Food Environments Within and Outside of Schools Play a Critical Role in Curtailing the Rise in Obesity among School-Aged Children over Time

BACKGROUND

Sound evidence for effective community-based strategies is needed to curtail upward trends in childhood obesity in the United States (US).

OBJECTIVES

The aim of the study was to assess the association between school and community food environments and the prevalence of obesity over time.

METHODS

Data were collected from K-12 schools in 4 low-income New Jersey cities in the US. School-level obesity prevalence, calculated from nurse-measured heights and weights at 4 time points, was used as the outcome variable. Data on the school food environment (SFE) measured the healthfulness of school lunch and competitive food offerings annually. The community food environment (CFE), i.e., the number of different types of food outlets within 400 m of schools, was also captured annually. The count and presence of food outlets likely to be frequented by students were calculated. Exposure to composite environment profiles both within schools and in communities around schools was assessed using latent class analysis. Data from 106 schools were analyzed using multilevel linear regression.

RESULTS

The prevalence of obesity increased from 25% to 29% over the course of the study. Obesity rates were higher in schools that had nearby access to a greater number of limited-service restaurants and lower in schools with access to small grocery stores and upgraded convenience stores participating in initiatives to improve healthful offerings. Interaction analysis showed that schools that offered unhealthier, competitive foods experienced a faster increase in obesity rates over time. Examining composite food environment exposures, schools with unhealthy SFEs and high-density CFEs experienced a steeper time trend (β = 0.018, P < 0.001) in obesity prevalence compared to schools exposed to healthy SFE and low-density CFEs.

CONCLUSIONS

Food environments within and outside of schools are associated with differential obesity trajectories over time and can play an important role in curtailing the rising trends in childhood obesity.

The relationship between changes in neighborhood physical environment and changes in physical activity among children: a prospective cohort study

BACKGROUND

Physical activity (PA) is associated with positive health outcomes over the entire life course. Many community-based interventions that promote PA focus on implementing incremental changes to existing facilities and infrastructure. The objective of this study was to determine if such upgrades were associated with increases in children's PA.

METHODS

Two cohorts of 3- to 15-year-old children (n = 599) living in 4 low-income New Jersey cities were followed during 2- to 5-year periods from 2009 to 2017. Data on children's PA were collected at 2 time points (T1 and T2) from each cohort using telephone survey of parents; data on changes to existing PA facilities were collected yearly from 2009 to 2017 using Open Public Records Act requests, publicly available data sources, and interviews with key stakeholders. PA changes were categorized into six domains (PA facility, park, trail, complete street, sidewalk, or bike lane) and coded as new opportunity, renovated opportunity, or amenity. A scale variable capturing all street-related upgrades (complete street, sidewalk, and bike lane) was constructed. PA was measured as the number of days per week the child engaged in at least 60 min of PA. The association between change in PA between T1 and T2, ranging from - 7 to + 7, and changes to the PA environment was modeled using weighted linear regression controlling for PA at T1, child age, sex, race, as well as household and neighborhood demographic and socioeconomic characteristics.

RESULTS

While most measures of the changes to the PA environment were not associated with change in PA between T1 and T2, the street-related upgrades were positively associated with the change in PA; specifically, for each additional standard deviation in street upgrades within a 1-mile radius of their homes, the change in PA was 0.42 (95% CI: 0.02, 0.82; p = 0.039) additional days. This corresponds to an 11% increase over the mean baseline value (3.8 days).

CONCLUSIONS

The current study supports funding of projects aimed at improving streets and sidewalks in cities, as it was shown that incremental improvements to the PA environment near children's homes will likely result in increased PA among children.

Differential Associations Between Changes in Food Environment and Changes in BMI Among Adults Living in Urban, Low-Income Communities

BACKGROUND

Food environments can contribute to excess weight gain among adults, but the evidence is mixed.

OBJECTIVES

This longitudinal study investigated the associations between changes in the food environment and changes in BMI in adults and whether changes in the food environment differentially impact various subgroups.

METHODS

At 2 time points, BMI was calculated using self-reported height and weight data from 517 adults (mean age, 41 years) living in 4 New Jersey cities. The counts of different types of food outlets within 0.4, 0.8, and 1.6 km of respondents' residences were collected at baseline and tracked until follow-up. A binary measure of social standing (social-advantage group, n = 219; social-disadvantage group, n = 298) was created through a latent class analysis using social, economic, and demographic variables. Multivariable linear regression modeled the associations between changes in BMI with measures of the food environment; additionally, interaction terms between the measures of food environment and social standing were examined.

RESULTS

Overall, over 18 months, an increase in the number of small grocery stores within 0.4 km of a respondent's residence was associated with a decrease in BMI (β = -1.0; 95% CI: -1.9, -0.1; P = 0.024), while an increase in the number of fast-food restaurants within 1.6 km was associated with an increase in BMI (β = 0.1; 95% CI: 0.01, 0.2; P = 0.027). These overall findings, however, masked some group-specific associations. Interaction analyses suggested that associations between changes in the food environment and changes in BMI varied by social standing. For instance, the association between changes in fast-food restaurants and changes in BMI was only observed in the social-disadvantage group (β = 0.1; 95% CI: 0.02, 0.2; P = 0.021).

CONCLUSIONS

In a sample of adults living in New Jersey, changes in the food environment had differential effects on individuals' BMIs, based on their social standing.

Evidence That Changes in Community Food Environments Lead to Changes in Children's Weight: Results from a Longitudinal Prospective Cohort Study

BACKGROUND

Strategies to improve the community food environment have been recommended for addressing childhood obesity, but evidence substantiating their effectiveness is limited.

OBJECTIVE

Our aim was to examine the impact of changes in availability of key features of the community food environment, such as supermarkets, small grocery stores, convenience stores, upgraded convenience stores, pharmacies, and limited service restaurants, on changes in children's body mass index z scores (zBMIs).

DESIGN

We conducted a longitudinal cohort study.

PARTICIPANTS/SETTING

Two cohorts of 3- to 15-year-old children living in 4 low-income New Jersey cities were followed during 2- to 5-year periods from 2009 through 2017. Data on weight status were collected at 2 time points (T1 and T2) from each cohort; data on food outlets in the 4 cities and within a 1-mile buffer around each city were collected multiple times between T1 and T2.

MAIN OUTCOME MEASURES

We measured change in children's zBMIs between T1 and T2.

STATISTICAL ANALYSIS

Changes in the food environment were conceptualized as exposure to changes in counts of food outlets across varying proximities (0.25 mile, 0.5 mile, and 1.0 mile) around a child's home, over different lengths of time a child was exposed to these changes before T2 (12 months, 18 months, and 24 months). Multivariate models examined patterns in relationships between changes in zBMI and changes in the food environment.

RESULTS

Increased zBMIs were observed in children with greater exposure to convenience stores over time, with a consistent pattern of significant associations across varying proximities and lengths of exposure. For example, exposure to an additional convenience store over 24 months within 1 mile of a child's home resulted in 11.7% higher odds (P = 0.007) of a child being in a higher zBMI change category at T2. Lower zBMIs were observed in children with increased exposure to small grocery stores selling an array of healthy items, with exposure to an additional small grocery store within 1 mile over 24 months, resulting in 37.3% lower odds (P < 0.05) of being in a higher zBMI change category at T2. No consistent patterns were observed for changes in exposure to supermarkets, limited service restaurants, or pharmacies.

CONCLUSIONS

Increased availability of small grocery stores near children's homes may improve children's weight status, whereas increased availability of convenience stores is likely to be detrimental.

Children's Consumption Patterns and Their Parent's Perception of a Healthy Diet

This study aims to examine children's fruit, vegetable, and added sugar consumption relative to the Dietary Guidelines for Americans and the American Heart Association's recommendations, as well as to compare children's reported consumption with parental perception of the child's overall diet quality. Data were drawn from 2 independent, cross sectional panels (2009-10 and 2014-15) of the New Jersey Child Health Study. The analytical sample included 2229 households located in five New Jersey cities. Daily consumption of fruit (cups), vegetables (cups), and added sugars (teaspoons) for all children (3-18 years old) were based on parent reports. Multivariate linear regression analyses estimated children's adjusted fruit, vegetable, and added sugar consumption across parents' perception categories (Disagree; Somewhat Agree; and Strongly Agree that their child eats healthy). Although only a small proportion of children meet recommendations, the majority of parents strongly agreed that their child ate healthy. Nonetheless, significant differences, in the expected direction, were observed in vegetable and fruit consumption (but not sugar) across parental perceptional categories for most age/sex groups. Dietary interventions tailored to parents should include specific quantity and serving-size information for fruit and vegetable recommendations, based on their child's age/sex, and highlight sources of added sugar and their sugar content.

The Special Supplemental Nutrition Program for Women, Infants, and Children Spillover Effect: Do Siblings Reap the Benefits?

BACKGROUND

Participation in the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC) among 0- to 5-year-old children is associated with healthier diets. Extension of dietary benefits to older, age-ineligible children (5-18 years old) residing in WIC households has not been fully investigated.

OBJECTIVE

Examine the association between household WIC participation and dietary behaviors of age-ineligible children.

DESIGN

Cross-sectional secondary analysis of data collected from 2 independent panels (2009-2010 and 2014) of the New Jersey Child Health Study, using household surveys. Questions derived from national surveys assessed consumption frequency of specific foods among 5- to 18-year-old children.

PARTICIPANTS/SETTING

The analytic sample included 616 age-ineligible children from households with incomes below 200% of the federal poverty level, 398 of whom were from WIC-participating households.

MAIN OUTCOME MEASURES

Eating behaviors were measured as frequency of daily consumption of fruit, vegetables, 100% juice, sugar-sweetened beverages, and sweet and salty snacks.

STATISTICAL ANALYSIS

Multivariable negative binomial models examined the association between eating behaviors and household WIC participation status adjusting for child's age, sex, and race; mother's education; city of residence; household size; and panel. Results are expressed as incidence rate ratios (IRRs).

RESULTS

Household WIC participation was not associated with dietary behaviors among age-ineligible children (5-18 years old) in the overall sample. However, healthier dietary patterns were observed for specific demographic groups. Compared with age-ineligible children in non-WIC households, age-ineligible children in WIC households had (1) a higher frequency of vegetable consumption among 12- to 18-year-old children (IRR = 1.29; 95% confidence interval [CI] 1.05-1.58; P = .015); (2) a marginally significant higher frequency of 100% juice consumption among females (IRR = 1.27; 95% CI 1.00-1.62; P = .053); and (3) a lower frequency of sugar-sweetened beverages consumption among Hispanic children (IRR = 0.61; 95% CI 0.43-0.86; P = .004).

CONCLUSIONS

Household WIC participation may positively influence dietary behaviors of age-ineligible children, suggesting a possible WIC spillover effect. Revisions to WIC package composition should consider the possible dietary implications for all children in the household.

School Food and Physical Activity Environment: A Longitudinal Analysis of Four School Districts in New Jersey

PURPOSE

Exposures to favorable environments in childhood, including those in schools, are associated with healthy habits among children. In this study, we developed a series of indices aimed at measuring students' exposure to different dimensions of the school food and physical activity (PA) environment. We implemented these indices to investigate how different aspects of the school food and PA environment changed over time and examined their correspondence with known changes in relevant policies and programs.

METHODS

All public schools (n= 141) in four school districts in New Jersey provided detailed food and PA environment data for each school year from 2010-2011 to 2015-2016. Seven food environment indices, three PA environment indices, and two additional indices that capture health-promoting initiatives at the school level and at the state or federal level were developed.

RESULTS

Although the school PA environment largely remained unchanged, several dimensions of the school food environment changed between 2010-2011 and 2015-2016. Overall, the number of healthy items increased over time in vending machines (p < .001), a la carte (p < .05), or through reimbursable school lunches (p < .001); decreases in number of unhealthy items were only detected in school lunches (p < .05). For most food indices, both the number of items offered and the trend over time varied across school levels.

CONCLUSIONS

Schools are a key venue for implementing policy and environment interventions aimed to promote healthy behaviors. Indices developed from easy-to-use survey questions captured multiple dimensions of the school food and PA environments and were sensitive to policy changes over time.

Predicted Impact of the Food and Drug Administration's Menu-Labeling Regulations on Restaurants in 4 New Jersey Cities

OBJECTIVES

To determine the proportion of restaurants that will be required to post calorie information under the Food and Drug Administration's menu-labeling regulations in 4 New Jersey cities.

METHODS

We classified geocoded 2014 data on 1753 restaurant outlets in accordance with the Food and Drug Administration's guidelines, which will require restaurants with 20 or more locations nationwide to post calorie information. We used multivariate logistic regression analyses to assess the association between menu-labeling requirements and census tract characteristics.

RESULTS

Only 17.6% of restaurants will be affected by menu labeling; restaurants in higher-income tracts have higher odds than do restaurants in lower-income tracts (odds ratio [OR] = 1.55; P = .02). Restaurants in non-Hispanic Black (OR = 1.62; P = .02) and mixed race/ethnicity (OR = 1.44; P = .05) tracts have higher odds than do restaurants in non-Hispanic White tracts of being affected.

CONCLUSIONS

Additional strategies are needed to help consumers make healthy choices at restaurants not affected by the menu-labeling law. These findings have implications for designing implementation strategies for the law and for evaluating its impact.

Cost of Children's Healthy vs Unhealthy Snacks Does Not Differ at Convenience Stores

OBJECTIVE

This study compared the prices of unhealthy (chips) and healthy (ready-to-eat fruit) snacks that students are likely to purchase from corner stores.

METHODS

Snacks were purchased from 325 New Jersey corner stores; chip prices were compared with fruit prices overall and by store sales volume and block group characteristics.

RESULTS

Prices did not differ significantly between chips and fruit in the overall sample in which both items were available (n = 104) (chips: $0.46 ± $0.15; fruit: $0.49 ± $0.19; P = .48) or by store or block group characteristics. Neither mean fruit prices nor mean chip prices differed by store sales volume or by neighborhood characteristics.

CONCLUSIONS AND IMPLICATIONS

Promoting ready-to-eat fruits in corner stores to children as a price-neutral alternative to calorically dense snacks can be a viable strategy to improve the nutritional quality of snacks commonly purchased at corner stores.

Short-Form Audit Instrument for Assessing Corner Store Healthfulness

PURPOSE

To develop a valid and feasible short-form corner store audit tool (SCAT) that could be used in-store or over the phone to capture the healthfulness of corner stores.

DESIGN

Nonexperimental.

SETTING

Four New Jersey cities.

SUBJECTS

Random selection of 229 and 96 corner stores in rounds 1 and 2, respectively.

MEASURES

An adapted version of the Nutrition Environment Measures Survey for Corner Stores (NEMS-CS) was used to conduct in-store audits. The 7-item SCAT was developed and used for round 2 phone audits.

ANALYSIS

Exploratory factor analysis and item response theory were used to develop the SCAT.

RESULTS

The SCAT was highly correlated with the adapted NEMS-CS ( r = .79). Short-form corner store audit tool scores placed stores in the same healthfulness categories as did the adapted NEMS-CS in 88% of the cases. Phone response matches indicated that store owners did not distinguish between 2% and low-fat milk and tended to round up the fruit and vegetable count to 5 if they had fewer varieties.

CONCLUSION

The SCAT discriminates between higher versus lower healthfulness scores of corner stores and is feasible for use as a phone audit tool.

Healthy store programs and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), but not the Supplemental Nutrition Assistance Program (SNAP), are associated with corner store healthfulness

In response to lack of access to healthy foods, many low-income communities are instituting local healthy corner store programs. Some stores also participate in the United States Department of Agriculture's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and the Supplemental Nutrition Assistance Program (SNAP). This study used two assessment tools to compare the healthfulness of offerings at stores participating in local healthy store programs (upgraded stores), WIC, and/or SNAP to that of similar non-participating stores. Based on store audits conducted in 315 New Jersey corner stores in 2014, we calculated healthy food availability scores using subsections of the Nutrition Environment Measures Survey for Corner Stores (NEMS-CS-Availability) and a short-form corner store audit tool (SCAT). We used multivariable regression to examine associations between program participation and scores on both instruments. Adjusting for store and block group characteristics, stores participating in a local healthy store program had significantly higher SCAT scores than did non-participating stores (upgraded: M = 3.18, 95% CI 2.65-3.71; non-upgraded: M = 2.52, 95% CI 2.32-2.73); scores on the NEMS-CS-Availability did not differ (upgraded: M = 12.8, 95% CI 11.6-14.1; non-upgraded: M = 12.5, 95% CI 12.0-13.0). WIC-participating stores had significantly higher scores compared to non-participating stores on both tools. Stores participating in SNAP only (and not in WIC) scored significantly lower on both instruments compared to non-SNAP stores. WIC-participating and non-SNAP corner stores had higher healthfulness scores on both assessment tools. Upgraded stores had higher healthfulness scores compared to non-upgraded stores on the SCAT.