Evidence map›Paper›PMID 25931988›Full record

ArticlePopulation health metrics2015

The County Health Rankings: rationale and methods.

Patrick L Remington, Bridget B Catlin, Keith P Gennuso

Open access · goldAbstract read
In one paragraph

Article in Population health metrics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 189 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
189citing papers in PubMed, 2 pooled it
37.8field-weighted citation impact, top 1% of its field
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

189 citing papers in PubMed, 2 syntheses or guidelines pooled it, 379 citations in OpenAlex.

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  17. Social determinants of health and type 2 diabetes in Asia.Journal of diabetes investigation · 2025
    Review
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129 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Patrick L RemingtonDepartment of Population Health Sciences, University of Wisconsin-Madison, 4263 Health Sciences Learning Center, 750 Highland Ave, Madison, WI 53705 USA.
Bridget B CatlinUniversity of Wisconsin Population Health Institute, University of Wisconsin-Madison, 505 WARF Office Building, 610 Walnut St., Madison, WI 53726 USA.
Keith P GennusoUniversity of Wisconsin Population Health Institute, University of Wisconsin-Madison, 575C WARF Office Building, 610 Walnut St., Madison, WI 53726 USA.
University of Wisconsin Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnnually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings-a "population health checkup" for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities.

methodsWe base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state.

resultsHealth outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. DISCUSSION: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community.

Indexed as

Health rankingsPopulation healthPublic health surveillance

Identifiers

PMID25931988
PMCPMC4415342
OpenAlexW1973853472

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.