Evidence map›Paper›PMID 26536469›Full record

ArticlePloS one2015

Differences in the Prevalence of Obesity, Smoking and Alcohol in the United States Nationwide Inpatient Sample and the Behavioral Risk Factor Surveillance System.

Elie S Al Kazzi, Brandyn Lau, Tianjing Li, Eric B Schneider, Martin A Makary, Susan Hutfless

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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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

6 authors.

Elie S Al KazziDivision of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Brandyn LauDepartment of Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Tianjing LiDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Eric B SchneiderDepartment of Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Martin A MakaryDepartment of Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Susan HutflessDivision of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.

Funding

Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
NCATS NIH HHS UL1 TR001079
6 · The paper itself

Abstract

backgroundThe lack of adequate and standardized recording of leading risk factors for morbidity and mortality in medical records have downstream effects on research based on administrative databases. The measurement of healthcare is increasingly based on risk-adjusted outcomes derived from coded comorbidities in these databases. However inaccurate or haphazard assessment of risk factors for morbidity and mortality in medical record codes can have tremendous implications for quality improvement and healthcare reform.

objectiveWe aimed to compare the prevalence of obesity, overweight, tobacco use and alcohol abuse of a large administrative database with a direct data collection survey. MATERIALS AND

methodsWe used the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for four leading risk factors in the United States Nationwide Inpatient Sample (NIS) to compare them with a direct survey in the Behavioral Risk Factor Surveillance System (BRFSS) in 2011. After confirming normality of the risk factors, we calculated the national and state estimates and Pearson's correlation coefficient for obesity, overweight, tobacco use and alcohol abuse between NIS and BRFSS.

resultsCompared with direct participant questioning in BRFSS, NIS reported substantially lower prevalence of obesity (p<0.01), overweight (p<0.01), and alcohol abuse (p<0.01), but not tobacco use (p = 0.18). The correlation between NIS and BRFSS was 0.27 for obesity (p = 0.06), 0.09 for overweight (p = 0.55), 0.62 for tobacco use (p<0.01) and 0.40 for alcohol abuse (p<0.01).

conclusionsThe prevalence of obesity, overweight, tobacco smoking and alcohol abuse based on codes is not consistent with prevalence based on direct questioning. The accuracy of these important measures of health and morbidity in databases is critical for healthcare reform policies.

Indexed as

AdolescentAdultAgedAged, 80 and overAlcoholismBehavioral Risk Factor Surveillance SystemBody Mass IndexFemaleHealth BehaviorHumansInpatientsMaleMiddle AgedObesityPopulation SurveillanceSmoking

Identifiers

PMID26536469
PMCPMC4633065

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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.