Interrelationships between physical multimorbidity, depressive symptoms and cognitive function among older adults in China, India and Indonesia: A four-way decomposition analysis.

OBJECTIVE: This paper explores the role of depressive symptoms (mediator/moderator) in the association between physical multimorbidity (exposure) and cognitive function (outcome) among older adults in the three most populous middle-income countries. METHODS: This study used cross-sectional data from China (2015 China Health and Retirement Longitudinal Study), India (2017/2018 Longitudinal Ageing Study in India), and Indonesia (2014/2015 Indonesian Family Life Survey), with a total sample of 73,199 respondents aged ≥ 45 years. Three domains of cognitive tests were harmonised across surveys, including time orientation, word recall, and numeracy. The four-way decomposition analysis assessed the mediation and interaction effects between exposure, mediator/moderator, and outcome, adjusted for covariates. RESULTS: The mean age of the respondents (in years) was slightly younger in Indonesia (56.0, SD = 8.8) than in China (59.5, SD = 9.3) and India (60.0, SD = 10.5). The proportion of male respondents was 49.3 % in China, 47.3 % in India, and 47.5 % in Indonesia. Respondents in China had the highest mean cognitive function z scores (54.7, SD = 19.9), followed by India (51.1, SD = 20.0) and Indonesia (51.0, SD = 18.4). Physical multimorbidity was associated with lower cognitive function in China and India (p < 0.0001), with 48.4 % and 40.0 % of the association explained by the mediating effect of depressive symptoms ('overall proportion due to mediation'). The association was not found in Indonesia. CONCLUSION: Cognitive functions were lower among individuals with physical multimorbidity, and depressive symptoms mainly explained the association. Addressing depressive symptoms among persons with physical multimorbidity is likely to have not only an impact on their mental health but could prevent cognitive decline.

Prevalence of chronic cough, its risk factors and population attributable risk in the Burden of Obstructive Lung Disease (BOLD) study: a multinational cross-sectional study.

Background: Chronic cough is a common respiratory symptom with an impact on daily activities and quality of life. Global prevalence data are scarce and derive mainly from European and Asian countries and studies with outcomes other than chronic cough. In this study, we aimed to estimate the prevalence of chronic cough across a large number of study sites as well as to identify its main risk factors using a standardised protocol and definition. Methods: We analysed cross-sectional data from 33,983 adults (≥40 years), recruited between Jan 2, 2003 and Dec 26, 2016, in 41 sites (34 countries) from the Burden of Obstructive Lung Disease (BOLD) study. We estimated the prevalence of chronic cough for each site accounting for sampling design. To identify risk factors, we conducted multivariable logistic regression analysis within each site and then pooled estimates using random-effects meta-analysis. We also calculated the population attributable risk (PAR) associated with each of the identifed risk factors. Findings: The prevalence of chronic cough varied from 3% in India (rural Pune) to 24% in the United States of America (Lexington,KY). Chronic cough was more common among females, both current and passive smokers, those working in a dusty job, those with a history of tuberculosis, those who were obese, those with a low level of education and those with hypertension or airflow limitation. The most influential risk factors were current smoking and working in a dusty job. Interpretation: Our findings suggested that the prevalence of chronic cough varies widely across sites in different world regions. Cigarette smoking and exposure to dust in the workplace are its major risk factors. Funding: Wellcome Trust.

The Indian Health and Demographic Surveillance System Network: Opportunity to Generate Evidence for Public Health Policy.

The Health and Demographic Surveillance System (HDSS) is a valuable longitudinal cohort study that tracks the health and demographic changes of a geographically defined population, serving as a platform for research and evidence-based policymaking. In India, there are nearly 20 HDSS sites covering diverse areas and populations totaling around two million. To foster collaboration, the Indian HDSS Network (IHN) was formed, comprising 19 sites from 16 institutes, covering a population of 1.5 million. The IHN aims to standardize data collection processes while allowing site-specific autonomy, generating high-quality longitudinal health, and demographic data. To ensure effective coordination, a governance structure with a rotating secretariat and working committee was proposed. The IHN envisions conducting robust multicentric research, supporting data-driven efforts to improve population health, and promoting research-policy synergy. The network's outcomes have the potential to optimize health research funding, generate epidemiological data, and provide evidence for public health policy. Collaboration within the IHN strengthens HDSS sites in newer technologies and community-based research, fostering capacity building. Seed funding is being sought to formalize and support the day-to-day functioning of the network, which holds promise for advancing population health and informing policymaking in India.