Evidence map›Paper›PMID 31050636›Full record

ArticlePreventing chronic disease2019

Identifying County-Level All-Cause Mortality Rate Trajectories and Their Spatial Distribution Across the United States.

Peter Baltrus, Khusdeep Malhotra, George Rust, Robert Levine, Chaohua Li, Anne H Gaglioti

Abstract readComparative Study
In one paragraph

Article in Preventing chronic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Observational
  2. Article
  3. Mortality during Resource Booms and Busts.Journal of environmental economics and management · 2022
    Article
  4. County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health.International journal of environmental research and public health · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

6 authors.

Peter BaltrusNational Center for Primary Care, Morehouse School of Medicine, Atlanta, Georgia.
Khusdeep MalhotraGeography and Urban Studies, Temple University, Philadelphia, Pennsylvania.
George RustDepartment of Behavioral Sciences and Social Medicine, Florida State University School of Medicine, Tallahassee, Florida.
Robert LevineDepartment of Family and Community Medicine, Baylor College of Medicine, Houston, Texas.
Chaohua LiNational Center for Primary Care, Morehouse School of Medicine, Atlanta, Georgia.
Anne H GagliotiNational Center for Primary Care, Morehouse School of Medicine, Atlanta, Georgia.

Funding

Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
Research Desogn and Biostatistics CoreU54MD007588 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI MAYBERRY, ROBERT M · 2012 to 2018
$24.8M
Women's Health Intervention StudyP20MD006881 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI AKINTOBI, TABIA HENRY · 2012 to 2016
$6.0M
Renewal Application for Clinical Research Education and Career Development (CRECDR25MD007589 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI PRISCILLA E PEMU, Alexander Quarshie · 2012 to 2026
$5.4M
NCATS NIH HHS UL1 TR002378NIMHD NIH HHS P20 MD006881NIMHD NIH HHS R25 MD007589NIMHD NIH HHS U54 MD007588
6 · The paper itself

Abstract

introductionAll-cause mortality in the United States declined from 1935 through 2014, with a recent uptick in 2015. This national trend is composed of disparate local trends. We identified distinct groups of all-cause mortality rate trajectories by grouping US counties with similar temporal trajectories.

methodsWe used all-cause mortality rates in all US counties for 1999 through 2016 and estimated discrete mixture models by using county level mortality rates. Proc Traj in SAS was used to detect how county trajectories clustered into groups on the basis of similar intercepts, slopes, and higher order terms. Models with increasing numbers of groups were assessed on the basis of model fit. We created county-level maps of mortality trajectory groups by using ArcGIS.

resultsEight unique trajectory groups were detected among 3,091 counties. The average mortality rate in the most favorable trajectory group declined 29.4%, from 592.3 deaths per 100,000 in 1999 to 418.2 in 2016. The least favorable mortality trajectory group declined 3.4% over the period, from 1,280.3 deaths per 100,000 to 1,236.9. We saw significant differences in the demographic and socioeconomic profiles and geographic patterns across the trajectory categories, with favorable mortality trajectories in the Northeast, Midwest, and on the West Coast and unfavorable trajectories concentrated in the Southeast.

conclusionsCounty-level disparities in all-cause mortality rates widened over the past 18 years. Further investigation of the determinants of the trajectory groupings and the geographic outliers identified by our research could inform interventions to achieve equitable distribution of county mortality rates.

Indexed as

GeographyLocal GovernmentCause of DeathForecastingHumansMortalitySocioeconomic FactorsUnited States

Identifiers

PMID31050636
PMCPMC6513472

What OpenQuestion holds

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LicenceCC BY
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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.