Evidence map›Paper›PMID 30730970›Full record

ArticlePloS one2019

Prevalence of multiple chronic conditions in New York State, 2011-2016.

Daniel Newman, Erica Levine, Sandeep P Kishore

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

3 authors.

Daniel NewmanArnhold Institute for Global Health at the Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.ORCID 0000-0002-5954-5668
Erica LevineArnhold Institute for Global Health at the Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
Sandeep P KishoreArnhold Institute for Global Health at the Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTo design effective policy and interventions, public health officials must have an accurate and granular picture of the state of multiple chronic conditions (MCC) in their region. The objective of this research is to describe the prevalence and distribution of MCC in New York State.

methodsWe performed a secondary data analysis of the Behavioral Risk Factor Surveillance System (BRFSS) from 2011 through 2016 for New York adults (n = 76,186). We analyzed the self-reported prevalence of individuals having 0, 1, 2, or ≥ 3 chronic conditions by sex, race/ethnicity, age, health insurance type, annual household income, and whether respondents lived in New York City. We also examined the most common condition dyads and triads. Finally, we assessed the prevalence of MCC (2 or more chronic conditions) by county across New York State, and neighborhood within New York City.

resultsDuring 2011-2016, 25.2% of adults in New York State had zero chronic conditions, 24.1% had 1 condition, 18.4% had 2 conditions, and 32.4% had 3 or more. The most prevalent dyad was hypertension and high cholesterol in 17.0% of individuals. The most prevalent triad was hypertension, high cholesterol, and arthritis in 4.5% of individuals. County prevalence of MCC ranged from 42.6% in Westchester County to 66.1% in Oneida County. The prevalence of MCC in New York City neighborhoods ranged from 33.5% in Gramercy Park-Murray Hill to 60.6% in High Bridge-Morrisania.

conclusionThis research contributes to the field's understanding of multiple chronic conditions and allows policy and public health leaders in New York to better understand the prevalence and distribution of MCC.

Indexed as

AdultAgedBehavioral Risk Factor Surveillance SystemFemaleHumansMaleMiddle AgedMultiple Chronic ConditionsNew York CityPrevalenceSelf ReportYoung Adult

Identifiers

PMID30730970
PMCPMC6366719

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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.