Evidence map›Paper›PMID 41136531›Full record

ArticleScientific reports2025

The association between 24-hour urinary biomarkers and metabolic syndrome: A cross-sectional study in zhejiang, China.

Yujia Fang, Xiaofu Du, Qingfang He, Lixin Wang, Jieming Zhong

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yujia FangZhejiang Provincial Center for Disease Control and Prevention, No. 3399 Binsheng Road, Hangzhou, 310051, China.
Xiaofu DuZhejiang Provincial Center for Disease Control and Prevention, No. 3399 Binsheng Road, Hangzhou, 310051, China.
Qingfang HeZhejiang Provincial Center for Disease Control and Prevention, No. 3399 Binsheng Road, Hangzhou, 310051, China.
Lixin WangZhejiang Provincial Center for Disease Control and Prevention, No. 3399 Binsheng Road, Hangzhou, 310051, China.
Jieming ZhongZhejiang Provincial Center for Disease Control and Prevention, No. 3399 Binsheng Road, Hangzhou, 310051, China. jmzhong@cdc.zj.cn.

Funding

Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0509800Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0509806
6 · The paper itself

Abstract

Metabolic syndrome (MetS) is a cluster of metabolic disorders associated with increased risks of cardiovascular diseases and type 2 diabetes, posing a significant public health challenge globally. Early identification of biomarkers for MetS is crucial for timely intervention. This study aimed to explore the association between 24-hour urine indicators (sodium, potassium, creatinine, and microalbumin) and MetS among Chinese adults, providing evidence for early MetS screening and intervention. A cross-sectional survey was conducted in 2017, involving 1175 Chinese residents aged 18-69 years. Data were collected via questionnaires, physical measurements, and laboratory tests, with 24-hour urine samples analyzed for sodium, potassium, creatinine, and microalbumin excretion. Participants were excluded if they had incomplete data, unqualified urine collection, or a self-reported history of hypertension or diabetes. Of the 1175 participants (median age 42 years; 48.17% male), the prevalence of MetS was 11.4%. The median 24-hour urine excretion levels were 158.42/24 hours mmol (sodium), 34.89 mmol/24 hours (potassium), 9.62 mmol/24 hours (creatinine), and 4.31 mg/24 hours (microalbumin). Specifically, 24-hour urine microalbumin excretion was significantly higher in participants with MetS (6.35 mg/24 h) than in those without (4.12 mg/24 h; P < 0.0001), while no significant differences were observed in sodium, potassium, or creatinine excretion between the two groups. Notably, elevated microalbumin excretion was associated with MetS components: central obesity, elevated blood pressure, elevated fasting blood glucose, and elevated triglycerides (all P < 0.05). When microalbumin excretion was divided into quartiles, adjusted odds ratios (adjusted for age, sex, and other confounders) for MetS and its component (elevated fasting blood glucose) increased with higher quartiles (MetS: 1.00, 1.53, 1.99, 2.75; P for trend = 0.0004; elevated fasting blood glucose: 1.00, 1.31, 1.35, 2.20; P for trend = 0.0005). These findings indicate that elevated 24-hour urine microalbumin excretion is independently associated with MetS in Chinese adults, suggesting its potential as a practical biomarker for early risk assessment and intervention.

Indexed as

BiomarkersMetabolic SyndromeAdolescentAdultAgedAlbuminuriaChinaCreatinineCross-Sectional StudiesFemaleHumansMaleMiddle AgedPotassiumPrevalenceSodiumBiomarkersCreatininePotassiumSodium24-hour urineCreatinineMetabolic syndromeMicroalbuminPotassiumSodium

Identifiers

PMID41136531
PMCPMC12552600

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