Evidence map›Paper›PMID 32053469›Full record

ArticlePublic health reports (Washington, D.C. : 1974)

Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems.

Peter Anthamatten, Deborah S K Thomas, Devon Williford, Jennifer C Barrow, Kirk A Bol, Arthur J Davidson, Sara J Deakyne Davies, Emily McCormick Kraus, David C Tabano, Matthew F Daley

Open access · bronzeAbstract read
In one paragraph

Article in Public health reports (Washington, D.C. : 1974). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

10 authors at 5 institutions in 1 country.

Peter AnthamattenDepartment of Geography and Environmental Sciences, University of Colorado Denver, Denver, CO, USA.ORCID 0000-0003-4413-9381
Deborah S K ThomasDepartment of Geography and Environmental Sciences, University of Colorado Denver, Denver, CO, USA.
Devon WillifordCenter for Health and Environment Data, Colorado Department of Public Health and Environment, Denver, CO, USA.
Jennifer C BarrowInstitute for Health Research, Kaiser Permanente Colorado, Denver, CO, USA.
Kirk A BolCenter for Health and Environment Data, Colorado Department of Public Health and Environment, Denver, CO, USA.
Arthur J DavidsonDenver Public Health, Denver, CO, USA.
Sara J Deakyne DaviesResearch Informatics, Analytics Resource Center, Children's Hospital Colorado, Aurora, CO, USA.
Emily McCormick KrausDenver Public Health, Denver, CO, USA.
David C TabanoInstitute for Health Research, Kaiser Permanente Colorado, Denver, CO, USA.
Matthew F DaleyInstitute for Health Research, Kaiser Permanente Colorado, Denver, CO, USA.
Kaiser Permanente · USColorado Department of Public Health and Environment · USDenver Public Health · USUniversity of Denver · USChildren's Hospital Colorado · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations. MATERIALS AND

methodsWe extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.

resultsWe identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region. PRACTICE IMPLICATIONS: The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.

Indexed as

Body Mass IndexElectronic Health RecordsGeographic Information SystemsAdolescentAdultChildChild, PreschoolColoradoFemaleHumansMaleObesityPopulation SurveillanceUrban Populationdisease surveillancemappingobesity

Identifiers

PMID32053469
PMCPMC7036605
OpenAlexW3006454884

What OpenQuestion holds

Textmetadata
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.