survey of young people aged 11–16 years found that nearly one in five did not eat breakfast before going to school [ 5 ]. Recent figures also show alarming numbers of obese and overweight children and young people [ 6 ]. Discussion about how to tackle the ‘epidemic’ of obesity is currently high on the health policy agenda [ 7 ], and effective health promotion remains a key strategy [ 8–10 ].

Evidence for the effectiveness of interventions is therefore needed to support policy and practice. The aim of this paper is to report a systematic review of the literature on young people and healthy eating. The objectives were

(i) to undertake a ‘systematic mapping’ of research on the barriers to, and facilitators of, healthy eating among young people, especially those from socially excluded groups (e.g. low-income, ethnic minority—in accordance with government health policy);

(ii) to prioritize a subset of studies to systematically review ‘in-depth’;

(iii) to ‘synthesize’ what is known from these studies about the barriers to, and facilitators of, healthy eating with young people, and how these can be addressed and

(iv) to identify gaps in existing research evidence.

General approach

This study followed standard procedures for a systematic review [ 11, 12 ]. It also sought to develop a novel approach in three key areas.

First, it adopted a conceptual framework of ‘barriers’ to and ‘facilitators’ of health. Research findings about the barriers to, and facilitators of, healthy eating among young people can help in the development of potentially effective intervention strategies. Interventions can aim to modify or remove barriers and use or build upon existing facilitators. This framework has been successfully applied in other related systematic reviews in the area of healthy eating in children [ 13 ], physical activity with children [ 14 ] and young people [ 15 ] and mental health with young people [16; S. Oliver, A. Harden, R. Rees, J. Shepherd, G. Brunton and A. Oakley, manuscript in preparation].

Second, the review was carried out in two stages: a systematic search for, and mapping of, literature on healthy eating with young people, followed by an in-depth systematic review of the quality and findings of a subset of these studies. The rationale for a two-stage review to ensure the review was as relevant as possible to users. By mapping a broad area of evidence, the key characteristics of the extant literature can be identified and discussed with review users, with the aim of prioritizing the most relevant research areas for systematic in-depth analysis [ 17, 18 ].

Third, the review utilized a ‘mixed methods’ triangulatory approach. Data from effectiveness studies (‘outcome evaluations’, primarily quantitative data) were combined with data from studies which described young people's views of factors influencing their healthy eating in negative or positive ways (‘views’ studies, primarily qualitative). We also sought data on young people's perceptions of interventions when these had been collected alongside outcomes data in outcome evaluations. However, the main source of young people's views was surveys or interview-based studies that were conducted independently of intervention evaluation (‘non-intervention’ research). The purpose was to enable us to ascertain not just whether interventions are effective, but whether they address issues important to young people, using their views as a marker of appropriateness. Few systematic reviews have attempted to synthesize evidence from both intervention and non-intervention research: most have been restricted to outcome evaluations. This study therefore represents one of the few attempts that have been made to date to integrate different study designs into systematic reviews of effectiveness [ 19–22 ].

Literature searching

A highly sensitive search strategy was developed to locate potentially relevant studies. A wide range of terms for healthy eating (e.g. nutrition, food preferences, feeding behaviour, diets and health food) were combined with health promotion terms or general or specific terms for determinants of health or ill-health (e.g. health promotion, behaviour modification, at-risk-populations, sociocultural factors and poverty) and with terms for young people (e.g. adolescent, teenager, young adult and youth). A number of electronic bibliographic databases were searched, including Medline, EMBASE, The Cochrane Library, PsycINFO, ERIC, Social Science Citation Index, CINAHL, BiblioMap and HealthPromis. The searches covered the full range of publication years available in each database up to 2001 (when the review was completed).

Full reports of potentially relevant studies identified from the literature search were obtained and classified (e.g. in terms of specific topic area, context, characteristics of young people, research design and methodological attributes).

Inclusion screening

Inclusion criteria were developed and applied to each study. The first round of screening was to identify studies to populate the map. To be included, a study had to (i) focus on healthy eating; (ii) include young people aged 11–16 years; (iii) be about the promotion of healthy eating, and/or the barriers to, or facilitators of, healthy eating; (iv) be a relevant study type: (a) an outcome evaluation or (b) a non-intervention study (e.g. cohort or case control studies, or interview studies) conducted in the UK only (to maximize relevance to UK policy and practice) and (v) be published in the English language.

The results of the map, which are reported in greater detail elsewhere [ 23 ], were used to prioritize a subset of policy relevant studies for the in-depth systematic review.

A second round of inclusion screening was performed. As before, all studies had to have healthy eating as their main focus and include young people aged 11–16 years. In addition, outcome evaluations had toFor a non-intervention study to be included it had to

(i) use a comparison or control group; report pre- and post-intervention data and, if a non-randomized trial, equivalent on sociodemographic characteristics and pre-intervention outcome variables (demonstrating their ‘potential soundness’ in advance of further quality assessment);

(ii) report an intervention that aims to make a change at the community or society level and

(iii) measure behavioural and/or physical health status outcomes.

(i) examine young people's attitudes, opinions, beliefs, feelings, understanding or experiences about healthy eating (rather than solely examine health status, behaviour or factual knowledge);

(ii) access views about one or more of the following: young people's definitions of and/or ideas about healthy eating, factors influencing their own or other young people's healthy eating and whether and how young people think healthy eating can be promoted and

(iii) privilege young people's views—presenting views directly as data that are valuable and interesting in themselves, rather than only as a route to generating variables to be tested in a predictive or causal model.

Non-intervention studies published before 1990 were excluded in order to maximize the relevance of the review findings to current policy issues.

Data extraction and quality assessment

All studies meeting inclusion criteria underwent data extraction and quality assessment, using a standardized framework [ 24 ]. Data for each study were entered independently by two researchers into a specialized computer database [ 25 ] (the full and final data extraction and quality assessment judgement for each study in the in-depth systematic review can be viewed on the Internet by visiting http://eppi.ioe.ac.uk ).

Outcome evaluations were considered methodologically ‘sound’ if they reported:Only studies meeting these criteria were used to draw conclusions about effectiveness. The results of the studies which did not meet these quality criteria were judged unclear.

(i) a control or comparison group equivalent to the intervention group on sociodemographic characteristics and pre-intervention outcome variables.

(ii) pre-intervention data for all individuals or groups recruited into the evaluation;

(iii) post-intervention data for all individuals or groups recruited into the evaluation and

(iv) on all outcomes, as described in the aims of the intervention.

Non-intervention studies were assessed according to a total of seven criteria (common to sets of criteria proposed by four research groups for qualitative research [ 26–29 ]):

(i) an explicit account of theoretical framework and/or the inclusion of a literature review which outlined a rationale for the intervention;

(ii) clearly stated aims and objectives;

(iii) a clear description of context which includes detail on factors important for interpreting the results;

(iv) a clear description of the sample;

(v) a clear description of methodology, including systematic data collection methods;

(vi) analysis of the data by more than one researcher and

(vii) the inclusion of sufficient original data to mediate between data and interpretation.

Data synthesis

Three types of analyses were performed: (i) narrative synthesis of outcome evaluations, (ii) narrative synthesis of non-intervention studies and (iii) synthesis of intervention and non-intervention studies together.

For the last of these a matrix was constructed which laid out the barriers and facilitators identified by young people alongside descriptions of the interventions included in the in-depth systematic review of outcome evaluations. The matrix was stratified by four analytical themes to characterize the levels at which the barriers and facilitators appeared to be operating: the school, family and friends, the self and practical and material resources. This methodology is described further elsewhere [ 20, 22, 30 ].

From the matrix it is possible to see:

(i) where barriers have been modified and/or facilitators built upon by soundly evaluated interventions, and ‘promising’ interventions which need further, more rigorous, evaluation (matches) and

(ii) where barriers have not been modified and facilitators not built upon by any evaluated intervention, necessitating the development and rigorous evaluation of new interventions (gaps).

Figure 1 outlines the number of studies included at various stages of the review. Of the total of 7048 reports identified, 135 reports (describing 116 studies) met the first round of screening and were included in the descriptive map. The results of the map are reported in detail in a separate publication—see Shepherd et al. [ 23 ] (the report can be downloaded free of charge via http://eppi.ioe.ac.uk ). A subset of 22 outcome evaluations and 8 studies of young people's views met the criteria for the in-depth systematic review.

The review process.

Outcome evaluations

Of the 22 outcome evaluations, most were conducted in the United States ( n = 16) [ 31–45 ], two in Finland [ 46, 47 ], and one each in the UK [ 48 ], Norway [ 49 ], Denmark [ 50 ] and Australia [ 51 ]. In addition to the main focus on promoting healthy eating, they also addressed other related issues including cardiovascular disease in general, tobacco use, accidents, obesity, alcohol and illicit drug use. Most were based in primary or secondary school settings and were delivered by teachers. Interventions varied considerably in content. While many involved some form of information provision, over half ( n = 13) involved attempts to make structural changes to young people's physical environments; half ( n = 11) trained parents in or about nutrition, seven developed health-screening resources, five provided feedback to young people on biological measures and their behavioural risk status and three aimed to provide social support systems for young people or others in the community. Social learning theory was the most common theoretical framework used to develop these interventions. Only a minority of studies included young people who could be considered socially excluded ( n = 6), primarily young people from ethnic minorities (e.g. African Americans and Hispanics).

Following detailed data extraction and critical appraisal, only seven of the 22 outcome evaluations were judged to be methodologically sound. For the remainder of this section we only report the results of these seven. Four of the seven were from the United States, with one each from the UK, Norway and Finland. The studies varied in the comprehensiveness of their reporting of the characteristics of the young people (e.g. sociodemographic/economic status). Most were White, living in middle class urban areas. All attended secondary schools. Table I details the interventions in these sound studies. Generally, they were multicomponent interventions in which classroom activities were complemented with school-wide initiatives and activities in the home. All but one of the seven sound evaluations included and an integral evaluation of the intervention processes. Some studies report results according to demographic characteristics such as age and gender.

Soundly evaluated outcome evaluations: study characteristics (n = 7)

RCT = Randomized Controlled Trial; CT = controlled trial (no randomization); PE = process evaluation.

Separate evaluations of the same intervention in two populations in New York (the Bronx and Westchester County).

The UK-based intervention was an award scheme (the ‘Wessex Healthy Schools Award’) that sought to make health-promoting changes in school ethos, organizational functioning and curriculum [ 48 ]. Changes made in schools included the introduction of health education curricula, as well as the setting of targets in key health promotion areas (including healthy eating). Knowledge levels, which were high at baseline, changed little over the course of the intervention. Intervention schools performed better in terms of healthy food choices (on audit scores). The impact on measures of healthy eating such as choosing healthy snacks varied according to age and sex. The intervention only appeared possibly to be effective for young women in Year 11 (aged 15–16 years) on these measures (statistical significance not reported).

The ‘Know Your Body’ intervention, a cardiovascular risk reduction programme, was evaluated in two separate studies in two demographically different areas of New York (the Bronx and Westchester County) [ 45 ]. Lasting for 5 years it comprised teacher-led classroom education, parental involvement activities and risk factor examination in elementary and junior high schools. In the Bronx evaluation, statistically significant increases in knowledge were reported, but favourable changes in cholesterol levels and dietary fat were not significant. In the Westchester County evaluation, we judged the effects to be unclear due to shortcomings in methods reported.

A second US-based study, the 3-year ‘Gimme 5’ programme [ 40 ], focused on increasing consumption of fruits and vegetables through a school-wide media campaign, complemented by classroom activities, parental involvement and changes to nutritional content of school meals. The intervention was effective at increasing knowledge (particularly among young women). Effects were measured in terms of changes in knowledge scores between baseline and two follow-up periods. Differences between the intervention and comparison group were significant at both follow-ups. There was a significant increase in consumption of fruit and vegetables in the intervention group, although this was not sustained.

In the third US study, the ‘Slice of Life’ intervention, peer leaders taught 10 sessions covering the benefits of fitness, healthy diets and issues concerning weight control [ 41 ]. School functioning was also addressed by student recommendations to school administrators. For young women, there were statistically significant differences between intervention and comparison groups on healthy eating scores, salt consumption scores, making healthy food choices, knowledge of healthy food, reading food labels for salt and fat content and awareness of healthy eating. However, among young men differences were only significant for salt and knowledge scores. The process evaluation suggested that having peers deliver training was acceptable to students and the peer-trainers themselves.

A Norwegian study evaluated a similar intervention to the ‘Slice of Life’ programme, employing peer educators to lead classroom activities and small group discussions on nutrition [ 49 ]. Students also analysed the availability of healthy food in their social and home environment and used a computer program to analyse the nutritional status of foods. There were significant intervention effects for reported healthy eating behaviour (but not maintained by young men) and for knowledge (not young women).

The second ‘North Karelia Youth Study’ in Finland featured classroom educational activities, a community media campaign, health-screening activities, changes to school meals and a health education initiative in the parents' workplace [ 47 ]. It was judged to be effective for healthy eating behaviour, reducing systolic blood pressure and modifying fat content of school meals, but less so for reducing cholesterol levels and diastolic blood pressure.

The evidence from the well-designed evaluations of the effectiveness of healthy eating initiatives is therefore mixed. Interventions tend to be more effective among young women than young men.

Young people's views

Table II describes the key characteristics of the eight studies of young people's views. The most consistently reported characteristics of the young people were age, gender and social class. Socioeconomic status was mixed, and in the two studies reporting ethnicity, the young people participating were predominantly White. Most studies collected data in mainstream schools and may therefore not be applicable to young people who infrequently or never attend school.

Characteristics of young people's views studies (n = 8)

All eight studies asked young people about their perceptions of, or attitudes towards, healthy eating, while none explicitly asked them what prevents them from eating healthily. Only two studies asked them what they think helps them to eat healthy foods, and only one asked for their ideas about what could or should be done to promote nutrition.

Young people tended to talk about food in terms of what they liked and disliked, rather than what was healthy/unhealthy. Healthy foods were predominantly associated with parents/adults and the home, while ‘fast food’ was associated with pleasure, friendship and social environments. Links were also made between food and appearance, with fast food perceived as having negative consequences on weight and facial appearance (and therefore a rationale for eating healthier foods). Attitudes towards healthy eating were generally positive, and the importance of a healthy diet was acknowledged. However, personal preferences for fast foods on grounds of taste tended to dominate food choice. Young people particularly valued the ability to choose what they eat.

Despite not being explicitly asked about barriers, young people discussed factors inhibiting their ability to eat healthily. These included poor availability of healthy meals at school, healthy foods sometimes being expensive and wide availability of, and personal preferences for, fast foods. Things that young people thought should be done to facilitate healthy eating included reducing the price of healthy snacks and better availability of healthy foods at school, at take-aways and in vending machines. Will-power and encouragement from the family were commonly mentioned support mechanisms for healthy eating, while teachers and peers were the least commonly cited sources of information on nutrition. Ideas for promoting healthy eating included the provision of information on nutritional content of school meals (mentioned by young women particularly) and better food labelling in general.

Table III shows the synthesis matrix which juxtaposes barriers and facilitators alongside results of outcome evaluations. There were some matches but also significant gaps between, on the one hand, what young people say are barriers to healthy eating, what helps them and what could or should be done and, on the other, soundly evaluated interventions that address these issues.

Synthesis matrix

Key to young people's views studies: Y1 , Dennison and Shepherd [ 56 ]; Y2 , Harris [ 57 ]; Y3 , McDougall [ 58 ]; Y4 , Miles and Eid [ 59 ]; Y5 , Roberts et al. [ 60 ]; Y6 , Ross [ 61 ]; Y7 , Watt and Sheiham [ 62 ]; Y8 , Watt and Sheiham [ 63 ]. Key to intervention studies: OE1 , Baranowski et al. [ 31 ]; OE2 , Bush et al. [ 32 ]; OE3 , Coates et al. [ 33 ]; OE4 , Ellison et al. [ 34 ]; OE5 , Flores [ 36 ]; OE6 , Fitzgibbon et al. [ 35 ]; OE7 , Hopper et al. [ 64 ]; OE8 , Holund [ 50 ]; OE9 , Kelder et al. [ 38 ]; OE10 , Klepp and Wilhelmsen [ 49 ]; OE11 , Moon et al. [ 48 ]; OE12 , Nader et al. [ 39 ]; OE13 , Nicklas et al. [ 40 ]; OE14 , Perry et al. [ 41 ]; OE15 , Petchers et al. [ 42 ]; OE16 , Schinke et al. [ 43 ]; OE17 , Wagner et al. [ 44 ]; OE18 , Vandongen et al. [ 51 ]; OE19 , Vartiainen et al. [ 46 ]; OE20 , Vartiainen et al. [ 47 ]; OE21 , Walter I [ 45 ]; OE22 , Walter II [ 45 ]. OE10, OE11, OE13, OE14, OE20, OE21 and OE22 denote a sound outcome evaluation. OE21 and OE22 are separate evaluations of the same intervention. Due to methodological limitations, we have judged the effects of OE22 to be unclear. Y1 and Y2 do not appear in the synthesis matrix as they did not explicitly report barriers or facilitators, and it was not possible for us to infer potential barriers or facilitators. However, these two studies did report what young people understood by healthy eating, their perceptions, and their views and opinions on the importance of eating a healthy diet. OE2, OE12, OE16 and OE17 do not appear in the synthesis matrix as they did not address any of the barriers or facilitators.

In terms of the school environment, most of the barriers identified by young people appear to have been addressed. At least two sound outcome evaluations demonstrated the effectiveness of increasing the availability of healthy foods in the school canteen [ 40, 47 ]. Furthermore, despite the low status of teachers and peers as sources of nutritional information, several soundly evaluated studies showed that they can be employed effectively to deliver nutrition interventions.

Young people associated parents and the home environment with healthy eating, and half of the sound outcome evaluations involved parents in the education of young people about nutrition. However, problems were sometimes experienced in securing parental attendance at intervention activities (e.g. seminar evenings). Why friends were not a common source of information about good nutrition is not clear. However, if peer pressure to eat unhealthy foods is a likely explanation, then it has been addressed by the peer-led interventions in three sound outcome evaluations (generally effectively) [ 41, 47, 49 ] and two outcome evaluations which did not meet the quality criteria (effectiveness unclear) [ 33, 50 ].

The fact that young people choose fast foods on grounds of taste has generally not been addressed by interventions, apart from one soundly evaluated effective intervention which included taste testings of fruit and vegetables [ 40 ]. Young people's concern over their appearance (which could be interpreted as both a barrier and a facilitator) has only been addressed in one of the sound outcome evaluations (which revealed an effective intervention) [ 41 ]. Will-power to eat healthy foods has only been examined in one outcome evaluation in the in-depth systematic review (judged to be sound and effective) (Walter I—Bronx evaluation) [ 45 ]. The need for information on nutrition was addressed by the majority of interventions in the in-depth systematic review. However, no studies were found which evaluated attempts to increase the nutritional content of school meals.

Barriers and facilitators relating to young people's practical and material resources were generally not addressed by interventions, soundly evaluated or otherwise. No studies were found which examined the effectiveness of interventions to lower the price of healthy foods. However, one soundly evaluated intervention was partially effective in increasing the availability of healthy snacks in community youth groups (Walter I—Bronx evaluation) [ 45 ]. At best, interventions have attempted to raise young people's awareness of environmental constraints on eating healthily, or encouraged them to lobby for increased availability of nutritious foods (in the case of the latter without reporting whether any changes have been effected as a result).

This review has systematically identified some of the barriers to, and facilitators of, healthy eating with young people, and illustrated to what extent they have been addressed by soundly evaluated effective interventions.

The evidence for effectiveness is mixed. Increases in knowledge of nutrition (measured in all but one study) were not consistent across studies, and changes in clinical risk factors (measured in two studies) varied, with one study detecting reductions in cholesterol and another detecting no change. Increases in reported healthy eating behaviour were observed, but mostly among young women revealing a distinct gender pattern in the findings. This was the case in four of the seven outcome evaluations (in which analysis was stratified by gender). The authors of one of the studies suggest that emphasis of the intervention on healthy weight management was more likely to appeal to young women. It was proposed that interventions directed at young men should stress the benefits of nutrition on strength, physical endurance and physical activity, particularly to appeal to those who exercise and play sports. Furthermore, age was a significant factor in determining effectiveness in one study [ 48 ]. Impact was greatest on young people in the 15- to 16-year age range (particularly for young women) in comparison with those aged 12–13 years, suggesting that dietary influences may vary with age. Tailoring the intervention to take account of age and gender is therefore crucial to ensure that interventions are as relevant and meaningful as possible.

Other systematic reviews of interventions to promote healthy eating (which included some of the studies with young people fitting the age range of this review) also show mixed results [ 52–55 ]. The findings of these reviews, while not being directly comparable in terms of conceptual framework, methods and age group, seem to offer some support for the findings of this review. The main message is that while there is some evidence to suggest effectiveness, the evidence base is limited. We have identified no comparable systematic reviews in this area.

Unlike other reviews, however, this study adopted a wider perspective through inclusion of studies of young people's views as well as effectiveness studies. A number of barriers to healthy eating were identified, including poor availability of healthy foods at school and in young people's social spaces, teachers and friends not always being a source of information/support for healthy eating, personal preferences for fast foods and healthy foods generally being expensive. Facilitating factors included information about nutritional content of foods/better labelling, parents and family members being supportive; healthy eating to improve or maintain one's personal appearance, will-power and better availability/lower pricing of healthy snacks.

Juxtaposing barriers and facilitators alongside effectiveness studies allowed us to examine the extent to which the needs of young people had been adequately addressed by evaluated interventions. To some extent they had. Most of the barriers and facilitators that related to the school and relationships with family and friends appear to have been taken into account by soundly evaluated interventions, although, as mentioned, their effectiveness varied. Many of the gaps tended to be in relation to young people as individuals (although our prioritization of interventions at the level of the community and society may have resulted in the exclusion of some of these interventions) and the wider determinants of health (‘practical and material resources’). Despite a wide search, we found few evaluations of strategies to improve nutritional labelling on foods particularly in schools or to increase the availability of affordable healthy foods particularly in settings where young people socialize. A number of initiatives are currently in place which may fill these gaps, but their effectiveness does not appear to have been reported yet. It is therefore crucial for any such schemes to be thoroughly evaluated and disseminated, at which point an updated systematic review would be timely.

This review is also constrained by the fact that its conclusions can only be supported by a relatively small proportion of the extant literature. Only seven of the 22 outcome evaluations identified were considered to be methodologically sound. As illustrated in Table III , a number of the remaining 15 interventions appear to modify barriers/build on facilitators but their results can only be judged unclear until more rigorous evaluation of these ‘promising’ interventions has been reported.

Finally, it is important to acknowledge that the majority of the outcome evaluations were conducted in the United States, and by virtue of the inclusion criteria, all the young people's views studies were UK based. The literature therefore might not be generalizable to other countries, where sociocultural values and socioeconomic circumstances may be quite different. Further evidence synthesis is needed on barriers to, and facilitators of, healthy eating and nutrition worldwide, particularly in developing countries.

The aim of this study was to survey what is known about the barriers to, and facilitators of, healthy eating among young people with a view to drawing out the implications for policy and practice. The review has mapped and quality screened the extant research in this area, and brought together the findings from evaluations of interventions aiming to promote healthy eating and studies which have elicited young people's views.

There has been much research activity in this area, yet it is disappointing that so few evaluation studies were methodologically strong enough to enable us to draw conclusions about effectiveness. There is some evidence to suggest that multicomponent school-based interventions can be effective, although effects tended to vary according to age and gender. Tailoring intervention messages accordingly is a promising approach which should therefore be evaluated. A key theme was the value young people place on choice and autonomy in relation to food. Increasing the provision and range of healthy, affordable snacks and meals in schools and social spaces will enable them to exercise their choice of healthier, tasty options.

We have identified that several barriers to, and facilitators of, healthy eating in young people have received little attention in evaluation research. Further work is needed to develop and evaluate interventions which modify or remove these barriers, and build on these facilitators. Further qualitative studies are also needed so that we can continue to listen to the views of young people. This is crucial if we are to develop and test meaningful, appropriate and effective health promotion strategies.

We would like to thank Chris Bonell and Dina Kiwan for undertaking data extraction. We would also like to acknowledge the invaluable help of Amanda Nicholas, James Thomas, Elaine Hogan, Sue Bowdler and Salma Master for support and helpful advice. The Department of Health, England, funds a specific programme of health promotion work at the EPPI-Centre. The views expressed in the report are those of the authors and not necessarily those of the Department of Health.

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• Published: 06 December 2017

Healthy food choices are happy food choices: Evidence from a real life sample using smartphone based assessments

• Deborah R. Wahl 1   na1 ,
• Karoline Villinger 1   na1 ,
• Laura M. König   ORCID: orcid.org/0000-0003-3655-8842 1 ,
• Katrin Ziesemer 1 ,
• Harald T. Schupp 1 &
• Britta Renner 1  

Scientific Reports volume  7 , Article number:  17069 ( 2017 ) Cite this article

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• Health sciences
• Human behaviour

Research suggests that “healthy” food choices such as eating fruits and vegetables have not only physical but also mental health benefits and might be a long-term investment in future well-being. This view contrasts with the belief that high-caloric foods taste better, make us happy, and alleviate a negative mood. To provide a more comprehensive assessment of food choice and well-being, we investigated in-the-moment eating happiness by assessing complete, real life dietary behaviour across eight days using smartphone-based ecological momentary assessment. Three main findings emerged: First, of 14 different main food categories, vegetables consumption contributed the largest share to eating happiness measured across eight days. Second, sweets on average provided comparable induced eating happiness to “healthy” food choices such as fruits or vegetables. Third, dinner elicited comparable eating happiness to snacking. These findings are discussed within the “food as health” and “food as well-being” perspectives on eating behaviour.

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Introduction.

When it comes to eating, researchers, the media, and policy makers mainly focus on negative aspects of eating behaviour, like restricting certain foods, counting calories, and dieting. Likewise, health intervention efforts, including primary prevention campaigns, typically encourage consumers to trade off the expected enjoyment of hedonic and comfort foods against health benefits 1 . However, research has shown that diets and restrained eating are often counterproductive and may even enhance the risk of long-term weight gain and eating disorders 2 , 3 . A promising new perspective entails a shift from food as pure nourishment towards a more positive and well-being centred perspective of human eating behaviour 1 , 4 , 5 . In this context, Block et al . 4 have advocated a paradigm shift from “food as health” to “food as well-being” (p. 848).

Supporting this perspective of “food as well-being”, recent research suggests that “healthy” food choices, such as eating more fruits and vegetables, have not only physical but also mental health benefits 6 , 7 and might be a long-term investment in future well-being 8 . For example, in a nationally representative panel survey of over 12,000 adults from Australia, Mujcic and Oswald 8 showed that fruit and vegetable consumption predicted increases in happiness, life satisfaction, and well-being over two years. Similarly, using lagged analyses, White and colleagues 9 showed that fruit and vegetable consumption predicted improvements in positive affect on the subsequent day but not vice versa. Also, cross-sectional evidence reported by Blanchflower et al . 10 shows that eating fruits and vegetables is positively associated with well-being after adjusting for demographic variables including age, sex, or race 11 . Of note, previous research includes a wide range of time lags between actual eating occasion and well-being assessment, ranging from 24 hours 9 , 12 to 14 days 6 , to 24 months 8 . Thus, the findings support the notion that fruit and vegetable consumption has beneficial effects on different indicators of well-being, such as happiness or general life satisfaction, across a broad range of time spans.

The contention that healthy food choices such as a higher fruit and vegetable consumption is associated with greater happiness and well-being clearly contrasts with the common belief that in particular high-fat, high-sugar, or high-caloric foods taste better and make us happy while we are eating them. When it comes to eating, people usually have a spontaneous “unhealthy = tasty” association 13 and assume that chocolate is a better mood booster than an apple. According to this in-the-moment well-being perspective, consumers have to trade off the expected enjoyment of eating against the health costs of eating unhealthy foods 1 , 4 .

A wealth of research shows that the experience of negative emotions and stress leads to increased consumption in a substantial number of individuals (“emotional eating”) of unhealthy food (“comfort food”) 14 , 15 , 16 , 17 . However, this research stream focuses on emotional eating to “smooth” unpleasant experiences in response to stress or negative mood states, and the mood-boosting effect of eating is typically not assessed 18 . One of the few studies testing the effectiveness of comfort food in improving mood showed that the consumption of “unhealthy” comfort food had a mood boosting effect after a negative mood induction but not to a greater extent than non-comfort or neutral food 19 . Hence, even though people may believe that snacking on “unhealthy” foods like ice cream or chocolate provides greater pleasure and psychological benefits, the consumption of “unhealthy” foods might not actually be more psychologically beneficial than other foods.

However, both streams of research have either focused on a single food category (fruit and vegetable consumption), a single type of meal (snacking), or a single eating occasion (after negative/neutral mood induction). Accordingly, it is unknown whether the boosting effect of eating is specific to certain types of food choices and categories or whether eating has a more general boosting effect that is observable after the consumption of both “healthy” and “unhealthy” foods and across eating occasions. Accordingly, in the present study, we investigated the psychological benefits of eating that varied by food categories and meal types by assessing complete dietary behaviour across eight days in real life.

Furthermore, previous research on the impact of eating on well-being tended to rely on retrospective assessments such as food frequency questionnaires 8 , 10 and written food diaries 9 . Such retrospective self-report methods rely on the challenging task of accurately estimating average intake or remembering individual eating episodes and may lead to under-reporting food intake, particularly unhealthy food choices such as snacks 7 , 20 . To avoid memory and bias problems in the present study we used ecological momentary assessment (EMA) 21 to obtain ecologically valid and comprehensive real life data on eating behaviour and happiness as experienced in-the-moment.

In the present study, we examined the eating happiness and satisfaction experienced in-the-moment, in real time and in real life, using a smartphone based EMA approach. Specifically, healthy participants were asked to record each eating occasion, including main meals and snacks, for eight consecutive days and rate how tasty their meal/snack was, how much they enjoyed it, and how pleased they were with their meal/snack immediately after each eating episode. This intense recording of every eating episode allows assessing eating behaviour on the level of different meal types and food categories to compare experienced eating happiness across meals and categories. Following the two different research streams, we expected on a food category level that not only “unhealthy” foods like sweets would be associated with high experienced eating happiness but also “healthy” food choices such as fruits and vegetables. On a meal type level, we hypothesised that the happiness of meals differs as a function of meal type. According to previous contention, snacking in particular should be accompanied by greater happiness.

Eating episodes

Overall, during the study period, a total of 1,044 completed eating episodes were reported (see also Table  1 ). On average, participants rated their eating happiness with M  = 77.59 which suggests that overall eating occasions were generally positive. However, experienced eating happiness also varied considerably between eating occasions as indicated by a range from 7.00 to 100.00 and a standard deviation of SD  = 16.41.

Food categories and experienced eating happiness

All eating episodes were categorised according to their food category based on the German Nutrient Database (German: Bundeslebensmittelschlüssel), which covers the average nutritional values of approximately 10,000 foods available on the German market and is a validated standard instrument for the assessment of nutritional surveys in Germany. As shown in Table  1 , eating happiness differed significantly across all 14 food categories, F (13, 2131) = 1.78, p  = 0.04. On average, experienced eating happiness varied from 71.82 ( SD  = 18.65) for fish to 83.62 ( SD  = 11.61) for meat substitutes. Post hoc analysis, however, did not yield significant differences in experienced eating happiness between food categories, p  ≥ 0.22. Hence, on average, “unhealthy” food choices such as sweets ( M  = 78.93, SD  = 15.27) did not differ in experienced happiness from “healthy” food choices such as fruits ( M  = 78.29, SD  = 16.13) or vegetables ( M  = 77.57, SD  = 17.17). In addition, an intraclass correlation (ICC) of ρ = 0.22 for happiness indicated that less than a quarter of the observed variation in experienced eating happiness was due to differences between food categories, while 78% of the variation was due to differences within food categories.

However, as Figure  1 (left side) depicts, consumption frequency differed greatly across food categories. Frequently consumed food categories encompassed vegetables which were consumed at 38% of all eating occasions ( n  = 400), followed by dairy products with 35% ( n  = 366), and sweets with 34% ( n  = 356). Conversely, rarely consumed food categories included meat substitutes, which were consumed in 2.2% of all eating occasions ( n  = 23), salty extras (1.5%, n  = 16), and pastries (1.3%, n  = 14).

Left side: Average experienced eating happiness (colour intensity: darker colours indicate greater happiness) and consumption frequency (size of the cycle) for the 14 food categories. Right side: Absolute share of the 14 food categories in total experienced eating happiness.

Amount of experienced eating happiness by food category

To account for the frequency of consumption, we calculated and scaled the absolute experienced eating happiness according to the total sum score. As shown in Figure  1 (right side), vegetables contributed the biggest share to the total happiness followed by sweets, dairy products, and bread. Clustering food categories shows that fruits and vegetables accounted for nearly one quarter of total eating happiness score and thus, contributed to a large part of eating related happiness. Grain products such as bread, pasta, and cereals, which are main sources of carbohydrates including starch and fibre, were the second main source for eating happiness. However, “unhealthy” snacks including sweets, salty extras, and pastries represented the third biggest source of eating related happiness.

Experienced eating happiness by meal type

To further elucidate the contribution of snacks to eating happiness, analysis on the meal type level was conducted. Experienced in-the-moment eating happiness significantly varied by meal type consumed, F (4, 1039) = 11.75, p  < 0.001. Frequencies of meal type consumption ranged from snacks being the most frequently logged meal type ( n  = 332; see also Table  1 ) to afternoon tea being the least logged meal type ( n  = 27). Figure  2 illustrates the wide dispersion within as well as between different meal types. Afternoon tea ( M  = 82.41, SD  = 15.26), dinner ( M  = 81.47, SD  = 14.73), and snacks ( M  = 79.45, SD  = 14.94) showed eating happiness values above the grand mean, whereas breakfast ( M  = 74.28, SD  = 16.35) and lunch ( M  = 73.09, SD  = 18.99) were below the eating happiness mean. Comparisons between meal types showed that eating happiness for snacks was significantly higher than for lunch t (533) = −4.44, p  = 0.001, d  = −0.38 and breakfast, t (567) = −3.78, p  = 0.001, d  = −0.33. However, this was also true for dinner, which induced greater eating happiness than lunch t (446) = −5.48, p  < 0.001, d  = −0.50 and breakfast, t (480) = −4.90, p  < 0.001, d  = −0.46. Finally, eating happiness for afternoon tea was greater than for lunch t (228) = −2.83, p  = 0.047, d  = −0.50. All other comparisons did not reach significance, t  ≤ 2.49, p  ≥ 0.093.

Experienced eating happiness per meal type. Small dots represent single eating events, big circles indicate average eating happiness, and the horizontal line indicates the grand mean. Boxes indicate the middle 50% (interquartile range) and median (darker/lighter shade). The whiskers above and below represent 1.5 of the interquartile range.

Control Analyses

In order to test for a potential confounding effect between experienced eating happiness, food categories, and meal type, additional control analyses within meal types were conducted. Comparing experienced eating happiness for dinner and lunch suggested that dinner did not trigger a happiness spill-over effect specific to vegetables since the foods consumed at dinner were generally associated with greater happiness than those consumed at other eating occasions (Supplementary Table  S1 ). Moreover, the relative frequency of vegetables consumed at dinner (73%, n  = 180 out of 245) and at lunch were comparable (69%, n  = 140 out of 203), indicating that the observed happiness-vegetables link does not seem to be mainly a meal type confounding effect.

Since the present study focuses on “food effects” (Level 1) rather than “person effects” (Level 2), we analysed the data at the food item level. However, participants who were generally overall happier with their eating could have inflated the observed happiness scores for certain food categories. In order to account for person-level effects, happiness scores were person-mean centred and thereby adjusted for mean level differences in happiness. The person-mean centred happiness scores ( M cwc ) represent the difference between the individual’s average happiness score (across all single in-the-moment happiness scores per food category) and the single happiness scores of the individual within the respective food category. The centred scores indicate whether the single in-the-moment happiness score was above (indicated by positive values) or below (indicated by negative values) the individual person-mean. As Table  1 depicts, the control analyses with centred values yielded highly similar results. Vegetables were again associated on average with more happiness than other food categories (although people might differ in their general eating happiness). An additional conducted ANOVA with person-centred happiness values as dependent variables and food categories as independent variables provided also a highly similar pattern of results. Replicating the previously reported analysis, eating happiness differed significantly across all 14 food categories, F (13, 2129) = 1.94, p  = 0.023, and post hoc analysis did not yield significant differences in experienced eating happiness between food categories, p  ≥ 0.14. Moreover, fruits and vegetables were associated with high happiness values, and “unhealthy” food choices such as sweets did not differ in experienced happiness from “healthy” food choices such as fruits or vegetables. The only difference between the previous and control analysis was that vegetables ( M cwc  = 1.16, SD  = 15.14) gained slightly in importance for eating-related happiness, whereas fruits ( M cwc  = −0.65, SD  = 13.21), salty extras ( M cwc  = −0.07, SD  = 8.01), and pastries ( M cwc  = −2.39, SD  = 18.26) became slightly less important.

This study is the first, to our knowledge, that investigated in-the-moment experienced eating happiness in real time and real life using EMA based self-report and imagery covering the complete diversity of food intake. The present results add to and extend previous findings by suggesting that fruit and vegetable consumption has immediate beneficial psychological effects. Overall, of 14 different main food categories, vegetables consumption contributed the largest share to eating happiness measured across eight days. Thus, in addition to the investment in future well-being indicated by previous research 8 , “healthy” food choices seem to be an investment in the in-the moment well-being.

Importantly, although many cultures convey the belief that eating certain foods has a greater hedonic and mood boosting effect, the present results suggest that this might not reflect actual in-the-moment experiences accurately. Even though people often have a spontaneous “unhealthy = tasty” intuition 13 , thus indicating that a stronger happiness boosting effect of “unhealthy” food is to be expected, the induced eating happiness of sweets did not differ on average from “healthy” food choices such as fruits or vegetables. This was also true for other stereotypically “unhealthy” foods such as pastries and salty extras, which did not show the expected greater boosting effect on happiness. Moreover, analyses on the meal type level support this notion, since snacks, despite their overall positive effect, were not the most psychologically beneficial meal type, i.e., dinner had a comparable “happiness” signature to snacking. Taken together, “healthy choices” seem to be also “happy choices” and at least comparable to or even higher in their hedonic value as compared to stereotypical “unhealthy” food choices.

In general, eating happiness was high, which concurs with previous research from field studies with generally healthy participants. De Castro, Bellisle, and Dalix 22 examined weekly food diaries from 54 French subjects and found that most of the meals were rated as appealing. Also, the observed differences in average eating happiness for the 14 different food categories, albeit statistically significant, were comparable small. One could argue that this simply indicates that participants avoided selecting bad food 22 . Alternatively, this might suggest that the type of food or food categories are less decisive for experienced eating happiness than often assumed. This relates to recent findings in the field of comfort and emotional eating. Many people believe that specific types of food have greater comforting value. Also in research, the foods eaten as response to negative emotional strain, are typically characterised as being high-caloric because such foods are assumed to provide immediate psycho-physical benefits 18 . However, comparing different food types did not provide evidence for the notion that they differed in their provided comfort; rather, eating in general led to significant improvements in mood 19 . This is mirrored in the present findings. Comparing the eating happiness of “healthy” food choices such as fruits and vegetables to that of “unhealthy” food choices such as sweets shows remarkably similar patterns as, on average, they were associated with high eating happiness and their range of experiences ranged from very negative to very positive.

This raises the question of why the idea that we can eat indulgent food to compensate for life’s mishaps is so prevailing. In an innovative experimental study, Adriaanse, Prinsen, de Witt Huberts, de Ridder, and Evers 23 led participants believe that they overate. Those who characterised themselves as emotional eaters falsely attributed their over-consumption to negative emotions, demonstrating a “confabulation”-effect. This indicates that people might have restricted self-knowledge and that recalled eating episodes suffer from systematic recall biases 24 . Moreover, Boelsma, Brink, Stafleu, and Hendriks 25 examined postprandial subjective wellness and objective parameters (e.g., ghrelin, insulin, glucose) after standardised breakfast intakes and did not find direct correlations. This suggests that the impact of different food categories on wellness might not be directly related to biological effects but rather due to conditioning as food is often paired with other positive experienced situations (e.g., social interactions) or to placebo effects 18 . Moreover, experimental and field studies indicate that not only negative, but also positive, emotions trigger eating 15 , 26 . One may speculate that selective attention might contribute to the “myth” of comfort food 19 in that people attend to the consumption effect of “comfort” food in negative situation but neglect the effect in positive ones.

The present data also show that eating behaviour in the real world is a complex behaviour with many different aspects. People make more than 200 food decisions a day 27 which poses a great challenge for the measurement of eating behaviour. Studies often assess specific food categories such as fruit and vegetable consumption using Food Frequency Questionnaires, which has clear advantages in terms of cost-effectiveness. However, focusing on selective aspects of eating and food choices might provide only a selective part of the picture 15 , 17 , 22 . It is important to note that focusing solely on the “unhealthy” food choices such as sweets would have led to the conclusion that they have a high “indulgent” value. To be able to draw conclusions about which foods make people happy, the relation of different food categories needs to be considered. The more comprehensive view, considering the whole dietary behaviour across eating occasions, reveals that “healthy” food choices actually contributed the biggest share to the total experienced eating happiness. Thus, for a more comprehensive understanding of how eating behaviours are regulated, more complete and sensitive measures of the behaviour are necessary. Developments in mobile technologies hold great promise for feasible dietary assessment based on image-assisted methods 28 .

As fruits and vegetables evoked high in-the-moment happiness experiences, one could speculate that these cumulate and have spill-over effects on subsequent general well-being, including life satisfaction across time. Combing in-the-moment measures with longitudinal perspectives might be a promising avenue for future studies for understanding the pathways from eating certain food types to subjective well-being. In the literature different pathways are discussed, including physiological and biochemical aspects of specific food elements or nutrients 7 .

The present EMA based data also revealed that eating happiness varied greatly within the 14 food categories and meal types. As within food category variance represented more than two third of the total observed variance, happiness varied according to nutritional characteristics and meal type; however, a myriad of factors present in the natural environment can affect each and every meal. Thus, widening the “nourishment” perspective by including how much, when, where, how long, and with whom people eat might tell us more about experienced eating happiness. Again, mobile, in-the-moment assessment opens the possibility of assessing the behavioural signature of eating in real life. Moreover, individual factors such as eating motives, habitual eating styles, convenience, and social norms are likely to contribute to eating happiness variance 5 , 29 .

A key strength of this study is that it was the first to examine experienced eating happiness in non-clinical participants using EMA technology and imagery to assess food intake. Despite this strength, there are some limitations to this study that affect the interpretation of the results. In the present study, eating happiness was examined on a food based level. This neglects differences on the individual level and might be examined in future multilevel studies. Furthermore, as a main aim of this study was to assess real life eating behaviour, the “natural” observation level is the meal, the psychological/ecological unit of eating 30 , rather than food categories or nutrients. Therefore, we cannot exclude that specific food categories may have had a comparably higher impact on the experienced happiness of the whole meal. Sample size and therefore Type I and Type II error rates are of concern. Although the total number of observations was higher than in previous studies (see for example, Boushey et al . 28 for a review), the number of participants was small but comparable to previous studies in this field 20 , 31 , 32 , 33 . Small sample sizes can increase error rates because the number of persons is more decisive than the number of nested observations 34 . Specially, nested data can seriously increase Type I error rates, which is rather unlikely to be the case in the present study. Concerning Type II error rates, Aarts et al . 35 illustrated for lower ICCs that adding extra observations per participant also increases power, particularly in the lower observation range. Considering the ICC and the number of observations per participant, one could argue that the power in the present study is likely to be sufficient to render the observed null-differences meaningful. Finally, the predominately white and well-educated sample does limit the degree to which the results can be generalised to the wider community; these results warrant replication with a more representative sample.

Despite these limitations, we think that our study has implications for both theory and practice. The cumulative evidence of psychological benefits from healthy food choices might offer new perspectives for health promotion and public-policy programs 8 . Making people aware of the “healthy = happy” association supported by empirical evidence provides a distinct and novel perspective to the prevailing “unhealthy = tasty” folk intuition and could foster eating choices that increase both in-the-moment happiness and future well-being. Furthermore, the present research lends support to the advocated paradigm shift from “food as health” to “food as well-being” which entails a supporting and encouraging rather constraining and limiting view on eating behaviour.

The study conformed with the Declaration of Helsinki. All study protocols were approved by University of Konstanz’s Institutional Review Board and were conducted in accordance with guidelines and regulations. Upon arrival, all participants signed a written informed consent.

Participants

Thirty-eight participants (28 females: average age = 24.47, SD  = 5.88, range = 18–48 years) from the University of Konstanz assessed their eating behaviour in close to real time and in their natural environment using an event-based ambulatory assessment method (EMA). No participant dropped out or had to be excluded. Thirty-three participants were students, with 52.6% studying psychology. As compensation, participants could choose between taking part in a lottery (4 × 25€) or receiving course credits (2 hours).

Participants were recruited through leaflets distributed at the university and postings on Facebook groups. Prior to participation, all participants gave written informed consent. Participants were invited to the laboratory for individual introductory sessions. During this first session, participants installed the application movisensXS (version 0.8.4203) on their own smartphones and downloaded the study survey (movisensXS Library v4065). In addition, they completed a short baseline questionnaire, including demographic variables like age, gender, education, and eating principles. Participants were instructed to log every eating occasion immediately before eating by using the smartphone to indicate the type of meal, take pictures of the food, and describe its main components using a free input field. Fluid intake was not assessed. Participants were asked to record their food intake on eight consecutive days. After finishing the study, participants were invited back to the laboratory for individual final interviews.

Immediately before eating participants were asked to indicate the type of meal with the following five options: breakfast, lunch, afternoon tea, dinner, snack. In Germany, “afternoon tea” is called “Kaffee & Kuchen” which directly translates as “coffee & cake”. It is similar to the idea of a traditional “afternoon tea” meal in UK. Specifically, in Germany, people have “Kaffee & Kuchen” in the afternoon (between 4–5 pm) and typically coffee (or tea) is served with some cake or cookies. Dinner in Germany is a main meal with mainly savoury food.

After each meal, participants were asked to rate their meal on three dimensions. They rated (1) how much they enjoyed the meal, (2) how pleased they were with their meal, and (3) how tasty their meal was. Ratings were given on a scale of one to 100. For reliability analysis, Cronbach’s Alpha was calculated to assess the internal consistency of the three items. Overall Cronbach’s alpha was calculated with α = 0.87. In addition, the average of the 38 Cronbach’s alpha scores calculated at the person level also yielded a satisfactory value with α = 0.83 ( SD  = 0.24). Thirty-two of 38 participants showed a Cronbach’s alpha value above 0.70 (range = 0.42–0.97). An overall score of experienced happiness of eating was computed using the average of the three questions concerning the meals’ enjoyment, pleasure, and tastiness.

Analytical procedure

The food pictures and descriptions of their main components provided by the participants were subsequently coded by independent and trained raters. Following a standardised manual, additional components displayed in the picture were added to the description by the raters. All consumed foods were categorised into 14 different food categories (see Table  1 ) derived from the food classification system designed by the German Nutrition Society (DGE) and based on the existing food categories of the German Nutrient Database (Max Rubner Institut). Liquid intake and preparation method were not assessed. Therefore, fats and additional recipe ingredients were not included in further analyses, because they do not represent main elements of food intake. Further, salty extras were added to the categorisation.

No participant dropped out or had to be excluded due to high missing rates. Missing values were below 5% for all variables. The compliance rate at the meal level cannot be directly assessed since the numbers of meals and snacks can vary between as well as within persons (between days). As a rough compliance estimate, the numbers of meals that are expected from a “normative” perspective during the eight observation days can be used as a comparison standard (8 x breakfast, 8 × lunch, 8 × dinner = 24 meals). On average, the participants reported M  = 6.3 breakfasts ( SD  = 2.3), M  = 5.3 lunches ( SD  = 1.8), and M  = 6.5 dinners ( SD  = 2.0). In comparison to the “normative” expected 24 meals, these numbers indicate a good compliance (approx. 75%) with a tendency to miss six meals during the study period (approx. 25%). However, the “normative” expected 24 meals for the study period might be too high since participants might also have skipped meals (e.g. breakfast). Also, the present compliance rates are comparable to other studies. For example, Elliston et al . 36 recorded 3.3 meal/snack reports per day in an Australian adult sample and Casperson et al . 37 recorded 2.2 meal reports per day in a sample of adolescents. In the present study, on average, M  = 3.4 ( SD  = 1.35) meals or snacks were reported per day. These data indicate overall a satisfactory compliance rate and did not indicate selective reporting of certain food items.

To graphically visualise data, Tableau (version 10.1) was used and for further statistical analyses, IBM SPSS Statistics (version 24 for Windows).

Data availability

The dataset generated and analysed during the current study is available from the corresponding authors on reasonable request.

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Bolger, N., Stadler, G. & Laurenceau, J. P. Power analysis for intensive longitudinal studies in Handbook of research methods for studying daily life (ed . Mehl, M. R. & Conner, T. S.) 285–301 (New York: The Guilford Press, 2012).

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Elliston, K. G., Ferguson, S. G., Schüz, N. & Schüz, B. Situational cues andmomentary food environment predict everyday eating behavior in adults withoverweight and obesity. Health Psychology 36 , 337–345 (2017).

Casperson, S. L. et al . A mobile phone food record app to digitally capture dietary intake for adolescents in afree-living environment: usability study. JMIR mHealth and uHealth 3 , e30 (2015).

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Acknowledgements

This research was supported by the Federal Ministry of Education and Research within the project SmartAct (Grant 01EL1420A, granted to B.R. & H.S.). The funding source had no involvement in the study’s design; the collection, analysis, and interpretation of data; the writing of the report; or the decision to submit this article for publication. We thank Gudrun Sproesser, Helge Giese, and Angela Whale for their valuable support.

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Deborah R. Wahl and Karoline Villinger contributed equally to this work.

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Department of Psychology, University of Konstanz, Konstanz, Germany

Deborah R. Wahl, Karoline Villinger, Laura M. König, Katrin Ziesemer, Harald T. Schupp & Britta Renner

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B.R. & H.S. developed the study concept. All authors participated in the generation of the study design. D.W., K.V., L.K. & K.Z. conducted the study, including participant recruitment and data collection, under the supervision of B.R. & H.S.; D.W. & K.V. conducted data analyses. D.W. & K.V. prepared the first manuscript draft, and B.R. & H.S. provided critical revisions. All authors approved the final version of the manuscript for submission.

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Wahl, D.R., Villinger, K., König, L.M. et al. Healthy food choices are happy food choices: Evidence from a real life sample using smartphone based assessments. Sci Rep 7 , 17069 (2017). https://doi.org/10.1038/s41598-017-17262-9

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• Qualitative research study on addressing barriers to healthy diet among low-income individuals at an urban, safety-net hospital
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• Erin Cahill 1 ,
• Stacie R Schmidt 2 ,
• Tracey L Henry 2 ,
• http://orcid.org/0000-0002-2791-9960 Gayathri Kumar 3 ,
• Sara Berney 4 ,
• Jada Bussey-Jones 2 and
• Amy Webb Girard 1
• 1 Emory University School of Public Health , Atlanta , Georgia , USA
• 2 Division of General Medicine and Geriatrics , Emory University School of Medicine , Atlanta , Georgia , USA
• 3 Emory University School of Medicine , Atlanta , Georgia , USA
• 4 North Carolina State University School of Public and International Affairs , Raleigh , North Carolina , USA
• Correspondence to Tracey L Henry, General Medicine and Geriatrics, Emory University, Atlanta, GA 30322, USA; henrytracey{at}hotmail.com

Background Some American households experience food insecurity, where access to adequate food is limited by lack of money and other resources. As such, we implemented a free 6-month Fruit and Vegetable Prescription Program within a large urban safety-net hospital .

Methods 32 participants completed a baseline and postintervention qualitative evaluation about food-related behaviour 6 months after study completion. Deductive codes were developed based on the key topics addressed in the interviews; inductive codes were identified from analytically reading the transcripts. Transcripts were coded in MAXQDA V.12 (Release 12.3.2).

Results The information collected in the qualitative interviews highlights the many factors that affect dietary habits, including the environmental and individual influences that play a role in food choices people make. Participants expressed very positive sentiments overall about their programme participation.

Conclusions A multifaceted intervention that targets individual behaviour change, enhances nutritional knowledge and skills, and reduces socioeconomic barriers to accessing fresh produce may enhance participant knowledge and self-efficacy around healthy eating. However, socioeconomic factors remain as continual barriers to sustaining healthy eating over the long term. Ongoing efforts that address social determinants of health may be necessary to promote sustainability of behaviour change.

• nutritional treatment
• nutrition assessment
• malnutrition

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https://doi.org/10.1136/bmjnph-2020-000064

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Introduction

Most US households have consistent, reliable access to enough food for active, healthy living. 1 Some American households, however, experience food insecurity, which is defined by the US Department of Agriculture (USDA) as a lack of consistent access to enough food for an active, healthy life. 1 In 2016, an estimated one in eight Americans were food insecure, equating to 42 million people. 1 Food insecurity can be influenced by a number of factors including income, employment and disability (Healthy People 2020). The prevalence of food insecurity varies across subgroups of the US population; some groups are more likely to be food insecure than others. The distribution of food insecurity across residence areas shows that the majority of food-insecure households are in metropolitan areas, with income as one of the primary characteristics associated with food insecurity. 2 Lower income households have a higher prevalence of food insecurity compared with higher income households. 2 Furthermore, food insecurity may increase the risk for obesity and chronic diseases. 3

Food assistance programmes such as the Women, Infants and Children programme and the Supplemental Nutrition Assistance Program (SNAP) help address barriers to accessing healthy food and may reduce food insecurity. 4 5 Interventions implemented within healthcare settings—such as onsite food pantries and mobile food distributions—that serve food-insecure populations have also been effective. 3

Our hospital is a large, urban safety-net hospital in metro Atlanta that provides care to low income and other vulnerable populations. In 2015, an assessment of food insecurity was conducted in the hospital’s primary care centre, where 323 patients completed a questionnaire that included questions regarding age, sex, race, household income, number of people in the household, zip code, diabetes status, the USDA two-item food security screener and SNAP utilisation. The study revealed that 55% of low-income patients receiving outpatient care were food-insecure. 6 To address this issue, we implemented a free 6-month Fruit and Vegetable Prescription Program (FVRx) within a primary care clinic at the hospital in 2016.

Eligible participants had a Body Mass Index (BMI)>30 and at least one associated chronic condition, such as diabetes. Components of the FVRx programme included 4 weeks of fruit and vegetable prescriptions to be redeemed for fresh fruits and vegetables packaged locally, monthly interactive groups classes on nutrition, and monthly cooking classes providing evidence-based nutrition and cooking skills education.

On completion of the programme, we conducted a postintervention qualitative evaluation among participants of the FVRx programme to assess (1) constraints on programme participation, (2) barriers to maintaining a healthy diet among participants, (3) participant capacity to sustain behaviour change during and after completion of the programme, in an effort to identify strategies that could improve participant retention and satisfaction with future programmes. This paper describes the results of this evaluation.

This evaluation incorporated a qualitative research study design. A telephone interview script was used to ask questions about patients’ experience with the FVRx programme, grocery shopping habits and the patient’s current fruit and vegetable consumption (see online supplementary appendix A ). Interview questions were developed to address the main goals of the evaluation, which were to investigate constraints on programme participation, barriers to maintaining a healthy diet among participants postintervention and strategies to improve participant retention.

Supplemental material

Enrolment of the 32 patients into the FVRx study occurred in June 2016; participation in the FVRx programme by the 32 participants took place from July 2016 to December 2016. Participants were referred to the programme by their primary care provider if they had a BMI>30 and at least one diet-related illness. All 32 participants had access to a phone rather their own or a family member’s phone.

The first author contacted the original 32 patients who participated in the FVRx programme by phone in June 2017, approximately 6 months after completing the programme. Six of 32 participants did not answer but had a working voicemail, for which a maximum of two messages were left. Additionally, the team encountered the wrong number for three participants, and full mailboxes for two numbers. Two numbers went unanswered (no voicemail) and one number was disconnected. Thus, of the 32 participants, 18 were reached by phone and verbally consented to participate in follow-up evaluation. Seven participants completed the programme while 11 participants attended a few classes but dropped out. None of the FVRx participants contacted refused to be interviewed.

Interviews were recorded using the TapeACall app and transcribed verbatim. Four interviews were not recorded due to technical difficulties with the app. In these instances, detailed notes were taken and were used in analyses in lieu of verbatim transcripts. A codebook was developed consisting of deductive and inductive codes. Deductive codes were developed based on the key topics addressed in the interviews; inductive codes were identified from analytically reading the transcripts. Transcripts were uploaded to and coded in MAXQDA V.12 (Release 12.3.2). Constant comparative analysis was used to compare experiences and perspectives between those who graduated and those who dropped out. This comparison was undertaken to understand how capabilities, motivations and opportunities changed over the course of their participation, and how this ultimately influenced programme retention.

Participant data on demographic and socioeconomic characteristics were collected at baseline ( table 1 ).

• View inline

Demographics of the FVRx participants*

Overall participant perspectives of the program

When asked about their main motivation for enrolling in the programme, most participants reported the desire to eat healthier and the desire to lose weight. ‘Motivation to enrol’ was one of the codes used in MAXQDA for the analysis, with subcodes of lose weight, eat healthy or doctor recommended. Of the 18 people interviewed, 8 or 44% mentioned enrolling in the programme to lose weight, and 11 or 61% mentioned enrolling to learn to eat healthy. When asked about the most useful thing they learnt in the programme, nearly all the respondents mentioned an improvement in their knowledge of nutrition, such as learning correct portion sizes or reading nutrition labels. Other participants reported enjoying meeting new people and having a sense of camaraderie and support from the group. Additionally, over half of the participants, including those who did not finish the classes, said they would like to enrol in the programme again if given the opportunity.

Participant capacity to sustain behaviour change

When asked about fruit and vegetable consumption since the programme ended, most respondents reported they continue to eat a good amount of fruits and vegetables ( Excerpts: ‘I’m beginning to start to like broccoli and been doing some kale’ and ‘Yes, I do a lot of salads and fruits…I am loving the fresh fruits’). The majority of participants reported that they continue to use the lessons they learnt in the healthy living and cooking classes when making food choices.

Of the 18, 15 or 83% respondents mentioned nutrition knowledge as a positive takeaway from the programme, and 15 of the 18 or 83% respondents also mentioned continuing to consume fruits and vegetables.

Constraints on program participation

Two participants mentioned that even though they were getting free food with the vouchers, it was still expensive ( Excerpt: ‘I had to pay a co-pay each time, and it just got too expensive…’). Others reported challenges in having transportation to attend the Healthy Living Classes ( Excerpt: ‘I wasn’t able at that time to have the transportation to go to all of them’). Another participant with mobility limitations had difficulty picking up their packaged fresh produce. Those who did not graduate cited their own or a family member’s poor health; out of pocket costs (ie, copays); lack of affordable transportation or parking; and/or inconvenient scheduling of the sessions. ‘Dropout/Missed Sessions Reasons’ code had a subcode of transportation/mobility, and four of the 18 or 22% of the respondents mentioned lack of transportation as their reason for not attending classes.

Barriers to maintaining a healthy diet among participants

When asked what they believe the biggest barrier to healthy eating is, the most commonly reported answer was cost (n=6) ( Excerpt: ‘…for people like me, that have so many medical bills…it’s easier to get the cheaper, unhealthy things…’). Another participant explained that her family often gets groceries from the food pantry, where the healthy options such as fresh produce are limited. Another reported barrier was finding the time to cook healthy meals, especially when working or caring for children. Over half of the respondents mentioned shopping at multiple stores in order to obtain the lowest prices ( Excerpt: ‘I shop at the cheapest store I can get it (fruits and vegetables) at’).

This evaluation reveals that most participants of the FVRx programme reported improved knowledge of nutrition and continue to consume fresh fruits and vegetables months after completion of the programme. However, FVRx participants continue to encounter barriers to maintaining a healthy diet with the most commonly reported barriers being the cost of fresh produce and competing priorities such as child care which prohibited time dedicated to healthy food preparation.

Lifestyle change interventions have been shown to be effective in the treatment and prevention of diet-related illnesses such as diabetes. 7 Similarly, other research has shown the use of goal setting and small groups to be promising tools in dietary behaviour modification, both of which are used in FVRx. 8 However, lifestyle change initiatives and health education may be ineffective in increasing healthy food consumption if they do not take into consideration other factors such as neighbourhood segregation, market strategies and poverty as important modifiers of accessibility. 9 In order to address the food insecurity in these low-income patients, we have to find ways to tackle the cost barriers they face when it comes to accessing healthier foods. Our FVRx programme attempts to integrate both health education and monetary incentives through vouchers, enabling improvement in participant knowledge of healthy eating and addressing any socioeconomic barriers to eating fresh fruits and vegetables during the intervention.

Without access to free fruits and vegetables through vouchers, consumption of fruits and vegetables continued to be met with challenges such as their cost and competing priorities that precluded time for healthy food preparation. This highlights the importance of incorporating strategies that equip participants with the knowledge and self-efficacy to continue healthy behaviours, even after the programme has ended. While the healthy living curriculum and cooking classes work to provide participants with those tools, conducting follow-up with participants at various intervals, via phone calls or hosting alumni events to serve as booster sessions, could be useful strategies to increase likelihood of continued behaviour.

There are a few limitations to this study. One limitation is that qualitative data were collected from a small sample of participants of the programme. However, this study was intended to be an evaluation of a pilot programme, and results will be used to inform expansion of the FVRx programme within our hospital.

Given the poverty status of many of our patients (figure 1), it is expected that many would have transient housing, possibly leading to the wrong number for three participants, and a disconnected telephone numbers for one another participant. Such social determinants might have also affected the ability to afford transportation to and from classes, as well as copays for the classes. We suspect these factors contributed to the high dropout rate (n=11) and the 44% non-response rate when calling patients 6 months postcompletion of the programme. This is potentially supported by our findings among the six respondents who mentioned cost as the biggest barrier; five of those were individuals who did not finish the programme. The interviews show that nearly all 18 of the respondents had the same motivation for starting the programme: to learn to eat better; however for those that did not ‘graduate’ (n=11), they reported current life circumstances as preventing them from completing the programme. This included health issues (their own or that of a family member), scheduling or difficulty with transportation to the programme site were reported by respondents as reasons for dropping out. These types of variables are not able to be addressed through the FVRx programming in the pilot phase of the programme, but should be researched and addressed in larger studies moving forward

Our multifaceted FVRx pilot programme enhanced participants’ nutritional knowledge and skills and continued consumption of fresh produce months after completion of the programme. However, socioeconomic factors remain as continual barriers to sustaining healthy eating. Additional efforts may be necessary to promote sustained healthy eating, such as skill building around gardening and growing fresh produce in the home. Using these types of innovative approaches may empower lower income populations to overcome barriers to healthy behaviour change. Efforts to improve participant retention in the programme, expand the programme to more participants and promote sustained behaviour change on programme completion are underway.

Acknowledgments

We would like to acknowledge Wholesome Wave Georgia, Project Open Hand, and The Common Market for their contributions to the FVRx program at our site. We are appreciative to Grady Memorial Hospital and the Primary Care Center for their innovative role in implementing systems change by supporting patient-centred group classes and FVRx prescriptions at our site.

• Coleman-Jensen A ,
• Rabbitt MP ,
• Gregory CA , et al
• Rabbitt M ,
• Laraia BA ,
• Oddo VM , et al
• Kreider B ,
• Pepper JV ,
• Ratcliffe C ,
• McKernan S-M ,
• Knowler WC ,
• Barrett-Connor E ,
• Fowler SE , et al
• Ammerman AS ,
• Lindquist CH ,
• Lohr KN , et al
• Azétsop J ,

Contributors All authors listed have contributed sufficiently to the project to be included as authors, and all those who are qualified to be authors are listed in the author byline. Authors’ contributions: EC conducted the study and the analysis for the study, and helped to write up the study. SRS (MD) gave idea for study and helped plan and conduct the study and helped write up the study. TLH (MD, MPH, MS, FACP) helped plan, developed and conducted the study along with helping write up the study. SB helped plan, developed and conducted the study along with helping to write up the study. GK (MD) helped plan the study and write up the study. JB-J (MD, FACP) helped plan and developed the study. AWG (PhD) supervised and assisted EC in conducting the study and analysing the study and helped to write up the study.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient consent for publication Not required.

Ethics approval All study protocols, informed consent documents and tools were reviewed and approved by the hospital review board and deemed exempt from review by Emory University Institutional Review Board. All participants gave verbal informed consent to participate and provided permission to record the call.

Provenance and peer review Not commissioned; externally peer reviewed.

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For patients with Type II Diabetes, dietary management is known to improve outcomes. However, the project site had no current evidence-based program in place to address dietary management. The purpose of this quantitative quasi-experimental quality improvement project was to determine if the implementation of the Association of Diabetes Care and Education Specialists (ADCES7) Framework on Self-Care Behaviors™ Healthy Eating Program would impact the pre-prandial blood glucose levels among adult type II diabetic patients in a nursing rehabilitation center in New York over four-weeks. The scientific underpinnings of the project were Nola Pender’s middle-range theory, the health promotion model and Everette Roger’s diffusion of innovation change model. The total sample size was 32 adult type II diabetic patients. Data on the pre-prandial blood glucose levels was measured using Nova Stat Strip glucometer at baseline and four weeks post-implementation. A paired t -test analysis showed a clinical and statistically significant reduction in the pre-prandial blood glucose levels from baseline ( M = 169.59, SD = 34.71) to post-implementation ( M = 160.96, SD = 32.08), t (31) = 2.52, p = .017. The findings suggest that the ADCES Framework on Self-Care Behaviors™ Healthy Eating Program may improve the blood glucose levels among this population. Recommendations include continuation of the project at the current site, and evaluating the impact of the framework on hemoglobin A1C levels over six months.

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12.4 Annotated Student Sample: "Healthy Diets from Sustainable Sources Can Save the Earth" by Lily Tran

Learning outcomes.

By the end of this section, you will be able to:

• Analyze how writers use evidence in research writing.
• Analyze the ways a writer incorporates sources into research writing, while retaining their own voice.
• Explain the use of headings as organizational tools in research writing.
• Analyze how writers use evidence to address counterarguments when writing a research essay.

Introduction

In this argumentative research essay for a first-year composition class, student Lily Tran creates a solid, focused argument and supports it with researched evidence. Throughout the essay, she uses this evidence to support cause-and-effect and problem-solution reasoning, make strong appeals, and develop her ethos on the topic.

Living by Their Own Words

Food as change.

public domain text For the human race to have a sustainable future, massive changes in the way food is produced, processed, and distributed are necessary on a global scale. end public domain text

annotated text Purpose. Lily Tran refers to what she sees as the general purpose for writing this paper: the problem of current global practices in food production, processing, and distribution. By presenting the “problem,” she immediately prepares readers for her proposed solution. end annotated text

public domain text The required changes will affect nearly all aspects of life, including not only world hunger but also health and welfare, land use and habitats, water quality and availability, energy use and production, greenhouse gas emissions and climate change, economics, and even cultural and social values. These changes may not be popular, but they are imperative. The human race must turn to sustainable food systems that provide healthy diets with minimal environmental impact—and starting now. end public domain text

annotated text Thesis. Leading up to this clear, declarative thesis statement are key points on which Tran will expand later. In doing this, she presents some foundational evidence that connects the problem to the proposed solution. end annotated text

THE COMING FOOD CRISIS

public domain text The world population has been rising exponentially in modern history. From 1 billion in 1804, it doubled to approximately 2 billion by 1927, then doubled again to approximately 4 billion in 1974. By 2019, it had nearly doubled again, rising to 7.7 billion (“World Population by Year”). It has been projected to reach nearly 10 billion by 2050 (Berners-Lee et al.). At the same time, the average life span also has been increasing. These situations have led to severe stress on the environment, particularly in the demands for food. It has been estimated, for example, that by 2050, milk production will increase 58 percent and meat production 73 percent (Chai et al.). end public domain text

annotated text Evidence. In this first supporting paragraph, Tran uses numerical evidence from several sources. This numerical data as evidence helps establish the projection of population growth. By beginning with such evidence, Tran underscores the severity of the situation. end annotated text

public domain text Theoretically, the planet can produce enough food for everyone, but human activities have endangered this capability through unsustainable practices. Currently, agriculture produces 10–23 percent of global greenhouse gas emissions. Greenhouse gases—the most common being carbon dioxide, methane, nitrous oxide, and water vapor— trap heat in the atmosphere, reradiate it, and send it back to Earth again. Heat trapped in the atmosphere is a problem because it causes unnatural global warming as well as air pollution, extreme weather conditions, and respiratory diseases. end public domain text

annotated text Audience. With her audience in mind, Tran briefly explains the problem of greenhouse gases and global warming. end annotated text

public domain text It has been estimated that global greenhouse gas emissions will increase by as much as 150 percent by 2030 (Chai et al.). Transportation also has a negative effect on the environment when foods are shipped around the world. As Joseph Poore of the University of Oxford commented, “It’s essential to be mindful about everything we consume: air-transported fruit and veg can create more greenhouse gas emissions per kilogram than poultry meat, for example” (qtd. in Gray). end public domain text

annotated text Transition. By beginning this paragraph with her own transition of ideas, Tran establishes control over the organization and development of ideas. Thus, she retains her sources as supports and does not allow them to dominate her essay. end annotated text

public domain text Current practices have affected the nutritional value of foods. Concentrated animal-feeding operations, intended to increase production, have had the side effect of decreasing nutritional content in animal protein and increasing saturated fat. One study found that an intensively raised chicken in 2017 contained only one-sixth of the amount of omega-3 fatty acid, an essential nutrient, that was in a chicken in 1970. Today the majority of calories in chicken come from fat rather than protein (World Wildlife Fund). end public domain text

annotated text Example. By focusing on an example (chicken), Tran uses specific research data to develop the nuance of the argument. end annotated text

public domain text Current policies such as government subsidies that divert food to biofuels are counterproductive to the goal of achieving adequate global nutrition. Some trade policies allow “dumping” of below-cost, subsidized foods on developing countries that should instead be enabled to protect their farmers and meet their own nutritional needs (Sierra Club). Too often, agriculture’s objectives are geared toward maximizing quantities produced per acre rather than optimizing output of critical nutritional needs and protection of the environment. end public domain text

AREAS OF CONCERN

Hunger and nutrition.

annotated text Headings and Subheadings. Throughout the essay, Tran has created headings and subheadings to help organize her argument and clarify it for readers. end annotated text

public domain text More than 820 million people around the world do not have enough to eat. At the same time, about a third of all grains and almost two-thirds of all soybeans, maize, and barley crops are fed to animals (Barnard). According to the World Health Organization, 462 million adults are underweight, 47 million children under 5 years of age are underweight for their height, 14.3 million are severely underweight for their height, and 144 million are stunted (“Malnutrition”). About 45 percent of mortality among children under 5 is linked to undernutrition. These deaths occur mainly in low- and middle-income countries where, in stark contrast, the rate of childhood obesity is rising. Globally, 1.9 billion adults and 38.3 million children are overweight or obese (“Obesity”). Undernutrition and obesity can be found in the same household, largely a result of eating energy-dense foods that are high in fat and sugars. The global impact of malnutrition, which includes both undernutrition and obesity, has lasting developmental, economic, social, and medical consequences. end public domain text

public domain text In 2019, Berners-Lee et al. published the results of their quantitative analysis of global and regional food supply. They determined that significant changes are needed on four fronts: end public domain text

Food production must be sufficient, in quantity and quality, to feed the global population without unacceptable environmental impacts. Food distribution must be sufficiently efficient so that a diverse range of foods containing adequate nutrition is available to all, again without unacceptable environmental impacts. Socio-economic conditions must be sufficiently equitable so that all consumers can access the quantity and range of foods needed for a healthy diet. Consumers need to be able to make informed and rational choices so that they consume a healthy and environmentally sustainable diet (10).

annotated text Block Quote. The writer has chosen to present important evidence as a direct quotation, using the correct format for direct quotations longer than four lines. See Section Editing Focus: Integrating Sources and Quotations for more information about block quotes. end annotated text

public domain text Among their findings, they singled out, in particular, the practice of using human-edible crops to produce meat, dairy, and fish for the human table. Currently 34 percent of human-edible crops are fed to animals, a practice that reduces calorie and protein supplies. They state in their report, “If society continues on a ‘business-as-usual’ dietary trajectory, a 119% increase in edible crops grown will be required by 2050” (1). Future food production and distribution must be transformed into systems that are nutritionally adequate, environmentally sound, and economically affordable. end public domain text

Land and Water Use

public domain text Agriculture occupies 40 percent of Earth’s ice-free land mass (Barnard). While the net area used for producing food has been fairly constant since the mid-20th century, the locations have shifted significantly. Temperate regions of North America, Europe, and Russia have lost agricultural land to other uses, while in the tropics, agricultural land has expanded, mainly as a result of clearing forests and burning biomass (Willett et al.). Seventy percent of the rainforest that has been cut down is being used to graze livestock (Münter). Agricultural use of water is of critical concern both quantitatively and qualitatively. Agriculture accounts for about 70 percent of freshwater use, making it “the world’s largest water-consuming sector” (Barnard). Meat, dairy, and egg production causes water pollution, as liquid wastes flow into rivers and to the ocean (World Wildlife Fund and Knorr Foods). According to the Hertwich et al., “the impacts related to these activities are unlikely to be reduced, but rather enhanced, in a business-as-usual scenario for the future” (13). end public domain text

annotated text Statistical Data. To develop her points related to land and water use, Tran presents specific statistical data throughout this section. Notice that she has chosen only the needed words of these key points to ensure that she controls the development of the supporting point and does not overuse borrowed source material. end annotated text

annotated text Defining Terms. Aware of her audience, Tran defines monocropping , a term that may be unfamiliar. end annotated text

public domain text Earth’s resources and ability to absorb pollution are limited, and many current agricultural practices undermine these capacities. Among these unsustainable practices are monocropping [growing a single crop year after year on the same land], concentrated animal-feeding operations, and overdependence on manufactured pesticides and fertilizers (Hamilton). Such practices deplete the soil, dramatically increase energy use, reduce pollinator populations, and lead to the collapse of resource supplies. One study found that producing one gram of beef for human consumption requires 42 times more land, 2 times more water, and 4 times more nitrogen than staple crops. It also creates 3 times more greenhouse gas emissions (Chai et al.). The EAT– Lancet Commission calls for “halting expansion of new agricultural land at the expense of natural ecosystems . . . strict protections on intact ecosystems, suspending concessions for logging in protected areas, or conversion of remaining intact ecosystems, particularly peatlands and forest areas” (Willett et al. 481). The Commission also calls for land-use zoning, regulations prohibiting land clearing, and incentives for protecting natural areas, including forests. end public domain text

annotated text Synthesis. The paragraphs above and below this comment show how Tran has synthesized content from several sources to help establish and reinforce key supports of her essay . end annotated text

Greenhouse Gas and Climate Change

public domain text Climate change is heavily affected by two factors: greenhouse gas emissions and carbon sequestration. In nature, the two remain in balance; for example, most animals exhale carbon dioxide, and most plants capture carbon dioxide. Carbon is also captured, or sequestered, by soil and water, especially oceans, in what are called “sinks.” Human activities have skewed this balance over the past two centuries. The shift in land use, which exploits land, water, and fossil energy, has caused increased greenhouse-gas emissions, which in turn accelerate climate change. end public domain text

public domain text Global food systems are threatened by climate change because farmers depend on relatively stable climate systems to plan for production and harvest. Yet food production is responsible for up to 30 percent of greenhouse gas emissions (Barnard). While soil can be a highly effective means of carbon sequestration, agricultural soils have lost much of their effectiveness from overgrazing, erosion, overuse of chemical fertilizer, and excess tilling. Hamilton reports that the world’s cultivated and grazed soils have lost 50 to 70 percent of their ability to accumulate and store carbon. As a result, “billions of tons of carbon have been released into the atmosphere.” end public domain text

annotated text Direct Quotation and Paraphrase. While Tran has paraphrased some content of this source borrowing, because of the specificity and impact of the number— “billions of tons of carbon”—she has chosen to use the author’s original words. As she has done elsewhere in the essay, she has indicated these as directly borrowed words by placing them within quotation marks. See Section 12.5 for more about paraphrasing. end annotated text

public domain text While carbon sequestration has been falling, greenhouse gas emissions have been increasing as a result of the production, transport, processing, storage, waste disposal, and other life stages of food production. Agriculture alone is responsible for fully 10 to 12 percent of global emissions, and that figure is estimated to rise by up to 150 percent of current levels by 2030 (Chai et al.). Münter reports that “more greenhouse gas emissions are produced by growing livestock for meat than all the planes, trains, ships, cars, trucks, and all forms of fossil fuel-based transportation combined” (5). Additional greenhouse gases, methane and nitrous oxide, are produced by the decomposition of organic wastes. Methane has 25 times and nitrous oxide has nearly 300 times the global warming potential of carbon dioxide (Curnow). Agricultural and food production systems must be reformed to shift agriculture from greenhouse gas source to sink. end public domain text

Social and Cultural Values

public domain text As the Sierra Club has pointed out, agriculture is inherently cultural: all systems of food production have “the capacity to generate . . . economic benefits and ecological capital” as well as “a sense of meaning and connection to natural resources.” Yet this connection is more evident in some cultures and less so in others. Wealthy countries built on a consumer culture emphasize excess consumption. One result of this attitude is that in 2014, Americans discarded the equivalent of $165 billion worth of food. Much of this waste ended up rotting in landfills, comprised the single largest component of U.S. municipal solid waste, and contributed a substantial portion of U.S. methane emissions (Sierra Club). In low- and middle-income countries, food waste tends to occur in early production stages because of poor scheduling of harvests, improper handling of produce, or lack of market access (Willett et al.). The recent “America First” philosophy has encouraged prioritizing the economic welfare of one nation to the detriment of global welfare and sustainability. end public domain text

annotated text Synthesis and Response to Claims. Here, as in subsequent sections, while still relying heavily on facts and content from borrowed sources, Tran provides her synthesized understanding of the information by responding to key points. end annotated text

public domain text In response to claims that a vegetarian diet is a necessary component of sustainable food production and consumption, Lusk and Norwood determined the importance of meat in a consumer’s diet. Their study indicated that meat is the most valuable food category to consumers, and “humans derive great pleasure from consuming beef, pork, and poultry” (120). Currently only 4 percent of Americans are vegetarians, and it would be difficult to convince consumers to change their eating habits. Purdy adds “there’s the issue of philosophy. A lot of vegans aren’t in the business of avoiding animal products for the sake of land sustainability. Many would prefer to just leave animal husbandry out of food altogether.” end public domain text

public domain text At the same time, consumers expect ready availability of the foods they desire, regardless of health implications or sustainability of sources. Unhealthy and unsustainable foods are heavily marketed. Out-of-season produce is imported year-round, increasing carbon emissions from air transportation. Highly processed and packaged convenience foods are nutritionally inferior and waste both energy and packaging materials. Serving sizes are larger than necessary, contributing to overconsumption and obesity. Snack food vending machines are ubiquitous in schools and public buildings. What is needed is a widespread attitude shift toward reducing waste, choosing local fruits and vegetables that are in season, and paying attention to how foods are grown and transported. end public domain text

annotated text Thesis Restated. Restating her thesis, Tran ends this section by advocating for a change in attitude to bring about sustainability. end annotated text

DISSENTING OPINIONS

annotated text Counterclaims . Tran uses equally strong research to present the counterargument. Presenting both sides by addressing objections is important in constructing a clear, well-reasoned argument. Writers should use as much rigor in finding research-based evidence to counter the opposition as they do to develop their argument. end annotated text

public domain text Transformation of the food production system faces resistance for a number of reasons, most of which dispute the need for plant-based diets. Historically, meat has been considered integral to athletes’ diets and thus has caused many consumers to believe meat is necessary for a healthy diet. Lynch et al. examined the impact of plant-based diets on human physical health, environmental sustainability, and exercise performance capacity. The results show “it is unlikely that plant-based diets provide advantages, but do not suffer from disadvantages, compared to omnivorous diets for strength, anaerobic, or aerobic exercise performance” (1). end public domain text

public domain text A second objection addresses the claim that land use for animal-based food production contributes to pollution and greenhouse gas emissions and is inefficient in terms of nutrient delivery. Berners-Lee et al. point out that animal nutrition from grass, pasture, and silage comes partially from land that cannot be used for other purposes, such as producing food directly edible by humans or for other ecosystem services such as biofuel production. Consequently, nutritional losses from such land use do not fully translate into losses of human-available nutrients (3). end public domain text

annotated text Paraphrase. Tran has paraphrased the information as support. Though she still cites the source, she has changed the words to her own, most likely to condense a larger amount of original text or to make it more accessible. end annotated text

public domain text While this objection may be correct, it does not address the fact that natural carbon sinks are being destroyed to increase agricultural land and, therefore, increase greenhouse gas emissions into the atmosphere. end public domain text

public domain text Another significant dissenting opinion is that transforming food production will place hardships on farmers and others employed in the food industry. Farmers and ranchers make a major investment in their own operations. At the same time, they support jobs in related industries, as consumers of farm machinery, customers at local businesses, and suppliers for other industries such as food processing (Schulz). Sparks reports that “livestock farmers are being unfairly ‘demonized’ by vegans and environmental advocates” and argues that while farming includes both costs and benefits, the costs receive much more attention than the benefits. end public domain text

FUTURE GENERATIONS

public domain text The EAT– Lancet Commission calls for a transformation in the global food system, implementing different core processes and feedback. This transformation will not happen unless there is “widespread, multi-sector, multilevel action to change what food is eaten, how it is produced, and its effects on the environment and health, while providing healthy diets for the global population” (Willett et al. 476). System changes will require global efforts coordinated across all levels and will require governments, the private sector, and civil society to share a common vision and goals. Scientific modeling indicates 10 billion people could indeed be fed a healthy and sustainable diet. end public domain text

annotated text Conclusion. While still using research-based sources as evidence in the concluding section, Tran finishes with her own words, restating her thesis. end annotated text

public domain text For the human race to have a sustainable future, massive changes in the way food is produced, processed, and distributed are necessary on a global scale. The required changes will affect nearly all aspects of life, including not only world hunger but also health and welfare, land use and habitats, water quality and availability, energy use and production, greenhouse gas emissions and climate change, economics, and even cultural and social values. These changes may not be popular, but they are imperative. They are also achievable. The human race must turn to sustainable food systems that provide healthy diets with minimal environmental impact, starting now. end public domain text

annotated text Sources. Note two important aspects of the sources chosen: 1) They represent a range of perspectives, and 2) They are all quite current. When exploring a contemporary topic, it is important to avoid research that is out of date. end annotated text

Works Cited

Barnard, Neal. “How Eating More Plants Can Save Lives and the Planet.” Physicians Committee for Responsible Medicine , 24 Jan. 2019, www.pcrm.org/news/blog/how-eating-more-plants-can-save-lives-and-planet. Accessed 6 Dec. 2020.

Berners-Lee, M., et al. “Current Global Food Production Is Sufficient to Meet Human Nutritional Needs in 2050 Provided There Is Radical Societal Adaptation.” Elementa: Science of the Anthropocene , vol. 6, no. 52, 2018, doi:10.1525/elementa.310. Accessed 7 Dec. 2020.

Chai, Bingli Clark, et al. “Which Diet Has the Least Environmental Impact on Our Planet? A Systematic Review of Vegan, Vegetarian and Omnivorous Diets.” Sustainability , vol. 11, no. 15, 2019, doi: underline 10.3390/su11154110 end underline . Accessed 6 Dec. 2020.

Curnow, Mandy. “Managing Manure to Reduce Greenhouse Gas Emissions.” Government of Western Australia, Department of Primary Industries and Regional Development, 2 Nov. 2020, www.agric.wa.gov.au/climate-change/managing-manure-reduce-greenhouse-gas-emissions. Accessed 9 Dec. 2020.

Gray, Richard. “Why the Vegan Diet Is Not Always Green.” BBC , 13 Feb. 2020, www.bbc.com/future/article/20200211-why-the-vegan-diet-is-not-always-green. Accessed 6 Dec. 2020.

Hamilton, Bruce. “Food and Our Climate.” Sierra Club, 2014, www.sierraclub.org/compass/2014/10/food-and-our-climate. Accessed 6 Dec. 2020.

Hertwich. Edgar G., et al. Assessing the Environmental Impacts of Consumption and Production. United Nations Environment Programme, 2010, www.resourcepanel.org/reports/assessing-environmental-impacts-consumption-and-production.

Lusk, Jayson L., and F. Bailey Norwood. “Some Economic Benefits and Costs of Vegetarianism.” Agricultural and Resource Economics Review , vol. 38, no. 2, 2009, pp. 109-24, doi: 10.1017/S1068280500003142. Accessed 6 Dec. 2020.

Lynch Heidi, et al. “Plant-Based Diets: Considerations for Environmental Impact, Protein Quality, and Exercise Performance.” Nutrients, vol. 10, no. 12, 2018, doi:10.3390/nu10121841. Accessed 6 Dec. 2020.

Münter, Leilani. “Why a Plant-Based Diet Will Save the World.” Health and the Environment. Disruptive Women in Health Care & the United States Environmental Protection Agency, 2012, archive.epa.gov/womenandgirls/web/pdf/1016healththeenvironmentebook.pdf.

Purdy, Chase. “Being Vegan Isn’t as Good for Humanity as You Think.” Quartz , 4 Aug. 2016, qz.com/749443/being-vegan-isnt-as-environmentally-friendly-as-you-think/. Accessed 7 Dec. 2020.

Schulz, Lee. “Would a Sudden Loss of the Meat and Dairy Industry, and All the Ripple Effects, Destroy the Economy?” Iowa State U Department of Economics, www.econ.iastate.edu/node/691. Accessed 6 Dec. 2020.

Sierra Club. “Agriculture and Food.” Sierra Club, 28 Feb. 2015, www.sierraclub.org/policy/agriculture/food. Accessed 6 Dec. 2020.

Sparks, Hannah. “Veganism Won’t Save the World from Environmental Ruin, Researchers Warn.” New York Post , 29 Nov. 2019, nypost.com/2019/11/29/veganism-wont-save-the-world-from-environmental-ruin-researchers-warn/. Accessed 6 Dec. 2020.

Willett, Walter, et al. “Food in the Anthropocene: The EAT– Lancet Commission on Healthy Diets from Sustainable Food Systems.” The Lancet, vol. 393, no. 10170, 2019. doi:10.1016/S0140-6736(18)31788-4. Accessed 6 Dec. 2020.

World Health Organization. “Malnutrition.” World Health Organization, 1 Apr. 2020, www.who.int/news-room/fact-sheets/detail/malnutrition. Accessed 8 Dec. 2020.

World Health Organization. “Obesity and Overweight.” World Health Organization, 1 Apr. 2020, www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. Accessed 8 Dec. 2020.

World Wildlife Fund. Appetite for Destruction: Summary Report. World Wildlife Fund, 2017, www.wwf.org.uk/sites/default/files/2017-10/WWF_AppetiteForDestruction_Summary_Report_SignOff.pdf.

World Wildlife Fund and Knorr Foods. Future Fifty Foods. World Wildlife Fund, 2019, www.wwf.org.uk/sites/default/files/2019-02/Knorr_Future_50_Report_FINAL_Online.pdf.

“World Population by Year.” Worldometer , www.worldometers.info/world-population/world-population-by-year/. Accessed 8 Dec. 2020.

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Meal planning is associated with food variety, diet quality and body weight status in a large sample of French adults

Pauline ducrot.

1 Equipe de Recherche en Epidémiologie Nutritionnelle, Centre de Recherche en Epidémiologie et Statistiques, Université Paris 13, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Bobigny, France

Caroline Méjean

Vani aroumougame.

2 Département de médecine générale, faculté de médecine Pierre et Marie Curie, UPMC Université Paris 6, 27, rue de Chaligny, 75012 Paris, France

Gladys Ibanez

Benjamin allès, emmanuelle kesse-guyot, serge hercberg.

3 Département de Santé Publique, Hôpital Avicenne, Bobigny Cedex, France

Sandrine Péneau

Associated data.

In France, there is a very strict regulation concerning the protection of personal data and privacy making difficult the availability of data (even non-nominal data).

Meal planning could be a potential tool to offset time scarcity and therefore encourage home meal preparation, which has been linked with an improved diet quality. However, to date, meal planning has received little attention in the scientific literature. The aim of our cross-sectional study was to investigate the association between meal planning and diet quality, including adherence to nutritional guidelines and food variety, as well as weight status.

Meal planning, i.e. planning ahead the foods that will be eaten for the next few days, was assessed in 40,554 participants of the web-based observational NutriNet-Santé study. Dietary measurements included intakes of energy, nutrients, food groups, and adherence to the French nutritional guidelines (mPNNS-GS) estimated through repeated 24-h dietary records. A food variety score was also calculated using Food Frequency Questionnaire. Weight and height were self-reported. Association between meal planning and dietary intakes were assessed using ANCOVAs, while associations with quartiles of mPNNS-GS scores, quartiles of food variety score and weight status categories (overweight, obesity) were evaluated using logistic regression models.

A total of 57% of the participants declared to plan meals at least occasionally. Meal planners were more likely to have a higher mPNNS-GS (OR quartile 4 vs . 1 = 1.13, 95% CI: [1.07–1.20]), higher overall food variety (OR quartile 4 vs . 1 = 1.25, 95% CI: [1.18–1.32]). In women, meal planning was associated with lower odds of being overweight (OR = 0.92 [0.87–0.98]) and obese (OR = 0.79 [0.73–0.86]). In men, the association was significant for obesity only (OR = 0.81 [0.69–0.94]).

Conclusions

Meal planning was associated with a healthier diet and less obesity. Although no causality can be inferred from the reported associations, these data suggest that meal planning could potentially be relevant for obesity prevention.

Electronic supplementary material

The online version of this article (doi:10.1186/s12966-017-0461-7) contains supplementary material, which is available to authorized users.

In industrialized countries, eating habits and cooking practices have considerably changed. First, time devoted to cooking has decreased: in the United States, it has been reduced from 1:63 hour per day in 1965–1966 to 58 min in 2006–2007 [ 1 ]. Additionally, the source of food consumed has changed: people consume less food prepared at home, whereas foods prepared away from home represent an increasing part of the diet [ 2 – 4 ].

In light of this observation, a number of studies have evaluated the potential impact of food prepared away from home on dietary quality, as well as weight status. These studies highlighted that the consumption of food prepared away from home is associated with a lower quality diet [ 5 – 8 ] and a higher body mass index [ 9 – 11 ], whereas benefits have been attributed to home-prepared food [ 2 , 12 – 14 ]. More frequent home food preparation has been associated with better adherence to dietary objectives [ 12 ], higher intakes of fruits, vegetables [ 13 , 14 ], fiber, folate and vitamin A, while lower intakes of fat in young people [ 13 ]. Therefore, home meal preparation has been increasingly promoted as a strategy for improving dietary quality and preventing obesity [ 12 – 15 ].

In designing strategies to promote home cooking, it is important to understand the patterns and correlates of home meal practices. Many studies have investigated the reasons why people cook less. Time scarcity and cooking skills were identified as common barriers to prepare home meals [ 6 , 11 , 12 , 16 , 17 ]. Previous research emphasized that individuals with lower cooking skills were more likely to consume away from home food such as ready meals or take-out meals from fast food or restaurants [ 11 , 18 ]. In response to these difficulties, a number of studies have evaluated the opportunity to improve cooking skills in order to promote healthy dietary patterns [ 19 – 21 ]. To face time pressure, a series of qualitative studies highlighted that parents resort to food choice coping strategies, such as meal simplification, taking out, or meal planning [ 16 , 17 , 22 – 26 ] despite their potential impact on diet quality. Among these strategies, time management skills [ 27 ] and in particular meal planning [ 28 , 29 ], which consists in deciding ahead the foods that will be eaten in the next few days, has been previously suggested as a solution to balance competing time demands and reduce barriers to healthy dietary practices. In the literature, very few studies have investigated meal planning practices and they often focused on adequate diet for diabetic subjects [ 30 – 32 ]. Studies performed on general populations showed that meal planning was positively associated with frequencies of home food preparation [ 29 ] and family meal [ 33 ], as well as the presence of fruits for dinner [ 34 ]. To our knowledge, only one study in the literature has evaluated the potential link between meal planning and food consumption. It focused on fruit and vegetables specifically, and showed that planning meal ahead was associated with higher fruit and vegetable intakes [ 35 ]. However, the latter presented weakness in the dietary intake assessment method since it consisted only of questions on the number of servings eaten per day. Additionally, meal planning was evaluated, among various practices, as a tool to maintain weight among successful weight losers [ 36 , 37 ] but no data exists on the potential relationship with weight status in the general population. In the present study, we hypothesize that meal planning might encourage home meal preparation, and therefore have beneficial effects on dietary quality and consequently on weight status. Thus, we first described meal planning practices among a large sample of individuals. Then, we investigated the relationships between meal planning and diet quality, based on adherence to nutritional guidelines, energy, macronutrients and food group intakes, as well as food variety. Finally, we evaluated the association between meal planning and weight status.

Study population

The NutriNet-Santé study ( http://info.etude-nutrinet-sante.fr ) is an ongoing web-based prospective observational cohort study launched in France in May 2009 with a scheduled follow-up of 10 years. It aims to investigate the relationship between nutrition and chronic disease risk, as well as the determinants of dietary behavior and nutritional status. The study was implemented in the French general population (internet-using adult volunteers, aged ≥18 years). The rationale, design and methodology of the study have been fully described elsewhere [ 38 ]. In brief, to be included into the study, participants have to complete a baseline set of self-administered web-based questionnaires assessing dietary intake, physical activity, anthropometric characteristics, lifestyle, socioeconomic conditions and health status. As part of the follow-up, participants are asked to complete the same set of questionnaires each year. Moreover, each month, participants are invited by e-mail to fill in optional questionnaires related to dietary intake, determinants of eating behaviors, nutritional and health status. This study is conducted in accordance with the Declaration of Helsinki, and all procedures were approved by the Institutional Review Board of the French Institute for Health and Medical Research (IRB Inserm n°0000388FWA00005831) and the Commission Nationale de l’Informatique et des Libertés (CNIL n°908450 and n°909216). All participants provided informed consent with an electronic signature. This study is registered in EudraCT (n°2013-000929-31).

Data collection

Meal planning questionnaire.

Meal planning practices were assessed via an optional questionnaire launched in the NutriNet-Santé cohort study in April 2014.

First, grocery shopping and cooking practices were evaluated. In particular, participants were asked to indicate whether they were involved in grocery shopping (every day, several times a week, once a week, less than once a week) and cooking (every day twice a day, every day once a day, several times a week but not every day, once a week, less than once a week, never) in their household. Then, participants were asked the following question “Generally, when do you choose the foods you are going to eat for meal?” (just before meal, during the day, the day before, few days before, one week before, never). Participants responding “never” were exempted to complete the rest of the questionnaire.

Participants were also asked whether having to think about what they have to cook is a constraint for them. The responses were rated on a 5-point Likert scale ranging from one (strongly disagree) to five (strongly agree).

Participants were then asked whether they planned meals, even in an irregular manner (yes I do, yes I did but not anymore, no I never planned meals). The definition of “planning meals” given to the participants was “to plan ahead the foods that will be eaten for the next few days”. Participants who reported planning meal currently were considered as “meal planners” whereas others were categorized as “non-meal planners”.

Finally, the questionnaire included questions about meal planning frequency (several times a week, once a week, once every two weeks, two to three times a month, not regularly), duration (a few days, one week, two weeks or more), period of the week (weekdays, weekend, weekdays and weekend) and sources of inspiration (personal recipe repertoire, Internet or apps, ingredients available during grocery shopping).

Socio-demographic and economic characteristics

At baseline and annually thereafter, participants in the NutriNet-Santé study are asked to provide socio-demographic data, including sex, age (18–30, 30–50, 50–65, >65 years), educational level (up to secondary, some college or university degree), monthly income (<1,200 €, 1,200–1,800 €, 1,800–2,700 € and >2,700 € per consumption unit), presence of children in the household (yes, no), history of dieting to lose weight during the past year (yes, no) and physical activity (low, moderate, high). Monthly household income is calculated per “consumption unit” (CU), where one CU is attributed for the first adult in the household, 0.5 CU for other persons aged 14 or older, and 0.3 CU for children under 14, following national statistics methodology and guidelines [ 39 ].

Physical activity was assessed using a short form of the French version of the International Physical Activity Questionnaire (IPAQ). The weekly energy expenditure expressed in metabolic equivalent task minutes per week was estimated, and three scores of physical activity were constituted [i.e., low (<30 min/day), moderate (30–59 min/day), and high (≥60 min/day)] according to the French guidelines for physical activity [ 40 ].

For the present study, we used the closest available data with respect to the assessment of meal planning practices.

Dietary measurements

At inclusion and once a year thereafter, participants are invited to complete three non-consecutive 24-h dietary records, randomly assigned over a 2-week period (two weekdays and one weekend day). For the present analysis, we selected participants who completed at least three 24-h dietary records since their inclusion in the cohort study (i.e. completed between May 2009 and December 2014). Participants reported all foods and beverages consumed at each eating occasion. They estimated the amounts eaten using validated photographs of portion sizes [ 41 ], using household measures or by indicating the exact quantity (grams) or volume (milliliters). Daily mean food intakes were calculated, weighted for the type of day of the week. Energy, nutrient and food group intakes were estimated using the NutriNet-Santé composition table including more than 2000 foods [ 42 ]. Dietary underreporting was identified on the basis of the method proposed by Black [ 43 ]. We hypothesize that meal planning encourages food preparation and therefore considered food groups that can be used in food preparation (e.g. eggs). In addition, we considered food groups that have nutritional interest (e.g. fruits). Thus, the following food groups were included in the study: fruits, vegetables, fish (including seafood and processed seafood), meat (including cooked ham, offal), eggs, milk, cheese, added fats (including oil, butter, margarine, vinaigrette), sugary products (e.g. cake, biscuits, sugars, honey, jam, chocolate) and starchy foods (including potato, legumes, pasta, rice, other cereals) with a specific focus on legumes and whole grain starchy foods (including whole grain pasta, rice, other cereals).

Adherence to nutritional guidelines was assessed using the PNNS Guideline Score (PNNS-GS). The 15-point PNNS-GS is a validated a priori score reflecting the adherence to the official French nutritional guidelines which has been extensively described elsewhere [ 44 ]. Details on computation of this score are in Additional file 1 . Briefly, it includes 13 components: eight refer to food-serving recommendations (fruit and vegetables; starchy foods; whole grain products; dairy products; meat, eggs and fish; fish and seafood; vegetable fat; water vs . soda), four refer to moderation in consumption (added fat; salt; sweets; alcohol) and one component pertains to physical activity [ 44 , 45 ]. Points are deducted for overconsumption of salt (>12 g/day), added sugars (>17.5% of energy intake), or when energy intake exceeds the needed energy level by more than 5%. Each component cut-off was that of the threshold defined by the PNNS public health objectives when available [ 45 ] otherwise they were established according to the French Recommended Dietary Allowances [ 46 ]. For the present analysis, we consider the mPNNS-GS, a modified version of the PNNS-GS, which takes into account only the dietary components, therefore excluding the physical activity component. Thus, the maximum score was 13.5.

Food variety score

Food variety has been defined as the number of different food items reported to be eaten over a given reference period [ 47 ]. Considering that seasonality is likely to influence food variety and that a period of 10 to 15 days has been recommended to accurately assess food variety [ 48 ], the food variety was evaluated using a Food Frequency Questionnaire (FFQ).

Sixteen months after baseline, participants were invited to complete a self-administrated 240-items FFQ to assess their usual dietary intake over the past year [ 49 ]. Participants were asked to report their consumption frequency on the basis of how many times they ate the standard portion size proposed (typical household measurements such as spoon or standard unit such as a yogurt). The frequency of consumption referred to usual consumption over the past year on an increasing scale including yearly, monthly, weekly or daily units, as suitable, and participants were asked to provide only one answer.

The food variety score corresponded to the number of FFQ items reported to be consumed at least once during the last year [ 47 ]. The maximum score was therefore 240. Fruit and vegetable variety scores were also computed based on the number of different fruits and vegetables reported by the participants.

Anthropometric data

Height and weight were assessed by using an anthropometric questionnaire, which was self-administered online, at baseline and each year thereafter [ 50 , 51 ]. For each participant, the closest available data to the meal planning questionnaire were used for the analysis.

Data were not collected for pregnant women. BMI (in kg/m 2 ) was calculated as the ratio of weight to squared height. Participants were classified as underweight or normal weight (BMI < 25), overweight (25 ≤ BMI < 30) and obesity (BMI ≥ 30) according to WHO references values [ 52 ].

Statistical analysis

The analysis focused on participants who had completed the meal planning questionnaire, had declared being involved in meal preparation in their household, and who had completed at least three 24-h dietary records since they were included in the study, as well as the FFQ.

Chi-square tests and Student’s t tests were used to compare characteristics of included vs . excluded participants, as well as meal planners vs . non-meal planners. Meal planners’ practices were also described. Continuous variables are presented as means ± SDs and categorical variables as percentages.

ANCOVAs were performed to investigate the relationship between meal planning and energy, macronutrients and food groups. However, for some particular food groups which did not exhibit normal distribution (i.e. eggs, milk, legumes, and whole grain starchy foods), mainly due to a high proportion of non-consumers, a binary variable (consumer/non-consumer) was created and a logistic regression analysis was performed. Logistic regression models were also used to assess the associations between meal planning and quartiles of mPNNS-GS, as well as quartiles of food variety scores (overall, fruit and vegetable) and BMI categories. Due to significant interactions and differences on the associations with meal planning, analyses on BMI were performed separately by sex.

Meal planning has been described as a cooking skill [ 53 ]. Thus, characteristics that have been shown to influence cooking practices, dietary intakes or weight status were considered as confounders in the present analyses. Models were therefore all adjusted for sex [ 1 , 54 , 55 ], age [ 56 ], educational level, monthly income [ 6 ], presence of children in the household [ 6 ], history of dieting to lose weight during the past year [ 57 ], physical activity [ 58 ], and cooking frequency. Models evaluating the associations with mPNNS-GS, macronutrient and food groups intakes were further adjusted for daily energy intake and number of 24-h dietary records completed by participants. The energy model was only adjusted on the number of 24-h records while the food variety models were adjusted on daily energy intake. Missing covariate data were imputed using multiple imputation method.

Sensitivity analyses were conducted on a subsample of individuals having responded to at least one of the dietary assessments (i.e. FFQ, dietary records). In addition, analyses were conducted using another definition of food variety score (number of FFQ items reported to be consumed more than once a week) [ 59 ].

All tests of statistical significance were two-sided and the type I error was set at 5%. Statistical analyses were performed using SAS software (version 9.3, SAS Institute Inc, Cary, NC, USA).

Among the 102,703 participants in the NutriNet-Santé study who received the meal planning questionnaire, a total of 52,949 participants (i.e. 51.6%) completed it. Among them, 1,754 were excluded because they declared not being involved in meal preparation in their household, 3,242 because of inadequate data in dietary records (less than three 24-h dietary records or underreporting) and 7,399 because they did not complete the FFQ, thus leading to a total of 40,554 participants available for analyses. Compared with excluded participants, included subjects were more likely to be women, older, to have a lower educational level, higher income, to have children living in the household, to be physically active, and less likely to have followed a diet to lose weight during the past year (all P  < 0.0001).

Our final sample comprised 78% of women and 22% of men, with a mean age of 52.2 ± 14.2 years. Among the included participants, 57.4% declared to plan their meals at least occasionally whereas 42.6% did not, among which 17.3% planned in the past and 25.3% never planned meals. Overall, the same proportions were observed in men (meal planners: 55.9% vs . non-meal planners: 44.1%) and women (meal planners: 57.8% vs . non-meal planners: 42.2%), but women were more likely to have planned meals in the past compared to men (19.0% vs . 11.3%).

Table  1 presents the sociodemographic and economic characteristics of meal planners and non-meal planners, as well as mean scores for mPNNS-GS, overall food variety and overweight prevalence. Overall, differences between the two groups were relatively limited. Compared with non-meal planners, individuals who plan meals were slightly more likely to be women, older, to have a higher educational level, a higher income, to have followed a diet to lose weight during the past year and to be physically active (all P  < 0.05). They were also more likely to have higher mPNNS-GS and overall food variety scores and to have a BMI < 25 kg/m 2 (all P  < 0.0001).

Sociodemographic, economic and lifestyle characteristics of meal planners vs . non-meal planners ( N  = 40,554 - NutriNet-Santé 2014)

Boldface indicates statistical significance

a Meal planners are individuals who “plan ahead the foods that will be eaten for the next few days”

b On the basis of Student’s t or chi-square tests as appropriate

c CU : Household Consumer Units. One CU is attributed for the first adult in the household, 0.5 for other persons aged 14 or older and 0.3 for children under 14

d mPNNS-GS: adherence to nutritional guidelines score, based on 24-h dietary records, range 0–13.5

e Food variety score: based on the food frequency questionnaire, range 0–240

Table  2 shows cooking practices in meal planners vs . non-meal planners, as well as details regarding meal practices among meal planners. Compared with non-meal planners, individuals who plan meals cooked more frequently. The majority of non-meal planners decided what food to prepare during the day or just before meal whereas meal planners reported to decide during the day, the day before or few days before. Finally, thinking about what food to prepare was less of a constraint for meal planners than for non-meal planners (all P  < 0.0001). Results among meal planners more specifically showed that the majority of participants planned their meals at least once a week. A non-negligible part (14.8%) also reported to plan meals not regularly. Three-quarters of participants planned meals for a few days, but less than a week. Meals were mostly planned for both weekdays and weekend. Most of the participants planned meals according to personal recipe repertoire or the ingredients available during grocery shopping.

Cooking practices and meal planning practices ( N  = 40,554 - NutriNet-Santé 2014)

a On the basis of chi-square tests

Intake of energy, nutrients and food groups in meal planners vs . non-meal planners are presented in Table  3 . Depending on the outcome, the percentage of explained variance (r 2 ) in ANOVAs varied from 0.10 to 0.75. Overall very small differences in energy, macronutrient and food group intakes were observed between meal planners and non-meal planners.

Energy, nutrients and food group intakes in meal planners vs . meal planners ( N  = 40,554 - NutriNet-Santé 2014)

1 P are based on ANCOVA models adjusted for sex, age, educational level, monthly income per household, presence of children in the household, history of dieting to lose weight during the past year, physical activity, cooking frequency, and number of dietary records

2 P are based on ANCOVA models adjusted for sex, age, educational level, monthly income per household, presence of children in the household, history of dieting to lose weight during the past year, physical activity, cooking frequency, number of dietary records, and daily energy intake

3 P are based on logistic regression models adjusted for sex, age, educational level, monthly income per household, presence of children in the household, history of dieting to lose weight during the past year, physical activity, cooking frequency, number of dietary records, and daily energy intake

a Total starchy foods includes potato, legumes, pasta, rice, other cereals, flour and whole grain forms

b Sugary products includes foods with high sugar content such as cake, biscuits, sugars, honey, jam, chocolate

c Whole grain starchy foods includes whole grain forms of pasta, rice, other cereals, and flour

The associations between meal planning and quartiles of mPNNS-GS, as well as quartiles of food variety score are presented in Table  4 .

Multinomial logistic regression analysis showing the association between meal planning and adherence to nutritional guideline score (mPNNS-GS) and food variety score ( N  = 40,554 - NutriNet-Santé 2014) a

a The modeled probability was the fact to plan meals

b Adjusted for sex, age, educational level, monthly income per household, presence of children in the household, history of dieting to lose weight during the past year, physical activity cooking frequency, and daily energy intake

Compared with non-meal planners, individuals who planned their meals were more likely to belong to quartiles 2, 3 and 4 of mPNNS-GS compared with quartile 1, thus reflecting a higher adherence to nutritional guidelines. Similarly, compared with non-meal planners, meal planners were also more likely to belong to quartiles 2, 3 and 4 of overall food variety, vegetable variety and fruit variety compared with quartile 1, thus reflecting a higher variety of the diet. For these models, the association of predicted probabilities and observed responses indicated percent concordant of 63.8 and 54.9%, respectively . Additional analysis considering mPNNS-GS and variety score as continuous variables revealed similar trends: meal planners exhibited higher mPNNS-GS (7.92 ± 0.008 vs . 7.88 ± 0.009, P  = 0.0001) and overall food variety score (113.81 ± 0.16 vs . 112.20 ± 0.19, P  < 0.0001) compared to non-meal planners.

The logistic regression analysis performed between meal planning and BMI classes is presented in Table  5 . In women, meal planning was associated with lower odds of being overweight and obese, while in men, meal planning was associated with lower odds of being obese only. For this model, the association of predicted probabilities and observed responses indicated a percent concordant of 70%.

Logistic regression analysis showing the association between meal planning and weight status in men and women ( N  = 40,554 - NutriNet-Santé 2014) a

b Adjusted for sex, age, educational level, monthly income per household, presence of children in the household, history of dieting to lose weight during the past year, physical activity, and cooking frequency

Using a large population-based sample of individuals, this study brought new insights about meal planning practices and their relationship with dietary quality and weight status. Meal planning was associated with better adherence to nutritional guidelines and higher food variety. Furthermore, planning meals was associated with lower odds of being overweight and obese in women and of being obese in men.

In our study, despite significant differences regarding sociodemographic, economic and lifestyle characteristics due to the large sample size, meal planners and non-meal planners exhibited very similar profiles. In particular, no significant difference in meal planning was observed in relation with the presence of children in the household. This result appears in contrast with previous qualitative studies suggesting that the presence of children increases the feeling of time scarcity [ 17 , 23 – 26 , 60 ] and therefore the need of developing time-saving strategies, such as meal planning. However, fatigue and time scarcity can also decrease the likelihood for following meal plans [ 26 ].

To our knowledge, this study is the first to describe meal planning practices in a general population sample. Overall, more than one out two participants revealed to plan their meals at least occasionally. Generally, individuals planned their meals several times a week, for a few days period including weekdays and weekend, and get inspiration mostly from their personal recipe repertoire or ingredients available during grocery shopping. A previous survey evaluating Canadians’ attitudes and habits with regard to home food preparation highlighted that about 40% of the participants decide what they will prepare for dinner during the day, 27% the day before and 33% at least two days before [ 29 ]. However, the latter did not explore the modalities of meal planning.

Based on a large sample of general population, our data support the notion that planning meal is indeed associated with a better adherence to nutritional guidelines and an increased food variety (overall, fruits and vegetables). However, it should be noted that only small differences were observed with energy, macronutrient and food group intakes specifically. Although meal planning has been previously suggested as a potential tool to improve dietary quality [ 28 , 29 ], to our knowledge, no study in the literature has investigated this related association. Previous authors highlighted that individuals deciding in advance what to prepare for dinner were more likely to cook homemade dishes [ 29 ]. Since more frequent food preparation has been linked with a better diet quality [ 12 – 14 ], this could potentially explain the healthier diet observed in meal planners. A few hypotheses can be made on how meal planning could encourage home food preparation. First, meal planning might address the issue of not knowing what to prepare for dinner, that has been previously described as a barrier for home meal preparation [ 29 ]. Second, by planning meals individuals may think about recipes that can be prepared in a limited period of time and, therefore reduce the feeling of time scarcity, that may limit home meal preparation [ 6 , 12 , 16 ] and increase the recourse to food choice coping strategies such as eating out, delivery meals or ready prepared food [ 17 , 23 – 25 ]. In addition, planning meals may reduce the risk of missing ingredients for home meal preparation which could also lead to the consumption of food prepared away from home. Finally, deciding what foods will be eaten in the next few days could also enable individuals to cook more diversified recipes and to anticipate grocery shopping for the specific ingredients needed, thus potentially explaining the increased food variety observed in meal planners. However, reverse causality cannot be excluded since individuals interested in having a healthy diet might be more likely to plan their meals. In line with this idea, meal-planners in our sample were more likely to have higher educational level, to have higher income, to be physically active and to have a lower BMI, characteristics that have been related with a better attitude towards healthy eating [ 61 ]. Differences were however limited.

Our results showed that women who planned meals were less likely to be overweight or obese, while in men, there was an association with obesity only. Since meal planners have a diet of higher quality, it potentially prevents overweight in these individuals [ 52 ]. However, we cannot exclude reverse causality. People attaching more importance to food and weight management might be more likely to plan their meals. In line with this hypothesis, two studies in the literature highlighted that meal planning is more frequently used by successful weight loss maintainers compared to those who did not maintain weight losses [ 36 , 37 ].

In terms of public health, our results bring supportive insights that promoting meal planning might encourage the preparation of healthier and more varied home meals. Previous studies showed that parents would be interested in learning how to plan meals [ 28 , 60 ], however, other findings suggested that meal planning is also perceived as complex and time consuming [ 62 ]. Specific tools might assist people in managing meal planning but to be adopted and sustainable over time, it is important to identify consumers’ needs. The present data highlighted that there are various ways of planning meals. As an example, we observed that the ingredients available during grocery shopping are likely to influence meal planning while existing tools rather propose menus to plan grocery shopping.

Strengths and limitations

A major strength of this study was its large sample size allowing an evaluation of meal planning practices at a population level. The wide range of socio-economic and lifestyle variables collected through the web-based platform enables the control of potential effects of confounding factors. In addition, the web-based tool used to assess 24-h dietary records has shown a good validity in prior studies [ 63 , 64 ]. However, because of the influence of seasonality on food variety, the FFQ was used to evaluate dietary variety since it allows usual intake estimates over a relatively long period of time [ 65 ].

This study was also subject to several limitations. First, the cross-sectional design of this study prevented any inference of causality. Moreover, since participants were volunteers in a nutrition focused cohort, they may have higher health consciousness and interest in nutritional issues. The fact that we selected only participants who completed both dietary assessment tools might have exacerbated this characteristic in our sample. Therefore, caution is needed when generalizing our results. However, sensitivity analyses including individuals with at least one of the dietary assessments (24-h dietary records or FFQ) revealed similar trends. Besides, the fact that participants had relatively high knowledge in nutrition could potentially account for the few differences observed in energy and food group intakes, since they may be able to cook healthful meals without planning meals. It is also important to consider that food variety score was based on FFQ data, which has been recorded at different time frames (16 months after the inclusion in the cohort). Thus, for participants included since a long time in the cohort study, the estimation may not represent their current dietary repertoire. In addition, data were self-reported, thus potentially leading to misreporting due, for example, to desirability bias. Nonetheless, previous validation studies performed on a subsample of the NutriNet-Santé study have supported the good validity of self-reported anthropometric and dietary data [ 63 , 64 , 66 ]. Finally, given that meal planning may be influenced by numerous parameters such as cooking practices and food availability in the surrounding, it is possible that some factors mediating the associations observed in the present paper were not taken into account in the analyses. The potential impact of cooking practices was however considered by adding cooking frequency as a confounder. Future research should be conducted to address the issue of how food availability could potentially influence the relationship observed between meal planning and diet quality.

Our results highlighted that individuals planning their meals were more likely to have a better dietary quality, including a higher adherence with nutritional guidelines as well as an increased food variety. Additionally, meal planning was associated with lower odds of being obese in men and women and overweight in women only. Although interventional or prospective research should be conducted in order to infer causality, these data suggest the potential interest of promoting meal planning to improve dietary quality and prevent overweight. Such a tool could partly address the issue of time scarcity reported by consumers for meal preparation and, might therefore encourage home cooking. Given the potential benefits of meal planning identified in this study, it would be interesting that future research evaluate the appropriation and the impact of applications designed to help individuals planning their meals.

Acknowledgments

We thank all scientists, dieticians, technicians, and assistants who help carry out the NutriNet-Santé study. We especially thank Younes Esseddik, Yasmina Chelghoum, Mohand Ait Oufella, Paul Flanzy and Thi Hong Van Duong, computer scientists; Veronique Gourlet, Charlie Menard, Fabien Szabo, Nathalie Arnault, Laurent Bourhis and Stephen Besseau, statisticians; and the dieticians. We are grateful to volunteers from the NutriNet-Santé study.

The NutriNet-Santé Study is supported by the French Ministry of Health (DGS), the French Institute for Public Health Surveillance (InVS), the French National Institute for Health and Medical Research (INSERM), the French National Institute for Agricultural Research (INRA), the Medical Research Foundation (FRM), the National Conservatory for Arts and Crafts (CNAM), the National Institute for Prevention and Health Education (INPES) and the University of Paris 13. This study is supported by the National Institute for Prevention and Health Education (INPES).

Availability of data and materials

Authors’ contributions.

PD: conducted the literature review, drafted the manuscript and performed analyses; CM, VA, GI, BA, EKG, SH and SP: were involved in the interpretation of results and critically reviewed the manuscript; and SH and SP: were responsible for the development of the design and the protocol of the study. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study is conducted in accordance with the Declaration of Helsinki, and all procedures were approved by the Institutional Review Board of the French Institute for Health and Medical Research (IRB Inserm n°0000388FWA00005831) and the Commission Nationale de l’Informatique et des Libertés (CNIL n°908450 and n°909216). All participants provided informed consent with an electronic signature. This study is registered in EudraCT (n°2013-000929-31).

Abbreviations

Additional file

French Nutrition and Health Program-Guideline Score (PNNS-GS) computation. (DOCX 16 kb)

Contributor Information

Pauline Ducrot, Email: [email protected] .

Caroline Méjean, Email: [email protected] .

Vani Aroumougame, Email: rf.oohay@uorainav .

Gladys Ibanez, Email: [email protected] .

Benjamin Allès, Email: [email protected] .

Emmanuelle Kesse-Guyot, Email: [email protected] .

Serge Hercberg, Email: [email protected] .

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The Art of Healthy Aging

Moffa, Christine PhD, RN, APRN, PMHNP-BC

AJN Senior Clinical EditorEmail: [email protected]

It's never too early to think about growing older.

September is National Healthy Aging Month. The observance began in 1992, four years before the oldest baby boomers would turn 50, and was recognized in 2021 by the U.S. Senate, with the goal of promoting a positive view of growing older. It's never too early to think about healthy aging, and as we're technically all aging by the minute, it should be of interest to everyone. While genetics play a role in healthy aging, lifestyle choices also factor in. In addition to exercise and healthy eating for physical well-being, the National Institutes of Health (NIH) also recommends ways to preserve one's mental health (for more, see www.nia.nih.gov/health/healthy-aging/what-do-we-know-about-healthy-aging ).

One way is by maintaining social connections. It's easy to forget about your social life when you're working a demanding job and coming home physically and mentally exhausted, or experiencing burnout and moral distress, as many nurses these days do. A few years ago, I was working on my PhD (which can be very isolating), which focused on workplace mistreatment of nurses. As you can imagine, being immersed in this topic for years and writing a dissertation on it can start to wear on you. I remember telling people, “If I could do this all again, I would prefer a more uplifting topic, like ‘jokes people tell at cocktail parties.’” I was kidding, of course, and it didn't occur to me at the time that humor had a place in health care research. It turns out that it does, as seen in this month's original research article by Cadiz and colleagues, “Exploring Nurses' Use of Humor in the Workplace: A Thematic Analysis.”

Reading this article made me reflect on my own experience working in different health care settings and the role humor played in connecting with coworkers and patients. I look back fondly on memories of friends I made at work and how laughing with them helped ease the tension between difficult shifts. I also use humor when working with patients in my role as a psychiatric mental health NP. It can serve to break the ice or to provide encouragement and demonstrate the human side of the provider–patient relationship. Once, when a patient was describing their disappointment at not reaching a life milestone in the time they expected to, I shared how it took me seven years to get my associate degree, adding, “I'm a late bloomer, but I got there eventually!” We both laughed and it helped normalize their situation. It's important to note that using humor is like seasoning a recipe: it's there to make the conversation more interesting and memorable, but you need to know when to add it and when it might be too much of a good thing.

Another NIH recommendation for healthy aging is to participate in hobbies and leisure activities. On our cover is a painting by Ren Hernandez, a nurse who discovered his talent during the pandemic. The piece is called ephemeral snow , and the artist says it “showcases strength among adversity.” In an email, Hernandez shared with me that “art, colors, and self-expression are extremely therapeutic, and it was such a solace for me during the height of the pandemic. . . . Through my art, I want everyone to explore their own latent creativity and find therapeutic ways of combating stress.” And this month's Conversations highlights the work of MK Czerwiec, a nurse and cofounder of the field of graphic medicine, who draws comics to process her experiences in health care.

While humor, art, and other creative outlets for stress reduction are great ways to focus on keeping ourselves healthy, I want to be clear that they are in no way meant to be a panacea for short staffing or other forms of mistreatment of nurses. Self-care and resilience do not make up for an unsafe and unhealthy work environment. A Project Evaluation article in this issue examines an intervention for providing peer support to “second victims”—health care workers who have experienced a negative patient outcome. And In the News covers the impact (or lack thereof) of using a team nursing model as a potential solution for staffing demands. Finally, Legal Clinic provides information on how nurses protect their livelihood when they understand nurse licensure.

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