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Ecology of Food and Nutrition Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gefn20
Consumer Food System Participation: A Community Analysis a
b
Mary K. Griffin & Jeffery Sobal a
Registered Dietitian, Independent Practitioner, Elmira, New York, USA b
Division of Nutritional Sciences, Cornell University, Ithaca, New York, USA Published online: 30 Oct 2014.
Click for updates To cite this article: Mary K. Griffin & Jeffery Sobal (2014) Consumer Food System Participation: A Community Analysis, Ecology of Food and Nutrition, 53:6, 579-595, DOI: 10.1080/03670244.2014.891992 To link to this article: http://dx.doi.org/10.1080/03670244.2014.891992
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Ecology of Food and Nutrition, 53:579–595, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 0367-0244 print/1543-5237 online DOI: 10.1080/03670244.2014.891992
Consumer Food System Participation: A Community Analysis MARY K. GRIFFIN Registered Dietitian, Independent Practitioner, Elmira, New York, USA
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JEFFERY SOBAL Division of Nutritional Sciences, Cornell University, Ithaca, New York, USA
This study examined the prevalence, patterns, and health associations of consumer participation in different stages of the food system using a survey of 663 adults in one U.S. county. Consumer food system participation by stage was 43% in food production, 47% in food processing, 65% in food distribution, 62% in food acquisition, 61% in food preparation, and 100% in food consumption. Consumers participated in an average of 3.7 of these 6 possible stages. Women and unmarried people participated in more stages. Food system participation was associated with few health problems, although people reporting some illnesses had higher food system participation. KEYWORDS food system, community, consumer, survey, health, nutrition, production, processing Everyone participates in food consumption, but little is known about involvement of food consumers across multiple stages of the food system. Unlike earlier historical eras, individuals in contemporary industrial and postindustrial nations are less dependent on their own participation across all stages of the food system to ensure that food is available for their consumption. However, consumers may choose to participate in the six major stages of the food system (Griffin, Sobal, and Lyson 2009; Sobal, Khan, and Bisogni 1998) representing food production, processing, distribution, acquisition, preparation, and consumption. For example, consumers are producers when they garden, hunt, fish, or gather for food. Consumers process foods by freezing or preserving (e.g., canning, drying). Individuals distribute surplus Address correspondence to Jeffery Sobal, Division of Nutritional Sciences, 407 Savage Hall, Cornell University, Ithaca, NY 14853, USA. E-mail: [email protected] 579
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foods to family, neighbors, or charities. Consumers purchase foods in markets, restaurants, or other settings. Consumers prepare food through cooking. Finally, all consumers ingest foods, and what they eat is manifested in health or disease after nutrient digestion and metabolism. How are health outcomes associated with participation in the food system? Fishing and hunting may facilitate consumption of particular foods, at least seasonally. Fishing for food may affect risk of contamination from fish caught in polluted waters (Alasalvar et al. 2010), but consumption of fish is also associated with lower morbidity and mortality (Takata et al. 2013). Preserving foods through freezing and canning promotes consumption of particular foods, and procedures used to preserve foods (e.g., salting) affect its nutritional value. Distributing foods through trades, gifts, or donations to food charities affects household food availability (Morton et al. 2008). Food shopping is an important point of control for the type and nutritional value of foods consumed (Hershey et al. 2001; Yoo et al. 2006). Involvement in food preparation influences nutrient intake (Crawford et al. 2007). Systems theory (Bertalanaffy 1968; Spedding 2012) provides a useful framework for examining patterns of participation in food behaviors and health conditions. Systems theory suggests that participation in many types of food activities should be examined as a whole because each activity may affect other activities, activities are situated within social and physical environments, and activities may individually and interactively influence outcomes like health. The food and nutrition system (Sobal 2004; Sobal et al. 1998) provides a common framework that encourages holistic and interdisciplinary examinations of food, eating, nutrition, and health. Prior research has not clearly examined the range of consumer food system participation or investigated whether participation across the scope of stages in the food system is associated with health problems. Reviews of the nutrition, food science, agricultural, consumer science, and economics literatures revealed relatively few studies exploring associations of health with gardening, hunting, fishing, food preservation, food shopping, and cooking (e.g., Casperson et al. 1991; Crawford et al. 2007; Smith and Miller 2011). The aims of this investigation were to: 1) quantify the prevalence of residents of a community food system who participate in food system stages of production, processing, distribution, acquisition, preparation, and consumption, 2) examine demographic patterns in consumer food system participation, and 3) investigate potential associations between the extent of food system participation and health problems.
METHODS Setting and Sample To examine consumer involvement in one community food and nutrition system, a cross-sectional postal mail survey of residents of one U.S. county
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in Upstate New York was conducted in 1999 (Griffin and Sobal 2013; Sobal and Nelson 2003). This county (population 97,000) provided a case example of a community food system that encompassed both rural and urban areas plus a diversity of ethnic groups. A city centrally located in the county had a population of 29,500 plus a university of about 19,000 students and a college of about 6,000 students. The data collection and analysis were approved by the University Institutional Review Board (IRB). The survey was sent by postal mail to a random sample of county residents from telephone book white pages supplemented by automobile registrations to reduce selection bias against people without telephones or with unlisted numbers. Tailored design (Dillman 2000) to maximize response rates used a postcard reminder and two follow-up letters to non-respondents.
Measures Individual survey questions assessed respondents’ participation in food system stages of (1) food production through gardening, hunting, and fishing; (2) food processing by freezing or preserving (canning, drying) foods; (3) food distribution through giving/trading food or donating food to feed the hungry; (4) food acquisition through being the primary household grocery shopper; (5) food preparation as being the primary household meal preparer/cook; and (6) food consumption as responding to questions about meal frequency. These activities were chosen for the initial survey and present analysis based on a review of the agriculture, nutrition, economics, food marketing, and sociology literature about food systems, with frequently mentioned activities included here. To construct a measure of involvement in multiple stages of the food system, a Food System Participation Index was calculated by summing responses to questions about behaviors in each of the stages in the system. This index had possible values from 1-6 and represented the number of stages from production to consumption in which consumers participated. A score of 1 represented only consumption, and a score of 6 represented participation across the whole food system. The index permits analysis of participation in multiple different food system activities. Respondents were asked whether they had high cholesterol, obesity, hypertension, food allergies, heart disease, diabetes, anemia, heart attack, cancer, food poisoning, bulimia, and anorexia nervosa. These illnesses were chosen based on their prevalence in the US population, their association with diet as a contributing factor, or the critical role diet and nutritional status play in mediating the illnesses (Erdman, Macdonald, and Zeisel 2012; National Research Council 1989). Body weight and height were self-reported and converted to body mass index (BMI) to measure obesity, with a BMI ≥ 30 identified as obese (Dietz and Robinson 1998; WHO Expert Committee 1995). Respondents also self-reported overall health status, rating their health
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as either excellent/good or fair/poor. Demographic characteristics of gender, ethnicity, age, household size, marital status, employment, educational achievement, and student status were collected.
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Analysis Data were first characterized for key variables using descriptive statistics. Multivariate logistic regression was used to determine how well and in what direction demographic variables were associated with participation in food system activities and with health problems. Regression diagnostics were run for each model (Kleinbaum et al. 2013), and for the models that did not fit the data, Chi-square analyses were used to confirm significance of those associations. Chi-square tests were used to examine if participation in different food and nutrition activities was related to nutrition and health problems. The Food System Participation Index was regressed on demographic variables using multiple linear regression, and was also used as a predictor of each health problem. Significance was reported at .05, .01, and .001 to permit readers to make their own interpretations of Type I error risk in the multiple statistical tests performed here (Bender and Lang 2001).
RESULTS Sample Characteristics A total of 667 surveys were completed for an overall response rate of 65% of deliverable surveys. Four respondents were under 18 or did not reside in the county, and their exclusion produced a final sample of 663. Gender, race, and education did not significantly differ among the three mailings, suggesting additional mailings would not produce different types of respondents. However, older people responded more to earlier mailings (p < .05), possibly because the survey was first administered in June when many college students were away. Demographic characteristics of respondents are summarized in table 1. Comparing the sample demographics with the U.S. Census data for the county revealed that the survey sample was representative with respect to gender, race, and household size. However, the sample was older, more likely to be employed, and more educated than the county population.
Food-System Stage Participation Over 42% of the consumers sampled were involved in some form of food production (gardening, hunting, fishing, or some combination, table 2). None of the demographic variables were significant predictors of gardening,
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Food System Participation TABLE 1 Demographic Characteristics of the Sample
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Characteristics Sex Female Race White Age (µ = 46 ± 17 years) 18–21 22–34 35–54 ≥ 55 Household size (µ = 2.6 ± 2.7) 1 person 2 people ≥ 3 people Marital status Currently married Employment Employed Education High school or less Some college Associates/Bachelors Graduate degree Student status Student 1 2
Sample
Census1
46%
51%
84%
90%
6% 24% 42% 29%
25% 29% 27% 19%
25% 40% 35%
27% 34% 39%
47%
NA2
66%
51%
20% 18% 30% 31%
33% 29% 22% 16%
16%
28%
Source: U.S. Census Bureau (1990). NA = Data not available.
indicating that gardening was fairly homogeneous across this sample, while men, individuals with fewer years of education, and non-students more often hunted or fished. Food processing was indicated by freezing and preserving foods. Overall participation in any food processing was 47%. Processing was done more often by female, older, or less-educated consumers. Participation in some form of food distribution, whether giving, trading, or donating food, was reported by almost two-thirds (65%) of respondents. Women more often participated in these food distribution activities, as did persons with fewer years of education, those who were white, and older consumers. Food acquisition involved 62% of respondents as the primary grocery shopper for their household. Women, the unmarried, the less-educated, and individuals living in small households more frequently shopped for groceries. Food preparation involved 61% of respondents reporting they were the primary cook for their household. Women, the unmarried, and respondents living in households with few or no other people more often cooked. Food consumption involved everyone in the sample (100%) reporting that they consumed food.
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35.8 11.0 10.6 41.1 24.6 32.2 53.0 61.7 60.8
Response (%)
Race (white) .22 .39 −.32 .32 .34 .39 .70∗∗ −.11 .01
Sex (male) −.24 1.35∗∗∗ 1.07∗∗∗ −.44∗ −.64∗∗ −.55∗∗ −.47∗∗ −1.32∗∗∗ −1.03∗∗∗ .01 −.02 −.01 .02∗ .02∗∗ .00 .02∗ .00 −.01
Age (years) −.02 .00 −.02 .09∗ −.01 .04 −.01 −.09∗ −.15∗∗
HH size .12 −.43 −.43 .51∗∗ .06 1.90 .35 −1.81∗∗∗ −1.64∗∗∗
Marital (married)
.10 −.38 −.26 −.23 .43 .09 .23 .03 −.03
Employment (working)
−.06 −.46∗∗∗ −.41∗∗∗ −.27∗∗∗ −.23∗∗ −.19∗∗∗ .16∗∗ .14∗ .11
Education
−.57 −2.46∗∗ −1.34 −.31 .15 −.48 .04 .67 .05
Student (student)
Note. Demographic variable figures are regression coefficients (betas) from logistic regressions, where subsystem activity was the dependent variable. Coding for dependent variables is: 0 = respondent does not perform, 1 = respondent performs. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
Garden Hunt Fish Freeze food Preserve food Give/Trade food Donate food Who shops (Acquisition) Who cooks (Preparation)
Participation activity
Demographic variables
TABLE 2 Consumer Food System Participation Activities and Associations with Demographic Characteristics
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Overall, participation in the food and nutrition system was greatest in the stages of (1) consumption, (2) distribution, and (3) acquisition. Participation was also heterogeneous, with women and people with less education more often participating in food system activities for each stage.
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Health Measures Findings about health measures are summarized in table 3. Hypercholesterolemia was the most prevalent health problem in the sample. Being older was the only significant predictor of high cholesterol. The average reported BMI was 24.6 ± 5.2 for women and 26.3 ± 4.4 for men, and 16% of respondents had a calculated BMI ≥ 30, the criterion for obesity. Married people and people with fewer years of education were more often obese than were the unmarried or college educated. No demographics significantly predicted hypertension. More women reported having allergies. Participants with heart disease were more often older respondents. More nonwhites had diabetes than whites. Women, nonwhites, and less-educated persons were more likely to report anemia. Men and older individuals reported significantly more heart attacks. Cancer was reported by only 3% of respondents, who were more often women than men. Food poisoning was also reported by few participants, with more women reporting this illness than men. A very small number of respondents (n = 4) reported having bulimia nervosa, and none of those surveyed reported having anorexia nervosa. With such a small sample size, a regression model could not be used, but Chi-square tests revealed that being white, employed, and a student were associated with bulimia. Over 80% stated that their health was excellent or good, with women, white, employed, and more educated consumers reporting more favorable health. Controlling for demographic characteristics (table 4) revealed that food system participation by freezing foods and preserving foods were associated with reporting high cholesterol. In contrast, food system participation by freezing foods and food preparation were associated with lower likelihood of reporting anemia.
Whole Food System Participation The food system participation index scores (figure 1) had a mean of 3.7 ± 1.3 stages, with most respondents involved in either three (26%) or four (30%) stages of the system. The majority of respondents who scored three were involved in acquisition, preparation, and consumption. Many of those who scored four were participating in either production, processing, distribution, and consumption, or else distribution, acquisition, preparation, and consumption. Approximately 10% of the sample was involved in all six stages
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16.0 15.9 15.6 10.5 7.8 5.2 4.7 3.7 3.2 1.9 0.6 0.0 81.0
High cholesterol Obesity Hypertension Food allergies Heart disease Diabetes Anemia Heart attack Cancer Food poisoning Bulimia Anorexia Good health
.03 .13 .41 −.73∗ −.02 −.17 −2.51∗∗∗ 1.50∗ −1.10∗ −2.23∗ −.89 − −.18
Sex (male)
Age (years) .04∗∗∗ .01 .06 .01 .04∗∗ .03 −.02 .05∗∗ .03 .03 −.03 − .02
Race (white) −.41 −.06 −.33 −.03 −.12 −1.32∗∗ −1.44∗∗ −.01 .09 .95 7.64 − .60∗
−.05 −.16 −.08 −.02 −.48 −.19 −.01 −.82 −.32 .03 −.31 − .04
HH size (people) .22 .66∗ −.34 −.57 .34 .20 .15 .32 1.14 −1.70 −.29 − −.19
Marital (married) .13 .54 −.18 .25 −.60 −.12 −.14 .33 −.60 1.21 6.43 − .96∗∗
Employment (working)
.01 −.41∗∗∗ −.11 .02 −.19 −.18 −.41∗∗ −.44 −.08 −.04 .18 − .25∗∗∗
Education
−.03 .28 −.89 .15 −.62 −6.82 .02 −5.43 −6.32 2.29 6.42 − 1.00
Student (student)
Note. Demographic variable figures are regression coefficients (betas) from logistic regressions, where health problem was the dependent variable. Coding for dependent variables is: 0 = respondent does not have, 1 = respondent has. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
Health response (%)
Health variable
Demographic variables
TABLE 3 Health Variables and Associations with Demographic Characteristics
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.09 .03 −.15 .23 −.66 .46 .25 −.77 −1.01 .59 10.20 − −.19
High cholesterol Obesity Hypertension Food allergies Heart disease Diabetes Anemia Heart attack Cancer Food poisoning Bulimia Anorexia Good health
.28 −.56 .12 −.39 −.13 .13 −.56 −.17 .12 −6.38 −7.60 − −.09
Hunt .31 −.19 .06 −.44 −.40 .56 .13 −1.62 .38 −.18 −7.56 − −.13
Fish
Preserve .13∗ .54 .26 −.16 −.49 .64 .20 −.54 −.27 .24 −1.41 − −.16
Freeze .20∗ .47 .21 .13 .26 .06 −1.09∗ −.09 .04 .83 −.37 − −.28 .12 .11 .01 .04 .13 −.07 −.66 −.16 .51 −.67 −10.29 − −.25
Give/trade
Note. Figures are measures of association (Somers’ d) derived from Chi-square test of independence. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
Garden
Health variable
Food system participation activity
TABLE 4 Association between Food System Participation Activities and Health Variables
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.26 .34 .21 .20 −.14 .48 −.16 .08 −.28 1.01 .94 − .27
Donate
3.6 .15 −.53 −.56 .31 .21 −.63 .61 .68 −.58 −.08 − −.53∗
Who shops
.14 −.17 −.23 .07 .29 .12 −.92∗ .36 −.63 −.77 .04 − −.22
Who cooks
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FIGURE 1 Participation in multiple stages of the food system. TABLE 5 Association between the Food System Participation Index and Demographic Variables Demographic variables Sex (male) Participation −.66∗∗∗ Index
Race (white) Age .15
.01
HH size
Marital (married)
−.02
−.50∗∗∗
Employment Student (working) Education (student) .11
−.05
−.16
Note. Figures are regression coefficients (betas) from linear regression, with food system participation as the dependent variable. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
of the food system. To examine how the index scores varied by demographics, a linear regression of the index was performed against demographic variables (table 5). Women and unmarried individuals scored significantly higher on the participation index. Health problems were regressed on the food system participation index, first alone and then adjusted for demographic variables, to determine whether a higher degree of food system participation (i.e., a higher index score) was associated with health conditions (table 6). Unadjusted for any demographic variables, only food allergies and diabetes were significantly associated with food system participation. Both were positively associated, meaning that individuals who were more likely to report having allergies and diabetes scored higher on the food system participation index. However, when demographic characteristics were controlled in a second regression model, the relationships were weaker and no longer significant. Thus, adjusting for all control variables, no health problems were found to be significantly associated with whole food system participation index scores.
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Food System Participation TABLE 6 Association between the Food System Participation Index and Health Variables
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Health problem High cholesterol Obesity Hypertension Food allergies Heart disease Diabetes Anemia Heart attack Cancer Food poisoning Bulimia Anorexia Self-reported health
Food System Participation Index
Adjusted Food System Participation Index
.06 .12 .04 .23∗ .10 .31∗ −.02 .05 .01 .39 .88 − −.06
.13 .17 .04 .05 .06 .28 −.31 .06 −.10 .14 .84 − −.08
Note. Figures are regression coefficients (betas) from linear regression, with food system participation as the dependent variable. The adjusted index represents a multivariate relationship between health and food system participation controlling for age, sex, race, household size, marital status, employment, education, and student status. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
DISCUSSION Community food system participation is of concern to food professionals involved in planning and producing products, programs, policies, and services (Boyle and Holben 2012). Food and nutrition professionals can benefit from knowledge about participation in many components of whole food systems (Hillers 1991; Smith and Miller 2011), especially consumer participation in the system (Novotny et al. 2011; Peters 1997). Consumers are the main targets of food advertisements, nutrition education messages, and health interventions that affect food choices and other food behaviors. Knowledge about consumer food system involvement can help improve educational messages and services by tailoring or targeting them to reflect patterns of consumer food system participation. For example, specific strategies may be used to increase fruit and vegetable consumption in a community where cancer rates are high, change the extent of consumer food system participation, like developing a community food donation network or facilitating vegetable gardening, or intervening in food stores to buy more local products to prevent obesity (Novotny et al. 2011). This investigation showed that the extent of consumer involvement in this community food system was moderate, with the majority of consumers participating in 3 to 4 of the 6 stages of the food system. Several consumer demographic characteristics were significantly associated with food system participation. Men more often produced food through hunting and fishing, while women more often processed and distributed food, shopped, and
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cooked. Hunting and fishing are seen as predominantly “male” activities in American society (Sobal 2005), whereas women more often fill the roles of food shopper and cook in American households (Harnack et al. 1998; Smith, Ng, and Popkin 2013). Older people more often processed and distributed food, perhaps because they had more time or resources, or were more involved in traditional food activities (Morton et al. 2008; Quandt, Popyach, and DeWalt 1994). Consumers living in larger households and married people more often preserved foods through freezing, while people living in smaller households and the unmarried more often shopped and cooked. Larger households may achieve better economies of scale by purchasing foods in bulk and storing them, while individuals who live alone probably have no other person with whom to share household food activities (Westenbrick et al. 1989). Consumers with fewer years of education were more often involved in production, processing, distribution, and acquisition. Educational achievement is a component of socioeconomic status (SES). Low SES individuals may have fewer resources to spend on food and thus pursue alternative food sources, purchase in bulk and preserve for future use, and empathize with people in need of food sharing (Dammann and Smith 2009). Demographic characteristics were also associated with health problems. Men more often reported heart attacks, an anticipated finding since gender is a risk factor for cardiovascular disease (Erdman et al. 2012). Nonwhites reported more diabetes and anemia, which parallels the higher prevalence of these illnesses among nonwhite ethnic groups in the United States (Kumanyika 2006). Older people more often reported high cholesterol, coronary heart disease, and heart attacks; these illnesses typically become more prevalent with aging in the U.S. (Erdman et al. 2012). Married people were more obese, possibly an effect of more regular, frequent meal consumption patterns or less exercise (Sobal, Hanson, and Frongillo 2009). The less-educated reported more cases of anemia, which is common (Kumanyika 2006), and obesity, perhaps because people with less education may purchase cheaper energy dense foods or be exposed to fewer messages about diet and exercise as mediators of body weight (Dammann and Smith 2009). Women, white, employed, and more educated respondents more often reported their health to be good, which mirrors health patterns across gender, ethnic, and socioeconomic groups in the United States (Erdman et al. 2012; Idler and Benyamini 1997). Women and unmarried individuals had significantly higher scores on the food system participation index. The significant gender relationship paralleled results of bivariate analyses of each individual activity and reflects traditional food roles in which acquisition and preparation roles are generally filled by women (Harnack et al. 1998; Smith et al. 2013). The relationship with marital status may be a consequence of unmarried people having no partner with whom to share labor involved in food acquisition and
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preparation tasks, or having more time to pursue activities such as food production and processing (Bove and Sobal 2006). Participation in the food system could provide healthier foods that reduce disease and/or less healthy foods that increase disease, or people with diseases may participate differently in the food system to manage their diseases. In these data, participation in food system activities was associated with few health problems, but those correlations that were significant revealed conflicting findings of both higher and lower prevalence of illness among consumers who are more active food system participants. In this analysis, food processing and preparation were negatively associated with anemia, while processing foods was positively associated with hypercholesterolemia. Processing and preparation are two stages of the food system where consumers have the greatest ability to alter the nutrient content of their food—for example, more frequently freezing foods like meats with high iron content or using cast iron cooking equipment to increase the iron content of food—which may explain why consumers in this sample who processed and cooked their own food reported fewer cases of anemia. With regards to hypercholesterolemia, processing foods may contribute to high cholesterol through the increased intake of simple sugars that are typically used in home food processing, particularly canning. However, the large number of positive associations we found between food system participation and health (see table 4), while not statistically significant, lend support to a hypothesis that consumers who are diagnosed with a health problem may increase their participation in the food system in order to more closely control the sources and nutrient content of their food. Associations between participation in some food system activities and health have previously been reported. Elderly men who garden have healthier cholesterol levels and lower blood pressure (Caspersen et al. 1991). Similar beneficial associations occur between cholesterol levels and household production of foods grown, raised, or caught at home (Blair, Giesecke, and Sherman 1991; Pearson et al. 1999; Zick et al. 2013). Greater fruit and vegetable consumption, higher nutrient intakes, and lower body weights are associated with fruit and vegetable gardening (Holben et al. 2004; Marsh 1998). In contrast, hunting has been associated with increased risk of cardiovascular illnesses (Peterson et al. 1999), and concerns exist about exposure to environmental contaminants through consumption of wild fish and game (Burger 2002). Participation in the food system has been shown, both in this analysis and in previous studies, to be associated with better health (Pearson et al. 1999), more illness (Peterson et al.1999), or neither (Hamelin, Mercier, and Bedard 2008). Two mechanisms may operate in relationships between food system participation and health: selection and causation (Goldman 1994). Selection may occur when people who have health problems or who wish to avoid health problems participate in the food system differently from
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those without health problems. Causation may occur when participation in the food system leads to better or worse health. Cross-sectional data such as these cannot definitively establish whether selection or causation is operating (Goldman 1994), but findings of cross-sectional associations can provide evidence in support of selection or causation relationships. To further explore these relationships, future studies need to examine food system participation and health using longitudinal research designs to explicitly analyze the extent of selection, causation, or both as mechanisms linking food system participation and health. Sampling limitations of this study include examining only one county in 1999, which may limit ability to generalize these findings to community food systems in other places and times. Non-respondents may have differed from the sample of respondents, despite the majority who responded. We assume that only literate individuals returned completed surveys, and because education was significantly associated with food system participation these findings may have been different if another data collection method (e.g., telephone surveys) was used. Measurement limitations may have occurred in this self-reported data, although mailed questionnaires have less social desirability responses than face-to-face interviews (Dillman 2000). While some bias occurs in selfreporting body weight and height, analysis of U.S. national data showed that measured weight and height are highly correlated with reported weight (r = .97) and reported height (r = .93) (Sobal, Hanson, and Frongillo 2009). Self-reported health is a subjective measure widely used as an overall health indicator, and it strongly predicts morbidity and mortality (Idler and Benyamini 1997).
Implications These findings suggest that food professionals may benefit from being aware of consumer food system participation. A diagnosis of coronary heart disease, hypertension, diabetes, or other diet-related illnesses may lead individuals to become more involved in food system activities, activities in which food professionals may provide information or target specific types of consumers for interventions. Food professionals also may want to facilitate broader food system involvement in their communities by raising consumer consciousness about increased food system participation as a way to control their dietary intake (Novotny et al. 2011; Sanlier and Karakus 2010), thereby raising awareness of the connections between diet, environment, and health (Harmon and Maretzki 2006; Hillers 1991; Peters 1997). This study contributes to research examining food systems and associations between health and food system participation. Food and nutrition activities not previously well studied were assessed in this study, and participation across the whole food system was also examined. Further research is
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needed to better understand associations between food system participation and health, including qualitative research about patterns of participation and quantitative analysis of longitudinal data to examine selection and causation in food system participation.
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REFERENCES Alasalvar, A., K. Miyashita, F. Shahidi, and U. Wanasundara. (eds). 2010. Handbook of seafood quality, safety, and health applications. New York, NY: WileyBlackwell. Bender, R. and S. Lange. 2001. Adjusting for multiple testing—when and how? Journal of Clinical Epidemiology 54:343–349. Bertalanffy, L. 1968. General systems theory: Foundation, development, applications. New York, NY: Braziller. Boyle, M.A., and D. H. Holben. 2012. Community nutrition in action: An entrepreneurial approach. 6th ed. Stamford, CT: Cengage Learning. Blair, D., C. C. Giesecke, and S. Sherman. 1991. A dietary, social, and economic evaluation of the Philadelphia Urban Gardening Project. Journal of Nutrition Education 23:161–167. Bove, C. A., and J. Sobal. 2006. Foodwork in newly married couples: Making family meals. Food, Culture and Society 9 (1):70–89. Burger, J. 2002. Daily consumption of wild fish and game: Exposures of high end recreationists. International Journal of Environmental Health Research 12 (4):343–354. Caspersen, C. J., B. P. M. Bloemberg, W. H. M. Saris, R. K. Merritt, and D. Kromhout. 1991. The prevalence of selected physical activities and their relation with coronary heart disease risk factors in elderly men: The Zutphen Study, 1985. American Journal of Epidemiology 133:1078–1092. Crawford, D., K. Ball, G. Mishra, J. Salmon, and A. Timperio. 2007. Which foodrelated behaviors are associated with healthier intakes of fruits and vegetables among women? Public Health Nutrition 10:256–265. Dammann, K. W., and C. Smith. 2009. Factors affecting low-income women’s food choices and the perceived impact of dietary intake and socioeconomic status on their health and weight. Journal of Nutrition Education and Behavior 41:242–253. Dietz, W. H., and T. N. Robinson. 1998. Use of body mass index as a measure for overweight in children and adolescents. Journal of Pediatrics 132:191–193. Dillman, D. A. 2000. Mail and internet surveys: The tailored design method. New York, NY: John Wiley. Erdman, J. W., I. A. Macdonald, and S. H. Zeisel. (eds.). 2012. Present knowledge in nutrition. International Life Sciences Institute (ILSI). 10th ed. Malden, MA: Wiley-Blackwell. Goldman, N. 1994. Social factors and health: The causation-selection issue revisited. Proceedings of the National Academy of Sciences 91:1251–1255. Griffin, M. K., J. Sobal, and T. A. Lyson. 2009. An analysis of a community food waste stream. Agriculture and Human Values 26 (1):67–81.
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Griffin, M. K., and J. Sobal. 2013. Sustainable food activities among consumers: A community study. Journal of Hunger and Environmental Nutrition 8:1–18. Harmon, A.H., and A.N. Maretzki. 2006. Assessing food system attitudes among youth: Development and evaluation of attitude measures. Journal of Nutrition Education and Behavior 38:91–95. Harnack, L., M. Story, B. Martinson, D. Neumark-Sztainer, and J. Stang. 1998. Guess who’s cooking? The role of men in meal planning, shopping, and preparation in U.S. families. Journal of the American Dietetic Association 98:995–1000. Hamelin, A.M., C. Mercier, and A. Bedard. 2008. Perception of needs and responses in food security: Divergence between households and stakeholders. Public Health Nutrition 11:1389–1396. Hershey, J., J. Anlicker, C. Miller, R.M. Mullis, S. Daugherty, S. Das, C.R. Bray, P. Dennee, M. Sigman-Grant, and A.H. Olivia. 2001. Food shopping practices are associated with dietary quality in low-income households. Journal of Nutrition Education 33 (Supplement 1):S16–S26. Hillers, V. 1991. Changing agriculture: Roles for food and nutrition educators. Journal of Nutrition Education 23(9):36–38. Holben, D. H., M. C. McClincy, J. P. Holcomb, K. L. Dean, and C. E. Walker. 2004. Food security status of households in Appalachian Ohio with children in Head Start. Journal of the American Dietetic Association 104 (2):238–241. Idler, E. L., and Y. Benyamini. 1997. Self-rated health: A review of twenty-seven community studies. Journal of Health and Social Behavior 38:21–37. Kleinbaum, D. G., L. L. Kupper, A. Nizam, and E. S. Rosenberg. 2013. Applied regression analysis and other multivariable methods. 5th ed. Stamford, CT: Cengage Learning. Kumanyika, S. 2006. Nutrition and chronic disease prevention: Priorities for U.S. minority groups. Nutrition Reviews 64:S9–14. Marsh, R. 1998. Building on traditional gardening to improve household food security. Food, Nutrition and Agriculture 22:4–14. Morton, L. W., E. A. Bitto, M. J. Oakland, and M. Sand. 2008. Accessing food resources: Rural and urban patterns of giving and getting food. Agriculture and Human Values 25:107–119. National Research Council. 1989. Diet and health: Implications for reducing chronic disease risk. Washington, DC: National Academy Press. Novotny, R., V. Vijayedva, V. Ramierez, S. K. Lee, N. Davison, and J. Gittelsohn. 2011. Development and implementation of a food system intervention to prevent childhood obesity in Rural Hawai’i. Hawai’i Medical Journal 70 (Supplement 1):42–46. Pearson, J. M., D. Schlettwein-Gsell, C.P.G.M. de Groot, and W. A. van Staveren. 1999. Using home-grown food is associated with higher nutrient intake in elderly people across Europe. Journal of Consumer Studies and Home Economics 23:27–35. Peters, J. 1997. Community food systems: Working toward a sustainable future. Journal of the American Dietetic Association 97:955–956. Peterson, A. T., J. Steffen, L. Terry, J. David, J. P. Porcari, and C. Foster. 1999. Metabolic responses associated with deer hunting. Medicine and Science in Sports and Exercise 31:1844–1848.
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Quandt, S. A., J. B. Popyach, and K. M. DeWalt. 1994. Home gardening and food preservation practices of the elderly in rural Kentucky. Ecology of Food and Nutrition 31:183–199. Sanlier, N., and S. S. Karakus. 2010. Evaluation of food purchasing behavior of consumers from supermarkets. British Food Journal 112 (2):140–150. Smith, C., and H. Miller. 2011. Accessing food systems in urban and rural Minnesotan communities. Journal of Nutrition Education and Behavior 43:492–504. Smith, L. P., S. W. Ng, and B. M. Popkin. 2013. Trends in U.S. home food preparation and consumption: Analysis of national nutrition surveys and time use studies from 1965–1966 to 2007–2008. Nutrition Journal 14:45. http://www.nutritionj. com Sobal, J. 2004. Food and nutrition systems. In Encyclopedia of Food and Drink in America, ed. A. Smith, 495–498. New York, NY: Oxford University Press. Sobal, J. 2005. Men, meat, and marriage: Models of masculinity. Food and Foodways 12 (1-2):135–158. Sobal, J., K. Hanson, and E. A. Frongillo. 2009. Gender, ethnicity, marital status, and body weight in the U.S. Obesity 17:2223–2231. Sobal, J., L. K. Kahn, and C. Bisogni. 1998. A conceptual model of the food and nutrition system. Social Science and Medicine 47:853–863. Sobal, J., and M. K. Nelson. 2003. Commensal eating patterns: A community study. Appetite 41:181–190. Spedding, C. 2012. An introduction to agricultural systems. 2nd ed. New York, NY: Springer. Takata, Y., X. Zhang, H. Li, Y. Gao, G. Yang, J. Gao, H. Cai, Y. Xiang, W. Zheng, and X. Shu. 2013. Fish intake and risks of total and cause-specific mortality in 2 population-based cohort studies of 134,296 men and women. American Journal of Epidemiology 178:46–57. Westenbrick, S., M. R. Lowik, K. F. Hulshof, and C. Kistemaker. 1989. Effects of household size on nutritional patterns. Journal of the American Dietetic Association 89:793–799. WHO Expert Committee. 1995. Physical status: The use and interpretation of anthropometry. World Health Organization: Geneva. Yoo, S., T. Baranowski, M. Missaghian, J. Baranowski, K. Cullen, J. O. Fischer, K. Watson, I. F. Zakeri, and T. Nicklas, T. 2006. Food-purchasing patterns for home: A grocery store-intercept survey. Public Health Nutrition 9:384–393. Zick, C. D., K. R. Smith, L. Kowalewski-Jones, C. Uno, and B. J. Merrill. 2013. Harvesting more than vegetables: The potential weight control effects of community gardening. American Journal of Public Health 103:1110–1115.
Ecology of Food and Nutrition Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gefn20
Consumer Food System Participation: A Community Analysis a
b
Mary K. Griffin & Jeffery Sobal a
Registered Dietitian, Independent Practitioner, Elmira, New York, USA b
Division of Nutritional Sciences, Cornell University, Ithaca, New York, USA Published online: 30 Oct 2014.
Click for updates To cite this article: Mary K. Griffin & Jeffery Sobal (2014) Consumer Food System Participation: A Community Analysis, Ecology of Food and Nutrition, 53:6, 579-595, DOI: 10.1080/03670244.2014.891992 To link to this article: http://dx.doi.org/10.1080/03670244.2014.891992
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Ecology of Food and Nutrition, 53:579–595, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 0367-0244 print/1543-5237 online DOI: 10.1080/03670244.2014.891992
Consumer Food System Participation: A Community Analysis MARY K. GRIFFIN Registered Dietitian, Independent Practitioner, Elmira, New York, USA
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JEFFERY SOBAL Division of Nutritional Sciences, Cornell University, Ithaca, New York, USA
This study examined the prevalence, patterns, and health associations of consumer participation in different stages of the food system using a survey of 663 adults in one U.S. county. Consumer food system participation by stage was 43% in food production, 47% in food processing, 65% in food distribution, 62% in food acquisition, 61% in food preparation, and 100% in food consumption. Consumers participated in an average of 3.7 of these 6 possible stages. Women and unmarried people participated in more stages. Food system participation was associated with few health problems, although people reporting some illnesses had higher food system participation. KEYWORDS food system, community, consumer, survey, health, nutrition, production, processing Everyone participates in food consumption, but little is known about involvement of food consumers across multiple stages of the food system. Unlike earlier historical eras, individuals in contemporary industrial and postindustrial nations are less dependent on their own participation across all stages of the food system to ensure that food is available for their consumption. However, consumers may choose to participate in the six major stages of the food system (Griffin, Sobal, and Lyson 2009; Sobal, Khan, and Bisogni 1998) representing food production, processing, distribution, acquisition, preparation, and consumption. For example, consumers are producers when they garden, hunt, fish, or gather for food. Consumers process foods by freezing or preserving (e.g., canning, drying). Individuals distribute surplus Address correspondence to Jeffery Sobal, Division of Nutritional Sciences, 407 Savage Hall, Cornell University, Ithaca, NY 14853, USA. E-mail: [email protected] 579
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foods to family, neighbors, or charities. Consumers purchase foods in markets, restaurants, or other settings. Consumers prepare food through cooking. Finally, all consumers ingest foods, and what they eat is manifested in health or disease after nutrient digestion and metabolism. How are health outcomes associated with participation in the food system? Fishing and hunting may facilitate consumption of particular foods, at least seasonally. Fishing for food may affect risk of contamination from fish caught in polluted waters (Alasalvar et al. 2010), but consumption of fish is also associated with lower morbidity and mortality (Takata et al. 2013). Preserving foods through freezing and canning promotes consumption of particular foods, and procedures used to preserve foods (e.g., salting) affect its nutritional value. Distributing foods through trades, gifts, or donations to food charities affects household food availability (Morton et al. 2008). Food shopping is an important point of control for the type and nutritional value of foods consumed (Hershey et al. 2001; Yoo et al. 2006). Involvement in food preparation influences nutrient intake (Crawford et al. 2007). Systems theory (Bertalanaffy 1968; Spedding 2012) provides a useful framework for examining patterns of participation in food behaviors and health conditions. Systems theory suggests that participation in many types of food activities should be examined as a whole because each activity may affect other activities, activities are situated within social and physical environments, and activities may individually and interactively influence outcomes like health. The food and nutrition system (Sobal 2004; Sobal et al. 1998) provides a common framework that encourages holistic and interdisciplinary examinations of food, eating, nutrition, and health. Prior research has not clearly examined the range of consumer food system participation or investigated whether participation across the scope of stages in the food system is associated with health problems. Reviews of the nutrition, food science, agricultural, consumer science, and economics literatures revealed relatively few studies exploring associations of health with gardening, hunting, fishing, food preservation, food shopping, and cooking (e.g., Casperson et al. 1991; Crawford et al. 2007; Smith and Miller 2011). The aims of this investigation were to: 1) quantify the prevalence of residents of a community food system who participate in food system stages of production, processing, distribution, acquisition, preparation, and consumption, 2) examine demographic patterns in consumer food system participation, and 3) investigate potential associations between the extent of food system participation and health problems.
METHODS Setting and Sample To examine consumer involvement in one community food and nutrition system, a cross-sectional postal mail survey of residents of one U.S. county
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in Upstate New York was conducted in 1999 (Griffin and Sobal 2013; Sobal and Nelson 2003). This county (population 97,000) provided a case example of a community food system that encompassed both rural and urban areas plus a diversity of ethnic groups. A city centrally located in the county had a population of 29,500 plus a university of about 19,000 students and a college of about 6,000 students. The data collection and analysis were approved by the University Institutional Review Board (IRB). The survey was sent by postal mail to a random sample of county residents from telephone book white pages supplemented by automobile registrations to reduce selection bias against people without telephones or with unlisted numbers. Tailored design (Dillman 2000) to maximize response rates used a postcard reminder and two follow-up letters to non-respondents.
Measures Individual survey questions assessed respondents’ participation in food system stages of (1) food production through gardening, hunting, and fishing; (2) food processing by freezing or preserving (canning, drying) foods; (3) food distribution through giving/trading food or donating food to feed the hungry; (4) food acquisition through being the primary household grocery shopper; (5) food preparation as being the primary household meal preparer/cook; and (6) food consumption as responding to questions about meal frequency. These activities were chosen for the initial survey and present analysis based on a review of the agriculture, nutrition, economics, food marketing, and sociology literature about food systems, with frequently mentioned activities included here. To construct a measure of involvement in multiple stages of the food system, a Food System Participation Index was calculated by summing responses to questions about behaviors in each of the stages in the system. This index had possible values from 1-6 and represented the number of stages from production to consumption in which consumers participated. A score of 1 represented only consumption, and a score of 6 represented participation across the whole food system. The index permits analysis of participation in multiple different food system activities. Respondents were asked whether they had high cholesterol, obesity, hypertension, food allergies, heart disease, diabetes, anemia, heart attack, cancer, food poisoning, bulimia, and anorexia nervosa. These illnesses were chosen based on their prevalence in the US population, their association with diet as a contributing factor, or the critical role diet and nutritional status play in mediating the illnesses (Erdman, Macdonald, and Zeisel 2012; National Research Council 1989). Body weight and height were self-reported and converted to body mass index (BMI) to measure obesity, with a BMI ≥ 30 identified as obese (Dietz and Robinson 1998; WHO Expert Committee 1995). Respondents also self-reported overall health status, rating their health
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as either excellent/good or fair/poor. Demographic characteristics of gender, ethnicity, age, household size, marital status, employment, educational achievement, and student status were collected.
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Analysis Data were first characterized for key variables using descriptive statistics. Multivariate logistic regression was used to determine how well and in what direction demographic variables were associated with participation in food system activities and with health problems. Regression diagnostics were run for each model (Kleinbaum et al. 2013), and for the models that did not fit the data, Chi-square analyses were used to confirm significance of those associations. Chi-square tests were used to examine if participation in different food and nutrition activities was related to nutrition and health problems. The Food System Participation Index was regressed on demographic variables using multiple linear regression, and was also used as a predictor of each health problem. Significance was reported at .05, .01, and .001 to permit readers to make their own interpretations of Type I error risk in the multiple statistical tests performed here (Bender and Lang 2001).
RESULTS Sample Characteristics A total of 667 surveys were completed for an overall response rate of 65% of deliverable surveys. Four respondents were under 18 or did not reside in the county, and their exclusion produced a final sample of 663. Gender, race, and education did not significantly differ among the three mailings, suggesting additional mailings would not produce different types of respondents. However, older people responded more to earlier mailings (p < .05), possibly because the survey was first administered in June when many college students were away. Demographic characteristics of respondents are summarized in table 1. Comparing the sample demographics with the U.S. Census data for the county revealed that the survey sample was representative with respect to gender, race, and household size. However, the sample was older, more likely to be employed, and more educated than the county population.
Food-System Stage Participation Over 42% of the consumers sampled were involved in some form of food production (gardening, hunting, fishing, or some combination, table 2). None of the demographic variables were significant predictors of gardening,
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Food System Participation TABLE 1 Demographic Characteristics of the Sample
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Characteristics Sex Female Race White Age (µ = 46 ± 17 years) 18–21 22–34 35–54 ≥ 55 Household size (µ = 2.6 ± 2.7) 1 person 2 people ≥ 3 people Marital status Currently married Employment Employed Education High school or less Some college Associates/Bachelors Graduate degree Student status Student 1 2
Sample
Census1
46%
51%
84%
90%
6% 24% 42% 29%
25% 29% 27% 19%
25% 40% 35%
27% 34% 39%
47%
NA2
66%
51%
20% 18% 30% 31%
33% 29% 22% 16%
16%
28%
Source: U.S. Census Bureau (1990). NA = Data not available.
indicating that gardening was fairly homogeneous across this sample, while men, individuals with fewer years of education, and non-students more often hunted or fished. Food processing was indicated by freezing and preserving foods. Overall participation in any food processing was 47%. Processing was done more often by female, older, or less-educated consumers. Participation in some form of food distribution, whether giving, trading, or donating food, was reported by almost two-thirds (65%) of respondents. Women more often participated in these food distribution activities, as did persons with fewer years of education, those who were white, and older consumers. Food acquisition involved 62% of respondents as the primary grocery shopper for their household. Women, the unmarried, the less-educated, and individuals living in small households more frequently shopped for groceries. Food preparation involved 61% of respondents reporting they were the primary cook for their household. Women, the unmarried, and respondents living in households with few or no other people more often cooked. Food consumption involved everyone in the sample (100%) reporting that they consumed food.
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35.8 11.0 10.6 41.1 24.6 32.2 53.0 61.7 60.8
Response (%)
Race (white) .22 .39 −.32 .32 .34 .39 .70∗∗ −.11 .01
Sex (male) −.24 1.35∗∗∗ 1.07∗∗∗ −.44∗ −.64∗∗ −.55∗∗ −.47∗∗ −1.32∗∗∗ −1.03∗∗∗ .01 −.02 −.01 .02∗ .02∗∗ .00 .02∗ .00 −.01
Age (years) −.02 .00 −.02 .09∗ −.01 .04 −.01 −.09∗ −.15∗∗
HH size .12 −.43 −.43 .51∗∗ .06 1.90 .35 −1.81∗∗∗ −1.64∗∗∗
Marital (married)
.10 −.38 −.26 −.23 .43 .09 .23 .03 −.03
Employment (working)
−.06 −.46∗∗∗ −.41∗∗∗ −.27∗∗∗ −.23∗∗ −.19∗∗∗ .16∗∗ .14∗ .11
Education
−.57 −2.46∗∗ −1.34 −.31 .15 −.48 .04 .67 .05
Student (student)
Note. Demographic variable figures are regression coefficients (betas) from logistic regressions, where subsystem activity was the dependent variable. Coding for dependent variables is: 0 = respondent does not perform, 1 = respondent performs. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
Garden Hunt Fish Freeze food Preserve food Give/Trade food Donate food Who shops (Acquisition) Who cooks (Preparation)
Participation activity
Demographic variables
TABLE 2 Consumer Food System Participation Activities and Associations with Demographic Characteristics
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Overall, participation in the food and nutrition system was greatest in the stages of (1) consumption, (2) distribution, and (3) acquisition. Participation was also heterogeneous, with women and people with less education more often participating in food system activities for each stage.
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Health Measures Findings about health measures are summarized in table 3. Hypercholesterolemia was the most prevalent health problem in the sample. Being older was the only significant predictor of high cholesterol. The average reported BMI was 24.6 ± 5.2 for women and 26.3 ± 4.4 for men, and 16% of respondents had a calculated BMI ≥ 30, the criterion for obesity. Married people and people with fewer years of education were more often obese than were the unmarried or college educated. No demographics significantly predicted hypertension. More women reported having allergies. Participants with heart disease were more often older respondents. More nonwhites had diabetes than whites. Women, nonwhites, and less-educated persons were more likely to report anemia. Men and older individuals reported significantly more heart attacks. Cancer was reported by only 3% of respondents, who were more often women than men. Food poisoning was also reported by few participants, with more women reporting this illness than men. A very small number of respondents (n = 4) reported having bulimia nervosa, and none of those surveyed reported having anorexia nervosa. With such a small sample size, a regression model could not be used, but Chi-square tests revealed that being white, employed, and a student were associated with bulimia. Over 80% stated that their health was excellent or good, with women, white, employed, and more educated consumers reporting more favorable health. Controlling for demographic characteristics (table 4) revealed that food system participation by freezing foods and preserving foods were associated with reporting high cholesterol. In contrast, food system participation by freezing foods and food preparation were associated with lower likelihood of reporting anemia.
Whole Food System Participation The food system participation index scores (figure 1) had a mean of 3.7 ± 1.3 stages, with most respondents involved in either three (26%) or four (30%) stages of the system. The majority of respondents who scored three were involved in acquisition, preparation, and consumption. Many of those who scored four were participating in either production, processing, distribution, and consumption, or else distribution, acquisition, preparation, and consumption. Approximately 10% of the sample was involved in all six stages
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16.0 15.9 15.6 10.5 7.8 5.2 4.7 3.7 3.2 1.9 0.6 0.0 81.0
High cholesterol Obesity Hypertension Food allergies Heart disease Diabetes Anemia Heart attack Cancer Food poisoning Bulimia Anorexia Good health
.03 .13 .41 −.73∗ −.02 −.17 −2.51∗∗∗ 1.50∗ −1.10∗ −2.23∗ −.89 − −.18
Sex (male)
Age (years) .04∗∗∗ .01 .06 .01 .04∗∗ .03 −.02 .05∗∗ .03 .03 −.03 − .02
Race (white) −.41 −.06 −.33 −.03 −.12 −1.32∗∗ −1.44∗∗ −.01 .09 .95 7.64 − .60∗
−.05 −.16 −.08 −.02 −.48 −.19 −.01 −.82 −.32 .03 −.31 − .04
HH size (people) .22 .66∗ −.34 −.57 .34 .20 .15 .32 1.14 −1.70 −.29 − −.19
Marital (married) .13 .54 −.18 .25 −.60 −.12 −.14 .33 −.60 1.21 6.43 − .96∗∗
Employment (working)
.01 −.41∗∗∗ −.11 .02 −.19 −.18 −.41∗∗ −.44 −.08 −.04 .18 − .25∗∗∗
Education
−.03 .28 −.89 .15 −.62 −6.82 .02 −5.43 −6.32 2.29 6.42 − 1.00
Student (student)
Note. Demographic variable figures are regression coefficients (betas) from logistic regressions, where health problem was the dependent variable. Coding for dependent variables is: 0 = respondent does not have, 1 = respondent has. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
Health response (%)
Health variable
Demographic variables
TABLE 3 Health Variables and Associations with Demographic Characteristics
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.09 .03 −.15 .23 −.66 .46 .25 −.77 −1.01 .59 10.20 − −.19
High cholesterol Obesity Hypertension Food allergies Heart disease Diabetes Anemia Heart attack Cancer Food poisoning Bulimia Anorexia Good health
.28 −.56 .12 −.39 −.13 .13 −.56 −.17 .12 −6.38 −7.60 − −.09
Hunt .31 −.19 .06 −.44 −.40 .56 .13 −1.62 .38 −.18 −7.56 − −.13
Fish
Preserve .13∗ .54 .26 −.16 −.49 .64 .20 −.54 −.27 .24 −1.41 − −.16
Freeze .20∗ .47 .21 .13 .26 .06 −1.09∗ −.09 .04 .83 −.37 − −.28 .12 .11 .01 .04 .13 −.07 −.66 −.16 .51 −.67 −10.29 − −.25
Give/trade
Note. Figures are measures of association (Somers’ d) derived from Chi-square test of independence. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
Garden
Health variable
Food system participation activity
TABLE 4 Association between Food System Participation Activities and Health Variables
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.26 .34 .21 .20 −.14 .48 −.16 .08 −.28 1.01 .94 − .27
Donate
3.6 .15 −.53 −.56 .31 .21 −.63 .61 .68 −.58 −.08 − −.53∗
Who shops
.14 −.17 −.23 .07 .29 .12 −.92∗ .36 −.63 −.77 .04 − −.22
Who cooks
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FIGURE 1 Participation in multiple stages of the food system. TABLE 5 Association between the Food System Participation Index and Demographic Variables Demographic variables Sex (male) Participation −.66∗∗∗ Index
Race (white) Age .15
.01
HH size
Marital (married)
−.02
−.50∗∗∗
Employment Student (working) Education (student) .11
−.05
−.16
Note. Figures are regression coefficients (betas) from linear regression, with food system participation as the dependent variable. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
of the food system. To examine how the index scores varied by demographics, a linear regression of the index was performed against demographic variables (table 5). Women and unmarried individuals scored significantly higher on the participation index. Health problems were regressed on the food system participation index, first alone and then adjusted for demographic variables, to determine whether a higher degree of food system participation (i.e., a higher index score) was associated with health conditions (table 6). Unadjusted for any demographic variables, only food allergies and diabetes were significantly associated with food system participation. Both were positively associated, meaning that individuals who were more likely to report having allergies and diabetes scored higher on the food system participation index. However, when demographic characteristics were controlled in a second regression model, the relationships were weaker and no longer significant. Thus, adjusting for all control variables, no health problems were found to be significantly associated with whole food system participation index scores.
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Food System Participation TABLE 6 Association between the Food System Participation Index and Health Variables
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Health problem High cholesterol Obesity Hypertension Food allergies Heart disease Diabetes Anemia Heart attack Cancer Food poisoning Bulimia Anorexia Self-reported health
Food System Participation Index
Adjusted Food System Participation Index
.06 .12 .04 .23∗ .10 .31∗ −.02 .05 .01 .39 .88 − −.06
.13 .17 .04 .05 .06 .28 −.31 .06 −.10 .14 .84 − −.08
Note. Figures are regression coefficients (betas) from linear regression, with food system participation as the dependent variable. The adjusted index represents a multivariate relationship between health and food system participation controlling for age, sex, race, household size, marital status, employment, education, and student status. ∗ p ≤ .05, ∗∗ p ≤ .01, ∗∗∗ p ≤ .001.
DISCUSSION Community food system participation is of concern to food professionals involved in planning and producing products, programs, policies, and services (Boyle and Holben 2012). Food and nutrition professionals can benefit from knowledge about participation in many components of whole food systems (Hillers 1991; Smith and Miller 2011), especially consumer participation in the system (Novotny et al. 2011; Peters 1997). Consumers are the main targets of food advertisements, nutrition education messages, and health interventions that affect food choices and other food behaviors. Knowledge about consumer food system involvement can help improve educational messages and services by tailoring or targeting them to reflect patterns of consumer food system participation. For example, specific strategies may be used to increase fruit and vegetable consumption in a community where cancer rates are high, change the extent of consumer food system participation, like developing a community food donation network or facilitating vegetable gardening, or intervening in food stores to buy more local products to prevent obesity (Novotny et al. 2011). This investigation showed that the extent of consumer involvement in this community food system was moderate, with the majority of consumers participating in 3 to 4 of the 6 stages of the food system. Several consumer demographic characteristics were significantly associated with food system participation. Men more often produced food through hunting and fishing, while women more often processed and distributed food, shopped, and
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cooked. Hunting and fishing are seen as predominantly “male” activities in American society (Sobal 2005), whereas women more often fill the roles of food shopper and cook in American households (Harnack et al. 1998; Smith, Ng, and Popkin 2013). Older people more often processed and distributed food, perhaps because they had more time or resources, or were more involved in traditional food activities (Morton et al. 2008; Quandt, Popyach, and DeWalt 1994). Consumers living in larger households and married people more often preserved foods through freezing, while people living in smaller households and the unmarried more often shopped and cooked. Larger households may achieve better economies of scale by purchasing foods in bulk and storing them, while individuals who live alone probably have no other person with whom to share household food activities (Westenbrick et al. 1989). Consumers with fewer years of education were more often involved in production, processing, distribution, and acquisition. Educational achievement is a component of socioeconomic status (SES). Low SES individuals may have fewer resources to spend on food and thus pursue alternative food sources, purchase in bulk and preserve for future use, and empathize with people in need of food sharing (Dammann and Smith 2009). Demographic characteristics were also associated with health problems. Men more often reported heart attacks, an anticipated finding since gender is a risk factor for cardiovascular disease (Erdman et al. 2012). Nonwhites reported more diabetes and anemia, which parallels the higher prevalence of these illnesses among nonwhite ethnic groups in the United States (Kumanyika 2006). Older people more often reported high cholesterol, coronary heart disease, and heart attacks; these illnesses typically become more prevalent with aging in the U.S. (Erdman et al. 2012). Married people were more obese, possibly an effect of more regular, frequent meal consumption patterns or less exercise (Sobal, Hanson, and Frongillo 2009). The less-educated reported more cases of anemia, which is common (Kumanyika 2006), and obesity, perhaps because people with less education may purchase cheaper energy dense foods or be exposed to fewer messages about diet and exercise as mediators of body weight (Dammann and Smith 2009). Women, white, employed, and more educated respondents more often reported their health to be good, which mirrors health patterns across gender, ethnic, and socioeconomic groups in the United States (Erdman et al. 2012; Idler and Benyamini 1997). Women and unmarried individuals had significantly higher scores on the food system participation index. The significant gender relationship paralleled results of bivariate analyses of each individual activity and reflects traditional food roles in which acquisition and preparation roles are generally filled by women (Harnack et al. 1998; Smith et al. 2013). The relationship with marital status may be a consequence of unmarried people having no partner with whom to share labor involved in food acquisition and
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preparation tasks, or having more time to pursue activities such as food production and processing (Bove and Sobal 2006). Participation in the food system could provide healthier foods that reduce disease and/or less healthy foods that increase disease, or people with diseases may participate differently in the food system to manage their diseases. In these data, participation in food system activities was associated with few health problems, but those correlations that were significant revealed conflicting findings of both higher and lower prevalence of illness among consumers who are more active food system participants. In this analysis, food processing and preparation were negatively associated with anemia, while processing foods was positively associated with hypercholesterolemia. Processing and preparation are two stages of the food system where consumers have the greatest ability to alter the nutrient content of their food—for example, more frequently freezing foods like meats with high iron content or using cast iron cooking equipment to increase the iron content of food—which may explain why consumers in this sample who processed and cooked their own food reported fewer cases of anemia. With regards to hypercholesterolemia, processing foods may contribute to high cholesterol through the increased intake of simple sugars that are typically used in home food processing, particularly canning. However, the large number of positive associations we found between food system participation and health (see table 4), while not statistically significant, lend support to a hypothesis that consumers who are diagnosed with a health problem may increase their participation in the food system in order to more closely control the sources and nutrient content of their food. Associations between participation in some food system activities and health have previously been reported. Elderly men who garden have healthier cholesterol levels and lower blood pressure (Caspersen et al. 1991). Similar beneficial associations occur between cholesterol levels and household production of foods grown, raised, or caught at home (Blair, Giesecke, and Sherman 1991; Pearson et al. 1999; Zick et al. 2013). Greater fruit and vegetable consumption, higher nutrient intakes, and lower body weights are associated with fruit and vegetable gardening (Holben et al. 2004; Marsh 1998). In contrast, hunting has been associated with increased risk of cardiovascular illnesses (Peterson et al. 1999), and concerns exist about exposure to environmental contaminants through consumption of wild fish and game (Burger 2002). Participation in the food system has been shown, both in this analysis and in previous studies, to be associated with better health (Pearson et al. 1999), more illness (Peterson et al.1999), or neither (Hamelin, Mercier, and Bedard 2008). Two mechanisms may operate in relationships between food system participation and health: selection and causation (Goldman 1994). Selection may occur when people who have health problems or who wish to avoid health problems participate in the food system differently from
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those without health problems. Causation may occur when participation in the food system leads to better or worse health. Cross-sectional data such as these cannot definitively establish whether selection or causation is operating (Goldman 1994), but findings of cross-sectional associations can provide evidence in support of selection or causation relationships. To further explore these relationships, future studies need to examine food system participation and health using longitudinal research designs to explicitly analyze the extent of selection, causation, or both as mechanisms linking food system participation and health. Sampling limitations of this study include examining only one county in 1999, which may limit ability to generalize these findings to community food systems in other places and times. Non-respondents may have differed from the sample of respondents, despite the majority who responded. We assume that only literate individuals returned completed surveys, and because education was significantly associated with food system participation these findings may have been different if another data collection method (e.g., telephone surveys) was used. Measurement limitations may have occurred in this self-reported data, although mailed questionnaires have less social desirability responses than face-to-face interviews (Dillman 2000). While some bias occurs in selfreporting body weight and height, analysis of U.S. national data showed that measured weight and height are highly correlated with reported weight (r = .97) and reported height (r = .93) (Sobal, Hanson, and Frongillo 2009). Self-reported health is a subjective measure widely used as an overall health indicator, and it strongly predicts morbidity and mortality (Idler and Benyamini 1997).
Implications These findings suggest that food professionals may benefit from being aware of consumer food system participation. A diagnosis of coronary heart disease, hypertension, diabetes, or other diet-related illnesses may lead individuals to become more involved in food system activities, activities in which food professionals may provide information or target specific types of consumers for interventions. Food professionals also may want to facilitate broader food system involvement in their communities by raising consumer consciousness about increased food system participation as a way to control their dietary intake (Novotny et al. 2011; Sanlier and Karakus 2010), thereby raising awareness of the connections between diet, environment, and health (Harmon and Maretzki 2006; Hillers 1991; Peters 1997). This study contributes to research examining food systems and associations between health and food system participation. Food and nutrition activities not previously well studied were assessed in this study, and participation across the whole food system was also examined. Further research is
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needed to better understand associations between food system participation and health, including qualitative research about patterns of participation and quantitative analysis of longitudinal data to examine selection and causation in food system participation.
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