Evidence map›Paper›PMID 27453928›Full record

ArticleSSM - population health2016

Reproductive justice & preventable deaths: state funding, family planning, abortion, and infant mortality, US 1980-2010.

Nancy Krieger, Sofia Gruskin, Nakul Singh, Mathew V Kiang, Jarvis T Chen, Pamela D Waterman, Jason Beckfield, Brent A Coull

Abstract read
In one paragraph

Article in SSM - population health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Laws Restricting Access to Abortion Services and Infant Mortality Risk in the United States.International journal of environmental research and public health · 2020
    Article
  8. Article
  9. Article
  10. Article
  11. Article
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

8 authors.

Nancy KriegerDept of Social and Behavioral Sciences (SBS), Harvard T. H. Chan School of Public Health (HSPH), Boston, MA (USA).
Sofia GruskinProgram on Global Health and Human Rights, Institute for Global Health, Keck School of Medicine; Gould School of Law, University of Southern California, Los Angeles, CA.
Nakul SinghDept of Biostatistics, Harvard T. H. Chan School of Public Health (HSPH), Boston, MA (USA).
Mathew V KiangDept of Social and Behavioral Sciences (SBS), Harvard T. H. Chan School of Public Health (HSPH), Boston, MA (USA).
Jarvis T ChenDept of Social and Behavioral Sciences (SBS), Harvard T. H. Chan School of Public Health (HSPH), Boston, MA (USA).
Pamela D WatermanDept of Social and Behavioral Sciences (SBS), Harvard T. H. Chan School of Public Health (HSPH), Boston, MA (USA).
Jason BeckfieldDept of Sociology, Harvard University, Cambridge, MA.
Brent A CoullDept of Biostatistics, Harvard T. H. Chan School of Public Health (HSPH), Boston, MA (USA).

Funding

Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
Statistical Methods for the Spatio-Temporal Assessment of Social Disparities in CancerP01CA134294 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANEUSE, SEBASTIEN, HERNAN, MIGUEL · 2008 to 2017
$6.8M
Jim Crow & health disparities: exploring age-period-cohort effectsR21CA168470 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI KRIEGER, NANCY · 2012 to 2013
$450k
NCI NIH HHS P01 CA134294NCI NIH HHS R21 CA168470NCI NIH HHS R35 CA197449
6 · The paper itself

Abstract

introductionLittle current research examines associations between infant mortality and US states' funding for family planning services and for abortion, despite growing efforts to restrict reproductive rights and services and documented associations between unintended pregnancy and infant mortality. MATERIAL AND

methodsWe obtained publicly available data on state-only public funding for family planning and abortion services (years available: 1980, 1987, 1994, 2001, 2006, and 2010) and corresponding annual data on US county infant death rates. We modeled the funding as both fraction of state expenditures and per capita spending (per woman, age 15-44). State-level covariates comprised: Title X and Medicaid per capita funding, fertility rate, and percent of counties with no abortion services; county-level covariates were: median family income, and percent: black infants, adults without a high school education, urban, and female labor force participation. We used Possion log-linear models for: (1) repeat cross-sectional analyses, with random state and county effects; and (2) panel analysis, with fixed state effects.

resultsFour findings were robust to analytic approach. First, since 2000, the rate ratio for infant death comparing states in the top funding quartile vs. no funding for abortion services ranged (in models including all covariates) between 0.94 to 0.98 (95% confidence intervals excluding 1, except for the 2001 cross-sectional analysis, whose upper bound equaled 1), yielding an average 15% reduction in risk (range: 8 to 22%). Second, a similar risk reduction for state per capita funding for family planning services occurred in 1994. Third, the excess risk associated with lower county income increased over time, and fourth, remained persistently high for counties with a high percent of black infants.

conclusionsInsofar as reducing infant mortality is a government priority, our data underscore the need, despite heightened contention, for adequate public funding for abortion services and for redressing health inequities.

Indexed as

abortionfamily planninghealth inequitiesinfant mortalityreproductive justicesocial policy

Identifiers

PMID27453928
PMCPMC4950871

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.