Evidence map›Paper›PMID 39310815›Full record

ArticleSocial science history2023

Wealth and Child Mortality in the Nineteenth-Century United States: Evidence from Three Panels of American Couples, 1850-1880.

J David Hacker, Martin Dribe, Jonas Helgertz

Abstract read
In one paragraph

Article in Social science history, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

J David HackerInstitute for Social Research and Data Innovation, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-5971-955X
Martin DribeDepartment of Economic History and Centre for Economic Demography, Lund University, Lund, Sweden.ORCID 0000-0003-2340-4668
Jonas HelgertzInstitute for Social Research and Data Innovation, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-2200-9095

Funding

Multigenerational Longitudinal Panel for Research on AgingR01AG057679 · NIA · UNIVERSITY OF MINNESOTA · PI Julia AR Drew, Steve Ruggles · 2018 to 2026
$10.0M
Minnesota Population Center Science and Technical CoreP2CHD041023 · NICHD · UNIVERSITY OF MINNESOTA · PI THERESA LOUISE OSYPUK · 2016 to 2026
$4.3M
Models of Demographic and Health Changes following Military ConflictR01HD082120 · NICHD · UNIVERSITY OF MINNESOTA · PI HACKER, J. DAVID · 2015 to 2019
$2.9M
NIA NIH HHS R01 AG057679NICHD NIH HHS P2C HD041023NICHD NIH HHS R01 HD082120
6 · The paper itself

Abstract

With only a few exceptions, the historical study of individual-level correlates of child mortality in the United States has been limited to the period surrounding the turn of the twentieth century, when children ever born and children surviving data collected by the 1900 and 1910 censuses allow indirect estimation of child mortality. The recent release of linked census data, such as the IPUMS MLP datasets, allows a different type of indirect estimation over a longer period. By following couples across subsequent decennial censuses, it is possible to infer child mortality by measuring whether couples' own children in the first census were still present in the second census. We focus our analysis on children aged 1-3 in the first of two linked censuses, who were less likely to be undercounted by the census than infants, and unlikely to be living apart from their parents in the second census. We estimate child mortality over the intervening decade and use OLS regression to correlate that mortality to the residence location and socioeconomic characteristics of their parents' households. We limit our analysis to three panel datasets for married couples linked between the 1850-60, 1860-70, and 1870-80 censuses, when real estate and personal estate wealth data were collected. Our results indicate a significant negative relationship between wealth and child mortality across all regions of the United States and over the entire period examined.

Identifiers

PMID39310815
PMCPMC11415258

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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.