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      Effects of Mobile Health App Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis

      review-article
      , BSc, MBBS, MPhil 1 , 2 , , , BSc, MBChB 3 , , BSc, MSc, PhD 2 , , BSc, MBBS, MSc, MD 1
      (Reviewer), (Reviewer), (Reviewer)
      Journal of Medical Internet Research
      JMIR Publications
      sedentary behavior, physical activity, physical fitness, aged, mHealth, mobile apps

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          Abstract

          Background

          High sedentary time, low physical activity (PA), and low physical fitness place older adults at increased risk of chronic diseases, functional decline, and premature mortality. Mobile health (mHealth) apps, apps that run on mobile platforms, may help promote active living.

          Objective

          We aimed to quantify the effect of mHealth app interventions on sedentary time, PA, and fitness in older adults.

          Methods

          We systematically searched five electronic databases for trials investigating the effects of mHealth app interventions on sedentary time, PA, and fitness among community-dwelling older adults aged 55 years and older. We calculated pooled standardized mean differences (SMDs) in these outcomes between the intervention and control groups after the intervention period. We performed a Cochrane risk of bias assessment and Grading of Recommendations, Assessment, Development, and Evaluation certainty assessment.

          Results

          Overall, six trials (486 participants, 66.7% [324/486] women; age mean 68 [SD 6] years) were included (five of these trials were included in the meta-analysis). mHealth app interventions may be associated with decreases in sedentary time (SMD=−0.49; 95% CI −1.02 to 0.03), increases in PA (506 steps/day; 95% CI −80 to 1092), and increases in fitness (SMD=0.31; 95% CI −0.09 to 0.70) in trials of 3 months or shorter and with increases in PA (753 steps/day; 95% CI −147 to 1652) in trials of 6 months or longer. Risk of bias was low for all but one study. The quality of evidence was moderate for PA and sedentary time and low for fitness.

          Conclusions

          mHealth app interventions have the potential to promote changes in sedentary time and PA over the short term, but the results did not achieve statistical significance, possibly because studies were underpowered by small participant numbers. We highlight a need for larger trials with longer follow-up to clarify if apps deliver sustained clinically important effects.

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          Most cited references19

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          Physical activity, fitness and fatness: relations to mortality, morbidity and disease risk factors. A systematic review.

          The purpose of this systematic review was to study the relative health risks of poor cardio-respiratory fitness (or physical inactivity) in normal-weight people vs. obesity in individuals with good cardio-respiratory fitness (or high physical activity). The core inclusion criteria were: publication year 1990 or later; adult participants; design prospective follow-up, case-control or cross-sectional; data on cardio-respiratory fitness and/or physical activity; data on BMI (body mass index), waist circumference or body composition; outcome data on all-cause mortality, cardiovascular disease mortality, cardiovascular disease incidence, type 2 diabetes or cardiovascular and type 2 diabetes risk factors. Thirty-six publications filled the criteria for inclusion. The data indicate that the risk for all-cause and cardiovascular mortality was lower in individuals with high BMI and good aerobic fitness, compared with individuals with normal BMI and poor fitness. In contrast, having high BMI even with high physical activity was a greater risk for the incidence of type 2 diabetes and the prevalence of cardiovascular and diabetes risk factors, compared with normal BMI with low physical activity. The conclusions of the present review may not be applicable to individuals with BMI > 35.
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            Cardiorespiratory fitness and adiposity as mortality predictors in older adults.

            Although levels of physical activity and aerobic capacity decline with age and the prevalence of obesity tends to increase with age, the independent and joint associations among fitness, adiposity, and mortality in older adults have not been adequately examined. To determine the association among cardiorespiratory fitness ("fitness"), adiposity, and mortality in older adults. Cohort of 2603 adults aged 60 years or older (mean age, 64.4 [SD, 4.8] years; 19.8% women) enrolled in the Aerobics Center Longitudinal Study who completed a baseline health examination during 1979-2001. Fitness was assessed by a maximal exercise test, and adiposity was assessed by body mass index (BMI), waist circumference, and percent body fat. Low fitness was defined as the lowest fifth of the sex-specific distribution of maximal treadmill exercise test duration. The distributions of BMI, waist circumference, and percent body fat were grouped for analysis according to clinical guidelines. All-cause mortality through December 31, 2003. There were 450 deaths during a mean follow-up of 12 years and 31 236 person-years of exposure. Death rates per 1000 person-years, adjusted for age, sex, and examination year were 13.9, 13.3, 18.3, and 31.8 across BMI groups of 18.5-24.9, 25.0-29.9, 30.0-34.9, and > or =35.0, respectively (P = .01 for trend); 13.3 and 18.2 for normal and high waist circumference (> or =88 cm in women; > or =102 cm in men) (P = .004); 13.7 and 14.6 for normal and high percent body fat (> or =30% in women; > or =25% in men) (P = .51); and 32.6, 16.6, 12.8, 12.3, and 8.1 across incremental fifths of fitness (P < .001 for trend). The association between waist circumference and mortality persisted after further adjustment for smoking, baseline health status, and BMI (P = .02) but not after additional adjustment for fitness (P = .86). Fitness predicted mortality risk after further adjustment for smoking, baseline health, and either BMI, waist circumference, or percent body fat (P < .001 for trend). In this study population, fitness was a significant mortality predictor in older adults, independent of overall or abdominal adiposity. Clinicians should consider the importance of preserving functional capacity by recommending regular physical activity for older individuals, normal-weight and overweight alike.
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              Impact of Cardiorespiratory Fitness on All-Cause and Disease-Specific Mortality: Advances Since 2009

              Cardiorespiratory fitness (CRF) has been one of the most widely examined physiological variables, particularly as it relates to functional capacity and human performance. Over the past three decades, CRF has emerged as a strong, independent predictor of all-cause and disease-specific mortality. The evidence supporting the prognostic use of CRF is so powerful that the American Heart Association recently advocated for the routine assessment of CRF as a clinical vital sign. Interestingly, the continuity of evidence of the inverse relationship between CRF and mortality over the past decade exists despite a wide variation of methods used to assess CRF in these studies, ranging from the gold-standard method of directly measured maximal oxygen uptake (VO2max) during cardiopulmonary exercise testing to estimation from exercise tests and non-exercise prediction equations. This review highlights new knowledge and the primary advances since 2009, with specific reference to the impact variations in CRF have on all-cause and disease-specific mortality.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                November 2019
                28 November 2019
                : 21
                : 11
                : e14343
                Affiliations
                [1 ] Primary Care Unit Department of Public Health and Primary Care University of Cambridge Cambridge United Kingdom
                [2 ] Medical Research Council Epidemiology Unit University of Cambridge Cambridge United Kingdom
                [3 ] Barking, Havering, and Redbridge University Hospitals Trust London United Kingdom
                Author notes
                Corresponding Author: Dharani Yerrakalva dharaniyerrakalva@ 123456googlemail.com
                Author information
                https://orcid.org/0000-0003-1830-5315
                https://orcid.org/0000-0003-0175-9601
                https://orcid.org/0000-0002-0431-2787
                https://orcid.org/0000-0002-2157-4797
                Article
                v21i11e14343
                10.2196/14343
                6908977
                31778121
                cd9596d2-a411-4915-a350-e0d24e3f3b5d
                ©Dharani Yerrakalva, Dhrupadh Yerrakalva, Samantha Hajna, Simon Griffin. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.11.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 17 April 2019
                : 19 June 2019
                : 1 August 2019
                : 24 September 2019
                Categories
                Review
                Review

                Medicine
                sedentary behavior,physical activity,physical fitness,aged,mhealth,mobile apps
                Medicine
                sedentary behavior, physical activity, physical fitness, aged, mhealth, mobile apps

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