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Background: In current years, the increase in older population has led to creating one of the main public health challenges, worldwide. Because of the special characteristics of older adults, this age group is exposed to possible problems, such as mental and physical disorders, that usually affect their functional independence. The study aimed to determine the psychosocial determinants (e.g., depression, social support, and self-efficacy) affecting functional independence among older population. Methods: Our search was conducted on three international databases (Web of Sciences, PubMed/Medline, and Scopus) for all the observational studies (cross-sectional, cohort or longitudinal designs) on the social and psychological determinants of functional independence among older adults. Papers published in English without limitation of time were reviewed from inception to 26 August 2023. The quality assessment tool was the Newcastle-Ottawa Scale (NOS). The I2 index was used to quantify the degree of heterogeneity among the studies. In the case of heterogeneity higher than 50%, the random effects model has been used for overall estimation of the effects; otherwise, the fixed effects model was used. The pooled associations were expressed as odds ratio (OR) and 95% confidence intervals (CIs). Stata version 14 software (StataCorp LP) was used for data analysis. The significance level was considered at 0.05. Results: In the initial search, 6978 articles were retrieved, and finally, considering the inclusion criteria, 46 articles were examined. Finally, 18 articles were eligible for meta-analysis. The findings indicated that among all the determinants affecting functional independence among older adults, depression could lead to a 76% increase in functional dependence. Conclusion: The findings provide a statistically significant relationship between psychosocial factors and functional independence. Depression was the strongest determinant of functional dependence among older adults. [ABSTRACT FROM AUTHOR]

Background: Postpartum weight retention (PPWR) has many health risks. Digital self-monitoring of weight can potentially make postpartum weight management easier. We aim to test to what extent the self-monitoring of weight, steps and mental health through an mHealth application increases postpartum weight loss and reduces the odds of substantial PPWR (≥5 kg). Methods: Participants were mothers in the intervention arm of the INTER-ACT multicenter randomized controlled trial (RCT), an inter-pregnancy lifestyle intervention among mothers with excessive gestational weight gain. Participants (n=288) had access to an mHealth application to log their weight, steps and mental health between 6 weeks and 6 months postpartum. A linear multiple regression model and a logistic regression model were run to test to what extent self-monitoring via the app increases postpartum weight loss and reduces the risk of substantial PPWR. Results: Women who logged their weight more often lost more weight (B=0.03, β=0.26, CIB =[0.01,0.05], P <0.01),>OR =[0.98, 0.999], P <.05).>OR =[0.97, 1.00], P <0.05),> Conclusion: Mothers with excessive gestational weight gain can benefit from app-based lifestyle interventions to reduce PPWR by self-monitoring their weight. More attention to mental health in PPWR interventions is needed. [ABSTRACT FROM AUTHOR]

Background: Given the impact of high intake of sugar-sweetened beverages on type 2 diabetes, intervention to reduce their consumption can be a top priority for any health system. Thus, the purpose of the present study is to simulate the impact of policy options related to reduce consumption of sugar-sweetened beverages (SSBs) on the prevalence and mortality of type 2 diabetes in Iranian men and women. Methods: A discrete event simulation (DES) model was used to predict the effect of several policy options on the prevalence and death from type 2 diabetes in Azar Cohort Databases. Population age- and sex-specific prevalence and incidence rate of diagnosed diabetes were derived from the national health data. The Preventable Risk Integrated Model (PRIME) model was used for coding the input parameters of simulation using R and Python software. Results: The prevalence and mortality rate of type 2 diabetes under the scenario of reduced consumption of SSBs indicated that the highest and the lowest prevalence and mortality rates of type 2 diabetes for men and women were related to no policy condition and replacing SSBs with healthy drinks, like water, respectively. Also, the maximum "number of deaths postponed/ prevented" from type 2 diabetes was related to replacing SSBs with water (n=2015), and an integration of reformulation and applying 10% tax on SSBs (n=1872), respectively. Conclusion: Simulating the effect of different policy options on reducing the consumption of SSBs showed "replacing of SSBs with water" as the most effective policy option in Iranian setting. [ABSTRACT FROM AUTHOR]