Determinants of body weight changes during Ramadan fasting in India amid COVID-19: A cross-sectional study

Ramadan intermittent fasting (RIF) presents unique challenges and opportunities for public health and clinical practice, especially in populations with a high prevalence of non-communicable diseases. This study aims to investigate the impact of RIF on weight change among Indian Muslims and explore the associated demographic, dietary, and behavioral factors. A cross-sectional survey was conducted with a sample of Indian Muslim adults who observed RIF. Participants were asked to report their demographic information, family and personal health history, and dietary and lifestyle behaviors before and during Ramadan month. The primary outcome was body weight change, with secondary outcomes including changes in dietary patterns, physical activity, and other health-related lifestyle behaviors. The study found that during Ramadan, nearly half of the participants (48.5%) self-reported a retained initial weight, while a significant fraction (30.9%) self-reported a modest weight reduction between 0.5 to 2.5 kg at the end of Ramadan. Additionally, self-reported eating practices demonstrated moderately altered by about half (48.4%) of the study participants, with 32.2% reporting minor changes and 8.2% indicating substantial changes. An urban residence was associated with a higher likelihood of weight gain, where urban residents showed 3 times the odds of increased weight compared to rural inhabitants. Employment status emerged as a significant determinant for weight fluctuation, influencing both weight gain and loss. During Ramadan, there was a significant rise in snacking frequency, increasing from 21.7% to 32.6% in comparison with pre-Ramadan. The consumption of large quantities of food more frequently grew from 14.9% to 36%, and the incidence of eating despite not being hungry went up from 17.4% to 33.2%. The study demonstrates that RIF is associated with variable changes in body weight among adult Indian Muslims, influenced by urbanization, employment status, and dietary changes. The findings suggest that clinicians should provide tailored advice about body weight regulation during Ramadan and consider integrating community-based health initiatives within religious settings to improve health outcomes.

Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital

BACKGROUND

Studying the genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may help determine outbreak clusters and virus transmission advantages to aid public health efforts during the pandemic. Thus, we tracked the evolution of SARS-CoV-2 by variant epidemiology, breakthrough infection, and patient characteristics as the virus spread during the Delta and Omicron waves. We also conducted phylogenetic analyses to assess modes of transmission.

METHODS

Nasopharyngeal samples were collected from a cohort of 900 patients with positive polymerase chain reaction (PCR) test results confirming COVID-19 disease. Samples underwent real-time PCR detection using TaqPath assays. Sequencing was performed with Ion GeneStudio using the Ion AmpliSeq™ SARS-CoV-2 panel. Variant calling was performed with Torrent Suite™ on the Torrent Server. For phylogenetic analyses, the MAFFT tool was used for alignment and the maximum likelihood method with the IQ-TREE tool to build the phylogenetic tree. Data were analyzed using SAS statistical software. Analysis of variance or t tests were used to assess continuous variables, and χ² tests were used to assess categorical variables. Univariate and multivariate logistic regression analyses were preformed to estimate odds ratios (ORs).

RESULTS

The predominant variants in our cohort of 900 patients were non-variants of concern (11.1 %), followed by Alpha (4.1 %), Beta (5.6 %), Delta (21.2 %), and Omicron (58 %). The Delta wave had more male than female cases (112 vs. 78), whereas the Omicron wave had more female than male cases (311 vs. 208). The oldest patients (mean age, 43.4 years) were infected with non-variants of concern; the youngest (mean age, 33.7 years), with Omicron. Younger patients were mostly unvaccinated, whereas elderly patients were mostly vaccinated, a statistically significant difference. The highest risk for breakthrough infection by age was for patients aged 30-39 years (OR = 12.4, CI 95 %: 6.6-23.2), followed by patients aged 40-49 years (OR = 11.2, CI 95 %: 6.1-23.1) and then 20-29 years (OR = 8.2, CI 95 %: 4.4-15.4). Phylogenetic analyses suggested the interaction of multiple cases related to outbreaks for breakthrough infections, healthcare workers, and intensive care unit admission.

CONCLUSION

The findings of this study highlighted several major public health ramifications, including the distribution of variants over a wide range of demographic and clinical variables and by vaccination status.