Evidence map›Paper›PMID 31428454›Full record

ArticleClinical hypertension2019

Familial aggregation and heritability of hypertension in Han population in Shanghai China: a case-control study.

An-le Li, Xiang Fang, Yi-Ying Zhang, Qian Peng, Xian-Hong Yin

Open access · diamondAbstract read
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Article in Clinical hypertension, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 17 citations in OpenAlex.

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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.

An-le LiJiading District Center for Disease Control and Prevention, Shanghai, China.ORCID 0000-0003-3200-4770
Xiang FangJiading District Center for Disease Control and Prevention, Shanghai, China.
Yi-Ying ZhangJiading District Center for Disease Control and Prevention, Shanghai, China.
Qian PengJiading District Center for Disease Control and Prevention, Shanghai, China.
Xian-Hong YinJiading District Center for Disease Control and Prevention, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo explore the familial aggregation and heritability of hypertension in Han in Shanghai China.

methodsAccording to l:l matched pairs design, 342 patients of hypertension and 342 controls were selected and investigate their nuclear family members in the case-control study. The method of genetic epidemiology research was used to explore the familial aggregation and heritability of hypertension.

resultsThe prevalence rate of hypertension of first-degree relatives was significantly higher (34.44%) than that of second- degree relatives (17.60%) and third-degree relatives (13.51%) in Han Population in Shanghai China. Separation ratio p was 0.217, and prevalence rate of case group relatives was higher than that of control group relatives. The results showed a phenomenon of familial aggregation in the distribution of hypertension. The heritability of first- degree relatives was 49.51%; that of second-degree relatives and third-degree relatives were respectively 23.42 and 21.41%.

conclusionThe distribution of essential hypertension has phenomenon of familial aggregation in Han Population in Shanghai China. The separation ratio of essential hypertension in this study shows that essential hypertension conform to the characteristics of multigene genetic disease. The heritability of first-degree relatives is bigger than that of second-degree relatives and third-degree relatives.

Indexed as

Familial aggregationHeritabilityHypertensionSegregation ratio

Identifiers

PMID31428454
PMCPMC6694643
OpenAlexW2968882594

What OpenQuestion holds

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LicenceCC BY
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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.