Evidence map›Paper›PMID 25584075›Full record

ArticleDiabetology & metabolic syndrome2014

Parent-offspring association of metabolic syndrome in the Framingham Heart Study.

Rumana J Khan, Samson Y Gebreab, Pia Riestra, Ruihua Xu, Sharon K Davis

Abstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2014. 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
–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

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

  1. Pooled it
  2. Article
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  4. Article
  5. Article
  6. Metabolic syndrome and male fertility disorders: Is there a causal link?Reviews in endocrine & metabolic disorders · 2021
    Review
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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

5 authors.

Rumana J KhanCardiovascular Section, Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Social Epidemiology Research Unit, National Human Genome Research Institute, 10 Center Drive, Room 7 N316 MSC 1644, Bethesda, MD 20892 USA.
Samson Y GebreabCardiovascular Section, Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Social Epidemiology Research Unit, National Human Genome Research Institute, 10 Center Drive, Room 7 N316 MSC 1644, Bethesda, MD 20892 USA.
Pia RiestraCardiovascular Section, Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Social Epidemiology Research Unit, National Human Genome Research Institute, 10 Center Drive, Room 7 N316 MSC 1644, Bethesda, MD 20892 USA.
Ruihua XuCardiovascular Section, Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Social Epidemiology Research Unit, National Human Genome Research Institute, 10 Center Drive, Room 7 N316 MSC 1644, Bethesda, MD 20892 USA.
Sharon K DavisCardiovascular Section, Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Social Epidemiology Research Unit, National Human Genome Research Institute, 10 Center Drive, Room 7 N316 MSC 1644, Bethesda, MD 20892 USA.

Funding

Social Exposures and Genetics of Cardiovascular DiseaseZIAHG200393 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI GIBBONS, GARY · 2014 to 2019
$13.1M
6 · The paper itself

Abstract

backgroundMetabolic syndrome (MetS) is a clustering of five metabolic risk factors including abdominal obesity, elevated blood pressure, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), and impaired fasting glucose. Few studies have fully reported the strength of clustering of these risk factors in a parent-offspring relationship. This analysis describes the associations between parents and their adult offspring in regard to MetS. It also estimates the association between each risk factor in parents and the presence of MetS in their offspring.

methodsWe analyzed data for 1193 offspring (565 sons, and 628 daughters) from the Framingham Offspring Study who attended examinations 5, 6, and 7. Information about their parents was collected from examinations 13, 14 and 15 of the Framingham Original Cohort study. We used pedigree file to combine parental and offspring's data. Participants were classified as having the MetS according to the Adult Treatment Panel III criteria. Analyses were conducted separately for mothers and fathers. Logistic regression was used to estimate the associations.

resultsAfter adjusting for age, education, smoking, alcohol consumption and physical activity level of offspring, no significant association was found between father's and their offspring's MetS. Mother's MetS was significantly and positively associated with their daughter's MetS (adjusted odds ratio or adj OR: 1.63; 95% confidence Interval, CI:1.02-2.61), but not with their sons' MetS. When analyzed by individual components, maternal impaired glucose (adj OR: 2.03; 95% CI: 1.02- 9.31), abdominal obesity (adj OR: 1.56; 95% CI: 0.98- 2.55) and low HDL-C (adj OR: 2.12; 95% CI: 1.36-3.32) were associated daughter's MetS. Maternal low HDL-C and raised total cholesterol showed marginal association with son's MetS. For fathers, only impaired glucose (adj OR: 4.91; 95% CI: 2.07- 11.68) was associated with their daughter's MetS.

conclusionsUsing the data from Framingham Heart Study, we demonstrate differential association of MetS and its components between parents and offspring. Mother's MetS was strongly related with daughter's MetS, but the association was inconsistent with son's MetS. No association was found between father's MetS and offspring's Mets. These results provide evidence that daughters with mother's MetS are in higher risk than daughters or sons with father's MetS.

Indexed as

Abdominal obesityFramingham Heart StudyImpaired fasting glucoseMetabolic syndromeParent-offspring

Identifiers

PMID25584075
PMCPMC4290436

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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.