Development and effect of a coordinated Community Health Worker (CHW) Intervention (C-CHW-I) model for the stroke survivors in Kerala, South India.

INTRODUCTION: Structured models for secondary prevention of stroke in community settings are scarce. We aimed to develop and evaluate a model for improving medication adherence and enhanced risk factor monitoring. METHODS: We developed a multimodal C-CHW-I model for stroke survivors. Following training, all patients received a minimum of three CHW home visits, and once in 3-month telephone-call and health education for six months by CHWs. Seven blocks from 16 blocks of the study area were randomised to additionally receive an SMS alert for six months to reinforce CHW involvement. The primary outcomes were medication adherence and risk factor monitoring, and the secondary outcome was risk factor control. RESULTS: The mean age of the study population was 64+12 years, 765(85%) had ischaemic stroke. In the overall study cohort receiving the CHW intervention, mean medication adherence significantly improved from 3.56(0.88) at baseline to 3.78(0.61) at 6 months; p<0.001. Overall risk factor monitoring improved from 42.7% to 49.7%, and mean (standard deviation) systolic blood pressure (SBP) significantly reduced from 138(21) mmHg to 132(15) mmHg at 6-months; p<0.001. In patients additionally receiving SMS-based intervention, a statistically significant improvement in medication adherence was seen at 3 months (3.76+0.64 versus 3.61+0.81; p=0.008) however no difference persisted at 6 months. The proportion of smokers and alcohol users reduced in both groups with a trend to greater reduction in the intervention group (smokers:5.9% versus 2.8% (p=0.446) and alcohol users: 1.6% versus 1.4%(p=0.474)). At six months, the SBP did not differ (SBP (132.1(16.2) in the SMS group versus 133.2(15.8) mmHg in the control group, p=0.409). CONCLUSION: Our model improved medication adherence and risk factor monitoring of stroke survivors in community settings, and this can reduce stroke burden in the community.

Associations of Antibiotics, Hormonal Therapies, Oral Contraceptives, and Long-Term NSAIDS With Inflammatory Bowel Disease: Results From the Prospective Urban Rural Epidemiology (PURE) Study.

BACKGROUND & AIMS: Several medications have been suspected to contribute to the etiology of inflammatory bowel disease (IBD). This study assessed the association between medication use and the risk of developing IBD using the Prospective Urban Rural Epidemiology cohort. METHODS: This was a prospective cohort study of 133,137 individuals between the ages of 20 and 80 from 24 countries. Country-specific validated questionnaires documented baseline and follow-up medication use. Participants were followed up prospectively at least every 3 years. The main outcome was the development of IBD, including Crohn's disease (CD) and ulcerative colitis (UC). Short-term (baseline but not follow-up use) and long-term use (baseline and subsequent follow-up use) were evaluated. Results are presented as adjusted odds ratios (aORs) with 95% CIs. RESULTS: During a median follow-up period of 11.0 years (interquartile range, 9.2-12.2 y), there were 571 incident IBD cases (143 CD and 428 UC). Incident IBD was associated significantly with baseline antibiotic (aOR, 2.81; 95% CI, 1.67-4.73; P = .0001) and hormonal medication use (aOR, 4.43; 95% CI, 1.78-11.01; P = .001). Among females, previous or current oral contraceptive use also was associated with IBD development (aOR, 2.17; 95% CI, 1.70-2.77; P < .001). Nonsteroidal anti-inflammatory drug users also were observed to have increased odds of IBD (aOR, 1.80; 95% CI, 1.23-2.64; P = .002), which was driven by long-term use (aOR, 5.58; 95% CI, 2.26-13.80; P < .001). All significant results were consistent in direction for CD and UC with low heterogeneity. CONCLUSIONS: Antibiotics, hormonal medications, oral contraceptives, and long-term nonsteroidal anti-inflammatory drug use were associated with increased odds of incident IBD after adjustment for covariates.

Cost-effectiveness of population-based screening for microalbuminuria in people with type 2 diabetes mellitus in India.

OBJECTIVES: Patients with diabetes have a higher risk of developing chronic kidney disease (CKD). Early detection of CKD through microalbuminuria screening, followed by treatment, delays the progression of CKD. We evaluated the cost-effectiveness of population-based screening of microalbuminuria among normotensive type 2 diabetes mellitus patients aged >40 years compared with no screening scenario using a decision tree combined with the Markov model. METHODS: We considered two scenarios: Scenario I - dipstick microalbuminuria followed by spot-urine albumin-creatinine ratio (ACR) and serum creatinine in sequence; Scenario II - spot urine ACR plus serum creatinine. A mathematical cohort of the target population was simulated over a lifetime horizon with an annual cycle. Data for the model were obtained from secondary resources. The incremental cost-effectiveness ratios (ICERs) were estimated for screening scenarios compared to nonscreening scenario, along with sensitivity analyses. RESULTS: The discounted ICER per quality-adjusted life years gained for annual microalbuminuria screening in the normotensive diabetic population in India were ₹ 24,114 (US$ 308) and ₹ 13,790 (US$ 176) for scenarios I and II, respectively. Annual screening by scenarios I and II resulted in a reduction of 180 and 193 end-stage renal disease (ESRD) cases per 100,000 population, respectively, resulting in a cost saving of ₹ 12.3 and 13.3 Crore spent on ESRD management over 10 years. Both scenarios were also cost-effective even at the screening frequencies of 5 and 10 yearly. CONCLUSION: Microalbuminuria screening was cost-effective at the threshold of one-time GDP per capita in India.

Biomarkers in the Prediction of Hemorrhagic Transformation in Acute Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: Hemorrhagic transformation (HT) is a complication that occurs spontaneously or after thrombolysis in acute ischemic stroke (AIS) and can increase morbidity and mortality. The association of biomarkers with the risk of HT has been variably reported. We conducted a systematic review of the literature and meta-analysis and sought to compare blood biomarkers associated with HT and its subtypes by evaluating its predictability and correlation with outcome in AIS. METHODS: The study protocol was registered in the PROSPERO database (CRD42020201334) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Among 2,230 articles identified from Cochrane Library, PubMed, and Web of Science databases, 30 quality-appraised articles were found eligible. Meta-analysis was conducted for matrix metalloproteinase-9 (MMP-9), cellular fibronectin (c-Fn), ferritin, S100 calcium-binding protein B (S100B), and neutrophil-lymphocyte ratio (NLR). We also reviewed biomarkers for correlation with the functional outcome at 90 days from stroke onset (poor outcome modified Rankin scale >2). RESULTS: The pooled diagnostic odds ratio (DORpooled) was the highest for baseline c-Fn levels (299.253 [95% CI, 20.508-4,366.709]), followed by MMP-9 (DORpooled, 29.571 [95% CI 17.750-49.267]) and ferritin (DORpooled, 24.032 [95% CI 2.557-225.871]). However, wide confidence intervals for ferritin and c-Fn suggested lesser reliability of the markers. Patients with MMP-9 levels ≥140 ng/mL were 29.5 times at higher risk of developing symptomatic HT after AIS (area under the curve = 0.881). S100B (DORpooled, 6.286 [95% CI, 1.861-21.230]) and NLR (DORpooled, 5.036 [95% CI, 2.898-8.749]) had lower diagnostic accuracies. Among the markers not included for meta-analysis, caveolin-1, thrombin-activated fibrinolysis inhibitor, plasminogen activator inhibitor-1, and soluble ST2 were highly sensitive. Elevated levels of MMP-9, ferritin, and NLR were found to be associated with poor functional outcomes and mortality. CONCLUSION: Of the 5 biomarkers, there was enough evidence that MMP-9 has higher diagnostic accuracy for predicting the risk of HT before thrombolysis. MMP-9, ferritin, and NLR also predicted poor short-term outcomes.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Setting-specific Transmission Rates: A Systematic Review and Meta-analysis.

BACKGROUND: Understanding the drivers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is crucial for control policies, but evidence of transmission rates in different settings remains limited. METHODS: We conducted a systematic review to estimate secondary attack rates (SARs) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a beta-binomial model to pool SARs across studies and a negative-binomial model to estimate Robs. RESULTS: Households showed the highest transmission rates, with a pooled SAR of 21.1% (95% confidence interval [CI]:17.4-24.8). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs 1.2%). Estimates of SARs and Robs for asymptomatic index cases were approximately one-seventh, and for presymptomatic two-thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals younger than 20 years of age in the household context, which is more limited when examining all settings. CONCLUSIONS: Our results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies, such as contact tracing, testing, and rapid isolation of cases. There were limited data to explore transmission patterns in workplaces, schools, and care homes, highlighting the need for further research in such settings.

Epidemiological profiling of fatal road crashes in Puducherry, South Coastal India.

Road crash fatalities form leading cause of deaths in India. Streamlining road crash data systems are essential for building robust prevention strategies. This study explores epidemiological profile of fatal road crashes in a south Indian urban setting. Between April and June 2019, secondary data on fatal road crashes in Puducherry district for 3-year period (2016, 2017, and 2018) were accessed from traffic police records and analyzed. Raw data accessed in descriptive format was converted to analyzable objective format by self-developed data extraction template. 154 fatal crashes happened in Puducherry during this period. Most victims were males (85.7%), in productive age group (41.5%), with higher rates in monsoon and winter seasons (35.1% each), during evening-to-night hours (41.6%), and during weekends (42%). Most offenders (91.2%) were men, elder than victims, with heavy motor vehicles (91.2%) being the culprit vehicle. Rash driving led to most deaths (53.2%).

Quality of medical prescriptions in diabetes and hypertension management in Kerala and its associated factors.

BACKGROUND: Kerala is facing challenges in the secondary prevention efforts of non-communicable diseases (NCDs). In spite of being the top performer in health parameters among Indian states, the burden of NCDs, especially diabetes mellitus (diabetes) and hypertension, is higher in Kerala. This research endeavours to identify the role of quality of medical prescriptions in secondary prevention of diabetes and hypertension and suggest corrective measures. METHODS: This cross-sectional study involved collection of prescription data and other details from consenting doctors across seven districts in Kerala. After the quality of prescription was assessed using a checklist, scores were generated, and cutoff points were used to classify the prescriptions. PASW version 18 software, was used for data analysis which included univariate and bivariate analyses and logistic regression. The proportion of quality prescriptions was estimated after adjusting for clustering, and the proportion of doctors writing quality prescriptions was also estimated. Prior to the study, ethical clearance from Independent ethics committee in Health action by People (HAP) and informed consent from all the study participants were obtained. RESULTS: After assessing 9199 prescriptions from 344 doctors, it was found that about 37.2% (95% CI: 34.9-39.4%) of the prescriptions were of good quality, and 48.2% (95% CI: 42.9-53.7%) of the doctors provided quality prescriptions. Factors associated with quality prescriptions were found to be knowledge about NCD guidelines, quality certifications of hospitals and usage of patient data management software. CONCLUSIONS: In the context of rising prevalence of NCDs and the challenges in the secondary prevention efforts, this is one of the first studies in Kerala to evaluate the quality of prescriptions to manage NCDs as prescriptions often reflect the quality of medical management. The study also addresses other factors associated with quality medical management. The findings indicate that the scope for improvement is more than 50%, when considered for the overall quality of prescriptions in diabetes and hypertension management. Further, it was found that appropriate training of doctors, adherence to treatment guidelines and the use of technology may improve the overall quality of prescriptions.

Using open-source data to explore distribution of built environment characteristics across Kerala, India.

BACKGROUND: Built environment characteristics in the neighborhood are of utmost priority for a healthy lifestyle in the fast-urbanizing countries. These characteristics are closely linked to the disease burden and challenges in low- and middle-income countries (LMICs), which have been unexplored using open-source data. The present technology offers online resources and open source software that enable researchers to explore built environment characteristics with health and allied phenomena. OBJECTIVES: This article intends to delineate methods to capture available and accessible objective built environment variables for a state in India and determine their distribution across the state. METHODS: Built environment variables such as population density and residential density were collated from the Census of India. Safety from crime and traffic were captured as crime rates and pedestrian accident rates, respectively, acquired from State Crime Records Bureau. Greenness, built-up density, and land slope were gathered from open-source satellite imagery repository. Road intersection density was derived from OpenStreetMap. Processing and analysis differed for each dataset depending on its source and nature. RESULTS: Each variable showed a distinct pattern across the state. Population and residential density were found to be closely related to each other across both districts and subdistricts. They were both positively related to crime rates, pedestrian accident rates, built-up density, and intersection density, whereas negatively related to land slope and greenness across the subdistricts. CONCLUSION: Delineating the distribution of built environment variables using available and open-source data in resource-poor settings is a first in public health research among LMICs. Cost-effectiveness and reproducible nature of open-source solutions could equip researchers in resource-poor settings to identify built environment characteristics and patterns across regions.

Containing the first outbreak of COVID-19 in a healthcare setting in India: The sree chitra experience.

The response to the first health worker case in India and novel strategies adopted in the context of evolving pandemic of COVID-19 is presented here. On the same day of confirmation, institutional COVID cell was established, and contact tracing was started. A total of 184 contacts were identified and quarantined. Hospital services were scaled down, and responsibilities were reassigned. In-house digital platforms were used for daily meetings, contact tracing, line listing, risk stratification, and research. Reverse transcription polymerase chain reaction-based severe acute respiratory syndrome-CoV2 testing facility was established in the institute. All high-risk contacts were given hydroxychloroquine prophylaxis. No secondary cases were found. Hospital preparedness, participatory decision-making through institutional COVID cell, optimal use of in-house digital platforms, and coordination with the state health department and national bodies, including Indian Council of Medical Research, were the supporting factors. Rapidly evolving guidelines, trepidation about the disease, logistic delays, and lack of support systems for people under quarantine were the challenges in the containment exercise.

Spatiotemporal clustering of dengue cases in Thiruvananthapuram district, Kerala.

BACKGROUND: Dengue cases are increasing in Kerala since 2010. Information on clustering of cases across locations and time periods is vital for disease surveillance and timely control. OBJECTIVES: The objective is to study spatiotemporal clustering of dengue cases and their climatic and physioenvironmental correlates in Thiruvananthapuram district during 2010-2014. METHODS: Health department data on reported cases of dengue were obtained from January 2011 to June 2014. Cases were individually geocoded, using Google Earth. Moran's I index was estimated to analyze spatial autocorrelation using GeoDa software. Space-time clustering across 178 geo-divisions within the district was analyzed using SaTScan software. Correlation analysis was done for space-time clustering with climatic variables. RESULTS: Definite spatial and temporal trends were found on analysis of a total of 8279 dengue cases. Significant spatial autocorrelation (Moran's I = 0.32, P< 0.01) and space-time clusters with very high log-likelihood ratios (P < 0.01) were found across geo-divisions. Pallichal panchayat was the most likely cluster in every year. The monthly incidence of dengue cases showed a significant positive association (P < 0.05) with a 2-month lag of mean minimum temperature (ρ = 0.39), 1-month lag of rainfall (ρ = 0.33), and 1-month lag of humidity (ρ = 0.38). Dengue occurrences showed an inverse association (P < 0.01) with mean maximum temperatures of the respective months (ρ= -0.48). CONCLUSION: Spatial analysis using epidemiological tools reveals spatial and temporal clustering of dengue cases within the district and their association with climatic parameters. This information can be used in controlling outbreaks in the future. This work upholds scope and feasibility of geospatial research in public health in India.

Wealth and cardiovascular health: a cross-sectional study of wealth-related inequalities in the awareness, treatment and control of hypertension in high-, middle- and low-income countries.

BACKGROUND: Effective policies to control hypertension require an understanding of its distribution in the population and the barriers people face along the pathway from detection through to treatment and control. One key factor is household wealth, which may enable or limit a household's ability to access health care services and adequately control such a chronic condition. This study aims to describe the scale and patterns of wealth-related inequalities in the awareness, treatment and control of hypertension in 21 countries using baseline data from the Prospective Urban and Rural Epidemiology study. METHODS: A cross-section of 163,397 adults aged 35 to 70 years were recruited from 661 urban and rural communities in selected low-, middle- and high-income countries (complete data for this analysis from 151,619 participants). Using blood pressure measurements, self-reported health and household data, concentration indices adjusted for age, sex and urban-rural location, we estimate the magnitude of wealth-related inequalities in the levels of hypertension awareness, treatment, and control in each of the 21 country samples. RESULTS: Overall, the magnitude of wealth-related inequalities in hypertension awareness, treatment, and control was observed to be higher in poorer than in richer countries. In poorer countries, levels of hypertension awareness and treatment tended to be higher among wealthier households; while a similar pro-rich distribution was observed for hypertension control in countries at all levels of economic development. In some countries, hypertension awareness was greater among the poor (Sweden, Argentina, Poland), as was treatment (Sweden, Poland) and control (Sweden). CONCLUSION: Inequality in hypertension management outcomes decreased as countries became richer, but the considerable variation in patterns of wealth-related inequality - even among countries at similar levels of economic development - underscores the importance of health systems in improving hypertension management for all. These findings show that some, but not all, countries, including those with limited resources, have been able to achieve more equitable management of hypertension; and strategies must be tailored to national contexts to achieve optimal impact at population level.

A Review of Automatic Methods Based on Image Processing Techniques for Tuberculosis Detection from Microscopic Sputum Smear Images.

Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis. It primarily affects the lungs, but it can also affect other parts of the body. TB remains one of the leading causes of death in developing countries, and its recent resurgences in both developed and developing countries warrant global attention. The number of deaths due to TB is very high (as per the WHO report, 1.5 million died in 2013), although most are preventable if diagnosed early and treated. There are many tools for TB detection, but the most widely used one is sputum smear microscopy. It is done manually and is often time consuming; a laboratory technician is expected to spend at least 15 min per slide, limiting the number of slides that can be screened. Many countries, including India, have a dearth of properly trained technicians, and they often fail to detect TB cases due to the stress of a heavy workload. Automatic methods are generally considered as a solution to this problem. Attempts have been made to develop automatic approaches to identify TB bacteria from microscopic sputum smear images. In this paper, we provide a review of automatic methods based on image processing techniques published between 1998 and 2014. The review shows that the accuracy of algorithms for the automatic detection of TB increased significantly over the years and gladly acknowledges that commercial products based on published works also started appearing in the market. This review could be useful to researchers and practitioners working in the field of TB automation, providing a comprehensive and accessible overview of methods of this field of research.

A randomized controlled trial of medication adherence and management of risk factors for secondary prevention of stroke (MaMoRS) using a smartphone-based application.

BACKGROUND: There are little data on the use of smartphone-based applications for medication adherence and risk-factor control for the secondary prevention of stroke in low-and-middle-income countries (LMICs). AIMS: The aim was to determine whether a smartphone-based app improved medication adherence, risk-factor control, and provided health education to stroke survivors for lifestyle and behavioral modifications. METHODS: An unblinded, single-center randomized controlled double arm trial with 1:1 allocation among stroke survivors was performed in South India. The primary outcome was medication adherence, with co-primary outcomes of lifestyle and behavioral factors and control of vascular risk factors, at 3 and 6 months. RESULTS: Among 351 stroke survivors screened, 209 were recruited. The mean (standard deviation (SD)) age of the intervention (n = 105) group was 60 (12) years and that of the control (n = 104) group was 60 (10) years. In the primary outcome, mean medication adherence significantly improved in the intervention group with a between group difference of 0.735 (95% confidence interval (CI) = 0.419 to 1.050), p < 0.001. Being in intervention group (OR = 4.5; 95% CI = 2.3 to 8.9), stroke recurrence (OR = 3.3 (95% CI = 1.9 to 7.8)), and regular physician visits (OR = 2.1; 95% CI = 1.0 to 4.4) were significant predictors of good medication adherence. Considering the co-primary outcomes, compared to the control group, participants in the intervention group had a greater improvement in self-reported healthy diet intake (p = 0.003), intake of fruits (p = 0.005), and were physically more active (p = 0.001). At 6 months, mean fasting blood sugar (p = 0.005) and high-density lipoprotein cholesterol higher (p = 0.024) in the intervention group. CONCLUSIONS: The use of a mobile app is an effective method to improve medication adherence and risk-factor control in stroke survivors and is feasible in LMICs like India. DATA ACCESS STATEMENT: Data used during the study are available from the corresponding author on request. TRIAL REGISTRATION: The study is registered in Clinical Trial Registry of India (CTRI/2022/06/042980).

Post-campaign coverage evaluation of a measles and rubella supplementary immunization activity in five districts in India, 2019-2020.

BACKGROUND: In alignment with the Measles and Rubella (MR) Strategic Elimination plan, India conducted a mass measles and rubella vaccination campaign across the country between 2017 and 2020 to provide a dose of MR containing vaccine to all children aged 9 months to 15 years. We estimated campaign vaccination coverage in five districts in India and assessed campaign awareness and factors associated with vaccination during the campaign to better understand reasons for not receiving the dose. METHODS AND FINDINGS: Community-based cross-sectional serosurveys were conducted in five districts of India among children aged 9 months to 15 years after the vaccination campaign. Campaign coverage was estimated based on home-based immunization record or caregiver recall. Campaign coverage was stratified by child- and household-level risk factors and descriptive analyses were performed to assess reasons for not receiving the campaign dose. Three thousand three hundred and fifty-seven children aged 9 months to 15 years at the time of the campaign were enrolled. Campaign coverage among children aged 9 months to 5 years documented or by recall ranged from 74.2% in Kanpur Nagar District to 90.4% in Dibrugarh District, Assam. Similar coverage was observed for older children. Caregiver awareness of the campaign varied from 88.3% in Hoshiarpur District, Punjab to 97.6% in Dibrugarh District, Assam, although 8% of children whose caregivers were aware of the campaign were not vaccinated during the campaign. Failure to receive the campaign dose was associated with urban settings, low maternal education, and lack of school attendance although the associations varied by district. CONCLUSION: Awareness of the MR vaccination campaign was high; however, campaign coverage varied by district and did not reach the elimination target of 95% coverage in any of the districts studied. Areas with lower coverage among younger children must be prioritized by strengthening the routine immunization programme and implementing strategies to identify and reach under-vaccinated children.

Social Determinants of Child Undernutrition in Adivasi Population in Northern Kerala: A Study Using Syndemic Framework.

OBJECTIVES: To understand the complex interaction of structural inequalities, co-occurring health conditions, and child undernutrition among the Adivasi population in North Kerala, India. METHODS: A mixed-method approach was employed in this study, which combined a cross-sectional survey and a case study design. A multistage cluster sampling method was used to select 167 children aged 24 to 60 mo from the study population. The mothers of these children were interviewed using a structured questionnaire to assess individual, parental, and household-level factors associated with child undernutrition. Two Paniya settlements, one with a high prevalence of child undernutrition (HPS) and the other with a low prevalence (LPS), were chosen as the primary units of the case study. RESULTS: The study found that the absence of a kitchen garden with fruits and vegetables [adjusted odds ratio (AOR) 2.85; 95% confidence interval (CI): 1.04-7.81] and a history of cough and fever (AOR 2.93; 95% CI: 1.24-6.93) were both associated with a higher risk of undernutrition in children. The case studies revealed that Adivasi children are undernourished due to a complex set of factors that persist throughout their lives, including unequal access to social capital, healthcare, and food security, as well as differences in hygiene practices due to the lack of access to clean water and sanitation. CONCLUSIONS: The findings underscore the need for social interventions to complement the current focus almost entirely on food supplementation programmes. Equitable action on Adivasi child malnutrition requires urgent policy and programmatic attention to social inequalities and access to basic amenities in Adivasi areas.

Tracing the Disparity Between Healthcare Policy-Based Infrastructure and Health Belief-Lead Practices: a Narrative Review on Indigenous Populations of India.

Most Indian tribes have limited access to healthcare facilities and rely heavily on traditional healing practices. This narrative review aimed to identify the disparities in the implementation of healthcare services and in accessing and availing these services by the indigenous population in India. We also have tried to throw light on the plausibility in strengthening the efficiency and efficacy of the public health system, by utilizing the available resources to its maximum potential, so that there will be a measurable outcome in the health status of these populations in India, coherently with the relevant sustainable development goals (SDG). The evidence from published literatures supports the fact that the disparity exists in the health status of indigenous populations in India as compared to the general populations. It emphasizes the need to address the key determinants such as the lack of knowledge, traditional healing practices and poor utilization of healthcare services provided to them. Various factors such as accessibility to healthcare resources, traditional healing practices, lack of awareness regarding healthcare services and schemes provided by the government, insufficient data regarding their issues and challenges and cultural and language barriers worsen the health status of indigenous people. However, our review reiterates that a well-structured and sustainable policy with reframed infrastructure and administration of healthcare system might bring a positive change in the health status of indigenous population in India.

The Prevalence of Mild Cognitive Impairment (Mci) among Older Population of Rural Kerala: A Cross-Sectional Study.

Background: There are only very few studies on estimating the prevalence of mild cognitive impairment (MCI) from India, particularly from a rural setting. The available studies were heterogeneous. Objective: The study estimated the prevalence of MCI in a rural setting in Kerala, India. Materials and Methods: We conducted a community-based, cross-sectional study among individuals aged 65 and above in rural Thiruvananthapuram, Kerala. A cluster-randomized sampling was adopted, the cluster being the wards in the village. It was a two-phase door-to-door survey. Grassroots-level health workers enrolled 366 elders in the selected four wards in the initial phase and collected information on the sociodemographic details, comorbidities, and other risk factors of the participants, using a semi-structured questionnaire. Additionally, the Everyday Abilities Scale for India (EASI) was administered to assess their activities of daily living. In the second phase, a neurologist and a psychologist examined those screened positive with EASI and diagnosed MCI and dementia based on the MCI Working Group of the European Consortium on Alzheimer's Disease and the DSM V criteria, respectively. Results: The prevalence of MCI and dementia was 18.6% (95% confidence interval [CI] 14.7%-23.4%) and 6.8% (4.46%-10.1%), respectively, among the study participants. The prevalence of MCI was higher among the unemployed and those above 70 years of age. Conclusion: The community prevalence of MCI is more than three times that of dementia among the elderly in rural Kerala.

Demographic and clinical characteristics of primary lung cancer patients in Kerala: Analysis of data from six teaching centers.

Background: Lung cancer continues to be the leading cause of cancer-related deaths in men and women. A breakdown by level of economic development shows no differences in cancer deaths in men but a higher rate of lung cancer deaths in women in industrialized countries as compared with developing nations. The risk factors for lung cancer most commonly include lifestyle, environmental, and occupational exposures. The role these factors play varies depending on geographic location, sex and race characteristics, genetic predisposition, as well as their synergistic interactions. Materials and Methods: It was a hospital-based registry, wherein hospitals were selected from three zones-north, central, and south zones of Kerala. The study was registered with clinical trial registry of India with Registration No. CTRI/2021/02/031299. Registry of lung cancer patients was prepared at all sites and institutional ethical clearance was received from all sites. All patients with primary lung cancer, histologically proven of all age groups were included in the study. Results: A total of 761 patients were registered from six teaching hospitals in Kerala who were diagnosed with primary lung cancer during the period 2017-2019. The mean age of the study population was 65.1 ± 10.2 years. Of all, 81.1% of them were males and 18.9% were females. Histologically, 56.4% had adenocarcinoma and 25.6% had squamous cell carcinoma. Conclusion: It was observed that the proportion of females diagnosed with primary lung cancer is increasing. Patients get diagnosed at a later stage of the disease, which calls for screening and early detection of lung cancer. As it accounts for the highest mortality among all other cancers, there is high scope for prevention and screening strategies.