Background: A growing body of studies that investigated the longitudinal association between physical activity (PA) and the outcome of incident obesity, coronary heart disease (CHD), diabetes and hypertension has become available in recent years. Thus, the purpose of this systematic review was to provide an update on the association between PA and onset of obesity, CHD, diabetes and hypertension in individuals aged ≥18 years who were free of the respective conditions at baseline. Methods: We systematically searched OVID, Pubmed, and Web of Science databases for pertinent literature published between January of 2012 and February of 2019. To ensure that conclusions are based on high quality evidence, we only included longitudinal studies conducted in samples of ≥500 participants and with ≥5 years of follow-up. Result: The search yielded 8929 records of which 26 were included in this review. Three studies were conducted on the outcome of incident obesity, eight on incident CHD, nine on incident diabetes, four on incident hypertension, one on the outcome of both diabetes and hypertension, and one on the outcome of CHD, diabetes and hypertension. Overall, there was an association between PA and lower risk of incident obesity, CHD and diabetes, but not hypertension. Higher levels or amount of PA were associated with a reduced risk of new onset of the respective diseases in 20 studies (77%). Whereas four studies reported an elevated risk of incidence of diseases with lower PA levels (15%). PA was not associated with incidence of diseases in two studies (8%).

Background Numerous smartphone apps are targeting physical activity and healthy eating, but empirical evidence on their effectiveness for initialization and maintenance of behavior change, especially in children and adolescents, is still limited. Objective The aim of this study was to conceptualize a theory-based and evidence-based mHealth intervention called SMARTFAMILY (SF) that targets physical activity and healthy eating in a collective family-based setting. Subsequently, the app will be refined and re-evaluated to analyze additional effects of just-in-time adaptive interventions (JITAIs) and gamification features. Methods A smartphone app based on behavior change theories and behavior change techniques was developed and implemented and will be evaluated with family members individually and cooperatively (SF trial). Existing evidence and gained results were used to refine and will be used to re-evaluate the app (SF2.0 trial). Both trials are cluster randomized controlled trials with 3 measurement occasions. The intervention group uses the app for 3 consecutive weeks, whereas the control group receives no treatment. Baseline measurements (T0) and postintervention measurements (T1) include physical activity (ie, self-reported and accelerometry) and healthy eating measurements (ie, self-reported fruit and vegetable intake) as the primary outcomes. The secondary outcomes (ie, self-reported) are intrinsic motivation, behavior-specific self-efficacy, and the family health climate, complemented by an intentional measure in SF2.0. Four weeks following T1, a follow-up assessment (T2) is completed by the participants, consisting of all questionnaire items to assess the stability of the intervention effects. Mixed-method analysis of covariance will be used to calculate the primary intervention effects (ie, physical activity, fruit and vegetable intake) while controlling for covariates, including family health climate, behavior-specific self-efficacy, and intrinsic motivation. Results This study is funded by the German Federal Ministry of Education and Research and ethically approved by the Karlsruhe Institute of Technology. For both trials, it is hypothesized that the apps will positively influence physical activity and healthy eating in the whole family. Furthermore, SF2.0 is expected to produce stronger effects (ie, higher effect sizes) compared to SF. SF app development and piloting are completed. Data acquisition for the SF trial is terminated and discontinued due to the COVID-19 pandemic. SF2.0 app development and piloting are completed, while data acquisition is ongoing. Participant recruitment for the SF 2.0 trial started in February 2020. The results for SF are expected to be published in mid-2021, and the results of SF2.0 are expected to be published in mid-2022. Conclusions In this study, it is hypothesized that targeting the whole family will facilitate behavior change at the individual level and the family level, as the implemented strategies address changes in daily family life. Furthermore, subsequent app development (SF2.0) with supplementary addition of motivation-enhancing features and a JITAI approach is expected to enhance positive intervention effects. Trial Registration German Clinical Trials Register DRKS00010415; https://tinyurl.com/yyo87yyu International Registered Report Identifier (IRRID) DERR1-10.2196/20534

BACKGROUND Numerous smartphone applications (app) are targeting physical activity (PA) and/or healthy eating (HE), but empirical evidence on their effectiveness for initialization and maintenance of behavior change, especially in children and adolescents is still limited. Individuals’ behavior is embedded in social settings, therefore, core settings such as the family need to be considered when designing mobile health (mHealth) apps. OBJECTIVE Purpose of this study therefore is to conceptualize a theory- and evidence-based mHealth intervention (called SMARTFAMILY (SF)) targeting PA and HE in a collective family-based setting. Subsequently, the app will be refined and re-evaluated in order to analyze additional effects of just-in-time adaptive interventions (JITAI) and gamification features. METHODS A smartphone app based on behavior change theories and -techniques was developed, implemented and evaluated in a collective family setting with family members individually and cooperatively using the SF-app (SF trial). Subsequently, existing evidence and gained results will be used to refine and -evaluate the app (SF2.0 trial). For both trials, a cluster-randomized controlled trial including three measurement occasions is conducted. The intervention group (IG) is using the app for three consecutive weeks, whereas the control group (CG) receives no treatment. Baseline- (T0) and post-measurements (T1) include PA (self-reported and accelerometry) and HE measurement (self-reported fruit and vegetable intake (FVI)) as primary outcomes. Secondary outcomes (self-reported) are intrinsic motivation, behavior-specific self-efficacy and the Family Health Climate (FHC), complemented by an intentional measure in SF2.0. Four weeks following T1, a follow-up assessment (T2) is completed by participants, consisting of all questionnaire items to assess the stability of the intervention effects. Mixed-method ANCOVAs are used to calculate primary intervention effects (PA, FVI) while controlling for covariates including FHC, behavior-specific self-efficacy, and intrinsic motivation. RESULTS A greater increase in PA (steps, minutes of moderate-to-vigorous PA) and HE is expected in the IG compared to the CG (SF and SF2.0). Furthermore, a further increase is expected in SF2.0 due to the additional motivating features. CONCLUSIONS This study aims at creating and testing a theory- and evidence-based mHealth intervention targeting PA and HE in a collective family-based setting. It is hypothesized that targeting the whole family facilitates behaviour change on the individual and the family level as the implemented strategies address changes in daily family life. Furthermore, subsequent app development (SF2.0) with supplementary addition of motivation-enhancing features and a JITAI approach is expected to enhance positive intervention effects. CLINICALTRIAL The study is registered with the German Clinical Trials Register under the registration number DRKS00010415. The study is funded by the German Federal Ministry of Education and Research.

We examined the longitudinal association between physical activity (PA) and the risk of incident metabolic syndrome (MetS) among middle-aged, community-dwelling adults, including 591 individuals (314 females; mean (SD) age, 43.8 (8.5) years) who were free of MetS at baseline. Habitual and sports-related PA was assessed by a self-reported questionnaire. MetS was defined based on HDL-cholesterols, triglycerides, glucose or HbA1c, blood pressure, and waist circumference. We calculated Cox proportional hazard ratios (HR) and 95% confidence intervals (CI) using regression analyses. Over a mean follow-up of 12.5 years, 205 participants developed incident MetS. Four different sports-related PA measures were associated with a decreased risk of incident MetS: (1) Engaging in ≥ 75 min/week (HR 0.71, 95% CI 0.53–0.94), (2) maintaining a continuously high amount from baseline to follow-up of ≥ 75 min/week (HR 0.66, 95% CI 0.46–0.94), (3) starting from < 150 min/week at baseline to ≥ 150 min/week at follow-up (HR 0.65, 95% CI 0.45–0.94), and (4) increasing from < 16.6 MET-hours/week at baseline to ≥ 16.6 MET-hours/week at follow-up (HR 0.47, 95% CI 0.31–0.71). Thus, maintaining, starting or increasing sports-related PA is associated with a lower risk of incident MetS.

Background In middle-aged and particularly older adults, body mass index (BMI) is associated with various health outcomes. We examined associations between physical activity (PA) and longitudinal BMI change in persons aged ≥ 50 years. Methods The sample included 5159 community-dwelling individuals aged ≥ 50 years (50.5% males, mean (SD) age 73.0 (10.2) years at baseline) who were enrolled in the Mayo Clinic Study of Aging (MCSA). Participants had information on PA within one year of baseline assessment, BMI at baseline, and potential follow-up assessments (mean (SD) follow-up 4.6 (3.7) years). Linear mixed-effect models were used to calculate the association between PA (moderate-vigorous physical activity, MVPA; and all PA composite score) and the longitudinal change in BMI, adjusted for baseline age, sex, education and medical comorbidities. In addition to interactions between years since baseline and PA, we also included 2- and 3-way interactions with baseline age to further assess whether age modifies the trajectory of BMI over time. Results We observed a decrease in BMI among participants engaging at a mean amount of PA (i.e., MVPA: 2.7; all PA: 6.8) and with a mean age (i.e., 73 years) at baseline (MVPA: estimate = -0.047, 95% CI -0.059, -0.034; all PA: estimate = -0.047, 95% CI -0.060, -0.035), and this decline is accelerated with increasing age. Participants with a mean age (i.e., 73 years) that engage at an increased amount of MVPA or all PA at baseline (i.e., one SD above the mean) do not decrease as fast with regard to BMI (MVPA: estimate = -0.006; all PA: estimate = -0.016), and higher levels of MVPA or all PA at baseline (i.e., two SD above the mean) were even associated with an increase in BMI (MVPA: estimate = 0.035; all PA: estimate = 0.015). Finally, MVPA but not all PA is beneficial at slowing BMI decline with increasing age. Conclusion PA, particularly at moderate-vigorous intensity, is associated with slower decline in longitudinal BMI trajectories. This implies that engaging in PA may be beneficial for healthy body weight regulation in middle and late adulthood.