{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:40:59Z","timestamp":1787013659012,"version":"build-2736575974"},"reference-count":109,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T00:00:00Z","timestamp":1633392000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Milbank Quarterly"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:sec>\n                    <jats:label\/>\n                    <jats:p>\n                      <jats:boxed-text content-type=\"box\" position=\"anchor\">\n                        <jats:caption>\n                          <jats:title>Policy Points<\/jats:title>\n                        <\/jats:caption>\n                        <jats:p>\n                          <jats:list list-type=\"bullet\">\n                            <jats:list-item>\n                              <jats:p>Policies that increase county income levels, particularly for middle\u2010income households, may reduce low birth weight rates and shrink disparities between Black and White infants.<\/jats:p>\n                            <\/jats:list-item>\n                            <jats:list-item>\n                              <jats:p>Given the role of aggregate maternal characteristics in predicting low birth weight rates, policies that increase human capital investments (e.g., funding for higher education, job training) could lead to higher income levels while improving population birth outcomes.<\/jats:p>\n                            <\/jats:list-item>\n                            <jats:list-item>\n                              <jats:p>The association between county income levels and racial disparities in low birth weight is independent of disparities in maternal risks, and thus a broad set of policies aimed at increasing income levels (e.g., income supplements, labor protections) may be warranted.<\/jats:p>\n                            <\/jats:list-item>\n                          <\/jats:list>\n                        <\/jats:p>\n                      <\/jats:boxed-text>\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Context<\/jats:title>\n                    <jats:p>Low birth weight (LBW; &lt;2,500 grams) and infant mortality rates vary among place and racial group in the United States, with economic resources being a likely fundamental contributor to these disparities. The goals of this study were to examine time\u2010varying county median income as a predictor of LBW rates and Black\u2010White LBW disparities and to test county prevalence and racial disparities in maternal sociodemographic and health risk factors as mediators.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Using national birth records for 1992\u20132014 from the National Center for Health Statistics, a total of approximately 27.4 million singleton births to non\u2010Hispanic Black and White mothers were included. Data were aggregated in three\u2010year county\u2010period observations for 868 US counties meeting eligibility requirements (\n                      <jats:italic>n<\/jats:italic>\n                      = 3,723 observations). Sociodemographic factors included rates of low maternal education, nonmarital childbearing, teenage pregnancy, and advanced\u2010age pregnancy; and health factors included rates of smoking during pregnancy and inadequate prenatal care. Among other covariates, linear models included county and period fixed effects and unemployment, poverty, and income inequality.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      An increase of $10,000 in county median income was associated with 0.34 fewer LBW cases per 100 live births and smaller Black\u2010White LBW disparities of 0.58 per 100 births. Time\u2010varying county rates of maternal sociodemographic and health risks mediated the association between median income and LBW, accounting for 65% and 25% of this estimate, respectively,\n                      <jats:italic>but<\/jats:italic>\n                      racial disparities in risk factors did not mediate the income association with Black\u2010White LBW disparities. Similarly, county median income was associated with very low birth weight rates and related Black\u2010White disparities.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Efforts to increase income levels\u2014for example, through investing in human capital, enacting labor union protections, or attracting well\u2010paying employment\u2014have broad potential to influence population reproductive health. Higher income levels may reduce LBW rates and lead to more equitable outcomes between Black and White mothers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/1468-0009.12532","type":"journal-article","created":{"date-parts":[[2021,10,7]],"date-time":"2021-10-07T12:10:48Z","timestamp":1633608648000},"page":"38-77","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Does a Rising Median Income Lift All Birth Weights? 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