Clinical Epidemiology and Global Health最新文献

{"title":"Celiac disease and COVID-19: Leveraging health registries for crucial insights and public health strategies","authors":"Beatrice Gasperini ,&nbsp;Antonio Cherubini ,&nbsp;Marco Pompili ,&nbsp;Donatella Sarti ,&nbsp;Emilia Prospero","doi":"10.1016/j.cegh.2025.101962","DOIUrl":"10.1016/j.cegh.2025.101962","url":null,"abstract":"<div><h3>Background</h3><div>Celiac disease is an immune-mediated disorder triggered by gluten in genetically predisposed individuals, characterized by the presence of specific antibodies and inflammation of the small intestine. This study aims to assess the risk of SARS-CoV-2 infection and clinical outcomes among individuals with celiac disease compared to the general population using administrative data from health registries.</div></div><div><h3>Methods</h3><div>This retrospective case-control study was conducted in the Marche region, Italy, using the Celiac Disease Registry and the Italian National Monitoring System for COVID-19, from February 25, 2020, to March 31, 2021. Propensity score matching (1:1) was applied to compare celiac patients and controls based on age, sex, residence. Socio-demographic variables, chronic conditions, clinical outcomes were assessed.</div></div><div><h3>Results</h3><div>Among 4488 celiac patients, 209 (4.65 %, 95 % CI: 4.05–5.31 %) contracted COVID-19. The infection rate in the celiac group (4.65 %) was similar to that in the non-celiac (4.43 %) (OR: 1.05, 95 % CI: 0.91–1.21, p = 0.49). Hospitalizations occurred in 7.2 % of non-celiac patients and 2.9 % of celiac patients (p = 0.015). After propensity score matching, 417 individuals were included in the analysis, showing no significant differences in clinical outcomes, including hospitalization and mortality, between the groups (p &gt; 0.05).</div></div><div><h3>Conclusions</h3><div>By integrating data from the Celiac Disease Registry and COVID-19 Monitoring System, we conducted a comprehensive analysis, providing valuable insights with minimal resource investment compared to interview-based studies. The findings suggest that celiac patients do not require additional COVID-19 precautions beyond standard public health measures, supporting the use of registries for informed healthcare decision-making.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101962"},"PeriodicalIF":2.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial insights into chronic bronchitis: Evaluating hotspots and environmental factors in MUDHRA-cohort of Mysuru district, India","authors":"Manjunatha M.C ,&nbsp;Mahesh P.A ,&nbsp;Madhu B ,&nbsp;Sawant Sushant Anil ,&nbsp;Karthik C.B","doi":"10.1016/j.cegh.2025.101921","DOIUrl":"10.1016/j.cegh.2025.101921","url":null,"abstract":"<div><h3>Background</h3><div>Geospatial techniques are critical for identifying potential environmental risk factors and implementing effective prevention strategies for chronic diseases. The <strong>M</strong>ysuru st<strong>U</strong>dies of <strong>D</strong>eterminants of <strong>H</strong>ealth in <strong>R</strong>ural <strong>A</strong>dults (MUDHRA)-Cohort was a notable study that systematically investigated the prevalence and risk factors associated with Chronic Bronchitis (CB) in 16 randomly selected villages of Mysuru District between 2006 and 2009. The objective of this study is to spatially visualize the highest prevalence of MUDHRA-CB at village level, and identifying potential environmental risk factors.</div></div><div><h3>Methods</h3><div>An analysis was conducted on a total of 8457 individuals aged 30 years and older to ascertain the presence of chronic bronchitis symptoms. To assess the prevalence of chronic bronchitis, a door-to-door survey was conducted using international Burden of Obstructive Lung Disease (BOLD) study questionnaires. The thematic map of chronic bronchitis burden was generated using Geographic Information System (GIS) tools and overlaid on the land use and land cover patterns extracted from Remote Sensing (RS) satellite images.</div></div><div><h3>Results</h3><div>The thematic map identified Karya village has having the highest prevalence (14.82 %), while there were no reported cases of chronic bronchitis in Alatthuru village. The land use land cover map generated showed the presence of a mine located around 310 m from Karya village. Inhalation of dust particles from the mine operations and wind direction could be attributed to the higher prevalence of chronic bronchitis.</div></div><div><h3>Conclusion</h3><div>Spatial epidemiological research studies that incorporate RS, GIS, and local field studies may aid in identifying potential environmental factors associated with a higher risk of chronic conditions.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101921"},"PeriodicalIF":2.3,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing ensemble deep learning models for precise detection of gynaecological cancers","authors":"Chetna Vaid Kwatra ,&nbsp;Harpreet Kaur ,&nbsp;Saiprasad Potharaju ,&nbsp;Swapnali N. Tambe ,&nbsp;Devyani Bhamare Jadhav ,&nbsp;Sagar B. Tambe","doi":"10.1016/j.cegh.2025.101956","DOIUrl":"10.1016/j.cegh.2025.101956","url":null,"abstract":"<div><h3>Problem considered</h3><div>The accurate and timely identification of gynaecological cancers is critical for improving patient outcomes and increasing survival rates. However, diagnostic imaging for these conditions is complex and prone to human error, necessitating advanced computational methods to enhance diagnostic reliability.</div></div><div><h3>Methods</h3><div>This study proposes an ensemble framework combining two state-of-the-art deep learning models, ResNet50 and Inception V3, for robust gynaecological malignancy detection. The synergistic integration of these models aims to leverage their strengths, significantly improving diagnostic performance. The models were trained and validated on a comprehensive dataset of medical images, including histopathology slides and radiological scans. The ensemble model's performance was rigorously evaluated using key metrics, including sensitivity, specificity, and overall diagnostic accuracy.</div></div><div><h3>Results</h3><div>The ensemble model achieved remarkable diagnostic accuracy, with results showing 99.8 % accuracy, 99.6 % sensitivity, and 99.9 % specificity. In comparison, the individual performance of ResNet50 and Inception V3 models was substantially lower. This demonstrates the effectiveness of the ensemble approach in detecting a wide range of gynaecological cancers, including ovarian and cervical malignancies.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101956"},"PeriodicalIF":2.3,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of 2021 surveillance system for under-five children with pneumonia in Bantul Regency, Indonesia","authors":"Nining Puji Lestari ,&nbsp;Vicka Oktaria ,&nbsp;Samsu Aryanto ,&nbsp;Bayu Satria Wiratama","doi":"10.1016/j.cegh.2025.101958","DOIUrl":"10.1016/j.cegh.2025.101958","url":null,"abstract":"<div><h3>Introduction</h3><div>Hospital involvement in pneumonia surveillance for children under five was found to be limited. This study aimed to assess the sensitivity of pneumonia surveillance using the capture-recapture method and provide an overview of pneumonia morbidity and mortality in children under five.</div></div><div><h3>Methods</h3><div>A descriptive study using secondary data on pneumonia cases among children under five in 2021 was conducted. Data were collected from all public health centers and eight selected hospitals in Bantul Regency, chosen based on the highest number of reported cases. <strong>The sample size included all identified cases from these facilities.</strong> Cases were defined as acute pneumonia in children under five, meeting ICD-10 criteria (J12, J13, J14, J15, J16, J17, J18, and P23.9). Data were analyzed descriptively.</div></div><div><h3>Results</h3><div>Hospitals accounted for 87.9 % (872 cases) of the 992 cases identified from both data sources. The sensitivity of surveillance systems was 2.9 % at public health centers, 21.7 % at hospitals, and 23.9 % when considering data from both sources. Furthermore, 85.7 % (n = 14) of the deaths were attributed to unspecified congenital pneumonia.</div></div><div><h3>Conclusions</h3><div>The sensitivity of under-five pneumonia surveillance in Bantul remains low, primarily due to limited hospital participation. Strengthening hospital engagement in surveillance activities and enhancing interventions for congenital pneumonia is essential for improving case detection and public health response.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101958"},"PeriodicalIF":2.3,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence and mortality of infective endocarditis in Kazakhstan: A nationwide epidemiological study (2018–2022)","authors":"Zhumakyz Kussainova ,&nbsp;Mark Dayer ,&nbsp;Tolkyn Bulegenov ,&nbsp;Askar Abiltayev ,&nbsp;Guzyal Abilmazhinova ,&nbsp;Olga Tashtemirova ,&nbsp;Gulzhanat Jakova ,&nbsp;Sholpan Abralina ,&nbsp;Gulnara Tuleshova ,&nbsp;Islam Salikhanov","doi":"10.1016/j.cegh.2025.101959","DOIUrl":"10.1016/j.cegh.2025.101959","url":null,"abstract":"<div><h3>Background</h3><div>Over the past two decades, the global incidence rate of Infective Endocarditis (IE) has increased significantly, reaching 7.0–14.3 cases per 100,000 individuals per annum. Concurrently, the three-month mortality rate has risen to nearly 40 %. Despite these alarming trends, the worldwide epidemiological profile of IE remains incomplete, mainly due to the lack of data from Central Asian countries. To address this gap, we have undertaken an in-depth analysis of the prevalence and mortality rates of IE in Kazakhstan.</div></div><div><h3>Methods</h3><div>Using a nationwide database, we identified the annual trends in prevalence and mortality from IE in Kazakhstan over 5 years. Cumulative survival and potential demographic and clinical predictors of mortality among 1061 patients with IE were evaluated.</div></div><div><h3>Results</h3><div>Between 2018 and 2022, the incidence rate of IE in Kazakhstan was 5.4 cases per 100,000 population per annum. 21.3 % of patients with IE required valve replacement. The peak in-hospital mortality rate was observed in 2021, reaching 27.8 %. Mortality rates were notably lower among patients who underwent surgery (OR 0.7; 95 % CI 0.48–0.92; p = 0.04).</div></div><div><h3>Conclusions</h3><div>In Kazakhstan, despite a relatively low incidence of IE, the mortality rate among patients remains alarmingly high. Our comprehensive epidemiological analysis provides critical insights into IE incidence and mortality trends in Kazakhstan, offering valuable data that can significantly enhance the understanding and management of IE across Central Asia.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101959"},"PeriodicalIF":2.3,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing the diagnosis accuracy and efficacy of presepsin (sCD14) and nCD64 in neonatal sepsis: A systematic review and meta-analysis","authors":"Amit Kumar Mittal ,&nbsp;Mamta Patel ,&nbsp;Dolat Singh Shekhawat ,&nbsp;Pratibha Singh ,&nbsp;Kuldeep Singh","doi":"10.1016/j.cegh.2025.101957","DOIUrl":"10.1016/j.cegh.2025.101957","url":null,"abstract":"<div><h3>Background</h3><div>Neonatal sepsis is a leading cause of morbidity and mortality among newborns, requiring early and accurate diagnosis for effective treatment. sCD14 and nCD64 have emerged as promising biomarkers due to their enhanced sensitivity and specificity compared to traditional methods.</div></div><div><h3>Objective</h3><div>To evaluate and compare the diagnostic accuracy and clinical utility of sCD14 and nCD64 in detecting neonatal sepsis.</div></div><div><h3>Methods</h3><div>A systematic review and meta-analysis were conducted, including studies that assessed the sensitivity, specificity, and overall diagnostic performance of sCD14 and nCD64. Various key metrics such as DOR, PLR, NLR, and AUC were analyzed.</div></div><div><h3>Results</h3><div>Eleven studies with 1303 neonates (777 sepsis cases, 526 controls) were included. For sCD14, the pooled sensitivity was 0.82 (95 % CI: 0.65–0.92), specificity was 0.79 (95 % CI: 0.59–0.91), and AUC was 0.88. For nCD64, pooled sensitivity was 0.84 (95 % CI: 0.78–0.89), specificity was 0.79 (95 % CI: 0.65–0.88), and AUC was 0.89. Both biomarkers demonstrated high diagnostic reliability, with DORs of 18 (sCD14) and 17.04 (nCD64).</div></div><div><h3>Conclusions</h3><div>sCD14 and nCD64 show significant potential as reliable biomarkers for the early diagnosis of neonatal sepsis. High diagnostic accuracy makes them valuable tools for improving clinical decision-making. However, further studies are needed to validate their practical implementation in routine neonatal care, feasibility, and cost-effectiveness.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101957"},"PeriodicalIF":2.3,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21)","authors":"Pinky Pandey ,&nbsp;Sacheendra Shukla ,&nbsp;Niraj Kumar Singh ,&nbsp;Mukesh Kumar","doi":"10.1016/j.cegh.2025.101949","DOIUrl":"10.1016/j.cegh.2025.101949","url":null,"abstract":"<div><h3>Aim</h3><div>This study aimed to delineate spatial variations in under-five mortality across Uttar Pradesh and evaluate the efficacy of various machine learning algorithms in identifying critical determinants influencing these mortality rates.</div></div><div><h3>Methods</h3><div>The study utilized data from the National Family and Health Survey (NFHS) - V. Four machine learning algorithms—Random Forests, Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes—were applied alongside a traditional logistic regression model. Predictive performance was evaluated using metrics such as model accuracy and receiver operating characteristic (ROC) curves. Descriptive analysis highlighted regional variations in under-five mortality rates.</div></div><div><h3>Results</h3><div>Notable regional disparities in under-five mortality were observed across Uttar Pradesh. Predictive accuracies ranged from 76 % to 79.4 %, with the logistic regression model achieving the highest accuracy (79.4 %). All ML models demonstrated comparable predictive capabilities. The most effective model identified key determinants of under-five mortality, including breastfeeding status, number of births in the preceding five years, child's gender, birth intervals, antenatal care, birth order, type of water source, and maternal body mass index.</div></div><div><h3>Conclusion</h3><div>Machine learning models provide valuable insights into the determinants of under-five mortality, with the logistic regression model demonstrating superior predictive performance. Policy measures targeting critical factors, such as promoting breastfeeding, optimizing birth intervals, and improving maternal health and antenatal care, can significantly enhance childhood survival rates in Uttar Pradesh.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101949"},"PeriodicalIF":2.3,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insecticide-treated nets utilization and influencing factors on middle school students in Southeast Nigeria. A cross-sectional study","authors":"Egbobe JohnPaul Otuomasiri ,&nbsp;Magnus Michael Sichalwe ,&nbsp;Ezaka Ephraim Ibeabuchi","doi":"10.1016/j.cegh.2025.101952","DOIUrl":"10.1016/j.cegh.2025.101952","url":null,"abstract":"<div><h3>Background</h3><div>Malaria is a major cause of mortality, leading to higher healthcare costs and reduced household income, particularly among low-income individuals. Successful eradication relied on individual acceptance, participation, and continuous education about control measures. This study explored factors influencing insecticide-treated net (ITN) utilization among middle school students in Southeast Nigeria.</div></div><div><h3>Methods</h3><div>An analytical cross-sectional study was conducted from October to November 2020, using systematic sampling to recruit 238 participants from three schools in Southeastern Nigeria. Data were analyzed with SPSS version 23, employing descriptive statistics for univariate analysis to determine ITN usage proportions. Bivariate analysis utilized cross-tabulation, while multivariate analysis involved linear regression.</div></div><div><h3>Results</h3><div>Most (96.6 %) were aware of ITNs, but regular usage was low at 20.6 %. Knowledge of ITNs and parental employment significantly influenced usage, with employed parents and greater awareness linked to higher utilization. Participants aged 15–19 were 2.258 times more likely to use ITNs than those aged 20–24. Additionally, awareness of ITNs increased the likelihood of usage by 8.638 times, and each point increase in malaria risk perception correlated with a 30.2 % increase in ITN usage likelihood.</div></div><div><h3>Conclusion</h3><div>Despite widespread awareness of ITNs, regular use is low, especially among students aged 20–24 and unemployed households. The positive link between knowledge and ITN use highlights the need for effective health education. Additionally, free distribution significantly boosts consumption, underscoring the importance of tailored interventions for vulnerable populations. Enhancing community understanding and access to ITNs is crucial for improving malaria prevention efforts.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101952"},"PeriodicalIF":2.3,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143199761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of a community-based health behaviour intervention on healthcare services use among people with type 2 diabetes in Nepal","authors":"Grish Paudel ,&nbsp;Corneel Vandelanotte ,&nbsp;M Mamun Huda ,&nbsp;Padam Kanta Dahal ,&nbsp;Lal Rawal","doi":"10.1016/j.cegh.2025.101954","DOIUrl":"10.1016/j.cegh.2025.101954","url":null,"abstract":"<div><h3>Background</h3><div>Community-based health behavioural interventions have effectively reduced the glycated haemoglobin level (HbA1c) among individuals with type 2 diabetes mellitus (T2DM). However, there is no evidence of such interventions in improving the healthcare utilisation in under-resourced settings. Therefore, this study aimed to assess the effect of intervention in improving the visits to health facilities and specialists and reducing emergency department visits and hospital admissions among people with T2DM in Nepal.</div></div><div><h3>Methods</h3><div>A cluster-randomised controlled trial was conducted in the Kavrepalanchowk and Nuwakot districts of Nepal, enrolling 481 people with clinically diagnosed type 2 diabetes, aged 30–70 years. A total of 30 study sites across two districts were randomly allocated into 15 intervention groups and 15 control groups. The participants in the intervention group received a community health worker and peer supporter-led health behavioural intervention for 6 months. The primary outcome of the study (health facility visits, specialist visits, emergency visits and hospital admissions) were assessed at baseline and 6 months post-intervention.</div></div><div><h3>Results</h3><div>Intervention participants reported a higher increase in health facility visits, specialist visits, emergency visits and hospital admissions by 7.2 %, 13.5 %, 1.3 % and 0.4 % respectively, compared to control participants. However, these changes were not statistically significant. Visits to health facilities significantly increased, but only among intervention participants attending more sessions (adjusted odds ratio [AOR] = 1.16, 95 % CI:1.05–1.28). Approximately half (45.4 %) of the intervention participants attended six or fewer intervention sessions out of twelve.</div></div><div><h3>Conclusion</h3><div>While the intervention had a positive effect on healthcare use in general, this was only significant in those with higher exposure to the intervention sessions. As such, efforts should be made that increase adherence and retention to the intervention sessions to maximise the benefit of this health behavioural intervention in improving healthcare service utilisation among individuals with type 2 diabetes in Nepal.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101954"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143199696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining rural-urban differences in life satisfaction and its association with health among elderly people in India: Evidence from LASI survey","authors":"Nipam Datta ,&nbsp;Sushanta Biswas ,&nbsp;Dwipen Barman ,&nbsp;Bijoy Das ,&nbsp;Piyal Basu Roy ,&nbsp;Abhijit Sarkar","doi":"10.1016/j.cegh.2025.101950","DOIUrl":"10.1016/j.cegh.2025.101950","url":null,"abstract":"<div><h3>Background</h3><div>Health-related issues are common phenomena in the human body with increasing age. This study explores the disparities in life satisfaction among the elderly population in rural and urban areas of India and its association with health.</div></div><div><h3>Methods</h3><div>Data from the Longitudinal Ageing Study in India (LASI) Wave-1 conducted in 2017-18 were used, with a sample size of 30,268 individuals aged 60 and above. The study employed multivariable regression models to assess the relationship between life satisfaction and physical, mental, and functional health, adjusting for socio-demographic variables. Mann-Whitney Wilcoxon test was performed to check the rural-urban differences in life satisfaction among elderly people.</div></div><div><h3>Results</h3><div>Older adults in urban areas reported higher life satisfaction (Mean = 0.67, SD = 0.24) than their rural counterparts (Mean = 0.61, SD = 0.24). Mental health was found to be a significant predictor of life satisfaction among the elderly in both rural (β 0.443, CI = 0.419, 0.468,p &lt; 0.001), and urban areas (β = 0.459, CI = 0.428, 0.489, p &lt; 0.001) and functional health was not significantly associated with life satisfaction in rural areas (β = 0.002, CI = −0.013, 0.017, p &lt; 0.001), but shows a significant associated with urban areas (β = 0.057, CI = 0.035, 0.078, p &lt; 0.001), highlighting the importance of accessible healthcare services.</div></div><div><h3>Conclusions</h3><div>The study highlights the need for development initiatives to enhance the well-being of senior citizens living in rural areas. Enhancing healthcare infrastructure, accessing medical facilities, and addressing functional limitations are essential steps to reduce disparities in life satisfaction.</div></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":"32 ","pages":"Article 101950"},"PeriodicalIF":2.3,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}