“fertility rates in states with abortion bans were higher than would have been expected in the absence of these policies, with the largest estimated differences among subpopulations experiencing the greatest structural disadvantages and in states with among the worst maternal and child health and well-being outcomes” Bell, Frank & al., JAMA, 13 Feb 2025
“The groups that are most likely to have children as a result of abortion bans are also individuals who are most likely, for a number of different reasons, to have higher rates of infant mortality,” THYT, 13 Feb 2025
“Infant mortality in Texas was 9.4 percent higher after abortion bans were implemented than would have been expected” THYT, 13 Feb 2025
“Evidence suggests that increases in the fertility rate due to abortion bans were especially large among people who experienced structural disadvantage, including racially minoritized individuals, those without a college degree, and individuals using public health insurance3—all groups with higher infant mortality rates.” Gemmil, Frank & al., JAMA, 13 Feb 2025
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This entry was posted on February 26, 2025 at 12:25 am and is filed under Books, Kids, Statistics with tags abortion, abortion ban, Bayesian hierarchical causal model, Bayesian hierarchical model, causality, Donald Trump, infant mortality, maternal mortality, my body my choice, panel data, Poisson factor model, posterior predictive check, Protect Abortion, reproductive rights, Roe v. Wade, social disparities, Stand Up To Trump, Supreme Court, Texas, The New York Times, US politics. You can follow any responses to this entry through the RSS 2.0 feed.
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