Long-term Effectiveness of mHealth Physical Activity Interventions: Systematic Review and Meta-analysis of Randomized Controlled Trials.

BACKGROUND: Mobile health (mHealth) interventions can increase physical activity (PA); however, their long-term impact is not well understood. OBJECTIVE: The primary aim of this study is to understand the immediate and long-term effects of mHealth interventions on PA. The secondary aim is to explore potential effect moderators. METHODS: We performed this study according to the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, the Cochrane Library, SCOPUS, and PsycINFO in July 2020. Eligible studies included randomized controlled trials of mHealth interventions targeting PA as a primary outcome in adults. Eligible outcome measures were walking, moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and energy expenditure. Where reported, we extracted data for 3 time points (ie, end of intervention, follow-up ≤6 months, and follow-up >6 months). To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool. RESULTS: Of the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence. CONCLUSIONS: mHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects.

Adolescent wine consumption is inversely associated with long-term weight gain: results from follow-up of 20 or 22 years.

BACKGROUND: Several studies have suggested a link between the type of alcoholic beverage consumption and body weight. However, results from longitudinal studies have been inconsistent, and the association between adolescent alcohol consumption long-term weight gain has generally not been examined. METHODS: The study was based on data from 720 Danish adolescents aged between 15 to 19 years at baseline from the Danish Youth and Sports Study (YSS). Self-reported alcohol use, height, weight, smoking, social economic status (SES) and physical activity levels were assessed in baseline surveys conducted in 1983 and 1985, and in the follow up survey which was conducted in 2005. Multiple linear regression analyses were used to examine the association between alcohol consumption in adolescence and subsequent weight gain later in midlife. RESULTS: There was no significant association between total alcohol consumption during adolescence and change in BMI into midlife (P = 0.079) (ß - 0.14; 95% CI -0.28, 0.005). Wine consumption was found to be inversely associated to subsequent BMI gain (P = 0.001) (ß - 0.46; 95% CI -0.82, - 0.09) while the results were not significant for beer and spirit. The relationship did not differ by gender, but smoking status was found to modify the relationship, and the inverse association between alcohol and BMI gain was seen only among non-smokers (P = 0.01) (ß - 0.24; 95% CI -0.41, - 0.06) while no association was found among smokers. Neither adolescent nor attained socioeconomic status in adulthood modified the relationship between alcohol intake and subsequent BMI gain. CONCLUSION: Among non-smoking adolescents, consumption of alcohol, and in particular wine, seems to be associated with less weight gain until midlife. TRIAL REGISTRATION: The YSS cohort was retrospectively registered on August 2017. (Study ID number: NCT03244150 ).

Vitamin D in early life and later risk of multiple sclerosis-A systematic review, meta-analysis.

The study examined results from previous studies of early life vitamin D exposure and risk of MS in adulthood, including studies on season or month of birth and of migration. A systematic review was conducted using PubMed and Web of Science databases as well as checking references cited in articles. The quality of studies was assessed using the Newcastle-Ottawa scale and the AMSTAR score. Twenty-eight studies were selected for analysis. Of these, six population studies investigated early life vitamin D exposure and risk of MS, and three found inverse while the remaining found no associations. A consistent seasonal tendency for MS seemed evident from 11/15 studies, finding a reduced occurrence of MS for Northern hemisphere children who were born late autumn, and late fall for children born in the Southern hemisphere. This was also confirmed by pooled analysis of 6/15 studies. Results of the migration studies showed an increased risk of MS if migration from high to low-MS-risk areas had occurred after age 15 years, while risk of MS was reduced for those migrating earlier in life (<15years). A similar, but inverse risk pattern was observed among migrants from low to high-MS-risk areas. One study found an increased risk of MS in the second generation of migrants when migrating from low to high-MS-risk areas. An association between early life vitamin D and later risk of MS seems possible, however evidence is still insufficient to conclude that low vitamin D exposure in early life increases the risk of MS in adulthood. PROSPERO register number: CRD 42016043229.