Neighborhoods and obesity

The neighourhood obesogenic built environment characteristics (OBCT) index: Practice versus theory

BACKGROUND

Obesity is a key risk factor for major chronic diseases such as type 2 diabetes and cardiovascular diseases. To extensively characterise the obesogenic built environment, we recently developed a novel Obesogenic Built environment CharacterisTics (OBCT) index, consisting of 17 components that capture both food and physical activity (PA) environments.

OBJECTIVES

We aimed to assess the association between the OBCT index and body mass index (BMI) in a nationwide health monitor. Furthermore, we explored possible ways to improve the index using unsupervised and supervised methods.

METHODS

The OBCT index was constructed for 12,821 Dutch administrative neighbourhoods and linked to residential addresses of eligible adult participants in the 2016 Public Health Monitor. We split the data randomly into a training (two-thirds; n = 255,187) and a testing subset (one-third; n = 127,428). In the training set, we used non-parametric restricted cubic regression spline to assess index's association with BMI, adjusted for individual demographic characteristics. Effect modification by age, sex, socioeconomic status (SES) and urbanicity was examined. As improvement, we (1) adjusted the food environment for address density, (2) added housing price to the index and (3) adopted three weighting strategies, two methods were supervised by BMI (variable selection and random forest) in the training set. We compared these methods in the testing set by examining their model fit with BMI as outcome.

RESULTS

The OBCT index had a significant non-linear association with BMI in a fully-adjusted model (p<0.05), which was modified by age, sex, SES and urbanicity. However, variance in BMI explained by the index was low (<0.05%). Supervised methods increased this explained variance more than non-supervised methods, though overall improvements were limited as highest explained variance remained <0.5%.

DISCUSSION

The index, despite its potential to highlight disparity in obesogenic environments, had limited association with BMI. Complex improvements are not necessarily beneficial, and the components should be re-operationalised.

A participatory approach to model the neighbourhood food environment

Inequalities in exposure to a health-promoting local food environment have been implicated in the generation of inequalities in diet-related behaviours and outcomes, including obesity and diabetes. Increasingly, poor diet and diet-related disease have been characterised as an emergent property of a complex system and, as such, the drivers of poor diet may be better understood by using a complex system perspective. In this study, we describe a participatory approach for understanding the system drivers of unhealthy food consumption. System dynamics (SD) was used to identify, understand, and visualise the elements of the neighbourhood food retail system that influence individuals' eating behaviour. Group Model Building (GMB), undertaken online with stakeholders (n = 11), was used to funnel existing knowledge and evidence on urban food environments and to build a conceptual system map of the local food retail environment inclusive of the drivers that influence the decision to purchase and consume meals that are high in fat, salt, and sugar (HFSS), and calories. The GMB was organised as a knowledge elicitation process involving a questionnaire, a workbook, and a structured workshop. The GMB generated a comprehensive causal loop diagram (CLD) of the retail environment inclusive of the drivers that influence the decision to purchase and consume unhealthy meals. The CLD was designed around two main variables (i) exposure to food outlets and (ii) food consumption. The system map built during the Group Model Building session linked exposure to food outlets with the possibility to purchase and consume unhealthy meals. The effectiveness of this link will be tested in an Agent-Based model. The conceptual model illustrates the complexity of the factors responsible for inequalities in unhealthy eating. The GMB approach provides a basis for building an agent-based model for local authorities to characterise their food retail environment, uncover potential leverage points for interventions and test them 'in silico' in a virtual environment.

Social and Structural Drivers of Health and Transition to Adult Care

CONTEXT

Youth with chronic health conditions experience challenges during their transition to adult care. Those with marginalized identities likely experience further disparities in care as they navigate structural barriers throughout transition.

OBJECTIVES

This scoping review aims to identify the social and structural drivers of health (SSDOH) associated with outcomes for youth transitioning to adult care, particularly those who experience structural marginalization, including Black, Indigenous, and 2-spirit, lesbian, gay, bisexual, transgender, queer or questioning, and others youth.

DATA SOURCES

Medline, Embase, CINAHL, and PsycINFO were searched from earliest available date to May 2022.

STUDY SELECTION

Two reviewers screened titles and abstracts, followed by full-text. Disagreements were resolved by a third reviewer. Primary research studying the association between SSDOH and transition outcomes were included.

DATA EXTRACTION

SSDOH were subcategorized as social drivers, structural drivers, and demographic characteristics. Transition outcomes were classified into themes. Associations between SSDOH and outcomes were assessed according to their statistical significance and were categorized into significant (P < .05), nonsignificant (P > .05), and unclear significance.

RESULTS

101 studies were included, identifying 12 social drivers (childhood environment, income, education, employment, health literacy, insurance, geographic location, language, immigration, food security, psychosocial stressors, and stigma) and 5 demographic characteristics (race and ethnicity, gender, illness type, illness severity, and comorbidity). No structural drivers were studied. Gender was significantly associated with communication, quality of life, transfer satisfaction, transfer completion, and transfer timing, and race and ethnicity with appointment keeping and transfer completion.

LIMITATIONS

Studies were heterogeneous and a meta-analysis was not possible.

CONCLUSIONS

Gender and race and ethnicity are associated with inequities in transition outcomes. Understanding these associations is crucial in informing transition interventions and mitigating health inequities.

Structural Racism as a Contributor to Lung Cancer Incidence and Mortality Rates Among Black Populations in the United States

BACKGROUND

Although racial disparities in lung cancer incidence and mortality have diminished in recent years, lung cancer remains the second most diagnosed cancer among US Black populations. Many factors contributing to disparities in lung cancer are rooted in structural racism. To quantify this relationship, we examined associations between a multidimensional measure of county-level structural racism and county lung cancer incidence and mortality rates among Black populations, while accounting for county levels of environmental quality.

METHODS

We merged 2016-2020 data from the United States Cancer Statistics Data Visualization Tool, a pre-existing county-level structural racism index, the Environmental Protection Agency's 2006-2010 Environmental Quality Index (EQI), 2023 County Health Rankings, and the 2021 United States Census American Community Survey. We conducted multivariable linear regressions to examine associations between county-level structural racism and county-level lung cancer incidence and mortality rates.

RESULTS

Among Black males and females, each standard deviation increase in county-level structural racism score was associated with an increase in county-level lung cancer incidence of 6.4 (95% CI: 4.4, 8.5) cases per 100,000 and an increase of 3.3 (95% CI: 2.0, 4.6) lung cancer deaths per 100,000. When examining these associations stratified by sex, larger associations between structural racism and lung cancer rates were observed among Black male populations than among Black females.

CONCLUSION

Structural racism contributes to both the number of new lung cancer cases and the number of deaths caused by lung cancer among Black populations. Those aiming to reduce lung cancer cases and deaths should consider addressing racism as a root-cause.

The association between neighborhood conditions and weight loss among older adults living in a large urban city

To elucidate the role of neighborhood walkability and crime on weight loss, we examined data from older adults residing in Chicago who participated in a randomized controlled trial lifestyle intervention. Controlling for individual demographic characteristics and the intervention assignment, the neighborhood homicide rate was significantly associated with weight change. Participants who resided in neighborhoods above the 50th percentile of homicide rate actually gained weight between pre- and post-intervention. On the other hand, there was no significant relationship between the level of walkability and weight loss. Our findings suggest that the social environment related to neighborhood crime may play a more important role in weight loss than the built environment, such as walkability. Urban characteristics related to walkability, such as sidewalks, may increase physical activity, however, interventions aiming to increase physical activity to promote weight loss will benefit by addressing the neighborhood social environment that determines how people navigate space.

Geographic disparities in access to liver transplantation

Since the Final Rule regarding transplantation was published in 1999, organ distribution policies have been implemented to reduce geographic disparity. While a recent change in liver allocation, termed acuity circles, eliminated the donor service area as a unit of distribution to decrease the geographic disparity of waitlisted patients to liver transplantation, recently published results highlight the complexity of addressing geographic disparity. From geographic variation in donor supply, as well as liver disease burden and differing model for end-stage liver disease (MELD) scores of candidates and MELD scores necessary to receive liver transplantation, to the urban-rural disparity in specialty care access, and to neighborhood deprivation (community measure of socioeconomic status) in liver transplant access, addressing disparities of access will require a multipronged approach at the patient, transplant center, and national level. Herein, we review the current knowledge of these disparities-from variation in larger (regional) to smaller (census tract or zip code) levels to the common etiologies of liver disease, which are particularly affected by these geographic boundaries. The geographic disparity in liver transplant access must balance the limited organ supply with the growing demand. We must identify patient-level factors that contribute to their geographic disparity and incorporate these findings at the transplant center level to develop targeted interventions. We must simultaneously work at the national level to standardize and share patient data (including socioeconomic status and geographic social deprivation indices) to better understand the factors that contribute to the geographic disparity. The complex interplay between organ distribution policy, referral patterns, and variable waitlisting practices with the proportion of high MELD patients and differences in potential donor supply must all be considered to create a national policy strategy to address the inequities in the system.

The Impact of Neighborhoods on Diabetes Risk and Outcomes: Centering Health Equity

Neighborhood environments significantly influence the development of diabetes risk factors, morbidity, and mortality throughout an individual's life. The social, economic, and physical environments of a neighborhood all affect the health risks of individuals and communities and also affect population health inequities. Factors such as access to healthy food, green spaces, safe housing, and transportation options can impact the health outcomes of residents. Social factors, including social cohesion and neighborhood safety, also play an important role in shaping neighborhood environments and can influence the development of diabetes. Therefore, understanding the complex relationships between neighborhood environments and diabetes is crucial for developing effective strategies to address health disparities and promote health equity. This review presents landmark findings from studies that examined associations between neighborhood socioeconomic, built and physical, and social environmental factors and diabetes-related risk and outcomes. Our framework emphasizes the historical context and structural and institutional racism as the key drivers of neighborhood environments that ultimately shape diabetes risk and outcomes. To address health inequities in diabetes, we propose future research areas that incorporate health equity principles and place-based interventions.

Neighborhood disinvestment and severe maternal morbidity in the state of California

BACKGROUND

Social determinants of health, including neighborhood context, may be a key driver of severe maternal morbidity and its related racial and ethnic inequities; however, investigations remain limited.

OBJECTIVE

This study aimed to examine the associations between neighborhood socioeconomic characteristics and severe maternal morbidity, as well as whether the associations between neighborhood socioeconomic characteristics and severe maternal morbidity were modified by race and ethnicity.

STUDY DESIGN

This study leveraged a California statewide data resource on all hospital births at ≥20 weeks of gestation (1997-2018). Severe maternal morbidity was defined as having at least 1 of 21 diagnoses and procedures (eg, blood transfusion or hysterectomy) as outlined by the Centers for Disease Control and Prevention. Neighborhoods were defined as residential census tracts (n=8022; an average of 1295 births per neighborhood), and the neighborhood deprivation index was a summary measure of 8 census indicators (eg, percentage of poverty, unemployment, and public assistance). Mixed-effects logistic regression models (individuals nested within neighborhoods) were used to compare odds of severe maternal morbidity across quartiles (quartile 1 [the least deprived] to quartile 4 [the most deprived]) of the neighborhood deprivation index before and after adjustments for maternal sociodemographic and pregnancy-related factors and comorbidities. Moreover, cross-product terms were created to determine whether associations were modified by race and ethnicity.

RESULTS

Of 10,384,976 births, the prevalence of severe maternal morbidity was 1.2% (N=120,487). In fully adjusted mixed-effects models, the odds of severe maternal morbidity increased with increasing neighborhood deprivation index (odds ratios: quartile 1, reference; quartile 4, 1.23 [95% confidence interval, 1.20-1.26]; quartile 3, 1.13 [95% confidence interval, 1.10-1.16]; quartile 2, 1.06 [95% confidence interval, 1.03-1.08]). The associations were modified by race and ethnicity such that associations (quartile 4 vs quartile 1) were the strongest among individuals in the "other" racial and ethnic category (1.39; 95% confidence interval, 1.03-1.86) and the weakest among Black individuals (1.07; 95% confidence interval, 0.98-1.16).

CONCLUSION

Study findings suggest that neighborhood deprivation contributes to an increased risk of severe maternal morbidity. Future research should examine which aspects of neighborhood environments matter most across racial and ethnic groups.

Housing instability and cardiometabolic health in the United States: a narrative review of the literature

Housing instability is variably defined but generally encompasses difficulty paying rent, living in poor or overcrowded conditions, moving frequently, or spending the majority of household income on housing costs. While there is strong evidence that people experiencing homelessness (i.e., lack of regular housing) are at increased risk for cardiovascular disease, obesity, and diabetes, less is known about housing instability and health. We synthesized evidence from 42 original research studies conducted in the United States examining the association of housing instability and cardiometabolic health conditions of overweight/obesity, hypertension, diabetes, and cardiovascular disease. The included studies varied widely in their definitions and methods of measuring housing instability, but all exposure variables were related to housing cost burden, frequency of moves, living in poor or overcrowded conditions, or experiencing eviction or foreclosure, measured at either the individual household level or at a population level. We also included studies examining the impact of receipt of government rental assistance, which serves as a marker of housing instability given that its purpose is to provide affordable housing for low-income households. Overall, we found mixed but generally adverse associations between housing instability and cardiometabolic health, including higher prevalence of overweight/obesity, hypertension, diabetes, and cardiovascular disease; worse hypertension and diabetes control; and higher acute health care utilization among those with diabetes and cardiovascular disease. We propose a conceptual framework for pathways linking housing instability and cardiometabolic disease that could be targeted in future research and housing policies or programs.

Neighborhood deprivation, built environment, and overweight in adolescents in the city of Oslo

BACKGROUND

Even though the social and built environment characteristics of neighborhoods have been studied as potential determinants of social inequalities in obesity among adults, fewer studies have focused on children. Our first aim was to investigate whether there were differences in the food and physical activity environments between different neighborhood deprivation levels in the city of Oslo. We also explored whether there was an association between the prevalence of overweight (including obesity) among adolescents and (i) neighborhood deprivation levels and (ii) food and physical activity environments of the neighborhoods they live in.

METHODS

We conducted a food and physical activity environment mapping (using ArcGIS Pro) in all neighborhoods of Oslo, which were defined by administrative boundaries (sub-districts). The neighborhood deprivation score was calculated based on the percentage of households living in poverty, unemployment in the neighborhood, and residents with low education. A cross-sectional study including 802 seventh graders from 28 primary schools in Oslo residing in 75 out of 97 sub-districts in Oslo was also performed. MANCOVA and partial correlations were ran to compare the built environment distribution between different neighborhood deprivation levels, and multilevel logistic regression analyses were used to explore the effect of neighborhood deprivation and the food and physical activity environments on childhood overweight.

RESULTS

We found that deprived neighborhoods had greater availability of fast food restaurants and fewer indoor recreational facilities compared to low-deprived neighborhoods. Additionally, we observed that the residential neighborhoods of the adolescents with overweight had greater availability of grocery and convenience stores when compared to the residential neighborhoods of the adolescents without overweight. Adolescents living in neighborhoods with high deprivation had a two-fold higher odds (95% CI = 1.1-3.8) to have overweight compared to adolescents living in neighborhoods with low deprivation, regardless of participants' ethnicity and parental education. However, the built environment did not determine the relationship between neighborhood deprivation and overweight in adolescents.

CONCLUSION

The neighborhoods in Oslo with higher deprivation levels had more obesogenic characteristics than the low-deprived neighborhoods. Adolescents living in high-deprived neighborhoods were more likely to have overweight than their counterparts from low-deprived neighborhoods. Thus, preventive measures targeting adolescents from high-deprived neighborhoods should be put in place in order to reduce incidence of overweight.

Social Determinants of Health and Racial/Ethnic Disparities in COVID-19 Mortality at the County Level in the Commonwealth of Virginia

BACKGROUND

Mortality due to coronavirus disease-2019 (COVID-19) among Black and Hispanic populations is disproportionately high compared to white populations. This study aimed to explore the association between COVID-19 mortality and social determinants of health (SDOH) among Black and Hispanic populations in Virginia.

METHOD

County-level publicly available COVID-19 mortality data from Virginia, covariates, and SDOH indicators were used. An independent t-test and hierarchical multiple regression analysis were performed to assess the association between SDOH and COVID-19 death rates, with a focus on racial/ethnic disparities.

RESULTS

Counties in the lowest quartile had a mean death rate of 44.72 (SD = 13.8), while those in the highest quartile had a mean death rate of 239.02 (SD = 123.9) per 100, 000 people ( P < .001). Counties with the highest death rates had significantly lower mean socioeconomic status. The regression analysis revealed that 32% of the variance in the COVID-19 mortality rate was associated with SDOH after controlling for the covariates ( P < .01). Identifying as Hispanic ethnicity accounted for 8.5% of the variance, while median household income, being uninsured, and education accounted for 32.7%, 12.9%, and 7.1%, respectively.

CONCLUSIONS

The findings provide evidence that disparities in SDOH experienced by Hispanic populations play a significant role in increased COVID-19 mortality, thus highlighting the social needs of low-income, low-education, and Hispanic populations to advance equity in health outcomes.

Proximity to High/Moderate vs Low Diversity Selection Food Stores and Patient Weight loss through 24 Months

PURPOSE

Explorations into the neighborhood food environment have not adequately extended to adults with obesity who undergo bariatric surgery. The objective of this study is to determine how diversity of food selection at food retail stores within proximities of 5- and 10-min walks associate with patient postoperative weight loss over 24 months.

MATERIALS AND METHODS

Eight hundred eleven patients (82.1% female; 60.0% White) who had primary bariatric surgery (48.6% gastric bypass) from 2015 to 2019 at The Ohio State University were included. EHR variables included race, insurance, procedure, and percent total weight loss (%TWL) at 2, 3, 6, 12, and 24 months. Proximity from patients' home addresses to food stores within a 5- (0.25 mile)- and 10-min (0.50 mile) walk were totaled for low (LD) and moderate/high (M/HD) diversity food selections. Bivariate analyses were conducted with %TWL at all visits and LD and M/HD selections within 5- (0, ≥ 1) and 10-min (0, 1, ≥ 2) walk proximities. Four mixed multilevel models were conducted with dependent variable %TWL over 24 months with visits as the between subjects factor and covariates: race, insurance, procedure, and interaction between proximity to type of food store selections with visits to determine association with %TWL over 24 months.

RESULTS

There were no significant differences for patients living within a 5- (p = 0.523) and 10-min (p = 0.580) walk in proximity to M/HD food selection stores and weight loss through 24 months. However, patients living in proximity to at least 1 LD selection store within a 5- (p = 0.027) and 1 or 2 LD stores within a 10-min (p = 0.015) walk had less weight loss through 24 months.

CONCLUSION

Overall, living in proximity to LD selection stores was a better predictor of postoperative weight loss over 24 months than living within proximity of M/HD selection stores.

Association of Obesity With Cognitive Decline in Black and White Americans

BACKGROUND AND OBJECTIVES

There are disparities in the prevalence of obesity by race, and the relationship between obesity and cognitive decline is unclear. The objective of this study was to determine whether obesity is independently associated with cognitive decline and whether the association between obesity and cognitive decline differs in Black and White adults. We hypothesized that obesity is associated with greater cognitive decline compared with normal weight and that the effect of obesity on cognitive decline is more pronounced in Black adults compared with their White counterparts.

METHODS

We pooled data from 28,867 participants free of stroke and dementia (mean, SD: age 61 [10.7] years at the first cognitive assessment, 55% female, 24% Black, and 29% obese) from 6 cohorts. The primary outcome was the annual change in global cognition. We performed linear mixed-effects models with and without time-varying cumulative mean systolic blood pressure (SBP) and fasting plasma glucose (FPG). Global cognition was set to a t-score metric (mean 50, SD 10) at a participant's first cognitive assessment; a 1-point difference represents a 0.1 SD difference in global cognition across the 6 cohorts. The median follow-up was 6.5 years (25th percentile, 75th percentile: 5.03, 20.15).

RESULTS

Obese participants had lower baseline global cognition than normal-weight participants (difference in intercepts, -0.36 [95% CI, -0.46 to -0.17]; p < 0.001). This difference in baseline global cognition was attenuated but was borderline significant after accounting for SBP and FPG (adjusted differences in intercepts, -0.19 [95% CI, -0.39 to 0.002]; p = 0.05). There was no difference in the rate of decline in global cognition between obese and normal-weight participants (difference in slope, 0.009 points/year [95% CI, -0.009 to 0.03]; p = 0.32). After accounting for SBP and FPG, obese participants had a slower decline in global cognition (adjusted difference in slope, 0.03 points/year slower [95% CI, 0.01 to 0.05]; p < 0.001). There was no evidence that race modified the association between body mass index and global cognitive decline (p = 0.34).

DISCUSSION

These results suggest that obesity is associated with lower initial cognitive scores and may potentially attenuate declines in cognition after accounting for BP and FPG.

Multilevel correlates of abdominal obesity in adolescents and youth living with HIV in peri-urban Cape Town, South Africa

BACKGROUND

Chronic non-communicable disease comorbidities are a major problem faced by people living with HIV (PLHIV). Obesity is an important factor contributing to such comorbidities and PLHIV face an elevated risk of obesity. However, there is data paucity on the intersection of obesity and HIV in adolescents and youth living with HIV (AYLHIV) in sub-Saharan Africa. We therefore aimed to investigate the prevalence of abdominal obesity and associated multilevel factors in AYLHIV in peri-urban Cape Town, South Africa.

METHODS

We conducted a cross-sectional study enrolling AYLHIV aged 15-24 years attending primary healthcare facilities in peri-urban Cape Town in 2019. All measures, except for physical examination measures, were obtained via self-report using a self-administered electronic form. Our outcome of interest was abdominal obesity (waist-to-height ratio ≥ 0.5). We collected individual-level data and data on community, built and food environment factors. Data was summarized using descriptive statistics, stratified by obesity status. Multilevel logistic regression was conducted to investigate factors associated with abdominal obesity, adjusted for sex and age.

FINDINGS

A total of 87 participants were interviewed, 76% were female and the median age was 20.7 (IQR 18.9-23.0) years. More than two fifths had abdominal obesity (41%; 95% CI: 31.0-51.7%), compared to published rates for young people in the general population (13.7-22.1%). In multilevel models, skipping breakfast (aOR = 5.42; 95% CI: 1.32-22.25) was associated with higher odds of abdominal obesity, while daily wholegrain consumption (aOR = 0.20; 95% CI: 0.05-0.71) and weekly physical activity (aOR = 0.24; 95% CI: 0.06-0.92) were associated with lower odds of abdominal obesity. Higher anticipated stigma was associated with reduced odds of obesity (aOR = 0.58; 95% CI: 0.33-1.00). Land-use mix diversity (aOR = 0.52; 95% CI: 0.27-0.97), access to recreational places (aOR = 0.37; 95% CI: 0.18-0.74), higher perceived pedestrian and traffic safety (aOR = 0.20; 95% CI: 0.05-0.80) and having a non-fast-food restaurant within walking distance (aOR = 0.30; 95% CI: 0.10-0.93) were associated with reduced odds of abdominal obesity. The main limitations of the study were low statistical power and possible reporting bias from self-report measures.

CONCLUSIONS

Our findings demonstrate a high prevalence of abdominal obesity and highlight multilevel correlates of obesity in AYLHIV in South Africa. An intersectoral approach to obesity prevention, intervening at multiple levels is necessary to intervene at this critical life stage.

Confronting racially exclusionary practices in the acquisition and analyses of neuroimaging data

Across the brain sciences, institutions and individuals have begun to actively acknowledge and address the presence of racism, bias, and associated barriers to inclusivity within our community. However, even with these recent calls to action, limited attention has been directed to inequities in the research methods and analytic approaches we use. The very process of science, including how we recruit, the methodologies we utilize and the analyses we conduct, can have marked downstream effects on the equity and generalizability of scientific discoveries across the global population. Despite our best intentions, the use of field-standard approaches can inadvertently exclude participants from engaging in research and yield biased brain-behavior relationships. To address these pressing issues, we discuss actionable ways and important questions to move the fields of neuroscience and psychology forward in designing better studies to address the history of exclusionary practices in human brain mapping.

Deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data for enhancing obesity estimation

BACKGROUND

Obesity is a serious public health problem. Existing research has shown a strong association between obesity and an individual's diet and physical activity. If we extend such an association to the neighborhood level, information about the diet and physical activity of the residents of a neighborhood may improve the estimate of neighborhood-level obesity prevalence and help identify the neighborhoods that are more likely to suffer from obesity. However, it is challenging to measure neighborhood-level diet and physical activity through surveys and interviews, especially for a large geographic area.

METHODS

We propose a method for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data, and examine the extent to which the derived measurements can enhance obesity estimation, in addition to the socioeconomic and demographic variables typically used in the literature. We conduct case studies in three different U.S. cities, which are New York City, Los Angeles, and Buffalo, using anonymized mobile phone location data from the company SafeGraph. We employ five different statistical and machine learning models to test the potential enhancement brought by the derived measurements for obesity estimation.

RESULTS

We find that it is feasible to derive neighborhood-level diet and physical activity measurements from anonymized mobile phone location data. The derived measurements provide only a small enhancement for obesity estimation, compared with using a comprehensive set of socioeconomic and demographic variables. However, using these derived measurements alone can achieve a moderate accuracy for obesity estimation, and they may provide a stronger enhancement when comprehensive socioeconomic and demographic data are not available (e.g., in some developing countries). From a methodological perspective, spatially explicit models overall perform better than non-spatial models for neighborhood-level obesity estimation.

CONCLUSIONS

Our proposed method can be used for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone data. The derived measurements can enhance obesity estimation, and can be especially useful when comprehensive socioeconomic and demographic data are not available. In addition, these derived measurements can be used to study obesity-related health behaviors, such as visit frequency of neighborhood residents to fast-food restaurants, and to identify primary places contributing to obesity-related issues.

Census-Tract-Level Median Household Income and Median Family Income Estimates: A Unidimensional Measure of Neighborhood Socioeconomic Status?

Previous studies suggested either census-tract-level median household income (MHI) or median family income (MFI) estimates may be used as a unidimensional measure of neighborhood socioeconomic status (SES) in the United States (US). To better understand its general use, the purpose of this study was to assess the usefulness of MHI and MFI in a wide range of geographic areas. Area-based socioeconomic data at the census tract level were obtained from the 2000 Census as well as the 2005-2009, 2010-2014, and 2015-2019 American Community Survey. MHI and MFI were used as two simple measures of neighborhood SES. Based on the five area-based indexes developed in the US, several census-tract-level socioeconomic indicators were used to derive five composite measures of neighborhood SES. Then, a series of correlation analyses was conducted to assess the relationships between these seven measures in the State of California and its seven Metropolitan Statistical Areas. Two simple measures were very strongly and positively correlated with one another, and were also strongly or very strongly correlated, either positively or negatively, with five composite measures. Hence, the results of this study support an analytical thinking that simple measures and composite measures may capture the same dimension of neighborhood SES in different geographic areas.

Food insecurity, food environments, and disparities in diet quality and obesity in a nationally representative sample of community-dwelling older Americans

Food insecurity, reflecting a household's low ability to purchase healthy food, is a public health concern that is associated with poor diet and obesity. Poor food environments, characterized as a neighborhood with low access to healthy, affordable food, may amplify the negative impact of food insecurity on diet and obesity. This study aims to investigate whether food insecurity and food environments are jointly associated with an increased risk of poor diet quality and obesity. We used data from a nationally representative sample of community-dwelling older adults in the Health and Retirement Study Health Care and Nutrition Survey and the National Neighborhood Data Archive to investigate the role of household and neighborhood characteristics on diet and obesity. Weighted regression models were estimated to examine the relationship between food insecurity and food environments as well as their interaction with diet quality and obesity. Food insecure respondents had lower Healthy Eating Index scores and were more likely to be obese than food secure respondents. Living in a poor food environment was associated with lower Healthy Eating Index scores, but not with obesity. We did not find any interaction between food insecurity and food environment in determining either healthy eating or obesity. Reducing food insecurity and increasing access to healthy food environments may encourage healthier eating among older adults, while alleviating food-related hardship may also reduce their obesity risk.

Socio-economic inequalities in the consumption of fruits and vegetables in Peru between 2014 and 2019

OBJECTIVE

To estimate the prevalence and socio-economic inequalities in adequate consumption of fruits and vegetables in Peru between 2014 and 2019.

DESIGN

Analytical cross-sectional study. The outcome variable was adequate consumption of fruits and vegetables, defined as the consumption of five or more servings of fruits and vegetables per d (yes/no). We used concentration curves and Erreygers concentration index to describe socio-economic inequalities and a microeconometric approach to determine the contribution of each variable to inequality.

SETTING

Peru.

PARTICIPANTS

Data from Peruvians aged 18 years or older collected by the Demographic and Family Health Survey.

RESULTS

The prevalence of adequate fruit and vegetable consumption did not change between 2014 (10·7 %; 95 % CI (10·0, 11·4)) and 2019 (11 %; 95 % CI (10·4, 11·7)). We found socio-economic inequalities in the adequate consumption of fruits and vegetables, with wealthier individuals having a higher prevalence of adequate consumption compared to poorer individuals in 2014 (19·2 % v. 3·5 %) and 2019 (18·6 % v. 4·7 %). The decomposition analysis found that education, urban areas and being wealthy were the main factors associated with socio-economic inequality in adequate fruit and vegetable consumption, being structural problems of society.

CONCLUSION

Despite the current regulations on healthy eating in Peru, adequate consumption of fruits and vegetables remains low, and there are socio-economic inequalities between the poorest and wealthiest individuals. Our findings suggest that more efforts are needed to increase the intake and assess the disparities in adequate fruit and vegetable consumption.

Association of Neighborhood Economic Trajectories With Changes in Weight Status Among Black and White Adults in the Southeastern US

IMPORTANCE

Neighborhood environment is an important factor associated with population disparities in obesity. However, few studies have examined whether and in what ways long-term trajectories of neighborhood conditions may be associated with weight outcomes. Moreover, there is a lack of research focusing on multidimensional and nuanced measures that make distinctions between multiple types of neighborhood change (eg, gentrification vs overall growth).

OBJECTIVE

To examine the association between long-term neighborhood economic trajectories and changes in weight status among Black and White adults residing in predominantly low-income communities in the southeastern US.

DESIGN, SETTING, AND PARTICIPANTS

This study was a longitudinal analysis of participants in the Southern Community Cohort Study. Five types of neighborhood economic trajectories (stability, growth, displacement, abandonment, and poverty concentration) were measured using data from the US Census and the American Community Survey from 2000 to 2016. Data were analyzed from December 12, 2021, to July 16, 2022. A total of 33 621 Black and White adults in the southeastern US were included in the analytic sample.

EXPOSURE

Neighborhood economic trajectory.

MAIN OUTCOMES AND MEASURES

Substantial weight gain and substantial weight loss (ie, gaining or losing ≥10% of baseline weight) between baseline (March 2002 to September 2009) and follow-up (November 2008 to January 2013) periods were assessed using self-reported information.

RESULTS

Among 33 621 participants, the mean (SD) age was 53.4 (8.8) years; 22 116 participants (65.8%) were women, 21 782 (64.8%) were Black, and 11 839 (35.2%) were White. Compared with residents in neighborhoods with stable trajectories, those in neighborhoods with growth trajectories that did not displace original residents were less likely to experience substantial weight gain (odds ratio [OR], 0.75; 95% CI, 0.58-0.97), whereas those in neighborhoods with poverty concentration trajectories were more likely to experience substantial weight gain (OR, 1.08; 95% CI, 1.00-1.17). These patterns appeared stronger among Black participants (eg, substantial weight gain in poverty concentration group: OR, 1.10 [95% CI, 1.00-1.22]; in growth group: OR, 0.76 [95% CI, 0.56-1.02]) compared with White participants (eg, substantial weight gain in poverty concentration group: OR, 1.03 [95% CI, 0.90-1.18]; in growth group: OR, 0.84 [95% CI, 0.52-1.36]). Differences in patterns were also observed among men (eg, substantial weight gain in poverty concentration group: OR, 1.02 [95% CI, 0.88-1.17]; in growth group: OR, 0.58 [95% CI, 0.35-0.96]) compared with women (eg, substantial weight gain in poverty concentration group: OR, 1.12 [95% CI, 1.02-1.23]; in growth group: OR, 0.83 [95% CI, 0.62-1.12]). However, none of the interaction terms between Black vs White participants and men vs women were statistically significant. Neighborhood trajectory was not associated with substantial weight loss (poverty concentration group: OR, 1.00 [95% CI, 0.93-1.09]; abandonment group: OR, 1.01 [95% CI, 0.84-1.15]; displacement group: OR, 1.04 [95% CI, 0.83-1.23]; growth group: OR, 0.88 [95% CI, 0.69-1.12]).

CONCLUSIONS AND RELEVANCE

In this cohort study, neighborhood economic trajectories were associated with weight gain. These findings highlight the importance of using more nuanced and multidimensional measures of neighborhood change in public health research.

Systematic literature review of instruments that measure the healthfulness of food and beverages sold in informal food outlets

BACKGROUND

Informal food outlets, defined as vendors who rarely have access to water and toilets, much less shelter and electricity, are a common component of the food environment, particularly in many non-Western countries. The purpose of this study was to review available instruments that measure the quality and particularly the healthfulness of food and beverages sold within informal food outlets.

METHODS

PubMed, LILACS, Web of Science, and Scopus databases were used. Articles were included if they reported instruments that measured the availability or type of healthy and unhealthy foods and beverages by informal food outlets, were written in English or Spanish, and published between January 1, 2010, and July 31, 2020. Two trained researchers reviewed the title, abstract and full text of selected articles; discrepancies were solved by two independent researchers. In addition, the list of references for selected articles was reviewed for any additional articles of relevance. The quality of published articles and documents was evaluated using JBI Critical appraisal checklist for analytical cross-sectional studies.

RESULTS

We identified 1078 articles of which 14 were included after applying the selection criteria. Three additional articles were considered after reviewing the references from the selected articles. From the final 17 articles, 13 measurement tools were identified. Most of the instruments were used in low- and middle-income countries (LMIC). Products were classified as healthy/unhealthy or produce/non-produce or processed/unprocessed based on availability and type. Six studies reported psychometric tests, whereas one was tested within the informal food sector.

CONCLUSIONS

Few instruments can measure the healthfulness of food and beverages sold in informal food outlets, of which the most valid and reliable have been used to measure formal food outlets as well. Therefore, it is necessary to develop an instrument that manages to measure, specifically, the elements available within an informal one. These actions are extremely important to better understand the food environment that is a central contributor to poor diets that are increasingly associated with the obesity and Non-communicable disease (NCD) pandemic.

Therapeutic potential of dopamine agonists in the treatment of type 2 diabetes mellitus

Diabetes is a global health concern that has affected almost 415 million people globally. Bromocriptine is a dopamine D2 agonist, which is a Food and Drug Administration (FDA)-approved drug to treat type 2 diabetes mellitus (T2DM) patients. However, it is considered that a novel treatment therapy is required which can be used in the treatment of diabetes with or without other antidiabetic agents. Dopamine agonists are usually used in neurological disorders like Parkinson's disease (PD), restless leg syndrome, and hyperprolactinemia. However, dopamine agonists including bromocriptine and cabergoline are also effective in reducing the glycemic level in T2DM patients. Bromocriptine was formerly used for the treatment of PD, hyperprolactinemia, and restless leg syndrome, but now it is used for improving glycemic levels as well as reducing free fatty acids and triglycerides. In addition, cabergoline has been found to be effective in glycemic control, but this drug is yet to be approved by the FDA due to its limitations and lack of study. Findings of the clinical trials of bromocriptine have suggested that it reduces almost 0.4-0.8% glycated hemoglobin and cardiovascular risk by 40% in insulin-resistant patients. Moreover, the safe use of bromocriptine in obese T2DM patients makes it a more attractive option as it causes weight loss. Indeed, bromocriptine is a novel therapy for T2DM patients, as its mechanism of action is unique in T2DM patients with minimal adverse effects. This review summarizes the potential of dopamine agonists in the treatment of T2DM.

Physical Activity Impacts of an Activity-Friendly Community: A Natural Experiment Study Protocol

Background

Stakeholders from multiple sectors are increasingly aware of the critical need for identifying sustainable interventions that promote healthy lifestyle behaviors. Activity-friendly communities (AFCs) have been known to provide opportunities for engaging in physical activity (PA) across the life course, which is a key to healthy living and healthy aging.

Purpose

Our purpose is to describe the study protocol developed for a research project that examines: (a) the short- and long-term changes in total levels and spatial and temporal patterns of PA after individuals move from non-AFCs to an AFC; and (b) what built and natural environmental factors lead to changes in PA resulting from such a move, either directly or indirectly (e.g., by affecting psychosocial factors related to PA).

Methods

This protocol is for a longitudinal, case-comparison study utilizing a unique natural experiment opportunity in Austin, Texas, USA. Case participants were those adults who moved from non-AFCs to an AFC. Matching comparison participants were residents from similar non-AFCs who did not move during the study period. Recruitment venues included local businesses, social and print media, community events, and individual referrals. Objectively measured moderate-to-vigorous PA and associated spatial and temporal patterns served as the key outcomes of interest. Independent (e.g., physical environments), confounding (e.g., demographic factors), and mediating variables (e.g., psychosocial factors) were captured using a combination of objective (e.g., GIS, GPS, Tanita scale) and subjective measures (e.g., survey, travel diary). Statistical analyses will be conducted using multiple methods, including difference-in-differences models, repeated-measures linear mixed models, hierarchical marked space-time Poisson point pattern analysis, and hierarchical linear mixed models.

Conclusion

Natural experiment studies help investigate causal relationships between health and place. However, multiple challenges associated with participant recruitment, extensive and extended data collection activities, and unpredictable intervention schedules have discouraged many researchers from implementing such studies in community-based populations. This detailed study protocol will inform the execution of future studies to explore how AFCs impact population health across the life course.

Income Disparities in Obesity Trends among U.S. Adults: An Analysis of the 2011-2014 California Health Interview Survey

The aim of this study was to examine income disparities in obesity trends among California adults. Data were obtained from the 2011−2014 California Health Interview Survey (n = 83,175 adults). Obesity for adults was defined as a body mass index of 30 kg/m2 or above. Family income was categorized as below 100%, 100% to 299%, or 300% and above of the federal poverty level (FPL). Weighted multiple logistic regression analyses were used to examine the association between family income and obesity across survey years after controlling for age, sex, race/ethnicity, smoking status, marital status, education, physical activity, and healthy diet. Obesity prevalence among California adults increased slightly from 25.1% in 2011 to 27.0% in 2014. Compared to 300% FPL or above, <100% FPL and 100−299% FPL were associated with increased odds of obesity, respectively (OR = 1.35, 95% CI = 1.22−1.50, for 100−299% FPL; OR = 1.18, 95% CI = 1.10−1.27, for 300% FPL or above). Each year, lower FPL was associated with higher odds of obesity, except for the year 2014. An inverse association between obesity and family income in each survey year was observed, with the magnitude of the income disparity decreasing from 2011 to 2014. The findings of this study show that family income was negatively associated with obesity among adults in California from 2011−2014, and the magnitude of the income disparity in obesity prevalence decreased over this period. Future studies need to examine potential risk factors associated with the decreasing trend.

Association Between Social Vulnerability and Achieving Glycemic Control Among Pregnant Individuals With Pregestational Diabetes

OBJECTIVE

To evaluate the association between community-level social vulnerability and achieving glycemic control (defined as hemoglobin A1c [Hb A1c] less than 6.0% or less than 6.5%) among individuals with pregestational diabetes.

METHODS

We conducted a retrospective cohort of individuals with pregestational diabetes with singleton gestations from 2012 to 2016 at a tertiary care center. Addresses were geocoded using ArcGIS and then linked at the census tract to the Centers for Disease Control and Prevention's 2018 SVI (Social Vulnerability Index), which incorporates 15 Census variables to produce a composite score and four scores across thematic domains (socioeconomic status, household composition and disability, minority status and language, and housing type and transportation). Scores range from 0 to 1, with higher values indicating greater community-level social vulnerability. The primary outcome was Hb A1c less than 6.0%, and, secondarily, Hb A1c less than 6.5%, in the second or third trimesters. Multivariable Poisson regression with robust error variance was used to evaluate the association between SVI score as a continuous measure and target Hb A1c.

RESULTS

Among 418 assessed pregnant individuals (33.0% type 1; 67.0% type 2 diabetes), 41.4% (173/418) achieved Hb A1c less than 6.0%, and 56.7% (237/418) Hb A1c less than 6.5% at a mean gestational age of 29.5 weeks (SD 5.78). Pregnant individuals with a higher SVI score were less likely to achieve Hb A1c less than 6.0% compared with those with a lower SVI score. For each 0.1-unit increase in SVI score, the risk of achieving Hb A1c less than 6.0% decreased by nearly 50% (adjusted risk ratio [aRR] 0.53; 95% CI 0.36-0.77), and by more than 30% for Hb A1c less than 6.5% (adjusted odds ratio 0.67; 95% CI 0.51-0.88). With regard to specific SVI domains, those who scored higher on socioeconomic status (aRR 0.50; 95% CI 0.35-0.71) as well as on household composition and disability (aRR 0.55; 95% CI 0.38-0.79) were less likely to achieve Hb A1c less than 6.0%.

CONCLUSION

Pregnant individuals with pregestational diabetes living in an area with higher social vulnerability were less likely to achieve glycemic control, as measured by HgbA1c levels. Interventions are needed to assess whether addressing social determinants of health can improve glycemic control in pregnancy.

Neighborhood deprivation and obesity: Sex-specific effects of cross-sectional, cumulative and residential trajectory indicators

Obesity is a long-term health issue that is becoming increasingly prevalent. Very few studies have considered the life course effects of neighborhood characteristics on obesity. In a sample of 35,856 adult participants (representative of the population of the Province of Quebec in Canada), we measured the association between neighborhood deprivation and obesity using logistic modelling on indicators of cross-sectional neighborhood deprivation, cumulative neighborhood deprivation and trajectories of neighborhood deprivation. For cross-sectional exposure, we found that females in our sample had higher odds of being affected by obesity when living in high-deprivation (OR 1.73, CI 1.41-2.13) or medium-deprivation neighborhoods (OR 1.27, CI 1.07-1.51) compared to females living in low-deprivation neighborhoods. Males also had higher odds of being affected by obesity when living in medium or high deprivation. For cumulative exposure to neighborhood deprivation, only females in the second highest category for longitudinal exposure to deprived neighborhoods had significantly higher odds of living with obesity (OR 1.89 CI 1.12-3.19) compared to females in the low cumulative exposure category. Using sequence analysis to determine neighborhood deprivation trajectories for up to 17 years, we found that females with a Deprived upward (OR 1.75 CI 1.10-2.78), an Average downward (OR 1.75 CI 1.08-2.84) or a Deprived trajectory (OR 1.81 CI 1.45-2.86) had higher odds of living with obesity compared to the Privileged trajectory. For males, there were no significant associations. Using trajectory indicators was beneficial to our analyses because this method shows that not only are individuals in low socioeconomic status neighborhoods at the end of their trajectory more susceptible to living with obesity, but so are those exposed to neighborhood deprivation at the beginning of their trajectory. These results could help to more precisely identify individuals at higher risk of developing obesity-related health issues.

Examining School and Neighborhood Effects of Socioeconomic Status on Childhood Obesity in the U.S

Obesity amongst Kindergartners in Texas is above the national average, particularly among Hispanic students. Research on the impact of school and neighborhood-level SES on obesity in childhood using multilevel models is lacking. Survey data were collected from Hispanic caregivers of pre-kindergarten students in Fall 2019 (n = 237). Students were clustered in thirty-two neighborhoods and twelve schools. The dependent variable was the child’s body mass index z-score (BMIz). Covariates included the child’s sex, primary caregiver’s marital status, education level, relationship to the child, and family income. Level-two variables included neighborhood poverty and school SES. CTableross-classified multilevel linear regression models were conducted to examine the unique associations of neighborhood poverty and school SES with individual student BMIz, and how they interact. Twenty-four percent of students were classified as overweight, and five percent were classified as obese. The models resulted in a significant association between school SES and BMIz (B = −0.13; SE = 0.06; p < 0.05) and between neighborhood poverty and BMIz (B = −1.41; SE = 0.49; p < 0.01). Individual students’ BMIz decreased as school SES increased and decreased as neighborhood poverty increased. Neighborhood poverty and school SES appear to play a role in the development of obesity in childhood, although in differing directions.

Physical and social environmental factors related to co-occurrence of unhealthy lifestyle behaviors

Previous work identifying determinants of co-occurrence of behavioral risk factors have focused on their association with individuals' characteristics with scant attention paid to their relationship to contextual factors. Data came from 21,007 individuals ≥15 years of age who participated in the cross-sectional 2011-2012 Spanish National Health Survey. Two indicators were defined by tobacco consumption, alcohol intake, diet, physical activity, and body mass index. The first indicator, based on dichotomized measures, ranges from 0 to 5. The second one (unhealthy lifestyle index), ranges from 0 to 15, with 0 denoting the healthiest score. Among the determinants, we examined social support, five perceived characteristics of the neighborhood, and the socioeconomic deprivation index of the census tract of residence. Data were analyzed using multilevel linear and logistic regression models adjusted for the main sociodemographic characteristics. Using the dichotomized indicator, the probability of having 3-5 risk factors versus <3 factors was associated with low social support (Odds Ratio [OR] 1.50; 95% Confidence Interval [CI]: 1.25-1.80). Issues surrounding neighborhood cleanliness (OR = 1.18; 95%CI: 1.04-1.33), air pollution (OR = 1.38; 95%CI: 1.16-1.64), and street crime (OR = 1.21; 95%CI: 1.03-1.42) were associated with determinants of co-occurrence. Risk factors co-occurrence increased as deprivation level increased: the OR for the highest deprivation quintile versus the lowest was 1.30 (95%CI: 1.14-1.48). Similar results were observed when using the unhealthy lifestyle index. Poorer physical and social environments are related to greater co-occurrence of risk factors for chronic diseases. Health promotion interventions targeting the prevention of risk factors should consider the contextual characteristics of the neighborhood environment.

Impact of Grocery Store Proximity on Store Preference Among Atlanta SNAP-Ed Participants

OBJECTIVE

To assess the association between grocery store proximities and the individual's grocery store preferences among Supplemental Nutrition Assistance Program Education participants in Atlanta.

METHODS

University of Georgia Supplemental Nutrition Assistance Program Education participants (n = 615, response rate is 36%) in 3 counties provided their preferred grocery store chains. The association between store proximity (both network distance and driving time) and store preference was measured through logistic regression controlling for age, sex, and race.

RESULTS

Descriptive statistics showed participants had widely varying proximities to grocery stores. Model results were significant for all smaller chains (Aldi, Big Bear, Wayfield, Food Depot, and Save-A-Lot), Kroger (P < 0.01), as well as for Walmart (time only, P = 0.002).

CONCLUSIONS AND IMPLICATIONS

Future studies might identify whether local groceries are more willing to partner on interventions or are more effective at reaching local residents. Surveys or techniques such as sketch mapping could also show whether individuals shop in neighborhoods close to work or friends and family.

Predictors of Active Transportation Among Safe Routes to School Participants in Arizona: Impacts of Distance and Income

BACKGROUND

Active transportation to school (ATS) is a component of a whole school approach to health promotion among youth.

METHODS

Individual- and school-level predictors of ATS were examined using data from parent surveys (N = 11,100) of students in grades 3-8 attending 112 schools in Arizona (United States) administering Safe Routes to School (SRTS) programs between 2007 and 2018. Multilevel logistic models were estimated to predict the likelihood of students using active (walking or biking) versus inactive travel (riding bus or car) to and from school, and across distance and school-level income categories.

RESULTS

Student grade, parent education, asking permission to use ATS, perceived health and school support for ATS, distance, and school income were predictive of ATS. The impact of demographic factors persisted across distances of ½ mile or less and at low- and medium-income schools but diminished as distance and income increased. Asking permission and perceived school support persisted across levels of distance and income, while perceiving ATS as healthy was significant only for distances under 1 mile.

CONCLUSIONS

SRTS programs should continue promoting health benefits and school support for ATS. SRTS may be particularly effective at low- and medium-income schools and among families living within ½ mile distances.

Addressing Structural Racism Is Critical for Ameliorating the Childhood Obesity Epidemic in Black Youth

Racism and childhood obesity are both pervasive factors adversely affecting the health and wellbeing of children and adolescents in the United States. The association between racism and obesity has been touched upon in the literature; yet most work has focused on a few dimensions of intersectionality of these two domains at one time. The renewed focus on structural racism as the primary contributor to distress of Black individuals in the United States has highlighted the urgency of identifying the contributions of racism to the childhood obesity epidemic. The current article is not a complete review of the literature, rather, it is meant to take a broad narrative review of the myriad ways in which racism contributes to the obesity epidemic in Black youth to serve as a call to action for more research, prevention, and intervention. The current article illustrates how a number of mechanisms for the etiology and maintenance of obesity are heavily influenced by racism and how addressing racism is critical for ameliorating the childhood obesity epidemic.

Interpreting a standardized and normalized measure of neighborhood socioeconomic status for a better understanding of health differences

BACKGROUND

Standardization and normalization of continuous covariates are used to ease the interpretation of regression coefficients. Although these scaling techniques serve different purposes, they are sometimes used interchangeably or confused for one another. Therefore, the objective of this study is to demonstrate how these scaling techniques lead to different interpretations of the regression coefficient in multilevel logistic regression analyses.

METHODS

Area-based socioeconomic data at the census tract level were obtained from the 2015-2019 American Community Survey for creating two measures of neighborhood socioeconomic status (SES), and a hypothetical data on health condition (favorable versus unfavorable) was constructed to represent 3000 individuals living across 300 census tracts (i.e., neighborhoods). Two measures of neighborhood SES were standardized by subtracting its mean and dividing by its standard deviation (SD) or by dividing by its interquartile range (IQR), and were normalized into a range between 0 and 1. Then, four separate multilevel logistic regression analyses were conducted to assess the association between neighborhood SES and health condition.

RESULTS

Based on standardized measures, the odds of having unfavorable health condition was roughly 1.34 times higher for a one-SD change or a one-IQR change in neighborhood SES; these reflect a health difference of individuals living in relatively high SES (relatively affluent) neighborhoods and those living in relatively low SES (relatively deprived) neighborhoods. On the other hand, when these standardized measures were replaced by its respective normalized measures, the odds of having unfavorable health condition was roughly 3.48 times higher for a full unit change in neighborhood SES; these reflect a health difference of individuals living in highest SES (most affluent) neighborhoods and those living in lowest SES (most deprived) neighborhoods.

CONCLUSION

Multilevel logistic regression analyses using standardized and normalized measures of neighborhood SES lead to different interpretations of the effect of neighborhood SES on health. Since both measures are valuable in their own right, interpreting a standardized and normalized measure of neighborhood SES will allow us to gain a more rounded view of the health differences of individuals along the gradient of neighborhood SES in a certain geographic location as well as across different geographic locations.

The role of food and activity environment in a bariatric surgery population: impact on postoperative weight loss

BACKGROUND

Food and activity factors may have an impact on weight in the general population, but little is known about how this affects postbariatric surgery weight loss.

OBJECTIVES

To understand the impact of environmental food and activity factors on weight loss after bariatric surgery.

SETTING

A multidisciplinary integrated health system with an accredited bariatric surgery program.

METHODS

An institutional review board-approved retrospective review of patients who underwent bariatric surgery from 2001-2018 was completed. Food security, food retailers, and activity factors associated with postoperative percentage of total body weight loss (TBWL) at short-term (1-2 yr), medium-term (3-5 yr), and long-term (≥6 yr) follow-up were evaluated.

RESULTS

Overall, 1673 patients were included; 90% experienced ≥20% TBWL in the short term and 65% in the long term. No differences in mean TBWL were observed for food deserts or areas with high versus low food insecurity. Mean TBWL was significantly different for low versus high healthy food density (32.5% versus 33.4%, P = .024) and low versus high fitness facility density (32.6% versus 33.4%, P = .048) at short-term follow-up. Increased mean TBWL was observed for counties with more versus less exercise opportunities at short and medium-term follow-up (33.4% versus 32.5%, P = .025; 31.2% versus 29.7%, P = .019).

CONCLUSION

Patients experienced significant TBWL after bariatric surgery. Living in a food desert or area with high food insecurity did not significantly impact mean TBWL. Healthy food density, fitness facility density, and exercise opportunities had a short- to medium-term impact on TBWL. These data can be used to support patients to maximize the benefits of bariatric surgery.

Examining the impacts of neighborhood poverty on bodyweight across the BMI distribution: a quantile and MSM modeling approach

PURPOSE

Given that the relationships between higher BMI and adverse health outcomes are nonconstant and most pronounced at either ends of the BMI distribution, we assess the association between neighborhood poverty and BMI at multiple points along the BMI distribution.

METHODS

Using data from the 1999 to 2015 Panel Study of Income Dynamics of Black and White adults in the United States, we estimate quantile regression models while jointly applying a marginal structural modeling approach to account for time-varying individual-level factors that may be simultaneously mediators as well as confounders.

RESULTS

Neighborhood poverty was not found to be associated with bodyweight at any point along the BMI distribution for Black or White males. However, high neighborhood poverty, compared to low neighborhood poverty, predicted increases in bodyweight for Black females at the lower end of the BMI distribution and for White females at the higher end of the BMI distribution. No association was found between neighborhood poverty and BMI at the mean.

CONCLUSIONS

Results identify the most vulnerable subgroups, suggesting that White females at the higher end of the BMI distribution as well as Black females at the lower end of the BMI distribution are particularly sensitive to obesogenic environments.

Assessing the relationship between adverse pregnancy outcomes and area-level deprivation in Wales 2014-2019: a national population-based cross-sectional study

OBJECTIVES

The aim of this study was to assess the relationship between deciles of area-level deprivation and seven adverse pregnancy outcomes in Wales.

DESIGN

Cross-sectional analysis.

SETTING

64 699 live births in Wales from 31 March 2014 to 16 September 2019.

PRIMARY OUTCOME VARIABLE

We examined each of the following seven adverse pregnancy outcomes: (1) small for gestational age (SGA); (2) large for gestational age; (3) preterm birth; (4) third-degree or fourth-degree perineal tear; (5) major postpartum haemorrhage (MPPH); (6) a lower Apgar score at 5 min and (7) emergency caesarean section.

RESULTS

There was no significant association between increasing aggregate measures of area-level deprivation and the adverse pregnancy outcomes we studied. Women living in an area with greater access to services are more likely to have a baby that is SGA (1.27, 95% CI 1.11 to 1.49), have a greater likelihood of a perineal tear (1.74, 95% CI 1.15 to 2.61), are significantly less likely to have MPPH (0.79, 95% CI 0.64 to 0.96), have a baby with an Apgar score of 0.26 higher (95% CI 0.22 to 0.29) and are significantly less likely to have an emergency caesarean section (0.81, 95% CI 0.73 to 0.88). Women living in areas with higher employment (0.26, 95% CI 0.19 to 0.36) and better health (0.26, 95% CI 0.19 to 0.35) were less likely to experience perineal tear.

CONCLUSIONS

There was no clear social-spatial gradient in area-level deprivation and adverse pregnancy outcomes. We found a stronger association for individual-level behavioural risk factors than area-level factors. These findings support the benefits that accessible and holistic person-centred care may bring through addressing individual behavioural risk factors. There is a need for improved data completeness and further individual-level data on risk factors such as employment and income to better understand the role which may be played by population-level policies and their pathways to affecting outcomes.

The effects of the built environment on the general health, physical activity and obesity of adults in Queensland, Australia

The built environment has been identified as a key factor for health intervention and obesity prevention. However, it is still unclear to what extent the built environment is associated with obesity and general health and to what extent such an association is mediated through variation in physical activity. This study aims to examine the associations between individual characteristics, the built environment, physical activity, general health and body mass index to reveal the pathways through which the built environment is associated with the prevalence of obesity. Using data from 1,788 adults aged 18 to 65 in Queensland from Wave 16 of the Household, Income, and Labour Dynamics in Australia survey, we use geographic information system-based methods to quantify built environment factors in 5D dimensions: Density, Diversity, Design, Distance and Destination accessibility. We then employ multi-level mixed-effect models to test the hypothesised relationships between individual characteristics, the built environment, physical activity, general health and body mass index. The results indicate that physical activity is positively associated with general health and negatively associated with the prevalence of obesity. Adjusting for individual characteristics, we find that built-environment factors have direct effects on physical activity but indirect effects on general health and obesity. Among these factors, greater green space exposure plays a key role in enhancing general health and reducing obesity. Low-density and car-dependent neighbourhoods can be activity-friendly and mitigate obesity if these neighbourhoods are also equipped with easy access to green space.

From the clinic to the community: Can health system data accurately estimate population obesity prevalence?

OBJECTIVE

Health system data were assessed for how well they can estimate obesity prevalence in census tracts.

METHODS

Clinical visit data were available from two large health systems (Kaiser Permanente Washington and University of Washington Medicine) in King County, Washington, as were census tract-level obesity prevalence estimates from the Behavioral Risk Factor Surveillance System (BRFSS). The health system data were geocoded to identify each patient's tract of residence, and the cross-sectional concordance between census tract-level obesity prevalence estimates computed from the two health systems in 2005 to 2006 and the concordance between University of Washington Medicine and BRFSS from 2012 to 2016 were assessed.

RESULTS

The spatial distribution of obesity was similar between the health systems (Spearman r = 0.63). The University of Washington Medicine estimates of rank order correlated well with BRFSS estimates (Spearman r = 0.85), though prevalence estimates from BRFSS were lower (mean obesity prevalence = 26% for University of Washington Medicine versus 20% for BRFSS, Wilcoxon rank sum test p < 0.001). Across all data sources, obesity was more prevalent in tracts with less educational attainment.

CONCLUSIONS

Health system clinical weight data can reliably replicate census tract-level spatial patterns in the ranking of obesity prevalence. Health system data may be an efficient resource for geographic obesity surveillance.

Developing the logic framework underpinning a whole-systems approach to childhood overweight and obesity prevention: Amsterdam Healthy Weight Approach

BACKGROUND

Whole-systems approaches (WSAs) are well placed to tackle the complex local environmental influences on overweight and obesity, yet there are few examples of WSAs in practice. Amsterdam Healthy Weight Approach (AHWA) is a long-term, municipality-led program to improve children's physical activity, diet, and sleep through action in the home, neighborhood, school, and city. Adopting a WSA, local political, physical, social, educational, and healthcare drivers of childhood obesity are viewed as a complex adaptive system. Since 2013, AHWA has reached >15,000 children. During this time, the estimated prevalence of 2-18-year-olds with overweight or obesity in Amsterdam has declined from 21% in 2012 to 18.7% in 2017. Declining trends are rarely observed in cities. There is a need to formally articulate AHWA program theory in order to: (i) inform future program evaluation which can interpret this decline within the context of AHWA and (ii) contribute a real-life example of a WSA to the literature.

METHODS

This study aimed to formally document the program theory of AHWA to permit future evaluation. A logic framework was developed through extensive document review and discussion, during program implementation.

RESULTS

The working principles of the WSA underpinning AHWA were made explicit in an overarching theory of change, articulated in a logic framework. The framework was operationalized using an illustrative example of sugar intake.

CONCLUSIONS

The logic framework will inform AHWA development, monitoring, and evaluation and responds to a wider need to outline the working principles of WSAs in public health.

Deprivation Index and Lifestyle: Baseline Cross-Sectional Analysis of the PREDIMED-Plus Catalonia Study

This baseline cross-sectional analysis from data acquired in a sub-sample of the PREDIMED-Plus study participants aimed to evaluate the relation between the Composite Socioeconomic Index (CSI) and lifestyle (diet and physical activity). This study involved 1512 participants (759 (52.2%) women) between 55 and 80 years with overweight/obesity and metabolic syndrome assigned to 137 primary healthcare centers in Catalonia, Spain. CSI and lifestyle (diet and physical activity) were assessed. Multiple linear regression or multinomial regression were applied to the data. Cluster analysis was performed to identify dietary patterns. The multiple linear regression model showed that a high deprivation index was related to a higher consumption of refined cereals (11.98 g/d, p-value = 0.001) and potatoes (6.68 g/d, p-value = 0.001), and to a lower consumption of fruits (−17.52 g/d, p-value = 0.036), and coffee and tea (−8.03 g/d, p-value = 0.013). Two a posteriori dietary patterns were identified by cluster analysis and labeled as “healthy” and “unhealthy”. In addition, the multinomial regression model showed that a high deprivation index was related to an unhealthy dietary pattern and low physical activity (OR 1.42 [95% CI 1.06–1.89]; p-value < 0.05). In conclusion, a high deprivation index was related to an unhealthy lifestyle (diet and physical activity) in PREDIMED-Plus study participants.

Food Acquisition and Shopping Patterns in the United States: Characteristics and Relation to Body Mass Index in the US Food Acquisition and Purchase Survey

BACKGROUND

Previous studies examined the association between shopping distance, frequency, and store type separately.

OBJECTIVES

The objective is to explore food acquisition and shopping habits using multidimensional measures and examine its association with body mass index (BMI).

DESIGN

A cross-sectional study was conducted.

PARTICIPANTS/SETTING

Four thousand four hundred sixty-six households from the US Food Acquisition and Purchase Survey during April 2012 to January 2013 were included in this analysis.

MAIN OUTCOMES MEASURES

Both continuous BMI and categorical BMI were used.

STATISTICAL ANALYSES

Latent class analysis was used to identify the latent profiles using travel distance and perceived travel time between residential location and primary store, store type, transportation mode, and farmers' market utilization. Multivariable linear regression and multinomial logistic regression were used to assess the association between the identified patterns and continuous and categorical BMI. All analyses were stratified by urbanicity.

RESULTS

Overall, 65% (weighted percentage) of households were located in an urban tract. Thirty-seven percent were categorized as Class 1 (households that shopped more proximally, used their own vehicle, and shopped at a farmers' market), 50% as Class 2 (households that shopped more distally, used their own vehicle, and shopped at a farmers' market), and 14% as Class 3 (households that shopped proximally but perceived longer travel time, used someone else's vehicle, and did not shop at a farmers' market). Among rural households, 54% were Class 1 and 46% were Class 2 (Class 3 was not identified). Socioeconomic status characteristics, proximity, and store food price concerns were associated with the identified patterns. However, no significant association was found between the identified patterns and BMI.

CONCLUSIONS

Food acquisition and shopping patterns were not associated with BMI in this national sample. However, future studies should also investigate the role of economic factors, such as food prices, in relation to shopping patterns and BMI.

What Are the Relationships between Psychosocial Community Characteristics and Dietary Behaviors in a Racially/Ethnically Diverse Urban Population in Los Angeles County?

To address existing gaps in public health practice, we used data from a 2014 internet panel survey of 954 Los Angeles County adults to investigate the relationships between psychosocial community characteristics (PCCs) and two key chronic disease-related dietary behaviors: fruit and vegetable (F+V) and soda consumption. Negative binomial regression models estimated the associations between 'neighborhood risks and resources' and 'sense of community' factors for each dietary outcome of interest. While high perceived neighborhood violence (p < 0.001) and perceived community-level collective efficacy (p < 0.001) were associated with higher F+V consumption, no PCCs were directly associated with soda consumption overall. However, moderation analyses by race/ethnicity showed a more varied pattern. High perceived violence was associated with lower F+V consumption among White and Asian/Native Hawaiian/Other Pacific Islander (ANHOPI) groups (p < 0.01). Inadequate park access and walking as the primary mode of transportation to the grocery store were associated with higher soda consumption among the ANHOPI group only (p < 0.05). Study findings suggest that current and future chronic disease prevention efforts should consider how social and psychological dynamics of communities influence dietary behaviors, especially among racially/ethnically diverse groups in urban settings. Intervention design and implementation planning could benefit from and be optimized based on these considerations.

Black-White disparities in women's physical health: The role of socioeconomic status and racism-related stressors

Black women have elevated rates of multiple physical illnesses and conditions when compared to White women - disparities that are only partially explained by socioeconomic status (SES). Consequently, scholars have called for renewed attention to the significance of racism-related stress in explaining Black-White disparities in women's physical health. Drawing on the biopsychosocial model of racism as a stressor and the intersectionality perspective, this study examines the extent to which SES and racism-related stressors - i.e., discrimination, criminalization, and adverse neighborhood conditions - account for disparities in self-rated physical health and chronic health conditions between Black and White women. Results indicate that Black women have lower SES and report greater exposure to racism-related stressors across all domains. Moreover, I find that SES and racism-related stressors jointly account for more than 90% of the Black-White disparity in women's self-rated physical health and almost 50% of the Black-White disparity in chronic health conditions. Theoretical and policy implications of these findings are discussed.

Associations of community, famliy and early individual factors with body mass index z-scores trajectories among Chinese children and adolescents

The prevalence of childhood overweight and obesity is increasing. This study aimed to examine trajectories of BMI z-scores among Chinese children and the potential determinants including early individual, family and community factors. Group-based trajectory modeling was employed to identify BMI z-scores trajectories of children aged 2-18 years using the five waves data (2010, 2012, 2014, 2016, and 2018) of the China Family Panel Studies (CFPS). Multivariate logistic regression was conducted to determine the association between early individual, family, community factors and BMI z-scores trajectories of children. We identified three trajectories for boys and girls, named Class 1 as "not-overweight", Class 2 as "persistent rapid descending but overweight during pre-school age", and Class 3 as "rapid rising up to school age and then become-overweight" class. Macrosomia (OR 1.772; 95% CI 1.188-2.644) and being a single child (OR 2.038; 95% CI 1.453-2.859) were more likely to belong in Class 3 among boys. Girls living in the advantaged communities (OR 1.539; 95% CI 1.052-2.252), rural-living (OR 1.558; 95% CI 1.133-2.142) and with none social integration (OR 1.496; 95% CI 1.07-2.091) were more likely to belong in Class 2. There are heterogeneous BMI z-scores trajectories of children aged 2-18, and pre-school age is a critical window that could predict the long-term growth patterns. BMI z-scores trends need to be monitored during pre-school age, focusing on those at higher risk of later overweight obesity status, and targeted interventions at the early individual, family, community levels are essential.

The association of dimensions of fruit and vegetable access in the retail food environment with consumption; a systematic review

The consumption of fruit and vegetables (F&V) is important for human health to protect against non-communicable disease and micronutrient deficiency. Increasing consumption of F&V may also benefit planetary health if these foods are substituted for foods with higher environmental footprints such as red meat or dairy. The retail food environment (RFE) is an influential junction between the food system and individual diets as it drives access to F&V through external (physical access) and personal (availability, affordability, acceptability) domains. We performed a systematic search of six literature databases (January 2021) for studies assessing access to F&V in the RFE and its association with F&V consumption in adults in high- and upper-middle income countries. 36 studies were identified and categorised by dimensions of food access – accessibility, affordability, acceptability, availability and accommodation. More than half of the studies (n = 20) were based in the USA. F&V accessibility was the most commonly reported dimension (n = 29); no study reported on accommodation. 6 studies were rated to be high quality. A positive association of increased availability of F&V options in the RFE with intake was identified in 9 of 15 studies. Associations in both acceptability and accessibility dimensions were inconsistent. No association was observed between F&V affordability and consumption although available data were limited. Many challenges exist to building a robust evidence base within food environment research including conceptual, definitional and methodological heterogeneity and measurement standardisation. Future food policies should consider multi-dimensional interventions to promote access to F&V in the RFE across all domains.

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First systematic review of dimensions of access in the retail food environment (RFE) and fruit and vegetable (F&V) intake.

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This review suggests potential importance of having access to available healthy options in the RFE for F&V intake.

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The absence of an association of F&V affordability with consumption is likely due to limited and mixed data availability.

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F&V accessibility and acceptability require development as dimensions of access for clearer links to be made.

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The retail food environment is complex but likely predictor of F&V consumption.

A life course perspective on BMI in rural America

Rural Americans are substantially more likely to be obese than their urban counterparts. A life course perspective offers insights into how growing up in rural areas may affect weight in young adulthood. Using data from the Panel Survey of Income Dynamics, this study follows the residential trajectories of 3157 respondents since birth. Living in a rural area during the critical period of early childhood (before age two) is predictive of higher BMI, while residence in later childhood and adolescence is not. Improving the health and wellbeing of rural mothers and infants could potentially help address the roots of rural obesity.

The impact of socioeconomic and environmental determinants on Mediterranean diet adherence: a municipal-level spatial analysis in Athens metropolitan area, Greece

The aim of this study was to identify the geographical variability, the socio-economic and the environmental determinants of adherence to the Mediterranean diet in a general population sample. Level of adherence to the Mediterranean diet was estimated by the ATTICA epidemiological study for 2,749 participants, while socio-economic, demographic, and environmental characteristics were provided by official national and international databases. Higher adherence to the Mediterranean diet was detected in areas with a greater proportion of females and older people, with lower unemployment rate and immigrant population, as well as, in areas covered at a greater extent by green and with higher frequency of supermarkets and street markets. The present findings provide evidence for policy makers to better understand how layers of influence intersect to shape individuals' eating habits, while they may also contribute in identifying areas of emerging interventions needed.

Genetic risk of obesity as a modifier of associations between neighbourhood environment and body mass index: an observational study of 335 046 UK Biobank participants

Background

There is growing recognition that recent global increases in obesity are the product of a complex interplay between genetic and environmental factors. However, in gene-environment studies of obesity, ‘environment’ usually refers to individual behavioural factors that influence energy balance, whereas more upstream environmental factors are overlooked. We examined gene-environment interactions between genetic risk of obesity and two neighbourhood characteristics likely to be associated with obesity (proximity to takeaway/fast-food outlets and availability of physical activity facilities).

Methods

We used data from 335 046 adults aged 40–70 in the UK Biobank cohort to conduct a population-based cross-sectional study of interactions between neighbourhood characteristics and genetic risk of obesity, in relation to body mass index (BMI). Proximity to a fast-food outlet was defined as distance from home address to nearest takeaway/fast-food outlet, and availability of physical activity facilities as the number of formal physical activity facilities within 1 km of home address. Genetic risk of obesity was operationalised by weighted Genetic Risk Scores of 91 or 69 single nucleotide polymorphisms (SNP), and by six individual SNPs considered separately. Multivariable, mixed-effects models with product terms for the gene-environment interactions were estimated.

Results

After accounting for likely confounding, the association between proximity to takeaway/fast-food outlets and BMI was stronger among those at increased genetic risk of obesity, with evidence of an interaction with polygenic risk scores (p=0.018 and p=0.028 for 69-SNP and 91-SNP scores, respectively) and in particular with a SNP linked to MC4R (p=0.009), a gene known to regulate food intake. We found very little evidence of gene-environment interaction for the availability of physical activity facilities.

Conclusions

Individuals at an increased genetic risk of obesity may be more sensitive to exposure to the local fast-food environment. Ensuring that neighbourhood residential environments are designed to promote a healthy weight may be particularly important for those with greater genetic susceptibility to obesity.

Association of Long-Term Trajectories of Neighborhood Socioeconomic Status With Weight Change in Older Adults

IMPORTANCE

Studying long-term changes in neighborhood socioeconomic status (SES) may help to better understand the associations between neighborhood exposure and weight outcomes and provide evidence supporting neighborhood interventions. Little previous research has been done to examine associations between neighborhood SES and weight loss, a risk factor associated with poor health outcomes in the older population.

OBJECTIVE

To determine whether improvements in neighborhood SES are associated with reduced likelihoods of excessive weight gain and excessive weight loss and whether declines are associated with increased likelihoods of these weight outcomes.

DESIGN, STUDY, AND PARTICIPANTS

This cohort study was conducted using data from the National Institutes of Health-AARP (formerly known as the American Association of Retired Persons) Diet and Health study (1995-2006). The analysis included a cohort of 126 179 adults (aged 50-71 years) whose neighborhoods at baseline (1995-1996) were the same as at follow-up (2004-2006). All analyses were performed from December 2018 through December 2020.

EXPOSURES

Living in a neighborhood that experienced 1 of 8 neighborhood SES trajectories defined based on a national neighborhood SES index created using data from the US Census and American Community Survey. The 8 trajectory groups, in which high, or H, indicated rankings at or above the sample median of a specific year and low, or L, indicated rankings below the median, were HHH (ie, high in 1990 to high in 2000 to high in 2010), or stable high; HLL, or early decline; HHL, or late decline; HLH, or transient decline; LLL, or stable low; LHH, or early improvement; LLH, or late improvement; and LHL, or transient improvement.

MAIN OUTCOMES AND MEASURES

Excessive weight gain and loss were defined as gaining or losing 10% or more of baseline weight.

RESULTS

Among 126 179 adults, 76 225 (60.4%) were men and the mean (SD) age was 62.1 (5.3) years. Improvements in neighborhood SES were associated with lower likelihoods of excessive weight gain and weight loss over follow-up, while declines in neighborhood SES were associated with higher likelihoods of excessive weight gain and weight loss. Compared with the stable low group, the risk was significantly reduced for excessive weight gain in the early improvement group (odds ratio [OR], 0.87; 95% CI, 0.79-0.95) and for excessive weight loss in the late improvement group (OR, 0.89; 95% CI, 0.80-1.00). Compared with the stable high group, the risk of excessive weight gain was significantly increased for the early decline group (OR, 1.19; 95% CI, 1.08-1.31) and late decline group (OR, 1.13; 95% CI, 1.04-1.24) and for excessive weight loss in the early decline group (OR, 1.15; 95% CI, 1.02-1.28). The increases in likelihood were greater when the improvement or decline in neighborhood SES occurred early in the study period (ie, 1990-2000) and was substantiated throughout the follow-up (ie, the early decline and early improvement groups). Overall, we found a linear association between changes in neighborhood SES and weight outcomes, in which every 5 percentile decline in neighborhood SES was associated with a 1.2% to 2.4% increase in the risk of excessive weight gain or loss (excessive weight gain: OR, 1.01; 95% CI, 1.00-1.02 for women; OR, 1.02; 95% CI, 1.01-1.03 for men; excessive weight loss: OR, 1.02; 95% CI, 1.01-1.03 for women; OR, 1.02; 95% CI, 1.01-1.03 for men; P for- trend < .0001).

CONCLUSIONS AND RELEVANCE

These findings suggest that changing neighborhood environment was associated with changes in weight status in older adults.