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"Fusing science and social justice, renowned public health researcher Dr. Arline T. Geronimus offers an urgent book exploring the ways in which systemic injustice erodes the health of marginalized people"--
Equality --- Ethnic and Racial Minorities. --- Health Inequities. --- Health --- MEDICAL / Public Health. --- Poverty --- Poverty. --- Racism in medicine --- Racism in medicine. --- Racism --- Racism. --- SOCIAL SCIENCE / Discrimination. --- SOCIAL SCIENCE / Disease & Health Issues. --- SOCIAL SCIENCE / Social Classes & Economic Disparity. --- Social Determinants of Health. --- Systemic Racism. --- Health aspects --- Health aspects. --- Social aspects --- Social aspects. --- United States. --- Sociology of health --- United States of America
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Teen childbearing is commonly viewed as an irrational behavior that leads to long-term socioeconomic disadvantage for mothers and their children. Cross-sectional studies that estimate relationships between maternal age at first birth and socioeconomic indicators measured later in life form the empirical basis for this view. However1 these studies have failed to account adequately for differences in family background among women who time their births at different ages. We present new estimates of the consequences of teen childbearing that take into account observed and unobserved family background heterogeneity, comparing sisters who have timed their first births at different ages. Sister comparisons suggest that previous estimates are biased by failure to control adequately for family background heterogeneity, and, as a result, have overstated the consequences of early fertility.
Teenage pregnancy --- Teenage mothers --- Poor teenagers --- Economic aspects. --- Economic conditions. --- Social conditions.
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Investigators of social differentials in health outcomes commonly augment incomplete micro data by appending socioeconomic characteristics of residential areas (such as median income in a zip code) to proxy for individual characteristics. However, little empirical attention has been paid to how well this aggregate information serves as a proxy for the individual characteristics of interest. We build on recent work addressing the biases inherent in proxies and consider two health-related examples within a statistical framework that illuminate the nature and sources of biases. Data from the Panel Study of Income Dynamics and the National Maternal and Infant Health Survey are linked to census data. We assess the validity of using the aggregate census information as a proxy for individual information when estimating main effects, and when controlling for potential confounding between socioeconomic and sociodemographic factors in measures of general health status and infant mortality. We find a general, but not universal, tendency for aggregate proxies to exaggerate the effects of micro-level variables and to do more poorly than micro-level variables at controlling for confounding. The magnitude and direction of these biases, however, vary across samples. Our statistical framework and empirical findings suggest the difficulties in and limits to interpreting proxies derived from aggregate census data as if they were micro-level variables. The statistical framework we outline for our study of health outcomes should be generally applicable to other situations where researchers have merged aggregate data with micro data samples.
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