Evidence map›Paper›PMID 28062275›Full record

ArticleAmerican journal of preventive medicine2017

Put the Family Back in Family Health History: A Multiple-Informant Approach.

Jielu Lin, Christopher S Marcum, Melanie F Myers, Laura M Koehly

Abstract readComparative Study
In one paragraph

Article in American journal of preventive medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  3. Observational
  4. Article
  5. Review
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  10. Developing Shared Appraisals of Diabetes Risk Through Family Health History Feedback: The Case of Mexican-Heritage Families.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2018
    Article
  11. 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

4 authors at 2 institutions in 1 country.

Jielu LinSocial and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland. Electronic address: lin.jielu@nih.gov.
Christopher S MarcumSocial and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland.
Melanie F MyersCincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Laura M KoehlySocial and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland.
National Human Genome Research Institute · USCincinnati Children's Hospital Medical Center · US

Funding

The influence of familial social context on risk dissemination and copingZIAHG200335 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI KOEHLY, LAURA M · 2009 to 2025
$13.6M
Methodological DevelopmentZIAHG200397 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI KOEHLY, LAURA M · 2016 to 2025
$1.7M
Social influence of family networks on T2D risk perceptions and health behaviorK18DK095473 · NIDDK · CINCINNATI CHILDRENS HOSP MED CTR · PI MYERS, MELANIE F · 2011 to 2011
$73k
Intramural NIH HHS ZIA HG200335NIDDK NIH HHS K18 DK095473
6 · The paper itself

Abstract

introductionAn accurate family health history is essential for individual risk assessment. This study uses a multiple-informant approach to examine whether family members have consistent perceptions of shared familial risk for four common chronic conditions (heart disease, Type 2 diabetes, high cholesterol, and hypertension) and whether accounting for inconsistency in family health history reports leads to more accurate risk assessment.

methodsIn 2012-2013, individual and family health histories were collected from 127 adult informants of 45 families in the Greater Cincinnati Area. Pedigrees were linked within each family to assess inter-informant (in)consistency regarding common biological family member's health history. An adjusted risk assessment based on pooled pedigrees of multiple informants was evaluated to determine whether it could more accurately identify individuals affected by common chronic conditions, using self-reported disease diagnoses as a validation criterion. Analysis was completed in 2015-2016.

resultsInter-informant consistency in family health history reports was 54% for heart disease, 61% for Type 2 diabetes, 43% for high cholesterol, and 41% for hypertension. Compared with the unadjusted risk assessment, the adjusted risk assessment correctly identified an additional 7%-13% of the individuals who had been diagnosed, with a ≤2% increase in cases that were predicted to be at risk but had not been diagnosed.

conclusionsConsiderable inconsistency exists in individual knowledge of their family health history. Accounting for such inconsistency can, nevertheless, lead to a more accurate genetic risk assessment tool. A multiple-informant approach is potentially powerful when coupled with technology to support clinical decisions.

Indexed as

PedigreeSurveys and QuestionnairesAdultAge FactorsCardiovascular DiseasesCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleGenetic Diseases, InbornHumansHyperlipidemiasHypertensionIncidenceMaleMedical History TakingMiddle Aged

Identifiers

PMID28062275
PMCPMC5401648
OpenAlexW2569866193

What OpenQuestion holds

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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.