Evidence map›Paper›PMID 42077456›Full record

ArticleFrontiers in endocrinology2026

The impact of daily steps on polycystic ovary syndrome patients.

Tianmei Wang, LiJuan Zhang, Liya Ma, Xiaodong Luo, Cong Li

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2026. 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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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

5 authors.

Tianmei WangDepartment of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
LiJuan ZhangDepartment of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Liya MaDepartment of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xiaodong LuoDepartment of Gynecology and Obstetrics, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Cong LiDepartment of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: As a reproductive-metabolic disorder, lifestyle interventions play a crucial role in managing Polycystic Ovary Syndrome (PCOS) patients. However, maintaining physical activity in PCOS patients is often challenging. Daily steps are now widely used to provide relatively simple physical activity goals for the general public. This study examines the impact of daily steps on patients with PCOS, aiming to develop simple and effective intervention strategies for them. Methods: This study included anthropometric parameters, metabolic indicators, sex hormones, and daily steps from women aged 16-40 years with PCOS (n=167) and without PCOS (n=152). Participants were divided into obese and non-obese groups based on BMI ≥ 25 kg/m² for intergroup comparisons, comprehensively evaluating the association between daily steps and various indicators. Results: Among PCOS patients, 42.9% were sedentary, while only 8.8% were active or highly active. Indicators significantly correlated with step count in the correlation analysis underwent further multivariate linear regression analysis. RCS analysis further validated the positive linear relationship between HDL and daily step count in PCOS patients (P for non-linear = 0.125). For PCOS patients without obesity, daily step count showed linear relationships with TG (P for non-linear = 0.211), HDL (P for non-linear = 0.255), and VAI (P for non-linear = 0.839). Additionally, daily steps showed linear relationships with body fat percentage (BFP, p=0.033, Conclusion: Daily steps exhibits a beneficial association with lipid and body fat metabolism in PCOS patients without obesity, making it a viable indicator for quantifying physical activity that can be incorporated into PCOS patient management.

Indexed as

ExerciseObesityPolycystic Ovary SyndromeWalkingAdolescentAdultBody Mass IndexFemaleHumansYoung Adultabdominal fatdaily stepsmetabolismPCOSwalking

Identifiers

PMID42077456
PMCPMC13128351

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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.