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      Leisure-Time Physical Activity and Cardiovascular Mortality in an Elderly Population in Northern Manhattan: A Prospective Cohort Study

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          Abstract

          <div class="section"> <a class="named-anchor" id="d3682374e207"> <!-- named anchor --> </a> <h5 class="section-title" id="d3682374e208">Background</h5> <p id="Par1">Previous studies of exercise have focused on measuring physical activity in totality using summary statistics such as metabolic equivalent score for total intensity or total energy count. </p> </div><div class="section"> <a class="named-anchor" id="d3682374e212"> <!-- named anchor --> </a> <h5 class="section-title" id="d3682374e213">Objective</h5> <p id="Par2">We aimed to examine the multidimensionality of leisure-time physical activity (LTPA) and to identify the specific LTPA components that were associated with cardiovascular mortality in the elderly. </p> </div><div class="section"> <a class="named-anchor" id="d3682374e217"> <!-- named anchor --> </a> <h5 class="section-title" id="d3682374e218">Design and Participants</h5> <p id="Par3">The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3298 participants recruited between 1993 and 2001, with a median follow-up of 17 years. </p> </div><div class="section"> <a class="named-anchor" id="d3682374e222"> <!-- named anchor --> </a> <h5 class="section-title" id="d3682374e223">Main Measures</h5> <p id="Par4">Physical activity questionnaire data were available in 3293 NOMAS participants, who were categorized into subgroups with similar exercise patterns by model-based cluster analysis. Three subgroup-defining LTPA features were identified and were considered as primary exposures in Cox proportional hazard models: frequency of activity, number of activity types (variety), and energy-to-duration ratio (EDR). We considered cardiovascular mortality and non-cardiovascular mortality as outcomes in Cox cause-specific proportional hazard models, and all-cause mortality as outcome in Cox models. </p> </div><div class="section"> <a class="named-anchor" id="d3682374e227"> <!-- named anchor --> </a> <h5 class="section-title" id="d3682374e228">Key Results</h5> <p id="Par5">A high activity frequency was associated with reduced cardiovascular mortality (hazard ratio, HR = 0.93, <i>P</i> = 0.03), but demonstrated no effect on non-cardiovascular death. A high EDR was associated with increased risk of cardiovascular death (HR = 1.30, <i>P</i> = 0.01). A high number of activity types was beneficial in reducing all-cause mortality (HR = 0.87, <i>P</i> = 0.01). </p> </div><div class="section"> <a class="named-anchor" id="d3682374e241"> <!-- named anchor --> </a> <h5 class="section-title" id="d3682374e242">Conclusions</h5> <p id="Par6">Exercise frequency was protective against cardiovascular mortality, and a high variety of activity was protective against all-cause mortality. The performance of frequent and varied non-intense exercise in an elderly population such as ours is achievable and can reduce the risk of death. </p> </div>

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          Most cited references12

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          Finite Mixture Models

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            Physical activity and stroke risk: a meta-analysis.

            Whether physical activity reduces stroke risk remains controversial. We used a meta-analysis to examine the overall association between physical activity or cardiorespiratory fitness and stroke incidence or mortality. We searched MEDLINE from 1966 to 2002 and identified 23 studies (18 cohort and 5 case-control) that met inclusion criteria. We estimated the overall relative risk (RR) of stroke incidence or mortality for highly and moderately active individuals versus individuals with low levels of activity using the general variance-based method. The meta-analysis documented that there was a reduction in stroke risk for active or fit individuals compared with inactive or unfit persons in cohort, case-control, and both study types combined. For cohort studies, highly active individuals had a 25% lower risk of stroke incidence or mortality (RR=0.75; 95% CI, 0.69 to 0.82) compared with low-active individuals. For case-control studies, highly active individuals had a 64% lower risk of stroke incidence (RR=0.36; 95% CI, 0.25 to 0.52) than their low-active counterparts. When we combined both the cohort and case-control studies, highly active individuals had a 27% lower risk of stroke incidence or mortality (RR=0.73; 95% CI, 0.67 to 0.79) than did low-active individuals. We observed similar results in moderately active individuals compared with inactive persons (RRs were 0.83 for cohort, 0.52 for case-control, and 0.80 for both combined). Furthermore, moderately and highly active individuals had lower risk of both ischemic and hemorrhagic strokes than low-active individuals. We conclude that moderate and high levels of physical activity are associated with reduced risk of total, ischemic, and hemorrhagic strokes.
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              Comparative validity of physical activity measures in older adults.

              To compare the validity of various physical activity measures with doubly labeled water (DLW)-measured physical activity energy expenditure (PAEE) in free-living older adults. Fifty-six adults aged ≥65 yr wore three activity monitors (New Lifestyles pedometer, ActiGraph accelerometer, and a SenseWear (SW) armband) during a 10-d free-living period and completed three different surveys (Yale Physical Activity Survey (YPAS), Community Health Activities Model Program for Seniors (CHAMPS), and a modified Physical Activity Scale for the Elderly (modPASE)). Total energy expenditure was measured using DLW, resting metabolic rate was measured with indirect calorimetry, the thermic effect of food was estimated, and from these, estimates of PAEE were calculated. The degree of linear association between the various measures and PAEE was assessed, as were differences in group PAEE, when estimable by a given measure. All three monitors were significantly correlated with PAEE (r=0.48-0.60, P<0.001). Of the questionnaires, only CHAMPS was significantly correlated with PAEE (r=0.28, P=0.04). Statistical comparison of the correlations suggested that the monitors were superior to YPAS and modPASE. Mean squared errors for all correlations were high, and the median PAEE from the different tools was significantly different from DLW for all but the YPAS and regression-estimated PAEE from the ActiGraph. Objective devices more appropriately rank PAEE than self-reported instruments in older adults, but absolute estimates of PAEE are not accurate. Given the cost differential and ease of use, pedometers seem most useful in this population when ranking by physical activity level is adequate. © 2011 by the American College of Sports Medicine
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                Author and article information

                Journal
                Journal of General Internal Medicine
                J GEN INTERN MED
                Springer Nature America, Inc
                0884-8734
                1525-1497
                February 2017
                October 17 2016
                February 2017
                : 32
                : 2
                : 168-174
                Article
                10.1007/s11606-016-3884-y
                5264679
                27752879
                a35481f1-3e50-4253-9c3e-e94a681ebb95
                © 2017

                http://www.springer.com/tdm

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