# Impact of intermittent fasting on physical activity: a national survey of Chinese residents aged 18–80 years

**Authors:** Feiying He, Shiyu Bai, Xiangchun Xu, Jingqiao Miao, Hongwen Yu, Jiale Qiu, Yibo Wu, Yangdong Fan, Lei Shi

PMC · DOI: 10.3389/fphys.2025.1582036 · 2025-05-12

## TL;DR

This study found that intermittent fasting is common among young Chinese adults and is linked to lower physical activity levels.

## Contribution

The study provides new insights into the relationship between intermittent fasting and physical activity in a large Chinese population.

## Key findings

- Intermittent fasting was practiced by 9.78% of participants, with the highest prevalence in those aged 18–34.
- Intermittent fasting was significantly associated with reduced physical activity levels.
- Subgroup analysis showed that sleep patterns influence the relationship between intermittent fasting and physical activity.

## Abstract

This study aims to investigate the prevalence of intermittent fasting (IF) among Chinese residents aged 18–80 and assess its impact on physical activity (PA) levels.

Data were sourced from the Psychology and Behavior Investigation of Chinese Residents, a nationally representative cross-sectional survey conducted between June 20 and 31 August 2022. A multistage stratified cluster sampling method was used. Propensity score matching (PSM) was applied to compare PA levels between individuals practicing IF and those not practicing it. Multiple logistic regression and subgroup analysis were performed to explore associations between PA levels and relevant factors.

IF was practiced by 9.78% of participants, with the highest prevalence (70.78%) among those aged 18–34. While there were no significant differences in baseline characteristics between the IF and non-IF groups, sleep duration differed. IF was significantly associated with reduced PA levels (OR = 0.769, 95%CI: 0.657–0.900), and subgroup analysis highlighted the effect of sleep patterns on PA.

IF is common among younger Chinese residents and correlates with lower PA levels, indicating a potential need for individualized health guidance to balance dietary strategies with PA.

## Full-text entities

- **Genes:** INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, GH1 (growth hormone 1) [NCBI Gene 2688] {aka GH, GH-N, GHB5, GHN, IGHD1A, IGHD1B}
- **Diseases:** type 2 diabetes (MESH:D003924), diabetes (MESH:D003920), cognitive function (MESH:D003072), eating disorders (MESH:D001068), sports injuries (MESH:D001265), asthma (MESH:D001249), psychiatric (MESH:D001523), fatigue (MESH:D005221), obesity (MESH:D009765), inflammatory (MESH:D007249), cognitive failures (MESH:D051437), cancer (MESH:D009369), insulin resistance (MESH:D007333), body image disorders (MESH:D057215), heart disease (MESH:D006331), PA (MESH:D059445), muscle loss (MESH:D009135), depression (MESH:D003866), nerve damage (MESH:D000080902), overweight (MESH:D050177), IF (MESH:D007003), hyperandrogenism (MESH:D017588), cardiovascular disease (MESH:D002318), mentally abnormal (MESH:D008607), weight loss (MESH:D015431)
- **Chemicals:** cholesterol (MESH:D002784), blood sugar (MESH:D001786), triiodothyronine (MESH:D014284), testosterone (MESH:D013739), alcohol (MESH:D000438)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12105048/full.md

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Source: https://tomesphere.com/paper/PMC12105048