The provisions and recognition of Schedule Castes (SCs), the constitutional term for the Dalits in India, have been exclusively extended to Hindus, Buddhists, and Sikhs (HBS). Omission of Dalit Muslims and Christians (MC) from the SC category stripped them of the affirmative action benefits tied with the SC status. This study aimed to explore how such differential treatment might play a role in differential health outcomes in Dalit women in India.
Drawing data on 177,346 Dalit women, aged 20 to 49 years, from two successive nationally representative surveys, we assessed the differential likelihood of hypertension and diabetes, between MC- and HBS- Dalit women. Accounting for birth cohort-, survey wave-, and state of residence- fixed effects, along with socioeconomic conditions and cardiometabolic risk factors, we obtained adjusted odds of having hypertension and diabetes in MC women. To check the validity of our results, we conducted similar analyses using data on 170,889 Scheduled Tribe (ST) women, another marginalized group, whose ST-status recognition were not tied to religion.
We found that Dalit MC women were 1.13 (95% CI: 1.03–1.25) and 1.19 (95% CI: 1.05–1.36) times more likely to have hypertension and diabetes, respectively, compared to Dalit HBS women. Conversely, no statistically significant differential likelihood of these conditions was observed between MC and HBS women in the ST sample.
Our investigation thus, indicated a potential link at the crossroads of religion and caste that may contribute to the health disparities among marginalized women in India.
Genomic sequencing has been an invaluable tool to determine the evolution of SARS-CoV-2. In the present study, we provided a comprehensive description of the SARS-CoV-2 variants circulated in the Philippines.
The dataset from the human COVID-19 infections was acquired by downloading the sequences and their associated metadata spanning from March 2020 to April 2024. Then, we executed several filtering criteria to acquire the final dataset for the Philippine samples and performed spatial distribution analysis and phylogenetic tree construction of the reported SARS-CoV-2 sequences.
A total of 16,679,203 SARS-CoV sequences were obtained, of which 17,393 (0.10 %) were sampled in the Philippines. Western Visayas reported the highest SARS-CoV-2 sequences (21.33 %), while the Bangsamoro Autonomous Region in Muslim Mindanao reported the least (0.48 %). The phylogenetic tree revealed the evolution of the detected SARS-CoV-2 variants circulating in the Philippines with 19 A as the first reported case (based on the GISAID submission), and 24 A (JN.1) as the currently circulating variant. Omicron variants have dominated the Philippines with 21 L (Omicron, BA.2) having 5102 cases (29.33 %), followed by 22B (BA.5) having 2184 cases (12.57 %). Using Pearson's Chi-square test of independence, we showed that there is a significant association between the age-groups and gender with the detection years.
Altogether, this analysis showed the updated epidemiological trends of the reported SARS-CoV-2 variants in the Philippines. This increases the importance of conducting surveillance on viral infectious diseases such as COVID-19 to provide the scope and trajectory of viral spread in a country.
The globally increasing older population raises concerns about age-related conditions, including cognitive impairment and depressive symptoms. In Latin America, nearly one-third of the population is affected by either of these conditions. However, data investigating the association between cognitive impairment and depressive symptoms, particularly in Brazil, are limited to small-scale studies that have not carefully examined the critical effects of variables such as education level and socioeconomic status on this relationship. We aimed at exploring this association in a representative population-based cohort.
We used the Brazilian Longitudinal Study of Aging (ELSI-BRAZIL) database to examine the relationship between depressive symptoms and cognitive impairment in Brazilian older adults, adjusted for potential confounders. Direct acyclic graphs and multivariable linear regression were used to build our model. Depressive symptoms were measured using a short version of the Center for Epidemiologic Studies Scale (CES D-8), and combined memory recall test as a surrogate of cognitive impairment.
The study included 8280 participants. Only education level was identified as a confounder for the relationship between memory loss and depressive symptoms. After adjusting for age, sex, and education level, there was strong evidence for a negative association between depressive symptoms and memory performance. For every 5-unit increase in the CES D-8 score, there was a reduction in memory capacity, translating to a loss of approximately one word in the combined words recall test (mean − 0.18, 95% CI -0.22; −0.15, P < 0.001). In addition, we found strong evidence for an interaction between socioeconomic status and depressive symptoms. Subjects belonging to medium socioeconomic status (SES) showed more pronounced memory decline, when compared to those with lower SES (mean − 0.28, 95% CI -0.42 to −0.14, P < 0.001).
In adults aged over 50, after adjusting for sex, age, and educational level, a 5-unit increase in CES D-8 score is associated with loss of one point in the combined memory recall test. This association seems to be confounded by educational level and significantly modified by socioeconomic status.
Under the collective weight of growing test volume, staffing constraints, and Medicare reimbursements cuts, an enhancement-based, alternative payment structure focused on rewarding the laboratory's care delivery efforts via benchmarking is appealing. However, achieving a value-based payment model requires the development of an inclusive laboratory care delivery model (LCDM) framework. Today, a holistic, practical LCDM framework for laboratory medicine does not exist. However, such creation is essential for establishing unifying tenants of practice for value-tracing by which standardized key performance and population health indicators can be derived. LAB-CARES is the first step in formulating an LCDM with the primary objective of defining and streamlining the processes and strategies necessary to deliver and articulate the value of diagnostic excellence across the healthcare system. The goal of LAB-CARES is to maximize efficiencies, enhance quality, disseminate clinical expertise, increase patient safety, and promote integrative practice. LAB-CARES is designed to improve an individual patient's quality of life (longitudinal laboratory results – beyond one test) and their surrounding communities (e.g., through surveillance and prevention – beyond one patient). Further professional conversation and efforts are paramount to integrate LAB-CARES as a formalized structure within the healthcare landscape.

