Background: Globally, Musculoskeletal disorders (MSDs) are the biggest contributor (17%) to years lived with disability. For offering diagnosis and appropriate health interventions options along with follow-up care, it is pertinent to have a thorough awareness of its associated risk factors. Objectives: The study aims to assess the prevalence and association between MSDs and risk factors among the Indian older adults above 45 years. Methodology: Prevalence of MSDs among 28,436 participants was estimated using nationally representative survey on older Indian adults. Spatial distribution maps were created to display the magnitude of MSD prevalence at Indian sub-national level. Association between presence of MSDs and associated risk factors (such as occupation, employment duration, physical activity, BMI, diabetes, hypertension, tobacco usage, and alcohol consumption) was explored through Multivariate logistic regression. P-value <0.05 was considered as statistically significant. Results: MSD was prevalent in over half of participants (53.5 (52.9–54.1)%), with more among females and in those aged >60 years (60.4 (59.3–61.4)%). Overall, joint pain (41.9 (41.3–41.4)%) was more common than back pain (32.6 (32.0–33.1)%). Prevalence was highest in Manipur (81.1 (77.9–83.9)%) and lowest in West Bengal (33.1 (30.7–35.5)%). MSD presence was positively associated with certain occupational groups, pre-obesity (BMI 25–29.9 Kg/m²), currently hypertensive, vigorous physical activity among overall population. Tobacco usage was positively associated, while alcohol consumption was linked to a lower occurrence of MSDs for 45–60 years age group. Conclusions: Customised policy interventions can be developed for specific age category of older Indian adults and musculoskeletal health can be improved by addressing modifiable risk factors such as physical inactivity, tobacco usage, avoiding workplace risks in occupations requiring manual labour as revealed by this study.

Existing evidence suggests a lower uptake of cervical cancer screening among Indian women. Coverage is lower in rural than urban women, but such disparities are less explored. So, the present study was conducted to explore the self-reported coverage of cervical cancer screening in urban and rural areas stratified by socio-demographic characteristics, determine the spatial patterns and identify any regional variations, ascertain the factors contributing to urban-rural disparities and those influencing the likelihood of screening among women aged 30–49 years factors residing in urban, rural, and overall Indian settings. We did a secondary analysis of the fifth round of the National Family Health Survey in India (2019-21) data with a sample size of 3,48,882 women. The coverage of cervical cancer screening was estimated using sampling weights. Urban-rural differences were compared using the chi-square test. Spatial patterns were analysed using aggregated district-level data, and the contribution of different independent variables to the urban-rural disparities was estimated using multivariate decomposition analysis. Multivariable logistic regression was conducted using STATA 17 to obtain the significant factors of reported screening in urban and rural areas. The nationwide coverage of cervical cancer screening was 2.0% (95% CI: 1.9-2.0). The urban (2.4%; 2.3–2.5) participants had higher screening coverage than their rural (1.8%; 1.7–1.8) counterparts. Moran’s I statistic confirmed the presence of spatial dependence and geographical gradient. Decomposition analysis depicted small urban-rural differences in the screening coverage of 0.60% (0.4–0.8). Endowment and coefficient contributed to 88.15% and 11.85% of the disparities. Compositional changes were contributed majorly by regional differences, low education, scheduled tribes, and having living children > 2. Higher odds of having screening were associated with older age (AOR 1.45, 95% CI: 1.03–1.28), higher education (1.32; 1.13–1.55), higher age of first intercourse (1.60; 1.43–1.79), married (1.25; 1.08–1.45) and diabetic (1.39; 1.17–1.65) women, and those from South India (6.76; 5.90–7.75). The odds were lower among Muslims, scheduled tribes and participants using hormonal contraceptives. There are significant urban-rural disparities in cervical cancer screening uptake that can be attributed to regional variation, educational inequalities, tribal groups, socio-economic inequalities and parity, necessitating the need to comprehensively design tailor-made advocacy initiatives and simultaneously address the broader determinants of health.

The Global Adult Tobacco Survey (GATS) shows a drop in tobacco use worldwide. Despite the drop, there still continues to be a significant number of tobacco users in India. Research on tobacco use among young persons is commonly prioritised in India, while studies on tobacco use among middle-aged (45–59 years) and elderly (≥ 60 years) adults are noticeably lacking. We have conducted this study with objective to estimate the distribution, determinants and socioeconomic inequalities of smoking (SM) and smokeless tobacco (SLT) consumption across Indian states and union territories. This study was based on 66,606 participants aged ≥ 45 years using Longitudinal Aging Study in India (LASI)-1 (2017–2018) data. Distribution of tobacco consumption (any form, smoking (SM), smokeless (SLT) and both) was documented as per Indian states and union territories with spatial distribution by Indian map. Demographic, socioeconomic, health related and behavioural determinants were established using nested multilevel regression modelling. Socioeconomic disparities were documented using concentration curve. P-value < 0.05 was considered as statistically significant. Overall, 36.78% participants documented using any form of tobacco; with higher consumption of SLT (19.88%) than smoking/SM (13.92%). Only 2.98% consumed both. Mizoram had highest consumption of tobacco in any form (78.21%) and smoking (35.18%). Elderly participants had higher odds of consuming tobacco (any 1.23 (1.18–1.28), SM 1.99 (1.14–1.27), SLT 1.08 (1.03–1.14) and both 1.27 (1.14–1.40 times) than middle aged participants. Females, OBC (other backward castes), urban residence had lower odds in all the categories, while being widow/ separated/ divorced, belonging to Muslim community, having clerical and skilled occupation, poor self-rated health, comorbidity and multimorbidity had higher odds. With decrease in the wealth index, educational status and frequency of physical activity the odds of tobacco consumption increased. The odds of higher tobacco consumption were documented from northeast region (2.56 (2.37–2.76) higher than north). Alcohol consumption had the highest odds (4.94 (4.69–5.21)). Participants exposed to media had lower odds (11% lower) of consuming tobacco. The socioeconomic inequalities in tobacco consumption were significantly distributed more among the poorest (any -0.064 (-0.072 to -0.056) and SLT -0.069 (-0.072 to -0.056)). Prioritising tobacco prevention and increasing availability and accessibility of cessation programmes that are suited with unique requirements and circumstances, even for elderly population, are essential focusing on the higher determinants across poorest section in the country.

Treatment delays are significantly associated with advanced stage, poor response to treatment, increased mortality risk, poor health outcomes, increased healthcare expenditures among cancer patients. However, factors associated with these delays have not yet been robustly evaluated. In order to bridge this gap, we determined the delayed time to treatment initiation (TTI) among cancer patients in India, ascertained its determinants, and assessed the trends of delayed TTI. We analysed data collected from 6695 cancer patients seeking outpatient/daycare treatment, recruited at purposively selected seven healthcare facilities across six states of India. Data on socio-demographic and clinical characteristics including date of cancer diagnosis, date of treatment initiation, cancer site, stage and type of treatment were collected to determine the median TTI and ascertain its determinants among cancer patients in India. Time to treatment initiation was calculated as the duration (days) between diagnosis of cancer (histologically/clinically) and date of initiation of treatment. Multi-variable logistic regression was employed to analyse the relationship between the outcome variable (TTI) and each explanatory variable. A Cox Proportional Hazard (CPH) model was used to conduct time-to-event analysis, and to assess the impact of government-funded health insurance on timely cancer treatment initiation. The median (IQR) overall TTI was 20 (7–39) days, with a mean of 53.7 days (SD, 192.9). The TTI was higher for those having head and neck cancer (median TTI: 29 days, IQR: 10.5–55.5) and those receiving radiotherapy as initial treatment (27.5 days, IQR: 10–49.5). Younger patients, those educated up to graduation level and males had significantly lower odds of delayed TTI. As compared to patients who were diagnosed between 1995 and 2017, those diagnosed after 2018 had a 36% (26–46%) higher odds of timely initiation of treatment within 30 days. Upon stratifying by enrolment under PMJAY, we found that while the access for timely treatment initiation increased by 33% for those who were not enrolled, vs. 90% among those enrolled under PM-JAY. Overall, this shows significant improvement in timely initiation of cancer treatment as a result of introduction of PM-JAY. The study highlights the positive impact of government-funded health insurance schemes on the timely access to cancer treatment in India. Our study recommends expanding AB PM-JAY cancer packages to include cost-effective treatments, increasing population coverage under screening programs and promoting e-RUPI to reduce financial constraints associated with diagnostic services to address delayed treatment initiation due to unknown cancer stages. Department of Health Research, 10.13039/501100007334 Ministry of Health and Family Welfare , New Delhi, India.

Introduction: Anaemia is a disease of public health importance with multi-causal pathways. Previous literature suggests the role of indoor air pollution (IAP) on haemoglobin levels, but this has been studied less due to logistic constraints. A high proportion of the population in developing countries, including India, still depends on unclean fuel, which exacerbates IAP. The objective was to study the association between anaemia and IAP among the older Indian adult population (≥ 45 years) as per gender. Methods: Our study analysed the nationally representative dataset of the Longitudinal Ageing Study in India (LASI 2017–18, Wave-1). We have documented the association of anaemia (outcome variable) with IAP (explanatory variable). To reduce the confounding effects of demographic and socioeconomic; health related and behavioural covariates; propensity score matching (PSM) was conducted. Nested multilevel regression modelling was conducted. States and union territories were categorised cross tabulated as low, middle and high as per anaemia and IAP exposure. P value < 0.05 was considered statistically significant. SATA version 17 was used for analysis. Results: More than half (52.52%) of the participants were exposed to IAP (male (53.55%) > female (51.63%)). The odds of having anaemia was significantly 1.19 times higher (AOR 1.19 (1.09–1.31)) among participants using unclean/ solid fuel. The adjusted odds were significantly higher among participants exposed to pollution-generating sources (AOR 1.30; 1.18–1.43), and household indoor smoking (AOR 1.17 (1.07–1.29). The odds of having anaemia were significantly higher (AOR 1.26; 1.15–1.38) among participants exposed to IAP, which was higher in males (AOR 1.36; 1.15–1.61) than females (AOR 1.21; 1.08–1.35). Empowered Action Group (EAG) states like Uttar Pradesh, Chhattisgarh, Madhya Pradesh, Bihar had both high anaemia and IAP exposure. Conclusion: This study established the positive association of anaemia with indoor air pollution among older Indian adults through a nationally representative large dataset. The association was higher among men. Further research is recommended to understand detailed causation and to establish temporality. It is a high time to implement positive intervention nationally to decrease solid/ unclean fuel usage, vulnerable ventilation, indoor smoking, IAP and health hazards associated with these with more focused actions towards EAG states.

Introduction: An aging population is associated with an increased risk of cognitive decline. Sleep duration, both excess and deficiency, is a risk factor for cognitive impairment. Therefore, this study was conducted to assess the relationship between sleep duration and cognition in the Indian population. Methods: This study was a secondary analysis of the first wave of the Longitudinal Aging Study in India (LASI) conducted across India in all 34 states and union territories. Sleep duration was calculated using sleep and wake times, whereas cognition was measured as a composite cognitive index. Both univariable and multivariable linear regressions were performed on the composite cognitive score. Subgroup analyses were conducted based on sex and age groups (45-59 years and ≥60 years). Results: The median (IQR) cognition score was 25 (20-30). A sleep duration of ≤4 hours was associated with a decrease in cognition status of 1.15 points (1.57-0.72), and a sleep duration of ≥9 hours was associated with a decrease of 0.93 points (1.25-0.60). Subgroup analysis revealed that this relationship remained consistent across both genders and both age groups. Conclusion: Both long and short durations of sleep were seen to be associated with a decrease in cognition scores among Indian adults, in both sexes and both age groups. Thus, proper sleep duration can help in the prevention of declining cognition as one ages and the development of dementia.