ASU Food Policy and Environment Research Group
A collection of scholarly work created by the ASU Food Policy and Environment Research Group under the leadership of Professor Punam Ohri-Vachaspati. The group examines policies, programs, and environments that influence food consumption and physical activity behaviors and health outcomes in disadvantaged populations. We aim to improve the health of children and families through comprehensive policy and environmental approaches.
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- Creators: DeLia, Derek Michael, 1969-
- Creators: Kahle, Lisa L
Background: Understanding determinants of high consumption of sugar-sweetened beverages (SSBs), a highly prevalent obesogenic behavior, will help build effective customized public health interventions.
Objective: Our aim was to identify child and parent lifestyle and household demographic factors predictive of high SSB consumption frequency in children from low-income, ethnically diverse communities that may help inform public health interventions.
Design: We used a cross-sectional telephone household survey.
Participants/setting: Participants were 717 boys and 686 girls aged 3 to 18 years old from the New Jersey Childhood Obesity Study living in five low-income cities (Camden, New Brunswick, Newark, Trenton, and Vineland). The adult most knowledgeable about household food shopping completed a questionnaire over the telephone inquiring about their and their child's dietary and physical activity habits, and household-, parent-, and child-level demographics.
Main outcome measures: Child's SSB consumption frequency was measured.
Statistical analysis performed: Multivariate ordered logit models were designed to investigate a variety of variables hypothesized to affect the frequency of SSB consumption. Exploratory stratified analyses by race, sex, and age were also conducted.
Results: Eight percent of our study participants never consumed SSBs, 45% consumed SSBs at least once per day, and 23% consumed twice or more per day. SSB consumption was higher among children 12 to 18 years vs 3 to 5 years (P<0.0001), of non-Hispanic black vs non-Hispanic white race/ethnicity (P=0.010), who were moderate fast food consumers vs never consumers (P=0.003), and those whose parents were high vs low SSB consumers (P<0.0001). Living in a non-English-speaking household (P=0.030), having a parent with a college or higher education vs less than high school (P=0.003), and having breakfast 6 to 7 days/wk vs never to 2 days/wk or less were associated with lower SSB consumption (P=0.001).
Conclusions: We identified a number of household-, parent-, and child-level predictors of SSB consumption, which varied by race, sex, and age, useful for building customized interventions targeting certain behaviors in ethnically diverse, low-income children.
Objectives: Conflicting findings on associations between food and physical activity (PA) environments and children's weight status demand attention in order to inform effective interventions. We assess relationships between the food and PA environments in inner-city neighborhoods and children's weight status and address sources of conflicting results of prior research.
Methods: Weight status of children ages 3-18 was assessed using parent-measured heights and weights. Data were collected from 702 children living in four low-income cities in New Jersey between 2009 and 2010. Proximity of a child's residence to a variety of food and PA outlets was measured in multiple ways using geo-coded data. Multivariate analyses assessed the association between measures of proximity and weight status.
Results: Significant associations were observed between children's weight status and proximity to convenience stores in the 1/4 mile radius (OR = 1.9) and with presence of a large park in the 1/2 mile radius (OR = 0.41). No associations were observed for other types of food and PA outlets.
Conclusions: Specific aspects of the food and PA environments are predictors of overweight and obese status among children, but the relationships and their detection are dependent upon aspects of the geospatial landscape of each community.
Disparities in healthy food access are well documented in cross-sectional studies in communities across the United States. However, longitudinal studies examining changes in food environments within various neighborhood contexts are scarce. In a sample of 142 census tracts in four low-income, high-minority cities in New Jersey, United States, we examined the availability of different types of food stores by census tract characteristics over time (2009–2017). Outlets were classified as supermarkets, small grocery stores, convenience stores, and pharmacies using multiple sources of data and a rigorous protocol. Census tracts were categorized by median household income and race/ethnicity of the population each year. Significant declines were observed in convenience store prevalence in lower- and medium-income and majority black tracts (p for trend: 0.004, 0.031, and 0.006 respectively), while a slight increase was observed in the prevalence of supermarkets in medium-income tracts (p for trend: 0.059). The decline in prevalence of convenience stores in lower-income and minority neighborhoods is likely attributable to declining incomes in these already poor communities. Compared to non-Hispanic neighborhoods, Hispanic communities had a higher prevalence of small groceries and convenience stores. This higher prevalence of smaller stores, coupled with shopping practices of Hispanic consumers, suggests that efforts to upgrade smaller stores in Hispanic communities may be more sustainable.
Objective: To evaluate five popular fast-food chains' menus in relation to dietary guidance.
Design: Menus posted on chains' websites were coded using the Food and Nutrient Database for Dietary Studies and MyPyramid Equivalents Database to enable Healthy Eating Index-2005 (HEI-2005) scores to be assigned. Dollar or value and kids' menus and sets of items promoted as healthy or nutritious were also assessed.
Setting: Five popular fast-food chains in the USA.
Subjects: Not applicable.
Results: Full menus scored lower than 50 out of 100 possible points on the HEI-2005. Scores for Total Fruit, Whole Grains and Sodium were particularly dismal. Compared with full menus, scores on dollar or value menus were 3 points higher on average, whereas kids' menus scored 10 points higher on average. Three chains marketed subsets of items as healthy or nutritious; these scored 17 points higher on average compared with the full menus. No menu or subset of menu items received a score higher than 72 out of 100 points.
Conclusions: The poor quality of fast-food menus is a concern in light of increasing away-from-home eating, aggressive marketing to children and minorities, and the tendency for fast-food restaurants to be located in low-income and minority areas. The addition of fruits, vegetables and legumes; replacement of refined with whole grains; and reformulation of offerings high in sodium, solid fats and added sugars are potential strategies to improve fast-food offerings. The HEI may be a useful metric for ongoing monitoring of fast-food menus.
Objective: The Social Ecological Model (SEM) has been used to describe the aetiology of childhood obesity and to develop a framework for prevention. The current paper applies the SEM to data collected at multiple levels, representing different layers of the SEM, and examines the unique and relative contribution of each layer to children's weight status.
Design: Cross-sectional survey of randomly selected households with children living in low-income diverse communities.
Setting: A telephone survey conducted in 2009-2010 collected information on parental perceptions of their neighbourhoods, and household, parent and child demographic characteristics. Parents provided measured height and weight data for their children. Geocoded data were used to calculate proximity of a child's residence to food and physical activity outlets.
Subjects: Analysis based on 560 children whose parents participated in the survey and provided measured heights and weights.
Results: Multiple logistic regression models were estimated to determine the joint contribution of elements within each layer of the SEM as well as the relative contribution of each layer. Layers of the SEM representing parental perceptions of their neighbourhoods, parent demographics and neighbourhood characteristics made the strongest contributions to predicting whether a child was overweight or obese. Layers of the SEM representing food and physical activity environments made smaller, but still significant, contributions to predicting children's weight status.
Conclusions: The approach used herein supports using the SEM for predicting child weight status and uncovers some of the most promising domains and strategies for childhood obesity prevention that can be used for designing interventions.