Evidence map›Paper›PMID 35709356›Full record

ArticlePreventing chronic disease2022

PLACES: Local Data for Better Health.

Kurt J Greenlund, Hua Lu, Yan Wang, Kevin A Matthews, Jennifer M LeClercq, Benjamin Lee, Susan A Carlson

Abstract read
In one paragraph

Article in Preventing chronic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 1 pooled it
–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

56 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Ambient Air Pollution and COVID-19 in California.Research report (Health Effects Institute) · 2026
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  18. Circadian-informed modeling predicts regional variation in obesity and stroke outcomes under different permanent US time policies.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  20. A Longitudinal Ecologic Analysis of Neighborhood-Level Social Inequalities in Health in Texas.International journal of environmental research and public health · 2025
    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

7 authors.

Kurt J GreenlundDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, MS S107-6, Atlanta GA 30341. Email: Keg9@cdc.gov.
Hua LuDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Yan WangDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Kevin A MatthewsDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Jennifer M LeClercqDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
Benjamin LeeOak Ridge Institute for Science and Education, Research Participation Program, Division of Population Health, Centers for Disease Control and Prevention, Atlanta, Georgia.
Susan A CarlsonDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Local-level data on the health of populations are important to inform and drive effective and efficient actions to improve health, but such data are often expensive to collect and thus rare. Population Level Analysis and Community EStimates (PLACES) (www.cdc.gov/places/), a collaboration between the Centers for Disease Control and Prevention (CDC), the Robert Wood Johnson Foundation, and the CDC Foundation, provides model-based estimates for 29 measures among all counties and most incorporated and census-designated places, census tracts, and ZIP Code tabulation areas across the US. PLACES allows local health departments and others to better understand the burden and geographic distribution of chronic disease-related outcomes in their areas regardless of population size and urban-rural status and assists them in planning public health interventions. Online resources allow users to visually explore health estimates geographically, compare estimates, and download data for further use and exploration. By understanding the PLACES overall approach and using the easy-to-use PLACES applications, practitioners, policy makers, and others can enhance their efforts to improve public health, including informing prevention activities, programs, and policies; identifying priority health risk behaviors for action; prioritizing investments to areas with the biggest gaps or inequities; and establishing key health objectives to achieve community health and health equity.

Indexed as

Health EquityRural PopulationCenters for Disease Control and Prevention, U.S.HumansPublic HealthUnited States

Identifiers

PMID35709356
PMCPMC9258452

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.