(1) Information Technology (IT) Business Process Outsourcing (BPO), the largest employment sector of India, contributes to rapid economic growth. However, the work of IT employees is sedentary, and the food environments of their worksites expose them to an obesogenic environment. This study aimed to assess their metabolic and lifestyle risk factors. (2) Methods: To examine the health and nutrition status of IT employees, anthropometric, biochemical and clinical assessments were conducted among 183 employees from three IT organizations of varied operational sizes. Their health-, diet- and physical activity-related practices were assessed using a questionnaire. The prevalence of MetS was assessed. Selected biomarker levels were assessed and associated with their self-perceived stress levels. (3) Results: The median age of the employees was 30 years (26–35 years). While 44.02% of employees were overweight, 16.85% of employees were obese. About 3.89% of employees were found to be diabetic, and HDL-C levels were lower than recommended in 64.93% of employees. In all, 29.87% of the study population were considered to have metabolic syndrome since they had metabolic risk scores ≥ 3. Those with metabolic syndrome were significantly older (p = 0.000), and levels of MDA (p = 0.003), homocysteine (p = 0.001), IL-6 (p = 0.017) and IL-4 (p = 0.000) were significantly higher among them. Although the prevalence of MetS was significantly lower among those aged >30 years, the lifestyle risk factors were significantly higher among them. (4) Conclusions: The assessed parameters indicate a high risk of developing NCDs among employees in the IT industry in India. This shows the need for the modification of lifestyle and workplace food and physical activity environments.

The prevalence of stunting among under- three Indian children though decreased, still it is considered to be alarmingly high. In most of the previous studies, traditional (linear and logistic) regression analyses were applied. They were limited to encapsulated cross-distribution variations. The objective of the current study was to examine how the different determinants were heterogeneous in various percentiles of height for age (HAZ) distribution. This article examined the change in the HAZ distribution of children and examined the relationships between the key co-variate trends and patterns in HAZ among children aged <3 years over a period of 24 years. Four successive rounds of the National Family Health Survey data 1992–93, 1998–99, 2005–06, and 2015–16 were used for analysis. The final study included 206579 children aged <3 years (N = 106136 male, 100443 female). To explain and analyse differences in the HAZ distribution, the lambda-mu-sigma (LMS) method was used. Trends in height for age (HAZ) distribution over time were analysed using separate gender-stratified quantile regression (QR). The selected socio-economic, demographic and other predictors were considered for this analysis. The quantile regressions have indicated that mothers who have higher than primary level education were more proactive in mitigating malnutrition among children at the lower end of the distribution. The age, birth order, mother’s body-mass-index (BMI) and economic status, among children, were some more determining factors for HAZ. Results of selected quantile regression were estimated at the 5^th, 10^th, 25^th, 50^th, 75^th, 90^th, and 95^th quantiles. The outcome of various covariates working differently across the HAZ distribution was suggested by quantile regression. The major discrepancies in different aspects were underlined by socioeconomic and demographic aspects among the Indian population. The heterogeneity of this effect was shown using quantile regression. Policymakers may choose to concentrate on the most important factors when formulating policies to lessen the prevalence of stunting in India.

The uncontrolled spread of (mis)information, news and propaganda related to COVID 19 created an ‘infodemic’ leading to panic and unscientific practices among the mass. With the largest number of internet users in the world, India has witnessed a steep rise in the number of people seeking information on social media related to COVID-19, which reached a staggering 22.3 million by March, 2020. This study aimed to evaluate the trend of COVID-19 associated food and nutrition news search by Indian internet users between 27^th January 2020 to 30^th June 2021 (time period between the first detected COVID-19 case and the end of the second wave in India) and its impact on their perceptions and practices. The association between the change in Relative Search Volume (RSV) on Google Trends (GT) of 34 popularly searched keywords classified by the researchers under 5 different categories—“Immunity”, “Eating behavior”, “Food safety”, “Food scares and concerns” and “Covid scare” showed a steep rise in search for immunity boosters, vitamin supplement brands “ayush kadha (ayurvedic decoction) during the first wave (April- August 2020). With a brief period of decline in the search trend, it again hiked correspondingly with the growing number of positive cases during the second wave in India. An online survey conducted on adult Indian internet users (n = 572) reported high (71.9%) consumption of Vitamin C rich fruits as well as Vitamin C (68.2%) and Zinc (61.4%) supplements to boost immunity. Traditional Indian spices like ginger and garlic were used by 62.9% and 50.9% respondents respectively. Most respondents reported to rely on social media for gathering COVID-19 associated tips for boosting immunity, however those with history of COVID-19 infection reported to rely more on doctors and health professionals for information. This study highlights the need of media and health literacy to advocate for the use of health information cautiously.

Clustering effects, such as those introduced by housing animals in shared cages, are often overlooked in preclinical lifespan studies, despite their potential to distort variance estimates and inflate Type I error rates, leading to misleading conclusions. This methodological oversight reduces statistical rigor and may undermine the reliability of findings. To address this gap, the current study examines the impact of accounting for clustering and nesting effects on lifespan analyses by comparing the results of statistical models which both account for and ignore these effects. Using 2019 data from the Interventions Testing Program (ITP), a large-scale initiative evaluating the effects of compounds on lifespan in UM-HET3 mice as a case study, we illustrate how different modeling approaches influence statistical estimates and conclusions. Clustering and nesting effects were addressed using linear mixed effects, and Cox frailty models, both of which explicitly account for cage-level dependencies and different levels of data nesting. Comparisons were made between unadjusted lifespan analyses and those incorporating clustering and nesting adjustments. The results of this case study indicate that properly adjusting for clustering and nesting effects can change the conclusions drawn from statistical significance tests as compared to unadjusted model approaches, and so it remains best practice to properly account for clustering and nesting to reduce the potential for inflated Type I error rates. These findings highlight the importance of accounting for clustering and nesting in preclinical research to ensure valid and robust statistical inference. By demonstrating the practical application of clustering adjustments, this work underscores the broader implications for improving reproducibility and rigor in lifespan studies and other experimental designs.

In India, the rising risk of overweight and obesity among adolescents is a significant public health concern, primarily associated with their frequent consumption of nutrient-poor snacks, sugar-sweetened beverages, and fast foods. Identifying the determinants of their food choices is crucial for developing effective nutrition promotion strategies. This study aimed to identify the determinants of food choices among adolescents in two metro cities in North and South India using a cross-sectional, mixed-methods approach. The study involved adolescents (n = 869) studying in 8^th and 9^th grades from randomly selected government and private schools, utilizing a pre-tested questionnaire and virtual food preference flip cards (quantitative phase), along with in-depth interviews with adolescents, teachers, and parents (n = 11) (qualitative phase). A four-level socio-ecological model was adopted to categorize the determinants associated with adolescent’s food choices. The findings revealed that taste (51%) was the primary determinant driving adolescents to choose outside foods, followed by peer influence (31%) and trendy foods (27%). In-depth interviews further highlighted the impact of social media, parental influence, celebrity endorsements, popular food trends, and marketing incentives such as toys and coupons on adolescents’ food choices. The study provides a springboard for future research into the development of a nutrition-friendly choice architecture to encourage adolescents to make healthy food choices. Public health policy should utilize these determinants to transform the existing food environment of adolescents.