Evidence map›Paper›PMID 33530935›Full record

ArticleBMC cardiovascular disorders2021

Socioeconomic and lifestyle determinants of the prevalence of hypertension among elderly individuals in rural southwest China: a structural equation modelling approach.

Li Xiao, Cai Le, Gui-Yi Wang, Lu-Ming Fan, Wen-Long Cui, Ying-Nan Liu, Jing-Rong Shen, Allison Rabkin Golden

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 2021. 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
–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

9 citing papers in PubMed.

  1. Article
  2. Impact of Social Determinants of Health on Cardiovascular Disease.Journal of the American Heart Association · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Delving the Role ofOxidative medicine and cellular longevity · 2022
    Review
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

8 authors.

Li XiaoSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.
Cai LeSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China. caile002@hotmail.com.
Gui-Yi WangSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.
Lu-Ming FanSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.
Wen-Long CuiSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.
Ying-Nan LiuSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.
Jing-Rong ShenSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.
Allison Rabkin GoldenSchool of Public Health, Kunming Medical University, 1168 Yu Hua Street, Chun Rong Road, Cheng Gong New City, Kunming, 650500, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study examines the association between socioeconomic and lifestyle factors and the prevalence of hypertension among elderly individuals in rural Southwest China.

methodsA cross-sectional survey of 4833 consenting adults aged ≥ 60 years in rural regions of Yunnan Province, China, was conducted in 2017. Data on individual socioeconomic status, sleep quality, physical activity level, and family history of hypertension were collected with a standardized questionnaire. Blood pressure, fasting blood glucose, height, weight, and waist circumference were also measured. An individual socioeconomic position (SEP) index was constructed using principal component analysis. Structural equation modelling (SEM) was applied to analyse the association between socioeconomic and lifestyle factors and the prevalence of hypertension.

resultsThe overall prevalence of hypertension was 50.6% in the study population. Body fat distribution, including measures of obesity and central obesity, had the greatest total effect on hypertension (0.21), followed by family history of hypertension (0.14), biological sex (0.08), sleep quality (- 0.07), SEP (- 0.06), physical inactivity (0.06), and diabetes (0.06). Body fat distribution, SEP, and family history of hypertension had both direct and indirect effects on hypertension, whereas physical inactivity, diabetes, and sleep quality were directly associated with the prevalence of hypertension. Biological sex was indirectly associated with the prevalence of hypertension.

conclusionsSEP, body fat distribution, physical inactivity, diabetes, and sleep quality critically influence the prevalence of hypertension. Future interventions to prevent and control hypertension should give increased attention to individuals with low SEP and should focus on controlling diabetes and obesity, increasing physical activity levels, and improving quality of sleep among older adults aged ≥ 60 years in rural Southwest China.

Indexed as

Life StyleRural HealthSocial Determinants of HealthSocioeconomic FactorsAdiposityAgedAge FactorsBlood PressureChinaCross-Sectional StudiesDiabetes MellitusFemaleHealth SurveysHumansHypertensionLatent Class AnalysisChinaHypertensionLifestyleOlder adultsSocioeconomic status

Identifiers

PMID33530935
PMCPMC7851929

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.