The Relationship of Neighborhood Socioeconomic Characteristics to Birthweight Among 5 Ethnic Groups in California

Pearl, Michelle; Braveman, Paula; Abrams, Barbara

doi:10.2105/ajph.91.11.1808

Cited by 250 publications

(185 citation statements)

References 36 publications

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“…Additionally, neighborhood SE characteristics were measured at a census tract‐level rather than census block‐level due to insufficient number of cases at these two neighborhood levels. However, prior studies showed that lag‐times up to several years61 and whether census tract or census block aggregate data are used are unlikely to affect observed relationships, because socioeconomic conditions tend to be generally stable over several years, and block‐level SE measures are quite similar within tracts 34, 61…”

Section: Discussionmentioning

confidence: 99%

“…Residential addresses of cases were geocoded using ArcGIS software program30 and were linked to information corresponding to later specified census tract SE variables based on unique census tract numbers. The following SE status components,2 measured at census‐tract level (which we will refer to as “neighborhood”), and previously associated with health outcomes31, 32, 33, 34, 35, 36 were included: percentage of population who indicated their race as white; median household income (MHI) as inflation adjusted dollars; percentage of population classified as rural; and percentage of population aged 25 years and over without some college education (Table 1). …”

Section: Methodsmentioning

confidence: 99%

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Regional socioeconomic disparities in outcomes for workers with low back pain in the United States

Shraim

Cifuentes

Willetts

et al. 2017

American J Industrial Med

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BackgroundAlthough regional socioeconomic (SE) factors have been associated with worse health outcomes, prior studies have not addressed important confounders or work disability.MethodsA national sample of 59 360 workers’ compensation (WC) cases to evaluate impact of regional SE factors on medical costs and length of disability (LOD) in occupational low back pain (LBP).ResultsLower neighborhood median household incomes (MHI) and higher state unemployment rates were associated with longer LOD. Medical costs were lower in states with more workers receiving Social Security Disability, and in areas with lower MHI, but this varied in magnitude and direction among neighborhoods. Medical costs were higher in more urban, more racially diverse, and lower education neighborhoods.ConclusionsRegional SE disparities in medical costs and LOD occur even when health insurance, health care availability, and indemnity benefits are similar. Results suggest opportunities to improve care and disability outcomes through targeted health care and disability interventions.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Regional socioeconomic disparities in outcomes for workers with low back pain in the United States

Shraim

Cifuentes

Willetts

et al. 2017

American J Industrial Med

View full text Add to dashboard Cite

show abstract

“…19 However, several recent studies have shown a relationship between neighborhood characteristics and maternal/infant health outcomes or other health outcomes, independent of individual characteristics. [20][21][22][23][24][25][26][27][28] For example, Perloff and Jaffee found that residence in a distressed urban neighborhood significantly increased the risk of late prenatal care, even after controlling for maternal risk. 25 O'Campo and others found that women living in high-risk neighborhoods benefited less from prenatal care than other women.…”

Section: Methodsmentioning

confidence: 99%

“…26 Pearl and others found that residents of less favorable neighborhoods had lower-birthweight infants. 27 There are numerous ways that neighborhoods could directly affect health, including factors such as crime or environmental pollution. Most of the previous neighborhood-level studies are based on data from the l980s and early l990s.…”

Section: Methodsmentioning

confidence: 99%

Trends in Maternal and Infant Health in Poor Urban Neighborhoods: Good News from the 1990s, but Challenges Remain

2005

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Objectives. During the 1990s, numerous public policy changes occurred that may have affected the health of mothers and infants in low-income neighborhoods. This article examines trends in key maternal and child health indicators to determine whether disparities between high-poverty neighborhoods and other neighborhoods have declined. Methods. Using neighborhood-level vital statistics and U.S. Census data, we categorized “neighborhoods” (Census tracts) as being high poverty (greater than 30% of population below the federal poverty level in 1990) or not. We compared trends in four key indicators—births to teenagers, late prenatal care, low birthweight; and infant mortality—over the 1990s among high-poverty and other neighborhoods in Cuyahoga County, Ohio; Denver, Colorado; Marion County, Indiana; and Oakland, California. Results. In all four metropolitan areas, trends in high-poverty neighborhoods were more favorable than in other neighborhoods. The most consistently positive trend was the reduction in the rate of teen births. The metropolitan areas with the most intensive programs to improve maternal and child health—Cuyahoga County and Oakland—saw the most consistent improvement across all indicators. Still, great disparities between high-poverty and other neighborhoods remain, and only Oakland shows promise of achieving some of the Healthy People 2010 maternal and child health goals in its high-poverty neighborhoods. Conclusions. While there has been a reduction in maternal and infant health disparities between high-poverty and other neighborhoods, much work remains to eliminate disparities and achieve the 2010 goals. Small area data are useful in isolating the neighborhoods that should be targeted. Experience from the 1990s suggests that a combination of several intensive interventions can be effective at reducing disparities.

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“…The methodology of geocoding residential addresses by linking them to U.S Census Bureau data and then using areabased socioeconomic measures in the study of health related outcomes has been extensively employed as a relatively inexpensive solution to the absence of population based, selfreported data socioeconomic status (SES) data including race/ethnicity, income and education [13,14]. Residential addresses may be linked at different geographic levels that by size, and include zip code, census tract, and census block.…”

Section: Introductionmentioning

confidence: 99%

Variation in Hispanic Self-Identification, Spanish Surname, and Geocoding: Implications for Ethnicity Data Collection

Ritzwoller¹,

Carroll²,

Gaglio³

et al. 2008

TOHSPJ

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This study examines the variation in surname analysis and geocoding, and their association with self-identified Hispanics in an HMO. We collected ethnicity data from three studies, and employed Spanish surname software and census tract level geocoding to create proxies for Hispanic ethnicity. We computed sensitivity, specificity, and estimated multivariate logistic regression models to examine the variation in the likelihood of a match between self-identified Hispanics and surname. Sensitivity and specificity with respect to surname varied across the three studies, ranging from 57%-91% and 89%-96%, respectively. Relative to self-report, the sensitivity of the census tract measure of density of Hispanics, varied from 5%-15%. Multivariate models suggest that the likelihood of a match between self-identified Hispanics and surname was not associated with age or gender. Self-identified Hispanics living in neighborhoods with the highest density of Hispanics were less likely than those in more mixed neighborhoods to have a Spanish surname. Employing the Spanish surname software on only densely populated Hispanic census tracts may not always improve the likelihood of correctly identifying Hispanic subjects.

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The Relationship of Neighborhood Socioeconomic Characteristics to Birthweight Among 5 Ethnic Groups in California

Abstract: In addition to individual socioeconomic characteristics, living in neighborhoods that are less socioeconomically advantaged may differentially influence birthweight, depending on women's ethnicity and nativity.

Cited by 250 publications

References 36 publications

Regional socioeconomic disparities in outcomes for workers with low back pain in the United States

Regional socioeconomic disparities in outcomes for workers with low back pain in the United States

Trends in Maternal and Infant Health in Poor Urban Neighborhoods: Good News from the 1990s, but Challenges Remain

Variation in Hispanic Self-Identification, Spanish Surname, and Geocoding: Implications for Ethnicity Data Collection

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