6: No. 1, January 2009
Perceptions of Individual and Community Environmental Influences on Fruit and Vegetable Intake, North Carolina, 2004
Josephine E. A. Boyington, PhD, MPH, RN, Britta Schoster, MPH, Kathryn Remmes Martin, MPH, Jack Shreffler, PhD, Leigh F. Callahan, PhD
Suggested citation for this article: Boyington JEA, Schoster B, Remmes Martin K, Shreffler J, Callahan LF. Perceptions of individual and community environmental influences on fruit and vegetable intake, North Carolina, 2004. Prev Chronic Dis 2009;6(1):A04.
Increases in obesity and other chronic conditions continue to fuel efforts for lifestyle behavior changes. However, many strategies do not address the impact of environment on lifestyle behaviors, particularly healthy dietary intake. This study explored the perceptions of environment on
intake of fruits and vegetables in a cohort of 2,479
people recruited from 22 family practices in North Carolina.
Participants were administered a health and social demographic survey. Formative assessment was conducted on a subsample of 32
people by using focus groups, semistructured individual interviews, community mapping, and photographs. Interviews and discussions were transcribed and content
was analyzed using ATLAS.ti version 5. Survey data were evaluated for means, frequencies, and group differences.
The 2,479 participants had a mean age of 52.8 years, mean body mass index
(BMI) of 29.4, and were predominantly female, white, married, and high school
graduates. The 32 subsample participants were older, heavier, and less educated. Some prevalent perceptions about contextual factors related to dietary intake included taste-bud fatigue (boredom with commonly eaten
foods), life stresses, lack of forethought in meal planning, current health status, economic status, the ability to garden, lifetime dietary exposure, concerns about food safety, contradictory nutrition messages from the media, and variable work schedules.
Perceptions about intake of fruits and vegetables intake are influenced by individual (intrinsic) and community (extrinsic) environmental factors. We suggest approaches for influencing behavior and changing perceptions using available resources.
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Lifestyle practices of unhealthy diet and physical inactivity are noted
determinants of chronic conditions, especially overweight and obesity (1). Nationally, chronic disease statistics document that the southeastern US region manifests some of the highest
rates of and the worst outcomes for chronic disease (2). North Carolina is representative of the southeastern region; its age-adjusted death rates for the 5 diseases that account for almost two-thirds of all annual deaths are higher than the national average (3). Furthermore, the combined prevalence of adult overweight and obesity is 63% (3).
of statistics is evidence of poor access to health services, poor economic opportunities, unique environmental challenges, and unhealthy lifestyle practices prevalent in this US region (3-6).
In North Carolina, approximately 77% of adults do not consume the recommended daily intake of 5 or more servings of fruits and vegetables and 26% do not engage in leisure time physical activity (3,4). These statistics underscore the prevalence of unhealthy behaviors and chronic conditions in this US region, yet provide little information about
the motivations and perceptions of residents relative to these factors. Especially
important is the paucity of data on peoples’ qualitative descriptions of their dietary behaviors in the context of their environment. This is of particular interest given that lifestyle choices, including those relating to diet, are complex decisions affected by the interaction between people (attitudes, thoughts, behaviors, perceptions) and their external social and physical environments (7-9).
Historically, most assessments of dietary and other lifestyle behaviors and attitudes have been conducted using survey methods. However, because of their systematic structure, surveys have been less able to contextualize individuals’ experiences and perceptions and do not facilitate easy assessment of motivational factors and contexts underpinning peoples’ behaviors (10). Nonetheless, they have been useful for identifying patterns of behavior and facilitating comparisons of
patterns across environments (10). However, interventions based on survey results, primarily individual-focused education strategies, have been limited in effecting behavior change and improving health outcomes (11). Researchers suggest that the absence of corresponding environmental changes may be responsible for this outcome (11).
In fact, despite numerous preventive efforts regarding dietary behavior and
chronic diseases, obesity and other chronic conditions continue to
increase in prevalence. This change indicates that the mere
identification of unhealthy behaviors and development of educational strategies
to change them may not be enough. Researchers often state that people’s
behaviors are contextual and must therefore be understood and addressed within
their environment (7,8,9,11-13). Yet, few studies have investigated individuals’
perceptions of the relationship between their environment and diet and physical
activity behaviors (11). Until recently, no unifying conceptual framework
existed to evaluate these relationships. However, a work group
of researchers has produced such a framework. The work group summarizes
its effort as the beginning phase in clarifying the relationship between the
environment and lifestyle behaviors and strongly encourages further inquiries on
“the extent of environmental influence and how [environment and lifestyle]
affect different individuals” (11).
An approach that has proved useful in both identifying and contextualizing lifestyle behaviors is formative research. This unique multimethod, exploratory approach combines social science techniques such as interviews, focus groups, and other qualitative methods with quantitative methods such as surveys (14). When these techniques are used to gather data for informing research conduct and intervention design, the term formative assessment is used. Formative research has been used
primarily by intervention researchers in community-based studies and has guided the development of several interventions (13,15,16). A unique strength of this approach is that it provides the basis for collection of relevant new data to guide research direction, research discourse, and data interpretation (13,15-17). Drawing on a large study to assess community and social determinants of chronic disease risk and outcomes among North Carolina adults, we used formative research to report specifically on findings relative to fruit and vegetable intake.
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Study design and sample description
The study proceeded in 2 phases: a telephone survey followed by a formative assessment phase. For the formative assessment, the research protocol included focus groups, semistructured individual interviews, photographs, and cursory community mappings.
Study participants were residents of North Carolina who had previously
consented to be part of a unique statewide practice-based research network
called the North Carolina Family Medicine Research Network (NC-FM-RN) (18). The NC-FM-RN was initiated in 2001 and currently includes a cohort of North Carolina residents previously recruited through a network of 25 family practice settings across the state. The cohort was enriched with new participants in 2004 and 2005. The sample for this study
included people who were part of the cohort in 2001 and 2004. They were recruited from 22 of the 25 sites. Further details on the structure, recruitment methods, and outcomes of the NC-FM-RN are available elsewhere (18). All the methods and the protocols for this study and the NC-FM-RN were approved by the University of North Carolina at
Chapel Hill Medical Institutional Review Board.
Survey procedures and measures
At the study’s outset in 2004-2005, previously enrolled participants from 22 of the 25 practices in the NC-FM-RN were
sent a letter that described the study, its objectives, what participants could expect, and reminded participants
that they had previously consented to be contacted for future studies. Consenting
participants were scheduled for the telephone survey, which included a 30-minute assessment of demographic, health, and social factors, and health attitudes,
behaviors, and beliefs related to chronic diseases. A total of 2,479 people from the cohort participated in the telephone survey, resulting in a 59.5% response rate. All measures in the survey were self-reported. Race was identified as non-Hispanic black, non-Hispanic white, or other (inclusive of all other races). Comorbidity was measured as reported diagnosis of
1 or more of 18 chronic conditions. Some of the conditions assessed were heart disease, hypertension, diabetes, and
depression. Comorbidity scores were calculated by summing the number of reported diagnoses. Body mass index (BMI) was calculated from self-reported weight and height,
and was reported as weight in kilograms/(height in meters)2. It was categorized according to
Centers for Disease Control and Prevention guidelines (underweight, <18.5; normal weight, 18.5-24.9; overweight, 25.0-29.9; and obese, >30.0) (19). The survey also included
the following 3 questions to assess participants’ perception of the quality,
variety, and affordability of fruits and vegetables in their environment:
- Thinking of the store where you do most of your grocery shopping, how would you rate the quality of their fresh fruits and vegetables?
- How would you rate the variety of their fresh fruits and vegetables?
- How would you rate the affordability of their fresh fruits and vegetables?
The response options for the first 2 questions ranged from excellent
to not applicable and for the third question, very affordable to not applicable.
Participants were eligible to participate in focus group discussions if they had completed the telephone survey. Six of the 22 NC-FM-RN practices were chosen as recruitment sites, and
patients from these sites were invited to participate first by letter and then by telephone calls. A total of 84 people were recruited, and 21 (25%) attended the discussion sessions. Seven focus groups, averaging 3 participants and lasting 1.5 hours, were conducted in 6 locations. Participants received
a gift of $20. Sessions were arranged, facilitated, and audiotaped with participants’ consent by 2 trained moderators (B.S., L.F.C.) and subsequently transcribed, coded, and analyzed
(B.S., K.R.M.) using ATLAS.ti version 5.0 software (Scientific Software
Development, GmbH, Berlin, Germany). Nutrition-specific thematic content and
coding analyses were further conducted (J.E.A.B.). Portions of the transcripts that
addressed participants’ reported consumption patterns of fresh fruits and
vegetables and their perceptions of environmental influences on their nutrition
behaviors were reviewed for emergent themes and compared across groups. Participants responded to
the question, “Do you think about getting
fruit and vegetables in your diet?”
Semistructured individual interviews
To broaden the range of perspectives, semistructured individual interviews were conducted with community members not demographically represented in the focus groups. These individuals were recruited from the same list used for the focus group participants. A total of 11
participants who were African American men, African American women, or white men were
intentionally recruited to participate in
telephone-administered interviews. This addition increased the formative assessment sample to 32.
Before each focus group session, a cursory geographic assessment of each of the 6 localities
was conducted. Research team members drove through the downtown sections of localities on the day of the session and identified physical assets that could serve as resources for or constraints to lifestyle behavior change. Relevant assets included the availability, type, and proximity of grocery stores, farm stands,
restaurants, and convenience stores. This endeavor helped moderators to contextualize the
behaviors and perceptions reported by the participants during the sessions.
Participants were asked to identify and photograph factors in their environment that they perceived demonstrated a relationship between their community and health. They were each given a disposable camera and a photo-diary with instructions on how to document their thoughts about their photographs. They were also instructed that the purpose of this activity was to facilitate discussion and that the activity was not a requirement for participation in the discussions. Submitted
photographs were coded as representative of barriers or facilitators if participants showed them to the group in their responses to nutrition questions or if the photographs
noticeably related to nutrition.
Plan of analysis
To identify demographic characteristics and group differences, survey results were analyzed using univariate and bivariate statistics. Differences in perceptions of affordability, accessibility, and variety of fruits and vegetables in neighborhood stores were tested by categories of race, BMI, socioeconomic status (SES) as determined by income and
poverty rate by census block group, education, and chronic disease status using χ2 test of differences at the α = .05 level. The
poverty rate by census block group variable was created by using 2000 census data, which indicated that 12.3% of the North Carolina population lives below the poverty level. Focus group transcripts were content-analyzed for prevalent perceptions related to fruit and vegetable intake (20,21). Identified perceptions were then categorized by using the conceptual framework proposed by Booth and colleagues (11) (Figure,
Figure. Framework of determinants of physical activity and
behavior, from Booth et al (11). Reprinted with permission. [A
text description of this figure is also available.]
The framework includes individual (intrinsic), lifestyle-enabling, and external (extrinsic) environmental factors. Pictorially (Figure), the framework consists of 7 concentric rings categorized from the innermost to the outermost ring as follows: psychobiologic core, cultural, social, enablers of choice, behavioral settings, proximal leverage points, and distal leverage points. Each ring consists of specific factors that are separate from those in other rings (further described
in Table 1). The individual’s environment includes the psychobiologic core and cultural and social segments. The
psychobiologic core consists of the individual’s current physical health status and encompasses factors such as genes, instinctive and conditioned behaviors, and experiential learning. The
cultural segment encompasses values, traits, and beliefs acquired from the social and cultural environment. The social segment covers how
people perceive themselves and their social roles, and includes acquired beliefs and values (11). Positioned between the individual and the external environments are the
enablers of choice. These are the barriers and facilitators to change that are proximal to the individual and include factors that facilitate interaction between the individual and the external environment to promote or hinder the lifestyle behavior of interest. The external environment includes the remaining 3 outermost rings
in the framework. The first of these 3, labeled
behavioral settings, are the contexts, both physical and social, in which lifestyle behaviors occur.
Proximal leverage points are “controllers of the structure and feature of the microenvironment that affect the choices related to the behavior of interest” (11). Finally,
distal leverage points reflect macro-level influences on behavior and address systemwide factors such as the health care system, the information industry,
the food industry, and the government. Application of this model to the qualitative transcripts allowed us to categorize participants’ perceptions as either internal or external environmental influences on fruit and vegetable intake. In this
report, the terms intrinsic and extrinsic are used to describe the individual (personal) and external (physical/social) environments, respectively.
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The survey sample (N = 2,479) had a mean (SD) age of 52.8 (15.3) years, was predominantly female (72%),
non-Hispanic white (75%), married (63%), and
had a high-school diploma (87%). More than 44% of the sample had a total annual household income of less than $30,000. The mean
(SD) BMI was 29.4 (7.1), and the mean (SD) number of comorbid conditions was 3 (2)
(Table 2). The most prevalent chronic conditions reported, aside from musculoskeletal diseases, were high blood pressure (45.3%), depression (30.8%), diabetes
(18.7%), ulcer or stomach disease (gastroesophageal reflux disease or
acid reflux and gastritis) (15.1%), and heart disease (14.8%). Some participants reported more than 1 of these conditions. Compared with the survey sample, the formative assessment sample of 32
participants was older (mean [SD] age, 56 [13.9] years), heavier (mean [SD] BMI, 32.2 [7.8]), poorer (66.7%
had annual household incomes <$30,000), and less educated (68.8% had a high school diploma) (Table
Telephone survey results
Participants responded to 3 survey questions assessing food quality, variety, and affordability
(Table 3). BMI and counts of comorbid conditions were associated with significant differences in perceptions about quality of fruits and vegetables available at the grocery store where participants regularly shopped. The number of comorbid conditions was also significantly related to perceptions of variety. For affordability, we found significant differences by income,
education, BMI, poverty rate by census block group, and comorbid conditions (Table 3).
Age was significant for all 3 questions.
Transcripts revealed a rich dataset of perceptions related to factors perceived to affect
intake of fruits and vegetables. Findings from the community mappings helped to contextualize participants’ perceptions. Photographs shown and discussed by participants during the sessions included images of farms, restaurants, kitchen spaces, convenience stores, gardens, buffet foods, and condiments, and generally supported participant perceptions. We used the framework by Booth and
colleagues to categorize perceptions on the basis of related environmental factors highlighted in the framework and by the influence (barrier or facilitator) of the perception on dietary behavior (Table 4). Most perceptions were categorized as either a barrier or a facilitator. However, some had dual influences.
The following intrinsic factors were identified as barriers: food preferences, fatigue of taste buds for certain foods, life stresses, lack of forethought in meal planning, current personal health status, aging, and perceived impact of food on current chronic disease status. Intrinsic factors perceived as facilitators were
the presence of chronic disease, lifetime experience related to intake of fruits and vegetables, preferences for certain fruits and vegetables, and personal or spousal health
status. At the extrinsic level, participants reported the following factors as facilitators: availability of home gardens, low cost of foods at farm stands, and childhood exposure to fruits and vegetables. Perceived barriers included contradictory media messages related to nutrition and health outcomes, worksite food options, food availability, and food cost at grocery stores. Finally, participants reported the following as factors perceived to have an interactive effect: concerns about food
safety and perceptions about the interaction between chronic disease status and social and environmental influences on behavior and health. For example, participants highlighted the interactions between physical fatigue due to changing work schedules or shifts and stresses resulting from trying to manage fatigue, work schedule, and personal dietary intake
at home. Some participants perceived chronic disease status as a facilitator, whereas to others it was a barrier.
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Intake of fruits and vegetables is a major factor in the prevention of chronic diseases. The continued increase in chronic disease and obesity and the corresponding increase in poor chronic disease outcomes require different approaches. Using survey methods, we found that this sample was significantly overweight and was affected by chronic diseases. The 2007 health profile of North Carolina residents indicates suboptimal nutritional
practices. Reportedly, only 23% of residents consume the recommended daily intake of 5 or more fruits and vegetables, and 26% did not participate in leisure-time physical activity (3).
A recent survey that assessed the dietary habits of 1,788 people who were part of the 2005 enrichment of the NC-FM-RN reported that less than one-third had a daily intake of 3 or more servings of fruits and vegetables (22). These participants were not part of the NC-FM-RN cohort when our study was conducted. However, the mean BMI (29.6), which was calculated from self-reported weight and height (22), was similar to that of our sample. State-level data regarding
participants’ contextual perceptions are lacking and were not assessed by the earlier study. Nevertheless, a recent study in the United Kingdom has reportedly demonstrated a relationship between individuals’ socioeconomic context, perceptions about food intake, and BMI status (23). Our study’s use of formative research methods enabled us to provide significant information about
a specific North Carolina population that complements the findings of other surveys on
perceptions about the variety, affordability, and quality of foods available to participants and the impact of context on
intake of fruits and vegetable.
We did find that differences in education, poverty level, chronic disease status, and income affected perceptions of affordability, which may affect individuals’ intake. Affordability was perceived as a barrier for
poorer participants. However, no racial differences were found. These findings suggest that economics or SES rather than race or culture may be the key variable differentiating participants’ perceptions of the affordability of fruits and
vegetables. In fact, studies indicate that income differences have a greater effect on diet quality than on overall energy intake between groups (24). We also found significant differences in BMI levels related to quality. A greater percentage of people with high BMI perceived the quality of the fruits and vegetables at their grocery store to be excellent compared
to people with low BMI. Perhaps those with higher BMI are less discriminating and perceived all foods, including fruits and
vegetables, to generally be of great quality. For categories of comorbid conditions, however, differences across all 3 variables (quality, variety, and affordability) were found between those with no chronic condition and those with several. People with no comorbid condition were less likely to rate the variety and quality of their foods as excellent and were somewhat likely to rate the affordability as excellent. This finding may reflect the association between comorbidity and disability and
their combined impact on income and access. People with more comorbid conditions are potentially more likely to be disabled (25), which affects their income and therefore could affect their perception of the affordability of fruits and vegetables. This might account for why a lower percentage of people with more chronic conditions perceived fruits and vegetables as very affordable. Similarly, it is possible that those with no comorbid condition reflect a health-conscious group that has
higher income and health expectations and are therefore more critical in their evaluations of the quality and variety of foods available to them. The lower percentage of people in this category who perceived that the quality and variety of fruits and vegetables available to them is excellent is consistent with this conclusion.
One potential limitation of this study is the small sample used for the formative assessment. Researchers, however, indicate that, regardless of qualitative methodology used (focus group or key informant interviewing), with adequate representation, a sample of 30 individuals is enough to uncover the perceptions of the majority of a population (26,27). Other limitations of the study are that
intake of fruits and vegetables,
nutrition behavior, and weight and height data (for BMI) were not directly measured. Hence, correlations and causality cannot be verified for these variables.
Participants’ perceptions of intrinsic and extrinsic influences on
intake of fruits and vegetables are consistent with those of other studies (23,28-30) but specifically indicate that in this sample, behaviors and attitudes toward fruits and vegetables are influenced by both intrinsic and extrinsic environmental
factors. Furthermore, they provide grounds for reconsidering the focus of approaches to dietary interventions to see how salient they are in addressing the perceived needs for (or barriers to) behavior change in this population. Many interventions are based on findings from surveys that tend to focus on individuals’ behaviors with less emphasis on context.
Our results suggest that a complex web of factors and perceptions underpins participants’
nutrition behaviors. Overall, the results suggest that interventions should use multifactorial approaches that
acknowledge the contexts of individuals and their environmental limitations and should provide options that people can use to achieve healthy lifestyle habits. Interestingly, most of the perceptions described by the participants of this study were more intrinsic than extrinsic. This finding suggests that individually focused interventions would be useful in
helping them with chronic disease risk management. Family practice settings, from which all the participants of this study were recruited, may be an ideal place to start because they can serve as important sources of information for health promotion and disease prevention (22,31-33). A recent study confirms that individually tailored messages can significantly affect the nutrition behaviors of people who visit family practice settings (33). However, researchers also indicate that the
come for interventionists (whether public health or primary care) to look more closely at context — the risk-laden conditions within communities — rather than limit the focus to individual risk factors” (34). Thus, the emphasis should not be limited to individually focused efforts but
expanded to include linking individuals and family practice settings with available community-based resources. This effort is feasible for North Carolina; already several community-based programs promote
healthy nutrition habits. One notable program is the Eat Smart Move More North Carolina statewide initiative (www.eatsmartmovemorenc.com). This program targets all North Carolinians and has offerings designed for a multitude of settings and audiences. These offerings can be individually tailored, and when executed properly, allow individuals to access resources that promote risk reduction by increasing healthy nutrition and physical activity practices.
The findings of this study indicate that many unfavorable intrinsic and some extrinsic factors are perceived to affect the
intake of fruits and vegetables of this sample of North
Carolinians. The perceptions evidenced are of concern because they are associated with behaviors that increase chronic disease risk. Options that would facilitate increased fruit and vegetable intake are needed, and family practice settings and community-based programs may be useful places to begin.
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This study was funded by National Institute of Arthritis and Musculoskeletal
and Skin Diseases grant no. 5P60-AR49465-01. Dr Boyington was supported by the
National Institute of Arthritis and Musculoskeletal and Skin Diseases
grant no. 5P60-AR49465-04S1, National Institutes of Health, the National Center on
Minority Health and Health Disparities grant no. R24 MD000167, and the Department of
Health and Human Services, Agency for Healthcare Research and Quality R24
HS013353. Ms Remmes Martin was supported by the Carolina Program on Health and Aging Research Predoctoral Fellowship (National Institute on Aging
grant no. 5-T32-AG00272), the Arthritis Foundation Doctoral Dissertation Award, and the ACR REF Health Professional Graduate Student Research Preceptorship
We thank the following participating family practices in the North Carolina Family Medicine Research Network for their assistance: Black River Health Services, Burgaw; Bladen Medical Associates, Elizabethtown; Blair Family Medicine, Wallace; Cabarrus Family Medicine, Concord; Cabarrus Family Medicine, Harrisburg; Cabarrus Family Medicine, Kannapolis; Cabarrus Family Medicine, Mt. Pleasant; Chatham Primary Care, Siler City; CMC-Biddle Point, Charlotte; CMC-North Park, Charlotte;
Community Family Practice, Asheville; Cornerstone Medical Center, Burlington; Dayspring Family Medicine, Eden; Family Practice of Summerfield, Summerfield; Goldsboro Family Physicians, Goldsboro; Henderson Family Medicine Clinic, Henderson; Orange Family Medical Group, Hillsborough; Person Family Medical Center, Roxboro; Pittsboro Family Medicine, Pittsboro; Prospect Hill Community Health Center, Prospect Hill; Robbins Family Practice, Robbins; and Village Family Medicine, Chapel Hill.
gratefully acknowledge Andrea Meier, PhD, for her technical and research assistance in developing study materials, training study investigators, and troubleshooting data analysis software problems; Thelma Mielenz, PhD, for her assistance with Table 2;
and Matthew Morrison for attending to the logistics of planning and executing the focus groups and key informant interviews. Buncombe County Library, Henderson County Council on Aging, North Carolina Cooperative Extension — Bladen County Center,
Person County Public Library, Rockingham County Public Library — Eden Branch, and Wayne County Public Library are also gratefully acknowledged for providing facilities for the focus group discussions. We also thank Diane Beth at the Physical Activity and Nutrition Branch of the North Carolina Department of Health and Human Services for her assistance in reviewing current nutrition-based health programs in North Carolina. Finally, we thank the
participants in the
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Corresponding Author: Josephine E. A. Boyington, PhD, MPH, RN, Health Scientist Administrator, NIH/NINR, One Democracy Plaza, 6701 Democracy Blvd, Suite 710, Bethesda, MD 20892.
Telephone: 301-594-2542. E-mail: email@example.com. Dr Boyington’s
contribution to this article occurred in association with her tenure as a
research associate/epidemiologist at Shaw University and as a Diversity Research
investigator at Thurston Arthritis Research Center, University of North Carolina
at Chapel Hill.
Author Affiliations: Britta Schoster, Jack Shreffler, Thurston Arthritis Research Center; Kathryn Remmes Martin, Thurston Arthritis Research Center,
Gillings School of Public Health, the Institute on Aging; Leigh F. Callahan, Thurston Arthritis Research Center, Department of Medicine, Department of Orthopedics, Department of Social Medicine, University of North Carolina at Chapel Hill.
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