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1.  Circadian rhythm of cortisol and neighborhood characteristics in a population-based sample: The Multi-Ethnic Study of Atherosclerosis 
Health & place  2011;17(2):625-632.
Although stress is often hypothesized to contribute to the effects of neighborhoods on health, very few studies have investigated associations of neighborhood characteristics with stress biomarkers. This study helps address the gap in the literature by examining whether neighborhood characteristics are associated with cortisol profiles. Analyses were based on data from the Multi-Ethnic Study of Atherosclerosis Stress study which collected multiple measures of salivary cortisol over three days on a population based sample of approximately 800 adults. Multilevel models with splines were used to examine associations of cortisol levels with neighborhood poverty, violence, disorder, and social cohesion. Neighborhood violence was significantly associated with lower cortisol values at wakeup and with a slower decline in cortisol over the earlier part of the day, after sociodemographic controls. Associations were weaker and less consistent for neighborhood poverty, social cohesion, and disorder. Results revealed suggestive, though limited, evidence linking neighborhood contexts to cortisol circadian rhythms.
doi:10.1016/j.healthplace.2010.12.019
PMCID: PMC3189702  PMID: 21292535
Neighborhood context; cortisol; biomarker; hierarchical linear modeling
2.  Hopelessness, Depression, and Early Markers of Endothelial Dysfunction in U.S. adults 
Psychosomatic medicine  2010;72(7):613-619.
Objective
This study examines whether the psychological traits of hopelessness and depressive symptoms are related to endothelial dysfunction.
Methods
Data come from a subsample of 434 respondents in the 2001–2003 Chicago Community Adult Health Study (CCAHS), a population-based survey designed to study the impact of psychological attributes, neighborhood environment, and socio-economic circumstances on adults age 18 and over. Circulating biomarkers of endothelial dysfunction including e-selectin, p-selectin and s-ICAM1 were obtained from serum samples. Hopelessness was measured by responses to two questions and depressive symptoms were measured by an 11-item version of the CES-D. Multivariate regression models tested whether continuous levels of the biomarkers (natural log transformed) were associated with levels of hopelessness and depressive symptoms separately and concurrently.
Results
In age- and sex-adjusted models, hopelessness showed significant positive linear associations with s-ICAM1. In contrast, there was no significant linear association between hopelessness and e-selectin and p-selectin. Adjustment for clinical risk factors including systolic pressure, chronic health conditions, smoking, and body mass index did not substantively alter these associations. Results from similar models for depressive symptoms did not reveal any association with the three biomarkers of endothelial dysfunction. The associations between hopelessness and e-selectin and s-ICAM1 were robust to the inclusion of adjustments for depressive symptoms.
Conclusions
Negative psychosocial traits may influence cardiovascular outcomes partially through their impact on the early stages of atherosclerosis, and specific psychosocial traits such as hopelessness may play a more direct role in this process than overall depressive symptoms.
doi:10.1097/PSY.0b013e3181e2cca5
PMCID: PMC3190596  PMID: 20498292
3.  The Link between Neighborhood Poverty and Health: Context or Composition? 
American Journal of Epidemiology  2008;168(6):611-619.
Cross-sectional studies of neighborhood context and health are subject to upward bias due to unobserved heterogeneity and to downward bias due to overadjustment for potential mediators in the pathway between neighborhood context and health. In this study, the authors employed two strategies that addressed these two sources of bias. First, to mitigate overadjustment of mediators, they adjusted for baseline characteristics observed just prior to the measurement of neighborhood context, using a combined propensity score and regression strategy. Second, to mitigate underadjustment of unmeasured confounders, they employed a fixed-effects modeling strategy to account for unobserved non-time-varying heterogeneity. Analyses were based on a nationally representative sample of the nonimmigrant US population from the Panel Study of Income Dynamics (1980–1997) in which respondent-rated health was regressed on neighborhood poverty. The samples consisted of approximately 6,000 respondents for the propensity score/regression models and 45,000 person-years for the fixed-effects models. Both modeling strategies yielded significant estimates of neighborhood poverty and supported a causal link between neighborhood context and health.
doi:10.1093/aje/kwn182
PMCID: PMC2584357  PMID: 18687664
causality; health status disparities; poverty; residence characteristics; social class
4.  The Link between Neighborhood Poverty and Health: Context or Composition? 
American journal of epidemiology  2008;168(6):611-619.
Cross-sectional studies of neighborhood context and health are subject to upward bias due to unobserved heterogeneity and to downward bias due to overadjustment for potential mediators in the pathway between neighborhood context and health. In this study, the authors employed two strategies that addressed these two sources of bias. First, to mitigate overadjustment of mediators, they adjusted for baseline characteristics observed just prior to the measurement of neighborhood context, using a combined propensity score and regression strategy. Second, to mitigate underadjustment of unmeasured confounders, they employed a fixed-effects modeling strategy to account for unobserved non-time-varying heterogeneity. Analyses were based on a nationally representative sample of the nonimmigrant US population from the Panel Study of Income Dynamics (1980–1997) in which respondent-rated health was regressed on neighborhood poverty. The samples consisted of approximately 6,000 respondents for the propensity score/regression models and 45,000 person-years for the fixed-effects models. Both modeling strategies yielded significant estimates of neighborhood poverty and supported a causal link between neighborhood context and health.
doi:10.1093/aje/kwn 182
PMCID: PMC2584357  PMID: 18687664
Causality; health status disparities; poverty; residence characteristics; social class
5.  Investigating the relationship between neighborhood poverty and mortality risk: A marginal structural modeling approach 
Extant observational studies generally support the existence of a link between neighborhood context and health. However, estimating the causal impact of neighborhood effects from observational data has proven to be a challenge. Omission of relevant factors may lead to overestimating the effects of neighborhoods on health while inclusion of time-varying confounders that may also be mediators (e.g., income, labor force status) may lead to underestimation. Using longitudinal data from the 1990 to 2007 years of the Panel Study of Income Dynamics, this study investigates the link between neighborhood poverty and overall mortality risk. A marginal structural modeling strategy is employed to appropriately adjust for simultaneous mediating and confounding factors. To address the issue of possible upward bias from the omission of key variables, sensitivity analysis to assess the robustness of results against unobserved confounding is conducted. We examine two continuous measures of neighborhood poverty – single-point and a running average. Both were specified as piece-wise linear splines with a knot at 20 percent. We found no evidence from the traditional naïve strategy that neighborhood context influences mortality risk. In contrast, for both the single-point and running average neighborhood poverty specifications, the marginal structural model estimates indicated a statistically significant increase in mortality risk with increasing neighborhood poverty above the 20 percent threshold. For example, below 20 percent neighborhood poverty, no association was found. However, after the 20 percent poverty threshold is reached, each 10 percentage point increase in running average neighborhood poverty was found to increase the odds for mortality by 89 percent [95% CI = 1.22, 2.91]. Sensitivity analysis indicated that estimates were moderately robust to omitted variable bias.
doi:10.1016/j.socscimed.2013.03.003
PMCID: PMC4180500  PMID: 23849239
Marginal structural modeling; Neighborhood effects; Longitudinal analysis; Causal modeling; Sensitivity analysis
6.  Education and levels of salivary cortisol over the day in U.S. adults 
Background
Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is hypothesized to be an important pathway linking socioeconomic position and chronic disease.
Purpose
This paper tests the association between education and the diurnal rhythm of salivary cortisol.
Methods
Up to 8 measures of cortisol (mean of 5.38 per respondent) over two days were obtained from 311 respondents, aged 18–70, drawn from the 2001–2002 Chicago Community Adult Health Study. Multi-level models with linear splines were used to estimate waking level, rates of cortisol decline, and area-under-the-curve over the day, by categories of education.
Results
Lower education (0–11 years) was associated with lower waking levels of cortisol, but not the rate of decline of cortisol, resulting in a higher area-under-the-curve for more educated respondents throughout the day.
Conclusions
This study found evidence of lower cortisol exposure among individuals with less education and thus does not support the hypothesis that less education is associated with chronic over-exposure to cortisol.
doi:10.1007/s12160-010-9224-2
PMCID: PMC3486742  PMID: 20812036
7.  The Dynamics of Income and Neighborhood Context for Population Health: Do Long Term Measures of Socioeconomic Status Explain More of the Black/White Health Disparity than Single-Point-In-Time Measures? 
Social science & medicine (1982)  2009;68(8):1368-1375.
Socioeconomic status, though a robust and strong predictor of health, has generally been unable to fully explain the health gap between blacks and whites in the United States. However, at both the individual and neighborhood levels, socioeconomic status is often treated as a static factor with only single-point-in-time measurements. These cross-sectional measures fail to account for possible heterogeneous histories within groups who may share similar characteristics at a given point in time. As such, ignoring the dynamic nature of socioeconomic status may lead to the underestimation of its importance in explaining health and racial health disparities.
In this study, I use national longitudinal data to investigate the relationship between neighborhood poverty and respondent-rated health, focusing on whether the addition of a temporal dimension reveals a stronger relationship between neighborhood poverty and health, and a greater explanatory power for the health gap between blacks and whites. Results indicate that long-term neighborhood measures are stronger predictors of health outcomes and explain a greater amount of the black/white health gap than single-point measures.
doi:10.1016/j.socscimed.2009.01.028
PMCID: PMC3401574  PMID: 19278767
racial health disparities; neighborhood effects; USA; socioeconomic status (SES); longtitudinal
8.  Neighborhood Effects on Health: Concentrated Advantage and Disadvantage 
Health & place  2010;16(5):1058-1060.
We investigate an alternative conceptualization of neighborhood context and its association with health. Using an index that measures a continuum of concentrated advantage and disadvantage, we examine whether the relationship between neighborhood conditions and health varies by socio-economic status. Using NHANES III data geo-coded to census tracts, we find that while largely uneducated neighborhoods are universally deleterious, individuals with more education benefit from living in highly educated neighborhoods to a greater degree than individuals with lower levels of education.
doi:10.1016/j.healthplace.2010.05.009
PMCID: PMC2918664  PMID: 20627796
concentrated advantage; neighborhood SES
9.  Does mental health history explain gender disparities in insomnia symptoms among young adults? 
Sleep medicine  2009;10(10):1118-1123.
Background
Insomnia is the most commonly reported sleep disorder, characterized by trouble falling asleep, staying asleep, or waking up too early. Previous epidemiological data reveal that women are more likely than men to suffer from insomnia symptoms. We investigate the role that mental health history plays in explaining the gender disparity in insomnia symptoms.
Methods
Using logistic regression, we analyze National Health and Nutritional Examination Survey (NHANES) III interview and laboratory data, merged with data on sociodemographic characteristics of the residential census tract of respondents. Our sample includes 5,469 young adults (ages 20 to 39) from 1429 census tracts.
Results
Consistent with previous research, we find that women are more likely to report insomnia symptoms compared to men (16.7% vs. 9.2%). However, in contrast to previous work, we show that the difference between women’s and men’s odds of insomnia becomes statistically insignificant after adjusting for history of mental health conditions (OR=1.08, p>.05).
Conclusions
The gender disparity in insomnia symptoms may be driven by higher prevalence of affective disorders among women. This finding has implications for clinical treatment of both insomnia and depression, especially among women.
doi:10.1016/j.sleep.2008.12.011
PMCID: PMC2805081  PMID: 19467926
Insomnia; Gender; Mental Health; Epidemiology; NHANES III
10.  Neighborhood context and ethnicity differences in body mass index: A multilevel analysis using the NHANES III survey (1988–1994) 
Economics and human biology  2007;5(2):179-203.
A growing body of literature has documented a link between neighborhood context and health outcomes. However, little is known about the relationship between neighborhood context and body mass index (BMI) or whether the association between neighborhood context and BMI differs by ethnicity. This paper investigates several neighborhood characteristics as potential explanatory factors for the variation of BMI across the United States; further, this paper explores to what extent segregation and the concentration of disadvantage across neighborhoods help explain ethnic disparities in BMI. Using data geo-coded at the census tract-level and linked with individual-level data from the Third National Health and Examination Survey in the United States (U.S.), we find significant variation in BMI across U.S. neighborhoods. In addition, neighborhood characteristics have a significant association with body mass and partially explain ethnic disparities in BMI, net of individual-level adjustments. These data also reveal evidence that ethnic enclaves are not in fact advantageous for the body mass index of Hispanics—a relationship counter to what has been documented for other health outcomes.
doi:10.1016/j.ehb.2007.03.006
PMCID: PMC2587036  PMID: 17507298
BMI; Weight; Obesity; NHANES; USA; Neighbourhood effects; Spatial analysis; Ethnicity; Social class
11.  Community Characteristics Associated with HIV Risk among Injection Drug Users in the San Francisco Bay Area: A Multilevel Analysis 
Community characteristics have been associated with racial and ethnic health disparities for a wide range of ailments and conditions. Previous research has found that rates of AIDS cases among injection drug users (IDUs) vary by community characteristics. However, few studies have examined whether community characteristics are associated with HIV risk behaviors among IDUs. To address this gap in the literature, we examined the associations between census-tract-level community characteristics and injection-related and sex-related HIV risk behaviors among IDUs in the San Francisco Bay Area. Individual HIV risk behaviors were collected from 4,956 IDUs between 1998 and 2002. Using 2000 US census data, we constructed four census-level community measures: percent African American, percent male unemployment, percent of households that receive public assistance, and median household income. All community variables were measured continuously. Multilevel modeling was used to determine if community characteristics were associated with recent (in the last 6 months) receptive and distributive syringe sharing, multiple sex partners, and unprotected sex risk while controlling for potential individual-level confounders. In bivariate analysis, most of the census-tract-level community characteristics were significantly associated with injection-related HIV risk, while no community characteristics were associated with sex-related risk. However, results from multivariate multilevel models indicate that only percent African American in a census tract was associated with receptive [adjusted odds ratio (AOR) = 0.93; 95% confidence interval (CI) = 0.89, 0.99] and distributive syringe sharing (AOR = 0.94; 95% CI = 0.92, 0.99), net of individual-level characteristics. Accounting for individual-level factors in the multivariate model in the sex-related risk models revealed a significant inverse relationship between percent African American and propensity to engage in unprotected sex (AOR = 0.95; 95% CI = 0.92, 0.99); community-level characteristics remained unassociated with multiple sex partners. In this exploratory analysis, percent African American in a census tract was inversely associated with injection-related risk. The census-tract-level community characteristics we examined seem to exert little influence on individual risk among long-term chronic IDUs. More research is needed examining the influence of other community characteristics that were unmeasured in this paper but might be related to sex and drug risk among IDUs such as shooting galleries, crack houses, drug markets, and availability of preventive HIV services.
doi:10.1007/s11524-007-9213-3
PMCID: PMC1988782  PMID: 17657607
Census data; Drug use; HIV/AIDS; Neighborhood; Risk factors
12.  Community Characteristics Associated with HIV Risk among Injection Drug Users in the San Francisco Bay Area: A Multilevel Analysis 
Community characteristics have been associated with racial and ethnic health disparities for a wide range of ailments and conditions. Previous research has found that rates of AIDS cases among injection drug users (IDUs) vary by community characteristics. However, few studies have examined whether community characteristics are associated with HIV risk behaviors among IDUs. To address this gap in the literature, we examined the associations between census-tract-level community characteristics and injection-related and sex-related HIV risk behaviors among IDUs in the San Francisco Bay Area. Individual HIV risk behaviors were collected from 4,956 IDUs between 1998 and 2002. Using 2000 US census data, we constructed four census-level community measures: percent African American, percent male unemployment, percent of households that receive public assistance, and median household income. All community variables were measured continuously. Multilevel modeling was used to determine if community characteristics were associated with recent (in the last 6 months) receptive and distributive syringe sharing, multiple sex partners, and unprotected sex risk while controlling for potential individual-level confounders. In bivariate analysis, most of the census-tract-level community characteristics were significantly associated with injection-related HIV risk, while no community characteristics were associated with sex-related risk. However, results from multivariate multilevel models indicate that only percent African American in a census tract was associated with receptive [adjusted odds ratio (AOR)=0.93; 95% confidence interval (CI)=0.89, 0.99] and distributive syringe sharing (AOR=0.94; 95% CI=0.92, 0.99), net of individual-level characteristics. Accounting for individual-level factors in the multivariate model in the sex-related risk models revealed a significant inverse relationship between percent African American and propensity to engage in unprotected sex (AOR=0.95; 95% CI=0.92, 0.99); community-level characteristics remained unassociated with multiple sex partners. In this exploratory analysis, percent African American in a census tract was inversely associated with injection-related risk. The census-tract-level community characteristics we examined seem to exert little influence on individual risk among long-term chronic IDUs. More research is needed examining the influence of other community characteristics that were unmeasured in this paper but might be related to sex and drug risk among IDUs such as shooting galleries, crack houses, drug markets, and availability of preventive HIV services.
doi:10.1007/s11524-007-9213-3
PMCID: PMC1988782  PMID: 17657607
Census data; Drug use; HIV/AIDS; Neighborhood; Risk factors

Results 1-12 (12)