Evidence map›Paper›PMID 41126087›Full record

ArticleBMC public health2025

The influence of socioeconomic disparities on the association of physical behavior with incident type 2 diabetes.

Puchen Zhou, Xin Geng, Chengjing Zhang, Tongtong Li, Fengchang Li, Yaying Cao, Dou Mao, Yunan Liu, Nan Wang, Kaixuan Li and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Puchen Zhou *CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Xin Geng *National Center for Liver Cancer, Naval Medical University, Shanghai, 201805, China.
Chengjing ZhangThe Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Tongtong LiCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Fengchang LiCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Yaying CaoSchool of Medicine and Health, Harbin Institute of Technology, Harbin, China.
Dou MaoCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Yunan LiuCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Nan WangCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Kaixuan LiCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Zilin XiaoCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China.
Xiliang ShangDepartment of Sports Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Chengwu FengCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China. fengchengwu2018@sinh.ac.cn.
Geng ZongCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue-yang Rd, Shanghai, 200031, China. zonggeng@sinh.ac.cn.

Funding

National Key R&D Program of China 2023YFF1104301National Natural Science Foundation of China 82373576
6 · The paper itself

Abstract

backgroundTo evaluate the influence of socioeconomic status (SES) on the associations of moderate to vigorous physical activity (MVPA), light intensity physical activity (LIPA), sedentary behavior, and sleep duration with incident type 2 diabetes (T2D).

methodsThe analysis included 69,461 participants from the UK Biobank who completed an accelerometer-based physical activity measurement. Individual-level SES was assessed via latent class analysis of household income, employment status, and education qualifications. The area-level SES was determined through the Townsend Deprivation Index. The additive hazard model and Cox proportional hazards model were employed to estimate the risk of T2D.

resultsAfter a median follow-up of 6.7 years, 1,252 cases of incident T2D were documented. The associations between physical behaviors and T2D risk differed significantly by SES. Compared with individuals with higher SES, those with lower SES presented greater increases in T2D risk associated with low MVPA (68 vs. 31 cases per 10,000 person-years; p for interaction = 0.030), high sedentary behavior (24 vs. 1 cases per 10,000 person-years; p for interaction < 0.001), and short sleep duration (23 vs. 5 cases per 10,000 person-years; p for interaction = 0.003). Area-level SES also modified the relationship between low MVPA and T2D risk on both additive and multiplicative scales (p for interaction < 0.001), with stronger effects observed in socioeconomically disadvantaged groups.

conclusionsAddressing insufficient MVPA, prolonged sedentary behavior, and inadequate sleep among individuals with lower SES could significantly reduce the number of T2D cases, highlighting the importance of targeted public health interventions to mitigate disparities in T2D incidence.

Indexed as

Diabetes Mellitus, Type 2ExerciseSocioeconomic Disparities in HealthAccelerometryAgedFemaleHumansIncidenceLow Socioeconomic StatusMaleMiddle AgedRisk FactorsSedentary BehaviorSleep DurationSocial ClassUK BiobankAccelerometerPhysical behaviorsSocioeconomic statusType 2 diabetes

Identifiers

PMID41126087
PMCPMC12542217

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.