This review was done to determine the prevalence of metabolic syndrome (MS) among adult general population in India. We also wanted to find the gender, setting, and region-wide distribution of MS in India. We conducted systematic searches in various databases including Medline, ScienceDirect, Cochrane library and Google Scholar from inception until August 2019. We included studies conducted in India reporting the prevalence of MS among adults aged 18 years or more. We used the Newcastle Ottawa scale to assess the quality of included studies. We carried out a meta-analysis with random-effects model and reported pooled prevalence with 95% confidence intervals (CIs). We used the Funnel plot to assess publication biases. In total, we analysed 113 data from 111 studies with 133,926 participants. Majority of the included studies (76 out of 111) had low risk of bias. We found significant heterogeneity among the included studies (p<0.001). We also found a symmetrical funnel plot indicating an absence of publication bias. The prevalence of MS among adult population in India was 30% (95%CI: 28%-33%). There was a steady increase in the burden across the age groups from 13% (18–29 years group) to 50% (50–59 years). We also found that people living in urban areas (32%; 95%CI: 29%-36%) had higher prevalence when compared to tribal (28%; 95%CI: 21%-36%) or rural adults (22%; 95%CI: 20%-25%). Gender distribution of MS showed that the females had higher prevalence (35%; 95%CI: 31%-38%) when compared to males 26% (95%CI: 22%-29%). Almost one in three adults in India suffer from MS. Females, people living in urban areas and in northeast region had higher prevalence of MS. Development and implementation of policies and protocols for the screening of MS would enable us in early diagnosis and treatment with special focus towards the vulnerable and high-risk groups.

Background: Nutritional status of the elderly population has become an important issue but often gets neglected. Both undernutrition and over nutrition are important public health priorities in this vulnerable group. Objectives: To determine the prevalence of malnutrition and factors associated with it among elderly population in rural Puducherry using mini-nutritional assessment (MNA) questionnaire. Materials and Methods: A community-based cross-sectional study was conducted among 279 elderly population between November and December 2016 in four villages of rural Puducherry, India. Information on sociodemographic characteristics and nutritional status of the elderlies were collected using validated MNA questionnaire. Body mass index was used to report obesity based on Asia-Pacific guidelines. Results: Among 279 participants, 178 (63.8%) were in the age group of 60–70 years, 190 (68.1%) were females, and 208 (74.6%) had no formal-education. Prevalence of malnutrition among elderly was found to be 17.9% (95% CI: 13.7–22.7) and about 58.8% (95% CI: 52.9–64.4) were at risk of malnutrition which was assessed using MNA questionnaire. Prevalence of obesity was found to be 32.5% (95% CI: 27.3–38.3) and 38.4% had inadequate fruits and vegetables intake. About 250 (89.6%) are living independently according to ADL score. Conclusion: Both undernutrition and over nutrition are important health issues to be considered among elderly population in this area. Primary healthcare strengthening to address and prevent this health issue by balanced dietary practices may improve their nutritional status, thereby enhancing their quality of life.

Background: Childhood mortality and morbidity has become a major public health issue in low-middle-income countries. However, evidence suggested that Low birth weight(LBW) is one of the most important risk factors for childhood deaths and disability.This study is designed to estimate the prevalence of low birth weight (LBW) in India and to identify maternal correlates associated with LBW. Methods: Data has been taken from National Family Health Survey 5 (2019–2021) for analysis. 149,279 women belonging to reproductive age group (15–49) year who had last recent most delivery preceding the NFHS-5 survey. Results: Mother's age, female child, birth interval of less than 24 months, their low educational level, low wealth index, rural residence, lack of insurance coverage, women with low BMI, anaemia, and no ANC visits during pregnancy are predictors that contribute to LBW in India. After adjusting for covariates, smoking and alcohol consupmtion is strongly correlated with LBW. Conclusion: Mother’s age, educational attainment and socioeconomic status of living has a highly significant with LBW in India. However, consumption of tobacco and cigarrettes are also associated with LBW.

Antenatal care (ANC) is essential in maternal and child health since it provides care to pregnant women from conception through to labour in order to ensure a safe pregnancy and childbirth. In recent years, mobile health (mHealth) interventions have emerged as a promising solution to improve maternal and child health outcomes in low- and middle-income countries (LMICs). The present study aimed to conduct a systematic review and meta-analysis of trials to evaluate the effectiveness of mHealth interventions to monitor prenatal care among pregnant women in LMICs. A systematic literature review was conducted using the databases CINHAL, Embase, MEDLINE, and PsycINFO on the effectiveness of mHealth interventions in monitoring the antenatal care of pregnant women. The study selection, data extraction of the included articles, and quality appraisal were assessed. Our study included six studies considering 7886 participants. All articles were from low- and middle-income countries (LMICs). Antenatal mothers who used a mobile health intervention were more likely (RR = 1.66, 95%CI = 1.07–2.58, I² = 98%) to attend ANC check-ups when compared with the women who did not use any mobile health applications or did not receive any short message services. mHealth technologies are being utilised more and more to increase care accessibility and improve maternal and fetal health. Policymakers should prioritise the integration of mHealth interventions into maternal healthcare services in LMICs, ensuring that they are cost-effective, accessible, and sustainable and that healthcare workers are trained to deliver these interventions effectively.