Weight of communities: A multilevel analysis of body mass index in 32,814 neighborhoods in 57 low- to middle-income countries (LMICs)

Neighbourhoods' social, built, and natural environment characteristics and body mass index in Latin American cities

BACKGROUND

Features of neighbourhoods affect body mass index (BMI) but this has been poorly acknowledged within the highly heterogeneous and unequal contexts of Latin American cities. We evaluated associations between social, built, and natural environment characteristics of neighbourhoods with BMI, and investigated whether these associations were modified by individual socioeconomic position (SEP).

METHODS

We linked individual data (n = 43 968) from national health surveys to data on neighbourhoods (n = 3428) and cities (n = 165) in Argentina, Chile, Colombia, and Mexico. Linear mixed models were used to estimate associations between neighbourhood education, intersection density, and greenness with BMI, adjusting for individual- and city-level characteristics.

RESULTS

Associations between neighbourhood education and BMI varied by country, in both magnitude and direction. In Argentina and Chile, higher neighbourhood education was associated with lower BMI. This negative association was also observed among women in Colombia and Mexico, although it was weaker. Among men in Colombia and Mexico, however, the association was positive. Associations of neighbourhood intersection density and greenness with BMI were less robust. In general, we did not find strong evidence of effect modification by individual SEP.

CONCLUSION

Neighbourhood education is associated with BMI beyond individual and city characteristics, although the associations are heterogenous across countries and by gender. Associations with built and natural features were less clear. Our results highlight the relevance of context-specific analysis for planning interventions that are aimed to reduce BMI and its unequal distribution in Latin American cities.

Influence of the urban context on the relationship between neighbourhood deprivation and obesity

BACKGROUND

In middle- and high-income countries, obesity is positively associated with neighbourhood deprivation. However, the moderating effect of the broader urban residential context on this relationship remains poorly understood.

METHODS

In this study, we have examined the nonlinear and geographically varying relationship between neighbourhood deprivation and the likelihood of being a person with overweight among participants of the French NutriNet-Santé adult cohort study (n = 68,698), adjusted for age, gender and educational level. Ten urban residential contexts (e.g., suburbs, peri-urban or rural areas) were defined. We used a multilevel generalised additive modelling framework for analyses.

RESULTS

We found that the relationship between neighbourhood deprivation and overweight differed according to urban context, in terms of both linearity and intensity. Overall, the deprivation-overweight relationship was strongly positive (with a higher prevalence of overweight in deprived neighbourhoods) in suburban areas of Paris and of other large French cities, while weak or null in small towns and rural areas, and intermediate in inner cities. In addition, we observed in suburbs of Paris and in peri-urban belts of large cities that beyond a certain level of neighbourhood deprivation, the relationship with overweight plateaued.

DISCUSSION

In a French population from a high-income country, suburbs, as well as moderately deprived neighbourhoods of peri-urban areas of large cities, are potential targets for public health and urban planning policies aiming at preventing obesity. Our results emphasize the value of local analyses to better capture the complexity and contextual variations of socioeconomic determinants of non-communicable diseases such as obesity.

Variation in Anthropometric Status and Growth Failure in Low- and Middle-Income Countries

BACKGROUND

Addressing anthropometric failure in low- and middle-income countries can have 2 targets of inference: addressing differences between individuals within populations (W_pop) or differences between populations (B_pop). We present a multilevel framework to apply both targets of inference simultaneously and quantify the extent to which variation in anthropometric status and growth failure is reflective of undernourished children or undernourished populations.

METHODS

Cross-sectional data originated from the Demographic and Health Surveys program, covering children under age 5 from 57 countries surveyed between 2001 and 2015.

RESULTS

A majority of variation in child anthropometric status and growth failure was attributable to W_pop-associated differences, accounting for 89%, 83%, and 85% of the variability in z scores for height for age, weight for age, and weight for height. B_pop-associated differences (communities, regions, and countries combined) were associated with 11%, 17%, and 15% of the variation in height-for-age z score, weight-for-age z score, and weight-for-height z score. Prevalence of anthropometric failure was closely correlated with mean levels of height and weight. Approximately 1% of W_pop variability, compared with 30% to 50% of the B_pop variability, was explained by mean values of maternal correlates of anthropometric status and failure. Although there is greater explanatory power B_pop, this varied because of modifiability of what constitutes population.

CONCLUSIONS

Our results suggest that universal strategies to prevent future anthropometric failure in populations combined with targeted strategies to address both the impending and existing burden among children are needed.

Neighborhood Socioeconomic Deprivation and Weight Change in a Large U.S. Cohort

INTRODUCTION

Both excessive weight gain and weight loss are important risk factors in the older population. Neighborhood environment may play an important role in weight change, but neighborhood effects on weight gain and weight loss have not been studied separately. This study examined the associations between neighborhood socioeconomic deprivation and excessive weight gain and weight loss.

METHODS

This analysis included 153,690 men and 105,179 women (aged 51-70 years). Baseline addresses were geocoded into geographic coordinates and linked to the 2000 U.S. Census at the Census tract level. Census variables were used to generate a socioeconomic deprivation index by principle component analysis. Excessive weight gain and loss were defined as gaining or losing >10% of baseline (1995-1996) body weight at follow-up (2004-2006). The analysis was performed in 2015.

RESULTS

More severe neighborhood socioeconomic deprivation was associated with higher risks of both excessive weight gain and weight loss after adjusting for individual indicators of SES, disease conditions, and lifestyle factors (Quintile 5 vs Quintile 1: weight gain, OR=1.36, 95% CI=1.28, 1.45 for men and OR=1.20, 95% CI=1.13, 1.27 for women; weight loss, OR=1.09, 95%% CI=1.02, 1.17 for men and OR=1.23, 95% CI=1.14, 1.32 for women). The findings were fairly consistent across subpopulations with different demographics and lifestyle factors.

CONCLUSIONS

Neighborhood socioeconomic deprivation predicts higher risk of excessive weight gain and weight loss.

Do neighborhoods matter differently for movers and non-movers? Analysis of weight gain in the longitudinal dallas heart study

The few available population-based longitudinal studies examining the link between change in neighborhood condition and weight change to date have only examined neighborhood changes generated by residential mobility. Applying a difference-in-difference analytic framework to data from the Dallas Heart Study (DHS), a multi-ethnic, population-based cohort in Dallas County, TX, we evaluated the relationship between changes in neighborhood condition and weight change for both movers and non-movers over an approximate seven-year follow-up period. We employed a novel measure of neighborhood condition based on property appraisal data to capture temporally consistent measures of change in neighborhood condition regardless of residential mobility. We observed an inverse relationship between weight change and change in neighborhood condition which was more pronounced for non-movers (1.9 fewer kilograms gained per 1-standard deviation improvement in neighborhood condition) than for movers (1.5 fewer kilograms gained per 1-standard deviation improvement in neighborhood condition).

Health at the borders: Bayesian multilevel analysis of women's malnutrition determinants in Ethiopia

BACKGROUND

Women's malnutrition, particularly undernutrition, remains an important public health challenge in Ethiopia. Although various studies examined the levels and determinants of women's nutritional status, the influence of living close to an international border on women's nutrition has not been investigated. Yet, Ethiopian borders are regularly affected by conflict and refugee flows, which might ultimately impact health.

OBJECTIVE

To investigate the impact of living close to borders in the nutritional status of women in Ethiopia, while considering other important covariates.

DESIGN

Our analysis was based on the body mass index (BMI) of 6,334 adult women aged 20-49 years, obtained from the 2011 Ethiopian Demographic and Health Survey (EDHS). A Bayesian multilevel multinomial logistic regression analysis was used to capture the clustered structure of the data and the possible correlation that may exist within and between clusters.

RESULTS

After controlling for potential confounders, women living close to borders (i.e. ≤100 km) in Ethiopia were 59% more likely to be underweight (posterior odds ratio [OR]=1.59; 95% credible interval [CrI]: 1.32-1.90) than their counterparts living far from the borders. This result was robust to different choices of border delineation (i.e. ≤50, ≤75, ≤125, and ≤150 km). Women from poor families, those who have no access to improved toilets, reside in lowland areas, and are Muslim, were independently associated with underweight. In contrast, more wealth, higher education, older age, access to improved toilets, being married, and living in urban or lowlands were independently associated with overweight.

CONCLUSIONS

The problem of undernutrition among women in Ethiopia is most worrisome in the border areas. Targeted interventions to improve nutritional status in these areas, such as improved access to sanitation, economic and livelihood support, are recommended.

School effects on non-verbal intelligence and nutritional status in rural Zambia

This study uses hierarchical linear modeling (HLM) to examine the school factors (i.e., related to school organization and teacher and student body) associated with non-verbal intelligence (NI) and nutritional status (i.e., body mass index; BMI) of 4204 3^rd to 7^th graders in rural areas of Southern Province, Zambia. Results showed that 23.5% and 7.7% of the NI and BMI variance, respectively, were conditioned by differences between schools. The set of 14 school factors accounted for 58.8% and 75.9% of the between-school differences in NI and BMI, respectively. Grade-specific HLM yielded higher between-school variation of NI (41%) and BMI (14.6%) for students in grade 3 compared to grades 4 to 7. School factors showed a differential pattern of associations with NI and BMI across grades. The distance to a health post and teacher's teaching experience were the strongest predictors of NI (particularly in grades 4, 6 and 7); the presence of a preschool was linked to lower BMI in grades 4 to 6. Implications for improving access and quality of education in rural Zambia are discussed.

Change in Neighborhood Socioeconomic Status and Weight Gain: Dallas Heart Study

INTRODUCTION

Despite a proposed connection between neighborhood environment and obesity, few longitudinal studies have examined the relationship between change in neighborhood socioeconomic deprivation, as defined by moving between neighborhoods, and change in body weight. The purpose of this study is to examine the longitudinal relationship between moving to more socioeconomically deprived neighborhoods and weight gain as a cardiovascular risk factor.

METHODS

Weight (kilograms) was measured in the Dallas Heart Study (DHS), a multiethnic cohort aged 18-65 years, at baseline (2000-2002) and 7-year follow-up (2007-2009, N=1,835). Data were analyzed in 2013-2014. Geocoded addresses were linked to Dallas County, TX, census block groups. A block group-level neighborhood deprivation index (NDI) was created. Multilevel difference-in-difference models with random effects and a Heckman correction factor (HCF) determined weight change relative to NDI change.

RESULTS

Forty-nine percent of the DHS population moved (263 to higher NDI, 586 to lower NDI, 47 within same NDI), with blacks more likely to move than whites or Hispanics (p<0.01), but similar baseline BMI and waist circumference were observed in movers versus non-movers (p>0.05). Adjusting for HCF, sex, race, and time-varying covariates, those who moved to areas of higher NDI gained more weight compared to those remaining in the same or moving to a lower NDI (0.64 kg per 1-unit NDI increase, 95% CI=0.09, 1.19). Impact of NDI change on weight gain increased with time (p=0.03).

CONCLUSIONS

Moving to more-socioeconomically deprived neighborhoods was associated with weight gain among DHS participants.

Neighborhood-level socioeconomic deprivation predicts weight gain in a multi-ethnic population: longitudinal data from the Dallas Heart Study

OBJECTIVE

The aim of this study is to examine a relationship between neighborhood-level socioeconomic deprivation and weight change in a multi-ethnic cohort from Dallas County, Texas and whether behavioral/psychosocial factors attenuate the relationship.

METHODS

Non-movers (those in the same neighborhood throughout the study period) aged 18-65 (N=939) in Dallas Heart Study (DHS) underwent weight measurements between 2000 and 2009 (median 7-year follow-up). Geocoded home addresses defined block groups; a neighborhood deprivation index (NDI) was created (higher NDI=greater deprivation). Multi-level modeling determined weight change relative to NDI. Model fit improvement was examined with adding physical activity and neighborhood environment perceptions (higher score=more unfavorable perceptions) as covariates. A significant interaction between residence length and NDI was found (p-interaction=0.04); results were stratified by median residence length (11 years).

RESULTS

Adjusting for age, sex, race/ethnicity, smoking, and education/income, those who lived in neighborhood >11 years gained 1.0 kg per one-unit increment of NDI (p=0.03), or 6 kg for those in highest NDI tertile compared with those in the lowest tertile. Physical activity improved model fit; NDI remained associated with weight gain after adjustment for physical activity and neighborhood environment perceptions. There was no significant relationship between NDI and weight change for those in their neighborhood ≤11 years.

CONCLUSIONS

Living in more socioeconomically deprived neighborhoods over a longer time period was associated with weight gain in DHS.

Economic development, urbanization, technological change and overweight: what do we learn from 244 Demographic and Health Surveys?

Obesity and overweight are spreading fast in developing countries, and have reached world record levels in some of them. Capturing the size, patterns and trends of the problem has, however, been severely hampered by the lack of comparable data in low and middle income countries. We seek to begin to fill this gap by testing several hypotheses on the determinants/correlates of overweight among women, related to the influence of economic and technological development. We undertake econometric analysis of nationally representative data on about 878,000 women aged 15-49 from 244 Demographic and Health Surveys (DHS) for 56 countries over the years 1991-2009. Our findings support most previously expressed hypotheses of what might explain obesity patterns in developing countries, but they also reject some prior notions and add considerable nuance to the emerging pattern.

Socioeconomic disparities in maternity care among Indian adolescents, 1990-2006

BACKGROUND

India, with a population of more than 1.21 billion, has the highest maternal mortality in the world (estimated to be 56000 in 2010); and adolescent (aged 15-19) mortality shares 9% of total maternal deaths. Addressing the maternity care needs of adolescents may have considerable ramifications for achieving the Millennium Development Goal (MDG)-5. This paper assesses the socioeconomic differentials in accessing full antenatal care and professional attendance at delivery by adolescent mothers (aged 15-19) in India during 1990-2006.

METHODS AND FINDINGS

Data from three rounds of the National Family Health Survey of India conducted during 1992-93, 1998-99, and 2005-06 were analyzed. The Cochran-Armitage and Chi-squared test for linear and non-linear time trends were applied, respectively, to understand the trend in the proportion of adolescent mothers utilizing select maternity care services during 1990-2006. Using pooled multivariate logistic regression models, the probability of select maternal healthcare utilization among women by key socioeconomic characteristics was appraised. After adjusting for potential socio-demographic and economic characteristics, the likelihood of adolescents accessing full antenatal care increased by only 4% from 1990 to 2006. However, the probability of adolescent women availing themselves of professional attendance at delivery increased by 79% during the same period. The study also highlights the desolate disparities in maternity care services among adolescents across the most and the least favoured groups.

CONCLUSION

Maternal care interventions in India need focused programs for rural, uneducated, poor adolescent women so that they can avail themselves of measures to delay child bearing, and for better antenatal consultation and delivery care in case of pregnancy. This study strongly advocates the promotion of a comprehensive 'adolescent scheme' along the lines of 'Continuum of Maternal, Newborn and Child health Care' to address the unmet need of reproductive and maternal healthcare services among adolescent women in India.

Early neonatal mortality in India, 1990-2006

The increased reach of health programs in India during the past few decades has contributed to a decline in postnatal mortality including infant and child mortality; however, reduction in neonatal mortality remained negligible. About seven out of ten neonatal deaths take place within a week after birth. The progress in reduction as well as dimension along which early neonatal mortality is patterned in India remains unclear. We examine the trend in early neonatal mortality and its possible demographic and socioeconomic predictors using nationally representative data. Data from the three cross-sectional rounds of the National Family Health Survey of India from 1992 to 1993, 1998 to 1999 and 2005 to 2006 were analyzed. Early neonatal mortality rate was estimated for selected demographic and socioeconomic population groups and for major states in India using information on births and deaths during the 3 years preceding the respective surveys. Using the multivariate logistic regression model, we assessed proximate determinants of early neonatal deaths during 1990-2006. Sex of the child, child's birth size, birth order and interval, type of child's birth, mother's age at child's birth, mother's educational status, religion, household economic status and region of residence emerged as significant predictors of early neonatal deaths. The adjusted multivariate analysis indicates that majority of the socio-demographic predictors reveal a negligible decline in the probability of early neonatal deaths during 1990-2006. Moreover, based on comprehensive reviews of scientific literature on newborn's survival we document some of the recommended ways to prevent early neonatal mortality in India.

Demographic and health surveys: a profile

Demographic and Health Surveys (DHS) are comparable nationally representative household surveys that have been conducted in more than 85 countries worldwide since 1984. The DHS were initially designed to expand on demographic, fertility and family planning data collected in the World Fertility Surveys and Contraceptive Prevalence Surveys, and continue to provide an important resource for the monitoring of vital statistics and population health indicators in low- and middle-income countries. The DHS collect a wide range of objective and self-reported data with a strong focus on indicators of fertility, reproductive health, maternal and child health, mortality, nutrition and self-reported health behaviours among adults. Key advantages of the DHS include high response rates, national coverage, high quality interviewer training, standardized data collection procedures across countries and consistent content over time, allowing comparability across populations cross-sectionally and over time. Data from DHS facilitate epidemiological research focused on monitoring of prevalence, trends and inequalities. A variety of robust observational data analysis methods have been used, including cross-sectional designs, repeated cross-sectional designs, spatial and multilevel analyses, intra-household designs and cross-comparative analyses. In this profile, we present an overview of the DHS along with an introduction to the potential scope for these data in contributing to the field of micro- and macro-epidemiology. DHS datasets are available for researchers through MEASURE DHS at www.measuredhs.com.