Evidence map›Paper›PMID 38405171›Full record

ArticleHealth science reports2024

How well do obesity indices predict undiagnosed hypertension in the Persian cohort (Shahedieh) adults community population of all ages?

Sara Jambarsang, Moslem Taheri Soodejani, Robert Tate, Reyhane Sefidkar

Open access · goldAbstract read
In one paragraph

Article in Health science reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 countries.

Sara JambarsangCenter for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology Shahid Sadoughi University of Medical Sciences Yazd Iran.
Moslem Taheri SoodejaniCenter for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology Shahid Sadoughi University of Medical Sciences Yazd Iran.
Robert TateCentre on Aging University of Manitoba Winnipeg Canada.
Reyhane SefidkarCenter for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology Shahid Sadoughi University of Medical Sciences Yazd Iran.ORCID 0000-0003-2395-8265
Shahid Sadoughi University of Medical Sciences and Health Services · IRResearch Manitoba · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Hypertension is the leading preventable risk factor for cardiovascular disease, chronic kidney disease and cognitive impairment, and mortality and disability worldwide. Since prevention, early detection, and treatment of blood pressure improve public health, the aim of present study was to determine the best obesity indices and estimate the optimal cut-off point for each one to predict the risk of elevated/stage 1 and undiagnosed hypertension in the population of center of Iran based on American ACC/AHA 2020 guidelines. Methods: This cross-sectional study was performed on 9715 people who enrolled in 2018 in Persian Adult Cohort in Shahedieh area of Yazd, Iran in 2018. The anthropometric indices including body mass index (BMI) and waist circumference (WC), wrist circumference, hip circumference, waist-to-hip ratio, and waist-to height ratio of individuals, were extracted. The receiver operating characteristic curve was utilized to determine the optimum cut-off point of each anthropometric index to predict hypertension stages and compare their predictive power by age-sex categories. Statistical analysis was done using SPSS version 23.0. Results: The results showed that BMI has the best predictive power to recognize the risk of elevated/stage 1 hypertension for female (area under the curve [AUC] = 0.72 and optimal cut-off = 30.10 kg/m Conclusion: Based on our findings, BMI and WC, which are simple, inexpensive, and noninvasive means, are the best markers to predict the risk of elevated/stage 1 and undiagnosed hypertension in young Iranians. It shows that the approach of reducing hypertension prevalence through primary prevention, early detection, and enhancing its treatment is achievable.

Indexed as

anthropometryhypertensionobesity indicesprimary preventionROC curve

Identifiers

PMID38405171
PMCPMC10885643
OpenAlexW4392102625

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.