Evidence map›Paper›PMID 36061950›Full record

ArticleSpatial demography2022

Decomposing County-Level Working-Age Mortality Trends in the United States Between 1999-2001 and 2015-2017.

Nick Graetz, Irma T Elo

Abstract read
In one paragraph

Article in Spatial demography, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  4. Observational
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  8. Evolution of the US nonmetropolitan mortality disadvantage by sex, state, and year, 1999-2019.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2025
    Article
  9. Article
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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

2 authors.

Nick GraetzPopulation Studies Center, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104, USA.ORCID 0000-0002-4362-2059
Irma T EloPopulation Studies Center, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104, USA.

Funding

Infrastructure for Population Research at PrincetonR24HD047879 · NICHD · PRINCETON UNIVERSITY · PI MASSEY, DOUGLAS S · 2004 to 2013
$7.3M
GRADUATE TRAINING IN DEMOGRAPHYT32HD007242 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI MICHEL GUILLOT · 1985 to 2026
$6.6M
Scientific and Technical Computing CoreP2CHD047879 · NICHD · PRINCETON UNIVERSITY · PI MASSEY, DOUGLAS S · 2014 to 2018
$2.0M
Causes of Geographic Divergence in American Mortality Between 1990 and 2015: Health Behaviors, Health Care Access and MigrationR01AG060115 · NIA · UNIVERSITY OF PENNSYLVANIA · PI ELO, IRMA T. · 2018 to 2022
$1.9M
NIA NIH HHS R01 AG060115NICHD NIH HHS P2C HD047879NICHD NIH HHS R24 HD047879NICHD NIH HHS T32 HD007242
6 · The paper itself

Abstract

Studies have documented significant geographic divergence in U.S. mortality in recent decades. However, few studies have examined the extent to which county-level trends in mortality can be explained by national, state, and metropolitan-level trends, and which county-specific factors contribute to remaining variation. Combining vital statistics data on deaths and Census data with time-varying county-level contextual characteristics, we use a spatially explicit Bayesian hierarchical model to analyze the associations between working-age mortality, state, metropolitan status and county-level socioeconomic conditions, family characteristics, labor market conditions, health behaviors, and population characteristics between 2000 and 2017. Additionally, we employ a Shapley decomposition to illustrate the additive contributions of each changing county-level characteristic to the observed mortality change in U.S. counties between 1999-2001 and 2015-2017 over and above national, state, and metropolitan-nonmetropolitan mortality trends. Mortality trends varied by state and metropolitan status as did the contribution of county-level characteristics. Metropolitan status predicted more of the county-level variance in mortality than state of residence. Of the county-level characteristics, changes in percent college-graduates, smoking prevalence and the percent of foreign-born population contributed to a decline in all-cause mortality over this period, whereas increasing levels of poverty, unemployment, and single-parent families and declines manufacturing employment slowed down these improvements, and in many nonmetropolitan areas were large enough to overpower the positive contributions of the protective factors.

Indexed as

County-level characteristicsDecompositionGeographic inequalitySpatial statisticsWorking-age mortality

Identifiers

PMID36061950
PMCPMC9435968

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.