Where We Live Matters for Our Health: Neighborhoods and Health

Details how a neighborhood's physical and socioeconomic environments, such as safety and access to fresh produce, exercise opportunities, and medical services, affect residents' health. Highlights local interventions to make neighborhoods healthier

The intersection of gender and race/ethnicity in smoking behaviors among menthol and non-menthol smokers in the United States

To determine whether menthol is related to initiation, quantity or quitting, we examined differences in smoking behaviors among menthol and non-menthol smokers, stratified by gender and race/ethnicity, and adjusting for age, income and educational attainment.Cross-sectional, using data from the 2005 National Health Interview Survey and Cancer Control Supplement.United States.Black, Hispanic and white women and men aged 25–64 years.For each group, we examined (i) proportion of menthol smokers (comparing current and former smokers); (ii) age of initiation, cigarettes smoked per day and quit attempt in the past year (comparing menthol and non-menthol current smokers); and (iii) time since quitting (comparing menthol and non-menthol former smokers). We calculated predicted values for each demographic group, adjusting for age, income and educational attainment.After adjusting for age, income and education, black (compared with Hispanic and white) and female (compared with male) smokers were more likely to choose menthol cigarettes. There was only one statistically significant difference in age of initiation, cigarettes smoked per day, quit attempts or time since quitting between menthol and non-menthol smokers: white women who smoked menthol cigarettes reported longer cessation compared with those who smoked non-menthol cigarettes.The results do not support the hypothesis that menthol smokers initiate earlier, smoke more or have a harder time quitting compared with non-menthol smokers. A menthol additive and the marketing of it, given the clear demographic preferences demonstrated here, however, may be responsible for enticing the groups least likely to smoke into this addictive behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79098/1/j.1360-0443.2010.03191.x.pd

Is neighborhood poverty harmful to every child? Neighborhood poverty, family poverty, and behavioral problems among young children

This longitudinal study investigates the association between neighborhood poverty and behavioral problems among young children. This study also examines whether social environments mediate the relationship between neighborhood poverty and behavioral problems. We used data from the third and fourth waves of the Fragile Families and Child Wellbeing study to assess behavioral problems separately for children who experienced no family poverty, moved out of family poverty, moved into family poverty, and experienced long‐term family poverty. Regression models assessed the effect of neighborhood poverty on behavioral problem outcomes among children aged 5 years, after controlling for sociodemographic characteristics and earlier behavioral problems. Results showed an association between neighborhood poverty and lower social cohesion and safety, which lead to greater externalizing problems among children with long‐term family poverty living in high‐poverty neighborhoods compared with those in low‐poverty neighborhoods. Policies and community resources need to be allocated to improve neighborhood social environments, particularly for poor children in high‐poverty neighborhoods.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148233/1/jcop22140.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148233/2/jcop22140_am.pd

Neighborhood sampling: how many streets must an auditor walk?

This study tested the representativeness of four street segment sampling protocols using the Pedestrian Environment Data Scan (PEDS) in eleven neighborhoods surrounding public housing developments in Houston, TX. The following four street segment sampling protocols were used (1) all segments, both residential and arterial, contained within the 400 meter radius buffer from the center point of the housing development (the core) were compared with all segments contained between the 400 meter radius buffer and the 800 meter radius buffer (the ring); all residential segments in the core were compared with (2) 75% (3) 50% and (4) 25% samples of randomly selected residential street segments in the core. Analyses were conducted on five key variables: sidewalk presence; ratings of attractiveness and safety for walking; connectivity; and number of traffic lanes. Some differences were found when comparing all street segments, both residential and arterial, in the core to the ring. Findings suggested that sampling 25% of residential street segments within the 400 m radius of a residence sufficiently represents the pedestrian built environment. Conclusions support more cost effective environmental data collection for physical activity research

Associations between Area-Level Unemployment, Body Mass Index, and Risk Factors for Cardiovascular Disease in an Urban Area

Introduction: Cardiovascular Disease (CVD) has been linked to "neighbourhood" socioeconomic status (nSES), often operationalized as a composite index of aggregate income, occupation and education within predefined administrative boundaries. The role of specific, non-composite socioeconomic markers has not been clearly explained. It is also unclear whether the relationship between nSES and CVD varies according to sex. We sought to determine whether area-level unemployment (ALU) was associated with CVD risk, and whether this association differed by sex. Methods: 342 individuals from the Montreal Neighbourhood Survey of Lifestyle and Health provided self-reported behavioural and socioeconomic information. A nurse collected biochemical and anthropometric data. ALU, a weighted average of the proportion of persons 15-years and older available for but without work, was measured using a Geographic Information System for a 250 m buffer centred on individual residence. Generalized Estimating Equations were used to estimate the associations between ALU, body mass index (BMI) and a cumulative score for total cardiometabolic risk (TCR). Results: After confounder adjustments, the mean 4th minus 1st quartile difference in BMI was 3.19 kg/m2 (95% CI: 2.39, 3.99), while the prevalence ratio for the 4th relative to 1st quartile for TCR was 2.20 (95 % CI: 1.53, 3.17). Sex interacted with ALU; women relative to men had greater mean 3.97 kg/m2 (95% CI: 2.08, 5.85) BMI and greater mean TCR 1.51 (95% CI: 0.78, 2.90), contrasted at mean ALU. Conclusions: Area-level unemployment is associated with greater CVD risk, and this association is stronger for women

Area-level socioeconomic characteristics and incidence of metabolic syndrome: a prospective cohort study

BACKGROUND The evidence linking socioeconomic environments and metabolic syndrome (MetS) has primarily been based on cross-sectional studies. This study prospectively examined the relationships between area-level socioeconomic position (SEP) and the incidence of MetS. METHODS A prospective cohort study design was employed involving 1,877 men and women aged 18+ living in metropolitan Adelaide, Australia, all free of MetS at baseline. Area-level SEP measures, derived from Census data, included proportion of residents completing a university education, and median household weekly income. MetS, defined according to International Diabetes Federation, was ascertained after an average of 3.6 years follow up. Associations between each area-level SEP measure and incident MetS were examined by Poisson regression Generalised Estimating Equations models. Interaction between area- and individual-level SEP variables was also tested. RESULTS A total of 156 men (18.7%) and 153 women (13.1%) developed MetS. Each percentage increase in the proportion of residents with a university education corresponded to a 2% lower risk of developing MetS (age and sex-adjusted incidence risk ratio (RR) = 0.98; 95% confidence interval (CI) =0.97-0.99). This association persisted after adjustment for individual-level income, education, and health behaviours. There was no significant association between area-level income and incident MetS overall. For the high income participants, however, a one standard deviation increase in median household weekly income was associated with a 29% higher risk of developing MetS (Adjusted RR = 1.29; 95%CI = 1.04-1.60). CONCLUSIONS While area-level education was independently and inversely associated with the risk of developing MetS, the association between area-level income and the MetS incidence was modified by individual-level income.Anh D Ngo, Catherine Paquet, Natasha J Howard, Neil T Coffee, Robert Adams, Anne Taylor and Mark Danie