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Abstract
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<div class="so-custom-list-label so-ol">•</div>
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<p id="para0002">Higher step count is inversely associated with the risk of premature
death and cardiovascular
events.
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<p id="para0003">As measured by accelerometers, 8959 steps/day (Q3) had a 40.36% lower
risk of all-cause
mortality than 4183 steps/day (Q1).
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<p id="para0004">As measured by accelerometers, 9500 steps/day (Q3) had a 35.05% lower
risk of cardiovascular
events than 3500 steps/day(Q1).
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<p id="para0005">These associations were in nonlinear dose–response patterns.</p>
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<h5 class="section-title" id="d1380640e244">Background</h5>
<p id="d1380640e246">A goal of 10,000 steps per day is widely advocated, but there
is little evidence to
support that goal. Our purpose was to examine the dose–response relationships between
step count and all-cause mortality and cardiovascular disease risk.
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<h5 class="section-title" id="d1380640e249">Methods</h5>
<p id="d1380640e251">Cochrane Central Register of Controlled Trials, EMBASE, OVID,
PubMed, Scopus, and
Web of Science databases were systematically searched for studies published before
July 9, 2021, that evaluated the association between daily steps and at least 1 outcome.
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<h5 class="section-title" id="d1380640e254">Results</h5>
<p id="d1380640e256">Sixteen publications (12 related to all-cause mortality, 5 related
to cardiovascular
disease; and 1 article contained 2 outcomes: both all-cause death and cardiovascular
events) were eligible for inclusion in the meta-analysis. There was evidence of a
nonlinear dose–response relationship between step count and risk of all-cause mortality
or cardiovascular disease (
<i>p</i> = 0.002 and
<i>p</i> = 0.014 for nonlinearity, respectively). When we restricted the analyses
to accelerometer-based
studies, the third quartile had a 40.36% lower risk of all-cause mortality and a 35.05%
lower risk of cardiovascular event than the first quartile (all-cause mortality: Q1 = 4183
steps/day, Q3 = 8959 steps/day; cardiovascular event: Q1 = 3500 steps/day, Q3 = 9500
steps/day; respectively).
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<h5 class="section-title" id="d1380640e265">Conclusion</h5>
<p id="d1380640e267">Our meta-analysis suggests inverse associations between higher
step count and risk
of premature death and cardiovascular events in middle-aged and older adults, with
nonlinear dose–response patterns.
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Because of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers. Twenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention. We conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods. From the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed. The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.
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