Evidence map›Paper›PMID 39799282›Full record

ArticleBMC public health2025

Associations of daily step count with all-cause mortality and cardiovascular mortality in hypertensive US adults: a cohort study from NHANES 2005-2006.

Tuo Guo, Yang Zhou, Guifang Yang, Aifang Zhong, Xiaogao Pan, Yuting Pu, Michael Simons, Lijuan Sheng, Xiangping Chai

Abstract read
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Article in BMC public health, 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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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

9 authors.

Tuo GuoDepartment of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China.
Yang ZhouDepartment of Intensive Care Unit, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China.
Guifang YangDepartment of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China.
Aifang ZhongDepartment of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China.
Xiaogao PanDepartment of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China.
Yuting PuDepartment of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China.
Michael SimonsYale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT, USA.
Lijuan ShengClinical Nursing Teaching and Research Section, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China. shenglijuannice1006@csu.edu.cn.
Xiangping ChaiDepartment of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China. chaixiangping@csu.edu.cn.

Funding

Key Project of Hunan Provincial Science and Technology Innovation 2020SK1014-2Key Research and Development Program of Hunan Province of China 2019SK2022
6 · The paper itself

Abstract

backgroundThe health benefits of physical activity, including walking, are well-established, but the relationship between daily step count and mortality in hypertensive populations remains underexplored. This study investigates the association between daily step count and both all-cause and cardiovascular mortality in hypertensive American adults.

methodsWe used data from the National Health and Nutrition Examination Survey 2005-2006, including 1,629 hypertensive participants with accelerometer-measured step counts. Cox proportional hazards models and restricted cubic spline regression were employed to assess the associations between daily step count and mortality outcomes. Analyses were adjusted for demographics, lifestyle factors, and comorbidities.

resultsOver an average follow-up of 12.57 years, 370 deaths occurred, of which 177 were due to cardiovascular causes. We observed non-linear associations between daily step count and mortality. Mortality risks were significantly reduced with step counts to 8,250 steps/day for all-cause mortality and 9,700 steps/day for cardiovascular mortality. Beyond these thresholds, the benefits plateaued.

conclusionIncreasing daily step count is associated with reduced all-cause and cardiovascular mortality in hypertensive individuals, with optimal benefits observed below 8,250 and 9,700 daily steps, respectively. Moderate levels of physical activity provide substantial health benefits, highlighting the importance of setting realistic and attainable activity goals for hypertensive populations.

Indexed as

Cardiovascular DiseasesHypertensionWalkingAccelerometryAdultAgedCause of DeathCohort StudiesFemaleHumansMaleMiddle AgedNutrition SurveysProportional Hazards ModelsUnited StatesDaily step countHypertensionMortalityNHANES

Identifiers

PMID39799282
PMCPMC11725191

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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.