S.V. Subramanian

Education and risk for acute myocardial infarction in 52 high, middle and low income countries. INTERHEART case-control study

Objective: To determine the effect of education and other measures of socioeconomic status (SES) on risk of acute myocardial infarction (AMI) in patients and controls from countries with diverse economic circumstances (high, middle, and low income countries). Design: Case-control study. Setting: 52 countries from all inhabited regions of the world. Participants: 12242 cases and 14622 controls. Main outcome measures: First non-fatal AMI. Results: SES was measured using education, family income, possessions in the household and occupation. Low levels of education (⩽8 years) were more common in cases compared to controls (45.0% and 38.1%; p<0.0001). The odds ratio (OR) for low education adjusted for age, sex and region was 1.56 (95% confidence interval 1.47 to 1.66). After further adjustment for psychosocial, lifestyle, other factors and mutually for other socioeconomic factors, the OR associated with education ⩽8 years was 1.31 (1.20 to 1.44) (p<0.0001). Modifiable lifestyle factors (smoking, exercise, consumption of vegetables and fruits, alcohol and abdominal obesity) explained about half of the socioeconomic gradient. Family income, numbers of possessions and non-professional occupation were only weakly or not at all independently related to AMI. In high-income countries (World Bank Classification), the risk factor adjusted OR associated with low education was 1.61 (1.33 to 1.94), whereas it was substantially lower in low-income and middle-income countries: 1.25 (1.14 to 1.37) (p for interaction 0.045). Conclusion: Of the SES measures we studied, low education was the marker most consistently associated with increased risk for AMI globally, most markedly in high-income countries.

School Level Contextual Factors Are Associated With the Weight Status of Adolescent Males and Females

Objective: To determine whether school context influences the BMI of adolescent males and females.

Social networks and health: a systematic review of sociocentric network studies in low- and middle-income countries.

In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex webs of dynamic social relationships. Harnessing such information may be especially important in contexts where resources are limited and people depend on their direct and indirect connections for support.

Using Cross-Classified Multilevel Models to Disentangle School and Neighborhood Effects: An Example Focusing on Smoking Behaviors among Adolescents in the United States

BACKGROUND Despite much interest in understanding the influence of contexts on health, most research has focused on one context at a time, ignoring the reality that individuals have simultaneous memberships in multiple settings. METHOD Using the example of smoking behavior among adolescents in the National Longitudinal Study of Adolescent Health, we applied cross-classified multilevel modeling (CCMM) to examine fixed and random effects for schools and neighborhoods. We compared the CCMM results with those obtained from a traditional multilevel model (MLM) focused on either the school and neighborhood separately. RESULTS In the MLMs, 5.2% of the variation in smoking was due to differences between neighborhoods (when schools were ignored) and 6.3% of the variation in smoking was due to differences between schools (when neighborhoods were ignored). However in the CCMM examining neighborhood and school variation simultaneously, the neighborhood-level variation was reduced to 0.4%. CONCLUSION Results suggest that using MLM, instead of CCMM, could lead to overestimating the importance of certain contexts and could ultimately lead to targeting interventions or policies to the wrong settings.

Disentangling the relative influence of schools and neighborhoods on adolescents’ risk for depressive symptoms

OBJECTIVES Although schools and neighborhoods influence health, little is known about their relative importance, or the influence of one context after the influence of the other has been taken into account. We simultaneously examined the influence of each setting on depression among adolescents. METHODS Analyzing data from wave 1 (1994-1995) of the National Longitudinal Study of Adolescent Health, we used cross-classified multilevel modeling to examine between-level variation and individual-, school-, and neighborhood-level predictors of adolescent depressive symptoms. Also, we compared the results of our cross-classified multilevel models (CCMMs) with those of a multilevel model wherein either school or neighborhood was excluded. RESULTS In CCMMs, the school-level random effect was significant and more than 3 times the neighborhood-level random effect, even after individual-level characteristics had been taken into account. Individual-level indicators (e.g., race/ethnicity, socioeconomic status) were associated with depressive symptoms, but there was no association with either school- or neighborhood-level fixed effects. The between-level variance in depressive symptoms was driven largely by schools as opposed to neighborhoods. CONCLUSIONS Schools appear to be more salient than neighborhoods in explaining variation in depressive symptoms. Future work incorporating cross-classified multilevel modeling is needed to understand the relative effects of schools and neighborhoods.

Time Trends in Racial and Ethnic Disparities in Asthma Prevalence in the United States From the Behavioral Risk Factor Surveillance System (BRFSS) Study (1999-2011).

OBJECTIVES We examined whether racial/ethnic disparities in the United States increased over time. METHODS We analyzed data from 3 868 956 adults across the United States from the Behavioral Risk Factor Surveillance System from 1999 to 2011. We used random intercepts models (individuals nested in states) to examine racial/ethnic disparities and time trends in asthma lifetime and its current prevalence, adjusted for covariates. We also investigated the heterogeneity in asthma prevalence by ethnicity of the major zone of residence. RESULTS Lifetime and current asthma prevalence were higher among non-Hispanic Black populations, with time trends highlighting increasing differences over time (b = 0.0078; 95% confidence interval [CI] = 0.0043, 0.0106). Lower odds ratios (ORs) of asthma were noted for Hispanic populations (OR = 0.74; 95% CI = 0.73, 0.76). Hispanics in states with more Puerto Rican residents reported greater risks of asthma (OR = 1.55; 95% CI = 1.24, 1.93) compared with Hispanics in states with larger numbers of Mexican or other ethnicities. CONCLUSIONS Disparities in asthma prevalence by racial/ethnic groups increased in the last decade, with non-Hispanic Blacks and Puerto Rican Hispanics at greater risk. Interventions targeting asthma treatments need to recognize racial, ethnic, and geographic disparities.

Association between maternal health literacy and child vaccination in India: a cross-sectional study

Background Education of mothers may improve child health. We investigated whether maternal health literacy, a rapidly modifiable factor related to mothers education, was associated with childrens receipt of vaccines in two underserved Indian communities. Methods Cross-sectional surveys in an urban and a rural site. We assessed health literacy using Indian child health promotion materials. The outcome was receipt of three doses of diphtheria-tetanus-pertussis (DTP3) vaccine. We used multivariate logistic regression to investigate the relationship between maternal health literacy and vaccination status independently in each site. For both sites, adjusted models considered maternal age, maternal and paternal education, child sex, birth order, household religion and wealth quintile. Rural analyses used multilevel models adjusted for service delivery characteristics. Urban analyses represented cluster characteristics through fixed effects. Results The rural analysis included 1170 women from 60 villages. The urban analysis included 670 women from nine slum clusters. In each site, crude and adjusted models revealed a positive association between maternal health literacy and DTP3. In the rural site, the adjusted OR was 1.57 (95% CI 1.11 to 2.21, p=0.010) for those with medium health literacy, and OR=1.30 (95% CI 0.89 to 1.91, p=0.172) for those with high health literacy. In the urban site, the adjusted OR was 1.10 (95% CI 0.65 to 1.88, p=0.705) for those with medium health literacy, and OR=2.06 (95% CI 1.06 to 3.99, p=0.032) for those with high health literacy. Conclusions In these study settings, maternal health literacy is independently associated with child vaccination. Initiatives targeting health literacy could improve vaccination coverage.

Is change in availability of sports facilities associated with change in physical activity? A prospective cohort study.

OBJECTIVE We examined whether change in distance to or number of sports facilities is related to change in metabolic equivalent task (MET) hours/week. METHOD 25,834 Finnish Public Sector study cohort participants reported their weekly physical activity in 2000 and 2008. Distances from each participants home to the nearest facility and number of facilities within 500m from home were calculated from geographic coordinates. We assessed changes in weekly MET hours of physical activity between the baseline and the follow-up in relation to change in distance to the nearest facility (remained close, decreased, remained distant, increased) and number of facilities <500m from home (remained high, increased, remained low, decreased). RESULTS The average decrease in MET hours was greater for those whose distance to a sports facility increased (-1.4 (95% CI -3.8--0.96)) (vs. remained close). The same was observed for those for whom the number of facilities near home decreased (-2.35 (95% CI -4.84-0.14)) (vs. remained high). Increase in availability was not related to increase in MET hours. CONCLUSIONS An increase in distance to and decrease in number of sports facilities were associated with a decrease in physical activity suggesting that changes in availability of facilities may affect physical activity levels.

Measuring psychosocial environments using individual responses: an application of multilevel factor analysis to examining students in schools.

Interest in understanding how psychosocial environments shape youth outcomes has grown considerably. School environments are of particular interest to prevention scientists as many prevention interventions are school-based. Therefore, effective conceptualization and operationalization of the school environment is critical. This paper presents an illustration of an emerging analytic method called multilevel factor analysis (MLFA) that provides an alternative strategy to conceptualize, measure, and model environments. MLFA decomposes the total sample variance-covariance matrix for variables measured at the individual level into within-cluster (e.g., student level) and between-cluster (e.g., school level) matrices and simultaneously models potentially distinct latent factor structures at each level. Using data from 79,362 students from 126 schools in the National Longitudinal Study of Adolescent to Adult Health (formerly known as the National Longitudinal Study of Adolescent Health), we use MLFA to show how 20 items capturing student self-reported behaviors and emotions provide information about both students (within level) and their school environment (between level). We identified four latent factors at the within level: (1) school adjustment, (2) externalizing problems, (3) internalizing problems, and (4) self-esteem. Three factors were identified at the between level: (1) collective school adjustment, (2) psychosocial environment, and (3) collective self-esteem. The finding of different and substantively distinct latent factor structures at each level emphasizes the need for prevention theory and practice to separately consider and measure constructs at each level of analysis. The MLFA method can be applied to other nested relationships, such as youth in neighborhoods, and extended to a multilevel structural equation model to better understand associations between environments and individual outcomes and therefore how to best implement preventive interventions.

Short-term and long-term associations between household wealth and physical growth: a cross-comparative analysis of children from four low- and middle-income countries

Background Stunting, a form of anthropometric failure, disproportionately affects children in developing countries with a higher burden on children living in poverty. How early life deprivation affects physical growth over various life stages is less well-known. Objective We investigate the short- and long-run associations between household wealth in early life with physical growth in childhood in four low- and middle-income countries to understand the persistent implications of early life conditions of poverty and resource constraints on physical growth. Design Longitudinal study of eight cohorts of children in four countries – Ethiopia, India, Peru, and Vietnam (n=10,016) – ages 6 months to 15 years, using data from the Young Lives project, 2002–2009. Physical growth outcomes are standardized height-for-age z-scores (HAZ) and stunting. The key exposure is household wealth measured at baseline using a wealth index, an asset-based indicator. Covariates include childs age and sex, caregivers educational status, household size, and place of residence. Results Baseline wealth index is significantly associated with higher physical growth rates as suggested by higher HAZ and lower odds of stunting. We found these associations in all four countries, for younger and older cohorts and for children who experienced changes in living standards. For the older cohort, despite the timing of the first survey at age 7–8 years, which is beyond the critical period of 1,000 days, there are lasting influences of early poverty, even for those who experienced changes in wealth. Conclusions Household wealth in early life matters for physical growth with conditions of poverty and deprivation influencing growth faltering even beyond the 1,000 days window. The influences of early childhood poverty, so prevalent among children in low- and middle-income countries, must be addressed by policies and programs targeting early life but also focusing on older children experiencing growth faltering.Background Stunting, a form of anthropometric failure, disproportionately affects children in developing countries with a higher burden on children living in poverty. How early life deprivation affects physical growth over various life stages is less well-known. Objective We investigate the short- and long-run associations between household wealth in early life with physical growth in childhood in four low- and middle-income countries to understand the persistent implications of early life conditions of poverty and resource constraints on physical growth. Design Longitudinal study of eight cohorts of children in four countries - Ethiopia, India, Peru, and Vietnam (n=10,016) - ages 6 months to 15 years, using data from the Young Lives project, 2002-2009. Physical growth outcomes are standardized height-for-age z-scores (HAZ) and stunting. The key exposure is household wealth measured at baseline using a wealth index, an asset-based indicator. Covariates include childs age and sex, caregivers educational status, household size, and place of residence. Results Baseline wealth index is significantly associated with higher physical growth rates as suggested by higher HAZ and lower odds of stunting. We found these associations in all four countries, for younger and older cohorts and for children who experienced changes in living standards. For the older cohort, despite the timing of the first survey at age 7-8 years, which is beyond the critical period of 1,000 days, there are lasting influences of early poverty, even for those who experienced changes in wealth. Conclusions Household wealth in early life matters for physical growth with conditions of poverty and deprivation influencing growth faltering even beyond the 1,000 days window. The influences of early childhood poverty, so prevalent among children in low- and middle-income countries, must be addressed by policies and programs targeting early life but also focusing on older children experiencing growth faltering.