Neighborhood and weight-related health behaviors in the Look AHEAD (Action for Health in Diabetes) Study

<p>Abstract</p> <p>Background</p> <p>Previous studies have shown that neighborhood factors are associated with obesity, but few studies have evaluated the association with weight control behaviors. This study aims to conduct a multi-level analysis to examine the relationship between neighborhood SES and weight-related health behaviors.</p> <p>Methods</p> <p>In this ancillary study to Look AHEAD (Action for Health in Diabetes) a trial of long-term weight loss among individuals with type 2 diabetes, individual-level data on 1219 participants from 4 clinic sites at baseline were linked to neighborhood-level data at the tract level from the 2000 US Census and other databases. Neighborhood variables included SES (% living below the federal poverty level) and the availability of food stores, convenience stores, and restaurants. Dependent variables included BMI, eating patterns, weight control behaviors and resource use related to food and physical activity. Multi-level models were used to account for individual-level SES and potential confounders.</p> <p>Results</p> <p>The availability of restaurants was related to several eating and weight control behaviors. Compared to their counterparts in neighborhoods with fewer restaurants, participants in neighborhoods with more restaurants were more likely to eat breakfast (prevalence Ratio [PR] 1.29 95% CI: 1.01-1.62) and lunch (PR = 1.19, 1.04-1.36) at non-fast food restaurants. They were less likely to be attempting weight loss (OR = 0.93, 0.89-0.97) but more likely to engage in weight control behaviors for food and physical activity, respectively, than those who lived in neighborhoods with fewer restaurants. In contrast, neighborhood SES had little association with weight control behaviors.</p> <p>Conclusion</p> <p>In this selected group of weight loss trial participants, restaurant availability was associated with some weight control practices, but neighborhood SES was not. Future studies should give attention to other populations and to evaluating various aspects of the physical and social environment with weight control practices.</p

Geographic Inequalities in All-Cause Mortality in Japan: Compositional or Contextual?

Background: A recent study from Japan suggested that geographic inequalities in all-cause premature adult mortality have increased since 1995 in both sexes even after adjusting for individual age and occupation in 47 prefectures. Such variations can arise from compositional effects as well as contextual effects. In this study, we sought to further examine the emerging geographic inequalities in all-cause mortality, by exploring the relative contribution of composition and context in each prefecture. Methods We used the 2005 vital statistics and census data among those aged 25 or older. The total number of decedents was 524,785 men and 455,863 women. We estimated gender-specific two-level logistic regression to model mortality risk as a function of age, occupation, and residence in 47 prefectures. Prefecture-level variance was used as an estimate of geographic inequalities in mortality, and prefectures were ranked by odds ratios (ORs), with the reference being the grand mean of all prefectures (value = 1). Results: Overall, the degree of geographic inequalities was more pronounced when we did not account for the composition (i.e., age and occupation) in each prefecture. Even after adjusting for the composition, however, substantial differences remained in mortality risk across prefectures with ORs ranging from 0.870 (Okinawa) to 1.190 (Aomori) for men and from 0.864 (Shimane) to 1.132 (Aichi) for women. In some prefectures (e.g., Aomori), adjustment for composition showed little change in ORs, while we observed substantial attenuation in ORs in other prefectures (e.g., Akita). We also observed qualitative changes in some prefectures (e.g., Tokyo). No clear associations were observed between prefecture-level socioeconomic status variables and the risk of mortality in either sex. Conclusions: Geographic disparities in mortality across prefectures are quite substantial and cannot be fully explained by differences in population composition. The relative contribution of composition and context to health inequalities considerably vary across prefectures

Exploring variations in childhood stunting in Nigeria using league table, control chart and spatial analysis

Background: Stunting, linear growth retardation is the best measure of child health inequalities as it captures multiple dimensions of children’s health, development and environment where they live. The developmental priorities and socially acceptable health norms and practices in various regions and states within Nigeria remains disaggregated and with this, comes the challenge of being able to ascertain which of the regions and states identifies with either high or low childhood stunting to further investigate the risk factors and make recommendations for action oriented policy decisions. Methods: We used data from the birth histories included in the 2008 Nigeria Demographic and Health Survey (DHS) to estimate childhood stunting. Stunting was defined as height for age below minus two standard deviations from the median height for age of the standard World Health Organization reference population. We plotted control charts of the proportion of childhood stunting for the 37 states (including federal capital, Abuja) in Nigeria. The Local Indicators of Spatial Association (LISA) were used as a measure of the overall clustering and is assessed by a test of a null hypothesis. Results: Childhood stunting is high in Nigeria with an average of about 39%. The percentage of children with stunting ranged from 11.5% in Anambra state to as high as 60% in Kebbi State. Ranking of states with respect to childhood stunting is as follows: Anambra and Lagos states had the least numbers with 11.5% and 16.8% respectively while Yobe, Zamfara, Katsina, Plateau and Kebbi had the highest (with more than 50% of their underfives having stunted growth). Conclusions: Childhood stunting is high in Nigeria and varied significantly across the states. The northern states have a higher proportion than the southern states. There is an urgent need for studies to explore factors that may be responsible for these special cause variations in childhood stunting in Nigeria

Individual and neighborhood-level socioeconomic characteristics in relation to smoking prevalence among black and white adults in the Southeastern United States: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Low individual-level socioeconomic status (SES) is associated with higher prevalence of cigarette smoking. Recent work has examined whether neighborhood-level SES may affect smoking behavior independently from individual-level measures. However, few comparisons of neighborhood-level effects on smoking by race and gender are available.</p> <p>Methods</p> <p>Cross-sectional data from adults age 40-79 enrolled in the Southern Community Cohort Study from 2002-2009 (19, 561 black males; 27, 412 black females; 6, 231 white males; 11, 756 white females) were used in Robust Poisson regression models to estimate prevalence ratios (PRs) and 95% confidence intervals (CI) for current smoking in relation to individual-level SES characteristics obtained via interview and neighborhood-level SES characteristics represented by demographic measures from US Census block groups matched to participant home addresses.</p> <p>Results</p> <p>Several neighborhood-level SES characteristics were modestly associated with increased smoking after adjustment for individual-level factors including lower percentage of adults with a college education and lower percentage of owner-occupied households among blacks but not whites; lower percentage of households with interest, dividends, or net rental income among white males; and lower percentage of employed adults among black females.</p> <p>Conclusions</p> <p>Lower neighborhood-level SES is associated with increased smoking suggesting that cessation programs may benefit from targeting higher-risk neighborhoods as well as individuals.</p

Socioeconomic characteristics of residential areas and risk of death: is variation in spatial units for analysis a source of heterogeneity in observed associations?

Evidence on the association between the adverse socioeconomic characteristics of residential area and mortality is mixed. We examined whether the choice of spatial unit is critical in detecting this association

Relation between Neighborhood Environments and Obesity in the Multiethnic Study of Atherosclerosis

This study investigated associations between neighborhood physical and social environments and body mass index in 2,865 participants of the Multi-Ethnic Study of Atherosclerosis (MESA) aged 45-84 years and residing in Maryland, New York, and North Carolina. Neighborhood (census tract) environments were measured in non-MESA participants residing in MESA neighborhoods (2000-2002). The neighborhood physical environment score combined measures of a better walking environment and greater availability of healthy foods. The neighborhood social environment score combined measures of greater aesthetic quality, safety, and social cohesion and less violent crime. Marginal maximum likelihood was used to estimate associations between neighborhood environments and body mass index (kg/m(2)) before and after adjustment for individual-level covariates. MESA residents of neighborhoods with better physical environments had lower body mass index (mean difference per standard deviation higher neighborhood measure = -2.38 (95% confidence interval (CI): -3.38, -1.38) kg/m(2) for women and -1.20 (95% CI: -1.84, -0.57) kg/m(2) for men), independent of age, race/ethnicity, education, and income. Attenuation of these associations after adjustment for diet and physical activity suggests a mediating role of these behaviors. In men, the mean body mass index was higher in areas with better social environments (mean difference = 0.52 (95% CI: 0.07, 0.97) kg/m(2)). Improvement in the neighborhood physical environment should be considered for its contribution to reducing obesihttp://deepblue.lib.umich.edu/bitstream/2027.42/58737/1/Relation between Neighborhood Environments and Obesity in the Multiethnic Study of Atherosclerosis.pd

Health inequalities in Germany: do regional-level variables explain differentials in cardiovascular risk?

Breckenkamp J, Mielck A, Razum O. Health inequalities in Germany: do regional-level variables explain differentials in cardiovascular risk? BMC Public Health. 2007;7(1): 132.Background: Socioeconomic status is a predictor not only of mortality, but also of cardiovascular risk and morbidity. An ongoing debate in the field of social inequalities and health focuses on two questions: 1) Is individual health status associated with individual income as well as with income inequality at the aggregate (e. g. regional) level? 2) If there is such an association, does it operate via a psychosocial pathway (e.g. stress) or via a ´´neo-materialistic´´ pathway (e.g. systematic under-investment in societal infrastructures)? For the first time in Germany, we here investigate the association between cardiovascular health status and income inequality at the area level, controlling for individual socio-economic status. Methods: Individual-level explanatory variables (age, socio-economic status) and outcome data (body mass index, blood pressure, cholesterol level) as well as the regional-level variable (proportion of relative poverty) were taken from the baseline survey of the German Cardiovascular Prevention Study, a cross-sectional, community-based, multi-center intervention study, comprising six socio-economically diverse intervention regions, each with about 1800 participants aged 25–69 years. Multilevel modeling was used to examine the effects of individual and regional level variables. Results: Regional effects are small compared to individual effects for all risk factors analyzed. Most of the total variance is explained at the individual level. Only for diastolic blood pressure in men and for cholesterol in both men and women is a statistically significant effect visible at the regional level. Conclusion: Our analysis does not support the assumption that in Germany cardiovascular risk factors were to a large extent associated with income inequality at regional level

Kidney disease in life-course socioeconomic context: the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: Persons belonging to the working class or living in an adverse social environment at particular periods of their life course may have an increased risk of chronic kidney disease (CKD). METHODS: This hypothesis was examined among participants of the Life Course Socioeconomic Status Study, an ancillary study of the Atherosclerosis Risk in Communities Study, conducted in 2001 (mean age, 67.4 years; N = 12,631). CKD was defined by hospital discharge diagnosis and/or estimated glomerular filtration rate less than 45 mL/min/1.73 m(2) (<0.75 mL/s/1.73 m(2)). Social class was categorized as working class or non-working class at ages 30, 40, or 50 years. Area-level socioeconomic status was based on a composite of census scores during the same period. Adjusted odds ratios were obtained within strata of white and African-American race. RESULTS: The adjusted odds ratio of CKD for persons belonging to the working class versus non-working class at age 30 was 1.4 (95% confidence interval, 1.0 to 2.0) in whites and 1.9 (95% confidence interval, 1.1 to 3.0) in African Americans. Working class membership was associated with CKD, even at earlier stages of adult life, and class was associated more strongly with CKD than was education. Working class membership also suggested a stronger association with CKD among African Americans than whites, independent of diabetes and hypertension status. At later periods in the life course, area socioeconomic status was associated with CKD. CONCLUSION: Socioeconomic factors, including area socioeconomic status and social class, are associated with CKD and may account for some of the racial disparity in kidney disease.http://deepblue.lib.umich.edu/bitstream/2027.42/78575/1/ShohamVupputri2007_AmJKidneyDisease.pd

Area deprivation and its association with health in a cross-sectional study: are the results biased by recent migration?

<p>Abstract</p> <p>Background</p> <p>The association between area deprivation and health has mostly been examined in cross-sectional studies or prospective studies with short follow-up. These studies have rarely taken migration into account. This is a possible source of misclassification of exposure, i.e. an unknown number of study participants are attributed an exposure of area deprivation that they may have experienced too short for it to have any influence. The aim of this article was to examine to what extent associations between area deprivation and health outcomes were biased by recent migration.</p> <p>Methods</p> <p>Based on data from the Oslo Health Study, a cross-sectional study conducted in 2000 in Oslo, Norway, we used six health outcomes (self rated health, mental health, coronary heart disease, chronic obstructive pulmonary disease, smoking and exercise) and considered migration nine years prior to the study conduct. Migration into Oslo, between the areas of Oslo, and the changes in area deprivation during the period were taken into account. Associations were investigated by multilevel logistic regression analyses.</p> <p>Results</p> <p>After adjustment for individual socio-demographic variables we found significant associations between area deprivation and all health outcomes. Accounting for migration into Oslo and between areas of Oslo did not change these associations much. However, the people who migrated into Oslo were younger and had lower prevalences of unfavourable health outcomes than those who were already living in Oslo. But since they were evenly distributed across the area deprivation quintiles, they had little influence on the associations between area deprivation and health. Evidence of selective migration within Oslo was weak, as both moving up and down in the deprivation hierarchy was associated with significantly worse health than not moving.</p> <p>Conclusion</p> <p>We have documented significant associations between area deprivation and health outcomes in Oslo after adjustment for socio-demographic variables in a cross-sectional study. These associations were weakly biased by recent migration. From our results it still appears that migration prior to study conduct may be relevant to investigate even within a relatively short period of time, whereas changes in area deprivation during such a period is of limited interest.</p