Biomedical subjects

Stephanie A Robert

Publications and source records attributed to Stephanie A Robert.

5 recordsLinked to original sources

PubMed2006

Racial segregation and health disparities between Black and White older adults.

OBJECTIVES: In this study, we examined whether racial segregation is associated with poorer self-rated health among older adults, and whether racial segregation helps explain race disparities in self-rated health between Black and White older adults. METHODS: We used multilevel data at the individual, neighborhood (tract), and county levels, from two national surveys-the Americans' Changing Lives (ACL) survey and the National Survey of Families and Households (NSFH). We used hierarchical linear models in order to regress self-rated health on county-, neighborhood-, and individual-level racial and socioeconomic variables. RESULTS: In the NSFH, there was an association between county racial segregation and poorer self-rated health among White but not Black older adults (net of county percent Black and percent poverty). In the ACL, there was no statistically significant association between racial segregation and self-rated health. In the NSFH, there was some indication that Black older adults had better self-rated health when living in neighborhoods with a higher percentage of Black residents than the county percentage. DISCUSSION: Although aggregate-level studies demonstrate associations between racial segregation and mortality rates, our multilevel analyses with two national data sets suggest only weak associations between racial segregation and self-rated health. However, socioeconomic status at multiple levels contributes to race disparities in health.

Aged↗

PubMed2004

A multilevel analysis of race, community disadvantage, and body mass index among adults in the US.

This study examined the contributions of both individual socioeconomic status (SES) and community disadvantage in explaining the higher body mass index (BMI) of black adults in the US. Data from a national survey of adults (1986 American's Changing Lives Study) were combined with tract-level community data from the 1980 census. Results of multilevel regression analyses showed that black women had an age-adjusted BMI score three points higher than non-black women. Individual SES (income, education, assets) was negatively associated with BMI in women, but it only reduced the association between race and BMI from 2.99 to 2.50. Adding community socioeconomic disadvantage index further reduced the race coefficient slightly from 2.50 to 2.21. Nevertheless, living in communities with higher socioeconomic disadvantage was associated with higher BMI net of age, race, individual SES, smoking, physical activity, stress, and social support. Community income inequality (Gini) had an independent positive association with BMI, but did not substantially reduce racial differences among women. Community percent black was not associated with BMI. Results for men demonstrated no statistically significant racial differences in BMI, and no association between BMI and either individual SES or community disadvantage. Although individual SES and community socioeconomic disadvantage each partly explained the higher average BMI among black women, clear racial disparities persisted. Moreover, race, individual SES, community socioeconomic disadvantage, and individual health behaviors were each independent predictors of BMI among women. Unexplained within- and between-community variance in BMI remained among both women and men, with most unexplained variation due to within-community variance. Because our evidence for women suggests that the determinants of obesity are multiple and multilevel, attempts to address this growing social problem will similarly require a multi-faceted and multilevel approach.

Adult↗

PubMed2004

Socioeconomic risk factors for breast cancer: distinguishing individual- and community-level effects.

BACKGROUND: Women are at higher risk of breast cancer if they have higher socioeconomic status (SES) or live in higher SES or urban communities. We examined whether women living in such communities remained at greater risk of breast cancer after controlling for individual education and other known individual-level risk factors. METHODS: Data were from a population-based, breast cancer case-control study conducted in Wisconsin from 1988 to 1995 (n = 14,667). Data on community SES and urbanicity come from the 1990 census, measured at the census tract and zip code levels. We evaluated relationships between individual- and community-level variables and breast cancer risk using multilevel logistic regression models with random community intercepts. RESULTS: After controlling for individual education and other individual-level risk factors (age, mammography use, family history of breast cancer, parity, age at first birth, alcohol intake, body mass index, hormone replacement use, oral contraceptive use, and menopausal status), women living in the highest SES communities had greater odds of having breast cancer than women living in the lowest SES communities (1.20; 95% confidence interval = 1.05-1.37). Similarly, the odds were greater for women in urban versus rural communities (1.17; 1.06-1.28). CONCLUSIONS: Community SES and urbanicity are apparently not simply proxies for individual SES. Future research should examine why living in such communities itself is associated with greater risk of breast cancer.

Adult↗

PubMed2004

Potential exposure to PCBs, DDT, and PBDEs from sport-caught fish consumption in relation to breast cancer risk in Wisconsin.

In Wisconsin, consumption of Great Lakes fish is an important source of exposure to polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethane (DDT), polybrominated diphenyl ethers (PBDEs), and other halogenated hydrocarbons, all of which may act as potential risk factors for breast cancer. We examined the association between sport-caught fish consumption and breast cancer incidence as part of an ongoing population-based case-control study. We identified breast cancer cases 20-69 years of age who were diagnosed in 1998-2000 (n = 1,481) from the Wisconsin Cancer Reporting System. Female controls of similar age were randomly selected from population lists (n = 1,301). Information about all sport-caught (Great Lakes and other lakes) fish consumption and breast cancer risk factors was obtained through telephone interviews. After adjustment for known and suspected risk factors, the relative risk of breast cancer for women who had recently consumed sport-caught fish was similar to women who had never eaten sport-caught fish [relative risk (RR) = 1.00; 95% confidence interval (CI), 0.86-1.17]. Frequency of consumption and location of sport-caught fish were not associated with an increased risk of breast cancer. Recent consumption of Great Lakes fish was not associated with postmenopausal breast cancer (RR = 0.78; 95% CI, 0.57-1.07), whereas risk associated with premenopausal breast cancer was elevated (RR = 1.70; 95% CI, 1.16-2.50). In this study we found no overall association between recent consumption of sport-caught fish and breast cancer, although there may be an increased breast cancer risk for subgroups of women who are young and/or premenopausal.

Adult↗

PubMed2003

Geocoding addresses from a large population-based study: lessons learned.

BACKGROUND: Geographic information systems (GIS) and spatial statistics are useful for exploring the relation between geographic location and health. The ultimate usefulness of GIS depends on both completeness and accuracy of geocoding (the process of assigning study participants' residences latitude/longitude coordinates that closely approximate their true locations, also known as address matching). The goal of this project was to develop an iterative geocoding process that would achieve a high match rate in a large population-based health study. METHODS: Data were from a study conducted in Wisconsin using mailing addresses of participants who were interviewed by telephone from 1988 to 1995. We standardized the addresses according to US Postal Service guidelines, used desktop GIS geocoding software and two versions of the Topologically Integrated Geographic Encoding and Referencing street maps, accessed Internet mapping engines for problematic addresses, and recontacted a small number of study participants' households. We also tabulated the project's cost, time commitment, software requirements, and brief notes for each step and their alternatives. RESULTS: Of the 14,804 participants, 97% were ultimately assigned latitude/longitude coordinates corresponding to their respective residences. The remaining 3% were geocoded to their zip code centroid. CONCLUSION: The multiple methods described in this work provide practical information for investigators who are considering the use of GIS in their population health research.

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