Associations Of Neighborhood Characteristics Research Articles

Income-related inequality in quality-adjusted life expectancy in Korea at the national and district levels

BackgroundThe aim of this study was to measure differences in quality-adjusted life expectancy (QALE) by income in Korea at the national and district levels.MethodsMortality rates and EuroQol-5D (EQ-5D) scores were obtained from the National Health Information Database of the National Health Insurance Service and the Korea Community Health Survey, respectively. QALE and differences in QALE among income quintiles were calculated using combined 2008–2014 data for 245 districts in Korea. Correlation analyses were conducted to investigate the associations of neighborhood characteristics with QALE and income gaps therein.ResultsQALE showed a graded pattern of inequality according to income, and increased over time for all levels of income and in both sexes, except for low-income quintiles among women, resulting in a widened inequality in QALE among women. In all 245 districts, pro-rich inequalities in QALE were found in both men and women. Districts with higher QALE and smaller income gaps in QALE were concentrated in metropolitan areas, while districts with lower QALE and larger income gaps in QALE were found in rural areas. QALE and differences in QALE by income showed relatively close correlations with socioeconomic characteristics, but relatively weak correlations with health behaviors, except for smoking and indicators related to medical resources.ConclusionsThis study provides evidence of income-based inequalities in health measured by QALE in all subnational areas in Korea. Furthermore, QALE and differences in QALE by income were closely associated with neighborhood-level socioeconomic characteristics.

Associations of Neighborhood Characteristics with Sleep Timing and Quality: The Multi-Ethnic Study of Atherosclerosis

To investigate the associations of specific neighborhood features (disorder, safety, social cohesion, physical environment, and socioeconomic status) with sleep duration and quality. Cross-sectional. One wave of a population-based study (Multi-Ethnic Study of Atherosclerosis). Community-dwelling participants in New York, NY and Los Angeles, CA. There were 1,406 participants (636 males, 770 females). NA. Sleep was assessed using reported hours of sleep, the Epworth Sleepiness Scale, and insomnia symptoms. Neighborhood characteristics were assessed via questionnaires administered to neighbors of study participants and were aggregated to the neighborhood (census tract) level using empirical Bayes estimation. An adverse social environment (characterized by high disorder, and low safety and social cohesion) was associated with shorter sleep duration after adjustment for the physical environment, neighborhood and individual-level socioeconomic status (SES), and other short sleep risk factors (mean difference per standard deviation increase in summary social environment scale 0.24 h 95% confidence interval 0.08, 0.43). Adverse neighborhood social and physical environments, and neighborhood SES were associated with greater sleepiness, but associations with physical environments were no longer statistically significant after adjustment for sociodemographic characteristics. Neighborhood SES was a weaker and less consistent predictor of specific measures of neighborhood social and physical environments. Neighborhood characteristics were not associated with insomnia. Shortened sleep related to adverse social environments represents one potential pathway through which neighborhoods may influence health.

Associations of Neighborhood Characteristics With the Location and Type of Food Stores

We investigated associations between local food environment and neighborhood racial/ethnic and socioeconomic composition. Poisson regression was used to examine the association of food stores and liquor stores with racial/ethnic composition and income in selected census tracts in North Carolina, Maryland, and New York. Predominantly minority and racially mixed neighborhoods had more than twice as many grocery stores as predominantly White neighborhoods (for predominantly Black tracts, adjusted stores per population ratio [SR]=2.7; 95% confidence interval [CI]=2.2, 3.2; and for mixed tracts, SR=2.2; 95% CI=1.9, 2.7) and half as many supermarkets (for predominantly Black tracts, SR=0.5; 95% CI=0.3, 0.7; and for mixed tracts, SR=0.7; 95% CI=0.5, 1.0, respectively). Low-income neighborhoods had 4 times as many grocery stores as the wealthiest neighborhoods (SR=4.3; 95% CI=3.6, 5.2) and half as many supermarkets (SR=0.5; 95% CI=0.3, 0.8). In general, poorer areas and non-White areas also tended to have fewer fruit and vegetable markets, bakeries, specialty stores, and natural food stores. Liquor stores were more common in poorer than in richer areas (SR=1.3; 95% CI=1.0, 1.6). Local food environments vary substantially by neighborhood racial/ethnic and socioeconomic composition and may contribute to disparities in health.