@article {7880, title = {Urban neighbourhood unemployment history and depressive symptoms over time among late middle age and older adults.}, journal = {J Epidemiol Community Health}, volume = {67}, year = {2013}, month = {2013 Feb}, pages = {153-8}, publisher = {67}, abstract = {

BACKGROUND: Little is known about how a neighbourhood{\textquoteright}s unemployment history may set the stage for depressive symptomatology. This study examines the effects of urban neighbourhood unemployment history on current depressive symptoms and subsequent symptom trajectories among residentially stable late middle age and older adults. Contingent effects between neighbourhood unemployment and individual-level employment status (ie, cross-level interactions) are also assessed.

METHODS: Individual-level survey data are from four waves (2000, 2002, 2004 and 2006) of the original cohort of the nationally representative US Health and Retirement Study. Neighbourhoods are operationalised with US Census tracts for which historical average proportion unemployed between 1990 and 2000 and change in proportion unemployed between 1990 and 2000 are used to characterise the neighbourhood{\textquoteright}s unemployment history. Hierarchical linear regressions estimate three-level (time, individual and neighbourhood) growth models.

RESULTS: Symptoms in 2000 are highest among those residing in neighbourhoods characterised by high historical average unemployment beginning in 1990 and increasing unemployment between 1990 and 2000, net of a wide range of socio-demographic controls including individual-level employment status. These neighbourhood unemployment effects are not contingent upon individual-level employment status in 2000. 6-year trajectories of depressive symptoms decrease over time on average but are not significantly influenced by the neighbourhood{\textquoteright}s unemployment history.

CONCLUSIONS: Given the current US recession, future studies that do not consider historical employment conditions may underestimate the mental health impact of urban neighbourhood context. The findings suggest that exposure to neighbourhood unemployment earlier in life may be consequential to mental health later in life.

}, keywords = {Age Factors, depression, Female, Humans, Logistic Models, Longitudinal Studies, Male, Middle Aged, Multilevel Analysis, Residence Characteristics, Retirement, Risk Factors, Socioeconomic factors, Stress, Psychological, Surveys and Questionnaires, Time Factors, Unemployment, United States, Urban Population}, issn = {1470-2738}, doi = {10.1136/jech-2012-201537}, author = {Richard G Wight and Carol S Aneshensel and Barrett, Christopher and Michelle J Ko and Joshua Chodosh and Arun S Karlamangla} } @article {7446, title = {Urban neighborhood context and mortality in late life.}, journal = {J Aging Health}, volume = {22}, year = {2010}, month = {2010 Mar}, pages = {197-218}, publisher = {22}, abstract = {

OBJECTIVE: To examine the contextual effects of urban neighborhood characteristics on mortality among older adults.

METHOD: Data are from the Study of Assets and Health Dynamics Among the Oldest Old (AHEAD). Death is assessed between the baseline assessment (1993) and the first follow-up interview (1995). Neighborhood data are from the 1990 Census.

RESULTS: The log odds of dying between the two time points are higher in high proportion Hispanic neighborhoods, net of individual-level sociodemographic variables, but this effect is partly mediated by individual-level health. The log odds of dying are significantly (p < .05) lower in affluent neighborhoods, controlling for all individual-level variables and neighborhood proportion Hispanic.

DISCUSSION: There are survival-related benefits of living in an affluent urban neighborhood, which we posit may be manifested through the diffusion of innovations in health care and health-promotion activities.

}, keywords = {Age Factors, Aged, Aging, Cognition, Confidence Intervals, depression, Female, Health Status, Humans, Los Angeles, Male, Middle Aged, Mortality, Odds Ratio, Poverty, Psychometrics, Residence Characteristics, Self Report, Socioeconomic factors, Statistics as Topic, Urban Population}, issn = {1552-6887}, doi = {10.1177/0898264309355980}, author = {Richard G Wight and Janet R. Cummings and Arun S Karlamangla and Carol S Aneshensel} } @article {7347, title = {Trajectories of cognitive function in late life in the United States: demographic and socioeconomic predictors.}, journal = {Am J Epidemiol}, volume = {170}, year = {2009}, month = {2009 Aug 01}, pages = {331-42}, publisher = {170}, abstract = {

This study used mixed-effects modeling of data from a national sample of 6,476 US adults born before 1924, who were tested 5 times between 1993 and 2002 on word recall, serial 7{\textquoteright}s, and other mental status items to determine demographic and socioeconomic predictors of trajectories of cognitive function in older Americans. Mean decline with aging in total cognition score (range, 0-35; standard deviation, 6.00) was 4.1 (0.68 standard deviations) per decade (95\% confidence interval: 3.8, 4.4) and in recall score (range, 0-20; standard deviation, 3.84) was 2.3 (0.60 standard deviations) per decade (95\% confidence interval: 2.1, 2.5). Older cohorts (compared with younger cohorts), women (compared with men), widows/widowers, and those never married (both compared with married individuals) declined faster, and non-Hispanic blacks (compared with non-Hispanic whites) and those in the bottom income quintile (compared with the top quintile) declined slower. Race and income differences in rates of decline were not sufficient to offset larger differences in baseline cognition scores. Educational level was not associated with rate of decline in cognition scores. The authors concluded that ethnic and socioeconomic disparities in cognitive function in older Americans arise primarily from differences in peak cognitive performance achieved earlier in the life course and less from declines in later life.

}, keywords = {Aged, Aged, 80 and over, Aging, Black or African American, Cognition, Confidence Intervals, Education, Female, Geriatric Assessment, Hispanic or Latino, Humans, Income, Male, Marital Status, Mexican Americans, Poverty, Sampling Studies, Socioeconomic factors, Surveys and Questionnaires, United States, White People}, issn = {1476-6256}, doi = {10.1093/aje/kwp154}, author = {Arun S Karlamangla and Miller-Martinez, Dana and Carol S Aneshensel and Teresa Seeman and Richard G Wight and Joshua Chodosh} } @article {7331, title = {Urban neighborhood context and change in depressive symptoms in late life.}, journal = {J Gerontol B Psychol Sci Soc Sci}, volume = {64}, year = {2009}, month = {2009 Mar}, pages = {247-51}, publisher = {64B}, abstract = {

OBJECTIVES: This study examines associations between urban neighborhood sociodemographic characteristics and change over time in late-life depressive symptoms.

METHODS: Survey data are from three waves (1993, 1995, and 1998) of the Study of Assets and Health Dynamics Among the Oldest Old, a U.S. national probability sample of noninstitutionalized persons aged 70 years or older in 1993. Neighborhoods are 1990 U.S. Census tracts. Hierarchical linear regression is used to estimate multilevel models.

RESULTS: The average change over time in depressive symptoms varies significantly across urban neighborhoods. Change in depressive symptoms is significantly associated with neighborhood-level socioeconomic disadvantage and ethnic composition in unadjusted models but not in models that control for individual-level characteristics.

CONCLUSIONS: Findings indicate that apparent neighborhood-level effects on change in depressive symptoms over time among urban-dwelling older adults reflect, for the most part, differences in characteristics of the neighborhood residents.

}, keywords = {Aged, Aged, 80 and over, Aging, Cultural Diversity, depression, Disability Evaluation, Educational Status, Female, Humans, Longitudinal Studies, Los Angeles, Male, Personality Inventory, Poverty, Psychosocial Deprivation, Residence Characteristics, Risk Factors, Urban Population}, issn = {1758-5368}, doi = {10.1093/geronb/gbn016}, author = {Richard G Wight and Janet R. Cummings and Arun S Karlamangla and Carol S Aneshensel} } @article {7200, title = {A multilevel analysis of urban neighborhood socioeconomic disadvantage and health in late life.}, journal = {Soc Sci Med}, volume = {66}, year = {2008}, month = {2008 Feb}, pages = {862-72}, publisher = {66}, abstract = {

The associations between neighborhood context and various indicators of health are receiving growing empirical attention, but much of this research is regionally circumscribed or assumes similar effects across the life course. This study utilizes a U.S. national sample to investigate the association between urban neighborhood socioeconomic disadvantage and health specifically among older adults. Data are from 3442 participants aged 70 years and older in the 1993 Asset and Health Dynamics Among the Oldest Old (AHEAD) Study, and the 1990 U.S. Census. Our approach underscores the importance of multiple dimensions of health (self-reported physician-diagnosed cardiovascular disease [CVD], functional status, and self-rated health) as well as multiple dimensions of neighborhood disadvantage, which are conceptualized as environmental hazards that may lead to a physiologically consequential stress response. We find that individual-level factors attenuate the association between neighborhood disadvantage and both CVD and functional status, but not self-rated health. Net of covariates, high neighborhood socioeconomic disadvantage is significantly associated with reporting poor health. In late life, neighborhood socioeconomic disadvantage is more consequential to subjective appraisals of health than diagnosed CVD or functional limitations.

}, keywords = {Aged, Female, Health Behavior, Health Status Disparities, Humans, Male, Poverty, Small-Area Analysis, Socioeconomic factors, United States, Urban Population}, issn = {0277-9536}, doi = {10.1016/j.socscimed.2007.11.002}, author = {Richard G Wight and Janet R. Cummings and Miller-Martinez, Dana and Arun S Karlamangla and Teresa Seeman and Carol S Aneshensel} } @article {7133, title = {Urban neighborhoods and depressive symptoms among older adults.}, journal = {J Gerontol B Psychol Sci Soc Sci}, volume = {62}, year = {2007}, month = {2007 Jan}, pages = {S52-9}, publisher = {62}, abstract = {

OBJECTIVE: This study seeks to determine whether depressive symptoms among older persons systematically vary across urban neighborhoods such that experiencing more symptoms is associated with low socioeconomic status (SES), high concentrations of ethnic minorities, low residential stability and low proportion aged 65 years and older.

METHODS: Survey data are from the Study of Assets and Health Dynamics Among the Oldest Old (AHEAD), a 1993 U.S. national probability sample of noninstitutionalized persons born in 1923 or earlier (i.e. people aged 70 or older). Neighborhood data are from the 1990 Census at the tract level. Hierarchical linear regression is used to estimate multilevel models.

RESULT: The average number of depressive symptoms varies across Census tracts independent of individual-level characteristics. Symptoms are not significantly associated with neighborhood SES, ethnic composition, or age structure when individual-level characteristics are controlled statistically. However, net of individual-level characteristics, symptoms are positively associated with neighborhood residential stability, pointing to a complex meaning of residential stability for the older population.

DISCUSSION: This study shows that apparent neighborhood-level socioeconomic effects on depressive symptoms among urban-dwelling older adults are largely if not entirely compositional in nature. Further, residential stability in the urban neighborhood may not be emotionally beneficial to its aged residents.

}, keywords = {Activities of Daily Living, Aged, Aged, 80 and over, Comorbidity, Cross-Sectional Studies, Depressive Disorder, Female, Health Status Indicators, Health Surveys, Humans, Incidence, Male, Minority Groups, Peer Group, Population Dynamics, Risk Factors, Social Environment, United States, Urban Population}, issn = {1079-5014}, doi = {10.1093/geronb/62.1.s52}, author = {Carol S Aneshensel and Richard G Wight and Miller-Martinez, Dana and Amanda L. Botticello and Arun S Karlamangla and Teresa Seeman} } @article {7087, title = {Urban neighborhood context, educational attainment, and cognitive function among older adults.}, journal = {Am J Epidemiol}, volume = {163}, year = {2006}, month = {2006 Jun 15}, pages = {1071-8}, publisher = {163}, abstract = {

Existing research has not addressed the potential impact of neighborhood context--educational attainment of neighbors in particular--on individual-level cognition among older adults. Using hierarchical linear modeling, the authors analyzed data from the 1993 Study of Assets and Health Dynamics Among the Oldest Old (AHEAD), a large, nationally representative sample of US adults born before 1924. Data from participants residing in urban neighborhoods (n = 3,442) were linked with 1990 US Census tract data. Findings indicate that 1) average cognitive function varies significantly across US Census tracts; 2) older adults living in low-education areas fare less well cognitively than those living in high-education areas, net of individual characteristics, including their own education; 3) this association is sustained when controlling for contextual-level median household income; and 4) the effect of individual-level educational attainment differs across neighborhoods of varying educational profiles. Promoting educational attainment among the general population living in disadvantaged neighborhoods may prove cognitively beneficial to its aging residents because it may lead to meliorations in stressful life conditions and coping deficiencies.

}, keywords = {Aged, Aged, 80 and over, Chi-Square Distribution, Cognition Disorders, Educational Status, Female, Humans, Linear Models, Male, Residence Characteristics, Risk Factors, Socioeconomic factors, United States, Urban Population}, issn = {0002-9262}, doi = {10.1093/aje/kwj176}, author = {Richard G Wight and Carol S Aneshensel and Miller-Martinez, Dana and Amanda L. Botticello and Janet R. Cummings and Arun S Karlamangla and Teresa Seeman} }