@article {1474, title = {Spousal similarity in subjective well-being: the Cardiovascular Health Study.}, journal = {Psychol Aging}, volume = {11}, year = {1996}, month = {1996 Dec}, pages = {582-90}, abstract = {

This study examines the extent to which one spouse{\textquoteright}s subjective well-being predicts that of the partner (N = 1,040 spousal pairs, 65 years or older). Prior research is extended in two ways: (a) The similarity of both affective domains (depressive symptoms, feelings about life as a whole, and satisfaction with the meaning and purpose of life) and nonaffective domains (perceived health) are examined, and (b) known predictors of well-being in older adults (sociodemographic variables, self and spouse health status variables, and exposure to common environmental events) are statistically controlled. Results indicate that one spouse{\textquoteright}s assessments of well-being and depression predict the other{\textquoteright}s well-being even after controlling for known predictors of these outcomes. Given the similarity of findings for affective and nonaffective domains, multiple mechanisms, including contagion, mate selection, and common environmental influences, are speculated as likely to contribute to this phenomenon.

}, keywords = {Activities of Daily Living, Adaptation, Psychological, Aged, Cardiovascular Diseases, Depression, Female, Geriatric Assessment, Humans, Male, Personal Satisfaction, Sick Role, Social Environment, Spouses}, issn = {0882-7974}, author = {Bookwala, J and Schulz, R} } @article {657, title = {Area characteristics and individual-level socioeconomic position indicators in three population-based epidemiologic studies.}, journal = {Ann Epidemiol}, volume = {11}, year = {2001}, month = {2001 Aug}, pages = {395-405}, abstract = {

PURPOSE: There is growing interest in incorporating area indicators into epidemiologic analyses. Using data from the 1990 U.S. Census linked to individual-level data from three epidemiologic studies, we investigated how different area indicators are interrelated, how measures for different sized areas compare, and the relation between area and individual-level social position indicators.

METHODS: The interrelations between 13 area indicators of wealth/income, education, occupation, and other socioenvironmental characteristics were investigated using correlation coefficients and factor analyses. The extent to which block-group measures provide information distinct from census tract measures was investigated using intraclass correlation coefficients. Loglinear models were used to investigate associations between area and individual-level indicators.

RESULTS: Correlations between area measures were generally in the 0.5--0.8 range. In factor analyses, six indicators of income/wealth, education, and occupation loaded on one factor in most geographic sites. Correlations between block-group and census tract measures were high (correlation coefficients 0.85--0.96). Most of the variability in block-group indicators was between census tracts (intraclass correlation coefficients 0.72--0.92). Although individual-level and area indicators were associated, there was evidence of important heterogeneity in area of residence within individual-level income or education categories. The strength of the association between individual and area measures was similar in the three studies and in whites and blacks, but blacks were much more likely to live in more disadvantaged areas than whites.

CONCLUSIONS: Area measures of wealth/income, education, and occupation are moderately to highly correlated. Differences between using census tract or block-group measures in contextual investigations are likely to be relatively small. Area and individual-level indicators are far from perfectly correlated and provide complementary information on living circumstances. Differences in the residential environments of blacks and whites may need to be taken into account in interpreting race differences in epidemiologic studies.

}, keywords = {Adult, Black or African American, Cardiovascular Diseases, Demography, Educational Status, Factor Analysis, Statistical, Humans, Income, Linear Models, Occupations, Risk Factors, Social Class, Social Environment, Socioeconomic Factors, Statistics, Nonparametric, United States, White People}, issn = {1047-2797}, doi = {10.1016/s1047-2797(01)00221-6}, author = {Diez-Roux, A V and Kiefe, C I and Jacobs, D R and Haan, M and Jackson, S A and Nieto, F J and Paton, C C and Schulz, R} } @article {1332, title = {Neighborhood disadvantage and ischemic stroke: the Cardiovascular Health Study (CHS).}, journal = {Stroke}, volume = {42}, year = {2011}, month = {2011 Dec}, pages = {3363-8}, abstract = {

BACKGROUND AND PURPOSE: Neighborhood characteristics may influence the risk of stroke and contribute to socioeconomic disparities in stroke incidence. The objectives of this study were to examine the relationship between neighborhood socioeconomic status and incident ischemic stroke and examine potential mediators of these associations.

METHODS: We analyzed data from 3834 whites and 785 blacks enrolled in the Cardiovascular Health Study, a multicenter, population-based, longitudinal study of adults ages>=65 years from 4 US counties. The primary outcome was adjudicated incident ischemic stroke. Neighborhood socioeconomic status was measured using a composite of 6 census tract variables. Race-stratified multilevel Cox proportional hazard models were constructed adjusted for sociodemographic, behavioral, and biological risk factors.

RESULTS: Among whites, in models adjusted for sociodemographic characteristics, stroke hazard was significantly higher among residents of neighborhoods in the lowest compared with the highest neighborhood socioeconomic status quartile (hazard ratio, 1.32; 95\% CI, 1.01-1.72) with greater attenuation of the hazard ratio after adjustment for biological risk factors (hazard ratio, 1.16; 0.88-1.52) than for behavioral risk factors (hazard ratio, 1.30; 0.99-1.70). Among blacks, we found no significant associations between neighborhood socioeconomic status and ischemic stroke.

CONCLUSIONS: Higher risk of incident ischemic stroke was observed in the most disadvantaged neighborhoods among whites, but not among blacks. The relationship between neighborhood socioeconomic status and stroke among whites appears to be mediated more strongly by biological than behavioral risk factors.

}, keywords = {Aged, Aged, 80 and over, Brain Ischemia, Female, Health Status Disparities, Humans, Incidence, Longitudinal Studies, Male, Poverty, Residence Characteristics, Risk, Risk Factors, Social Class, Social Environment, Socioeconomic Factors, Stroke, Urban Population}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.111.622134}, author = {Brown, Arleen F and Liang, Li-Jung and Vassar, Stefanie D and Stein-Merkin, Sharon and Longstreth, W T and Ovbiagele, Bruce and Yan, Tingjian and Escarce, Jos{\'e} J} }