Evidence map›Paper›PMID 37185646›Full record

ArticleBMJ open2023

Impact of urinary sodium excretion on the prevalence and incidence of metabolic syndrome: a population-based study.

Lu Yin, Sidong Li, Yongmei He, Lin Yang, Li Wang, Chao Li, Yaqin Wang, Jing Wang, Pingting Yang, Jiangang Wang and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

4 citing papers in PubMed, 4 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

12 authors at 6 institutions in 3 countries.

Lu YinMedical Research & Biometrics Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0001-9596-3325
Sidong LiDivision of Life Sciences and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
Yongmei HeDepartment of Health Management, Aerospace Center Hospital, Beijing, China.
Lin YangDepartment of Cancer Epidemiology and Prevention Research, Alberta Health Services, Edmonton, Alberta, Canada.
Li WangMedical Research & Biometrics Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chao LiHunan Key Laboratory for Bioanalysis of Complex Matrix Samples, Changsha, Hunan, China.
Yaqin WangHealth Management Center, Central South University Third Xiangya Hospital, Changsha, Hunan, China.
Jing WangMedical Research & Biometrics Center, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Pingting YangHealth Management Center, Central South University Third Xiangya Hospital, Changsha, Hunan, China.
Jiangang WangHealth Management Center, Central South University Third Xiangya Hospital, Changsha, Hunan, China.
Zhiheng ChenHealth Management Center, Central South University Third Xiangya Hospital, Changsha, Hunan, China.
Ying LiHealth Management Center, Central South University Third Xiangya Hospital, Changsha, Hunan, China lydia0312@csu.edu.cn.
Central South University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNAerospace Center Hospital · CNAlberta Health Services · CAMatrix Research (United States) · USUniversity of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the association of metabolic syndrome (MetS) risk with 24-hour urinary sodium excretion (24hUNaE) estimated from spot urine samples.

designSerial cross-sectional studies were conducted, and those with multiple repeated examinations were used to assess the MetS incidence risk. SETTING AND

participantsA health check-up programme was conducted between 2018 and 2021 and enrolled 59 292 participants to evaluate the relationship between MetS risk and 24hUNaE in the Third Xiangya Hospital, Changsha, China. Among these participants, 9550 had at least two physical examinations during this period, which were used to evaluate the association of a new occurrence of MetS with 24hUNaE. OUTCOMES: Guidelines for the prevention and treatment of dyslipidaemia in Chinese adults (revised in 2016) were used to define prevalent and incident MetS.

resultsThe prevalence of MetS was 19.3% at the first check-up; among individuals aged ≤55 years, the risk was higher in men than women, while among older individuals, a similar prevalence was observed in both sexes. A significant increase in MetS prevalence was observed per unit increase in 24hUNaE (adjusted OR (AOR) 1.11; 95% CI 1.09 to 1.13), especially for the prevalence of central obesity and elevated blood pressure. Additionally, 27.4% of the participants among the 7842 participants without MetS at the first check-up (male vs female: 37.3% vs 12.9%) were found to have a new occurrence of MetS at the second, third and/or fourth check-ups. A 25% increase in MetS incidence was observed per unit increase in 24hUNaE (95% CI 1.19 to 1.32), which was more prominent in the participants with a new occurrence of central obesity and elevated fasting blood glucose.

conclusionsAlthough the prevalence of MetS seemed stable, new occurrences of MetS remained high, which might result in MetS recurrence. The influence of sodium intake on MetS development is probably attributed to the increase in blood pressure and central obesity, but a new occurrence of MetS may develop through elevated blood glucose and central obesity.

Indexed as

Metabolic SyndromeAdultBlood GlucoseCross-Sectional StudiesFemaleHumansIncidenceMaleObesityObesity, AbdominalPrevalenceRisk FactorsSodiumBlood GlucoseSodiumEPIDEMIOLOGYHealth policyPRIMARY CARE

Identifiers

PMID37185646
PMCPMC10151878
OpenAlexW4367046484

What OpenQuestion holds

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LicenceCC BY-NC
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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.