Evidence map›Paper›PMID 40752241›Full record

ArticleSocial science & medicine (1982)2025

Sex-selective abortion bans and the birth outcomes of Asian immigrants.

Emma Zang, Keitaro Okura, Melissa Tian

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Emma ZangDepartment of Sociology, Yale University, New Haven, CT, USA. Electronic address: emma.zang@yale.edu.
Keitaro OkuraDepartment of Sociology, Yale University, New Haven, CT, USA.
Melissa TianDepartment of Sociology, Yale University, New Haven, CT, USA.

Funding

Yale Study Support Suite (YES3): Dashboard and Web Portal Software Supporting Research Workflow through integrated, customizable REDCap External ModulesP30AG021342 · NIA · YALE UNIVERSITY · PI Albert C Shaw · 2002 to 2026
$37.9M
Linked Lives, Linked Health: Health Trajectories of Persons with Cognitive Impairment and Their Caregivers' HealthR21AG074238 · NIA · YALE UNIVERSITY · PI ZANG, EMMA · 2021 to 2022
$473k
NIA NIH HHS P30 AG021342NIA NIH HHS R21 AG074238
6 · The paper itself

Abstract

The pro-life movement in the United States has achieved significant legislative victories in restricting abortion access. Among these, sex-selective abortion bans (SSABs)-prohibitions on abortions sought based on fetal sex-have garnered little scholarly attention. Advocates of SSABs often invoke xenophobic stereotypes, claiming that Asian immigrants hold a cultural preference for sons and engage in sex-selective abortions of female fetuses. This study examines the impact of SSABs on Asian immigrant mothers' birth outcomes, hypothesizing that these laws foster a stigmatizing social climate that exacerbates maternal stress and adversely affects infant health. Using natality data from the National Vital Statistics System (2005-2019) and a triple-difference approach, we find that SSABs significantly increased the likelihood of low birth weight and preterm births among infants born to Asian immigrant mothers. These findings highlight the broader health consequences of policies rooted in xenophobia, underscoring the need for nuanced policy discussions surrounding abortion access, anti-Asian hate, and immigrant well-being in the United States.

Indexed as

Abortion, InducedAsianEmigrants and ImmigrantsPregnancy OutcomeAdultFemaleHumansInfant, NewbornMalePregnancyPremature BirthUnited StatesAbortion bansAsian immigrantsPopulation healthSocial determinantsStructural racismXenophobia

Identifiers

PMID40752241
PMCPMC12362279

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.