Association of daily step counts and intensity in obesity among older Chinese women: a cross-sectional study

Higher daily step counts and intensity appear associated with a lower risk of obesity, although daily step counts is not associated with BMI. For women aged 60-70, aiming for over 9,135 steps/day is suggested. Adjusting step counts and intensity according to individual circumstances is advisable.

Authors

Institutions

Publication Details

Journal
BMC Public Health
Published
2025-05-30
DOI
https://doi.org/10.1186/s12889-025-23089-1
Primary Topic
Physical Activity and Health
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association of daily step counts and intensity in obesity among older Chinese women: a cross-sectional study

Yang Pan, Ting Li, Xiaoyu Ren, Xianliang Zhang et al.
BMC Public Health
Physical Activity and Health
article

Association of daily step counts and intensity in obesity among older Chinese women: a cross-sectional study

Yang Pan, Ting Li, Xiaoyu Ren, Xianliang Zhang, Litao Du, Si Chen, Qiang He, Shuting Yin, Qinmei Wu
article en

Abstract

Higher daily step counts and intensity appear associated with a lower risk of obesity, although daily step counts is not associated with BMI. For women aged 60-70, aiming for over 9,135 steps/day is suggested. Adjusting step counts and intensity according to individual circumstances is advisable.

BMC Public HealthVol. 25(1)
Shandong University (CN)
Natural Science Foundation of Shandong Province
Gender equality
Openalex Percentile: Top 84%
Physical Activity and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.