Prevalence of DSM-5 mild and major neurocognitive disorder in India: Results from the LASI-DAD.

INTRODUCTION: India, with its rapidly aging population, faces an alarming burden of dementia. We implemented DSM-5 criteria in large-scale, nationally representative survey data in India to characterize the prevalence of mild and major Neurocognitive disorder. METHODS: The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) (N = 4,096) is a nationally representative cohort study in India using multistage area probability sampling methods. Using neuropsychological testing and informant reports, we defined DSM-5 mild and major neurocognitive disorder, reported its prevalence, and evaluated criterion and construct validity of the algorithm using clinician-adjudicated Clinical Dementia Ratings (CDR)®. RESULTS: The prevalence of mild and major neurocognitive disorder, weighted to the population, is 17.6% and 7.2%. Demographic gradients with respect to age and education conform to hypothesized patterns. Among N = 2,390 participants with a clinician-adjudicated CDR, CDR ratings and DSM-5 classification agreed for N = 2,139 (89.5%) participants. DISCUSSION: The prevalence of dementia in India is higher than previously recognized. These findings, coupled with a growing number of older adults in the coming decades in India, have important implications for society, public health, and families. We are aware of no previous Indian population-representative estimates of mild cognitive impairment, a group which will be increasingly important in coming years to identify for potential therapeutic treatment.

Trajectories and correlates of poor mental health in India over the course of the COVID-19 pandemic: a nationwide survey.

INTRODUCTION: The COVID-19 pandemic had large impacts on mental health; however, most existing evidence is focused on the initial lockdown period and high-income contexts. By assessing trajectories of mental health symptoms in India over 2 years, we aim to understand the effect of later time periods and pandemic characteristics on mental health in a lower-middle income context. METHODS: We used data from the Real-Time Insights of COVID-19 in India cohort study (N=3709). We used covariate-adjusted linear regression models with generalised estimating equations to assess associations between mental health (Patient Health Questionnaire (PHQ-4) score; range 0-12) and pandemic periods as well as pandemic characteristics (COVID-19 cases and deaths, government stringency, self-reported financial impact, COVID-19 infection in the household) and explored effect modification by age, gender and rural/urban residence. RESULTS: Mental health symptoms dropped immediately following the lockdown period but rose again during the delta and omicron waves. Associations between mental health and later pandemic stages were stronger for adults 45 years of age and older (p<0.001). PHQ-4 scores were significantly associated with all pandemic characteristics considered, including estimated COVID-19 deaths (PHQ-4 difference of 0.10 units; 95% CI 0.06 to 0.13), government stringency index (0.14 units; 95% CI 0.11 to 0.18), self-reported major financial impacts (1.20 units; 95% CI 1.09 to 1.32) and COVID-19 infection in the household (0.36 units; 95% CI 0.23 to 0.50). CONCLUSION: While the lockdown period and associated financial stress had the largest mental health impacts on Indian adults, the effects of the pandemic on mental health persisted over time, especially among middle-aged and older adults. Results highlight the importance of investments in mental health supports and services to address the consequences of cyclical waves of infections and disease burden due to COVID-19 or other emerging pandemics.

Defining anthropometric thresholds (mid-arm circumference and calf circumference) in older adults residing in the community: a cross-sectional analysis using data from the population representative Longitudinal Aging Study in India (LASI DAD).

OBJECTIVES: To identify factors associated with malnutrition (undernutrition and overnutrition) and determine appropriate cut-off values for mid-arm circumference (MAC) and calf circumference (CC) among community-dwelling Indian older adults. DESIGN: Data from the first wave of harmonised diagnostic assessment of dementia for Longitudinal Ageing Study in India (LASI-DAD) were used. Various sociodemographic factors, comorbidities, geriatric syndromes, childhood financial and health status were included. Anthropometric measurements included body mass index (BMI), MAC and CC. SETTING: Nationally representative cohort study including 36 Indian states and union territories. PARTICIPANTS: 4096 older adults aged >60 years from LASI DAD. OUTCOME MEASURES: The outcome variable was BMI, categorised as low (<18.5 kg/m2), normal (18.5-22.9 kg/m2) and high (>23 kg/m2). The cut-off values of MAC and CC were derived using ROC curve with BMI as the gold standard. RESULTS: 902 (weighted percentage 20.55%) had low BMI, 1742 (44.25%) had high BMI. Undernutrition was associated with age, wealth-quintile and impaired cognition, while overnutrition was associated with higher education, urban living and comorbidities such as hypertension, diabetes and chronic heart disease. For CC, the optimal lower and upper cut-offs for males were 28.1 cm and >31.5 cm, respectively, while for females, the corresponding values were 26 cm and >29 cm. Similarly, the optimal lower and upper cut-offs for MAC in males were 23.9 cm and >26.9 cm, and for females, they were 22.5 cm and >25 cm. CONCLUSION: Our study identifies a high BMI prevalence, especially among females, individuals with higher education, urban residents and those with comorbidities. We establish gender-specific MAC and CC cut-off values with significant implications for healthcare, policy and research. Tailored interventions can address undernutrition and overnutrition in older adults, enhancing standardised nutritional assessment and well-being.

Trajectories and correlates of poor mental health in India over the course of the COVID-19 pandemic: a nation-wide survey.

Introduction: The COVID-19 pandemic had large impacts on mental health; however, most existing evidence is focused on the initial lockdown period and high-income contexts. By assessing trajectories of mental health symptoms in India over two years, we aim to understand the effect of later time periods and pandemic characteristics on mental health in a lower-middle income context. Methods: We used data from the Real-Time Insights of COVID-19 in India (RTI COVID-India) cohort study (N=3,662). We used covariate-adjusted linear regression models with generalized estimating equations to assess associations between mental health (PHQ-4 score) and pandemic periods as well as pandemic characteristics (COVID-19 cases and deaths, government stringency, self-reported financial impact, COVID-19 infection in the household) and explored effect modification by age, gender, and rural/urban residence. Results: Mental health symptoms dropped immediately following the lockdown period but rose again during the delta and omicron waves. Associations between mental health and later pandemic stages were stronger for adults 45 years of age and older (p<0.001). PHQ-4 scores were significantly and independently associated with all pandemic characteristics considered, including estimated COVID-19 deaths (PHQ-4 difference of 0.041 SD units; 95% Confidence Interval 0.030 - 0.053), government stringency index (0.060 SD units; 0.048 - 0.072), self-reported major financial impacts (0.45 SD units; 0.41-0.49), and COVID-19 infection in the household (0.11 SD units; 0.07-0.16). Conclusion: While the lockdown period and associated financial stress had the largest mental health impacts on Indian adults, the effects of the pandemic on mental health persisted over time, especially among middle-age and older adults. Results highlight the importance of investments in mental health supports and services to address the consequences of cyclical waves of infections and disease burden due to COVID-19 or other emerging pandemics.

Cohort Profile: Real-Time Insights of COVID-19 in India (RTI COVID-India).

BACKGROUND: The coronavirus disease (COVID) pandemic caused disruption globally and was particularly distressing in low- and middle-income countries such as India. This study aimed to provide population representative estimates of COVID-related outcomes in India over time and characterize how COVID-related changes and impacts differ by key socioeconomic groups across the life course. METHODS: The sample was leveraged from an existing nationally representative study on cognition and dementia in India: Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD). The wave-1 of LASI-DAD enrolled 4096 older adults aged 60 years and older in 3316 households from 18 states and union territories of India. Out of the 3316 LASI-DAD households, 2704 with valid phone numbers were contacted and invited to participate in the Real-Time Insights COVID-19 in India (RTI COVID-India) study. RTI COVID-India was a bi-monthly phone survey that provided insight into the individual's knowledge, attitudes, and behaviour towards COVID-19 and changes in the household's economic and health conditions throughout the pandemic. The survey was started in May 2020 and 9 rounds of data have been collected. FINDINGS TILL DATE: Out of the 2704 LASI-DAD households with valid phone numbers, 1766 households participated in the RTI COVID-India survey at least once. Participants were in the age range of 18-102 years, 49% were female, 66% resided in rural area. Across all rounds, there was a higher report of infection among respondents aged 60-69 years. There was a greater prevalence of COVID-19 diagnosis reported in urban (23.0%) compared to rural areas (9.8%). Respondents with higher education had a greater prevalence of COVID-19 diagnosis compared to those with lower or no formal education. Highest prevalence of COVID-19 diagnosis was reported from high economic status compared to middle and low economic status households. Comparing education gradients in experiencing COVID-19 symptoms and being diagnosed, we observe an opposite pattern: respondents with no formal schooling reported the highest level of experiencing COVID-19 symptoms, whereas the greatest proportion of the respondents with secondary school or higher education reported being diagnosed with COVID-19. FUTURE PLANS: The study group will analyse the data collected showing the real-time changes throughout the pandemic and will make the data widely available for researchers to conduct further studies.

Prevalence of dementia in India: National and state estimates from a nationwide study.

INTRODUCTION: Prior estimates of dementia prevalence in India were based on samples from selected communities, inadequately representing the national and state populations. METHODS: From the Longitudinal Aging Study in India (LASI) we recruited a sample of adults ages 60+ and administered a rich battery of neuropsychological tests and an informant interview in 2018 through 2020. We obtained a clinical consensus rating of dementia status for a subsample (N = 2528), fitted a logistic model for dementia status on this subsample, and then imputed dementia status for all other LASI respondents aged 60+ (N = 28,949). RESULTS: The estimated dementia prevalence for adults ages 60+ in India is 7.4%, with significant age and education gradients, sex and urban/rural differences, and cross-state variation. DISCUSSION: An estimated 8.8 million Indians older than 60 years have dementia. The burden of dementia cases is unevenly distributed across states and subpopulations and may therefore require different levels of local planning and support. HIGHLIGHTS: The estimated dementia prevalence for adults ages 60+ in India is 7.4%. About 8.8 million Indians older than 60 years live with dementia. Dementia is more prevalent among females than males and in rural than urban areas. Significant cross-state variation exists in dementia prevalence.

Deep phenotyping and genomic data from a nationally representative study on dementia in India.

The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is a nationally representative in-depth study of cognitive aging and dementia. We present a publicly available dataset of harmonized cognitive measures of 4,096 adults 60 years of age and older in India, collected across 18 states and union territories. Blood samples were obtained to carry out whole blood and serum-based assays. Results are included in a venous blood specimen datafile that can be linked to the Harmonized LASI-DAD dataset. A global screening array of 960 LASI-DAD respondents is also publicly available for download, in addition to neuroimaging data on 137 LASI-DAD participants. Altogether, these datasets provide comprehensive information on older adults in India that allow researchers to further understand risk factors associated with cognitive impairment and dementia.

Performance of the Informant Questionnaire on Cognitive Decline for the Elderly (IQCODE) in a nationally representative study in India: the LASI-DAD study.

BACKGROUND: Low and middle-income countries like India anticipate rapid population aging and increases in dementia burden. In India, dementia screening scales originally developed in other contexts need to be assessed for feasibility and validity, given the number of different languages and varying levels of literacy and education. METHOD: Using data from the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (N = 4,028), we characterize the performance of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). We described patterns and correlates of missingness, evaluated the psychometric properties of the scale, and assessed criterion validity against the Hindi Mental State Examination (HMSE) using linear regression. RESULTS: Several IQCODE items had high levels of missingness, which was associated with urbanicity, respondent's gender, and informant's generation (same vs. younger generation). Full IQCODE scores showed strong criterion validity against the HMSE; each 1-point increase in IQCODE score was associated with a 3.03-point lower score on the HMSE, controlling for age, gender, and urbanicity. The statistically significant association between IQCODE and HMSE was stronger in urban than rural settings (p-value for interaction = 0.04). Associations between IQCODE and HMSE remained unchanged after removing the three items with the highest levels of differential missingness (remembering addresses and telephone numbers, ability to work with familiar machines, ability to learn to use new gadget or machine). CONCLUSION: Findings raise questions about the value of including items with high proportions of missingness, which may signal cultural irrelevance, while removing them did not affect criterion validity.

Adherence to COVID-19 protective behaviours in India from May to December 2020: evidence from a nationally representative longitudinal survey.

OBJECTIVES: Since the onset of the COVID-19 pandemic, behavioural interventions to reduce disease transmission have been central to public health policy worldwide. Sustaining individual protective behaviour is especially important in low-income and middle-income settings, where health systems have fewer resources and access to vaccination is limited. This study seeks to assess time trends in COVID-19 protective behaviour in India. DESIGN: Nationally representative, panel-based, longitudinal study. SETTING: We conducted a panel survey of Indian households to understand how the adoption of COVID-19 protective behaviours has changed over time. Our data span peaks and valleys of disease transmission over May-December 2020. PARTICIPANTS: Respondents included 3719 adults from 1766 Indian households enrolled in the Harmonised Diagnostic Assessment of Dementia for the Longitudinal Ageing Study in India. ANALYSIS: We used ordinary least squares regression analysis to quantify time trends in protective behaviours. RESULTS: We find a 30.6 percentage point (95% CI (26.7 to 34.5); p<0.01) decline in protective behaviours related to social distancing over the observation period. Mask wearing and handwashing, in contrast, decreased by only 4.3 percentage points (95% CI (0.97 to 7.6); p<0.05) from a high base. Our conclusions are unchanged after adjusting for recorded COVID-19 caseload and nationwide COVID-19 containment policy; we also observe significant declines across socioeconomic strata spanning age, gender, education and urbanicity. CONCLUSION: We argue that these changes reflect, at least in part, 'COVID-19 fatigue,' where adherence to social distancing becomes more difficult over time irrespective of the surrounding disease environment.

Learning From Clinical Consensus Diagnosis in India to Facilitate Automatic Classification of Dementia: Machine Learning Study.

BACKGROUND: The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is the first and only nationally representative study on late-life cognition and dementia in India (n=4096). LASI-DAD obtained clinical consensus diagnosis of dementia for a subsample of 2528 respondents. OBJECTIVE: This study develops a machine learning model that uses data from the clinical consensus diagnosis in LASI-DAD to support the classification of dementia status. METHODS: Clinicians were presented with the extensive data collected from LASI-DAD, including sociodemographic information and health history of respondents, results from the screening tests of cognitive status, and information obtained from informant interviews. Based on the Clinical Dementia Rating (CDR) and using an online platform, clinicians individually evaluated each case and then reached a consensus diagnosis. A 2-step procedure was implemented to train several candidate machine learning models, which were evaluated using a separate test set for predictive accuracy measurement, including the area under receiver operating curve (AUROC), accuracy, sensitivity, specificity, precision, F1 score, and kappa statistic. The ultimate model was selected based on overall agreement as measured by kappa. We further examined the overall accuracy and agreement with the final consensus diagnoses between the selected machine learning model and individual clinicians who participated in the clinical consensus diagnostic process. Finally, we applied the selected model to a subgroup of LASI-DAD participants for whom the clinical consensus diagnosis was not obtained to predict their dementia status. RESULTS: Among the 2528 individuals who received clinical consensus diagnosis, 192 (6.7% after adjusting for sampling weight) were diagnosed with dementia. All candidate machine learning models achieved outstanding discriminative ability, as indicated by AUROC >.90, and had similar accuracy and specificity (both around 0.95). The support vector machine model outperformed other models with the highest sensitivity (0.81), F1 score (0.72), and kappa (.70, indicating substantial agreement) and the second highest precision (0.65). As a result, the support vector machine was selected as the ultimate model. Further examination revealed that overall accuracy and agreement were similar between the selected model and individual clinicians. Application of the prediction model on 1568 individuals without clinical consensus diagnosis classified 127 individuals as living with dementia. After applying sampling weight, we can estimate the prevalence of dementia in the population as 7.4%. CONCLUSIONS: The selected machine learning model has outstanding discriminative ability and substantial agreement with a clinical consensus diagnosis of dementia. The model can serve as a computer model of the clinical knowledge and experience encoded in the clinical consensus diagnostic process and has many potential applications, including predicting missed dementia diagnoses and serving as a clinical decision support tool or virtual rater to assist diagnosis of dementia.

Measurement and Structure of Cognition in the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia.

OBJECTIVES: To test whether a relatively complex model of human cognitive abilities based on Cattell-Horn-Carroll (CHC) theory, developed mainly in English-speaking samples, adequately describes correlations among tests in the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD), and to develop accurate measures of cognition for older individuals in India. DESIGN: LASI-DAD participants were recruited from participants aged 60 years and older from 14 states in the core LASI survey, with a stratified sampling design. SETTING: Participants were interviewed at home or in a participating hospital, according to their preferences. PARTICIPANTS: Community-residing older adults aged 60 years and older (N = 3,224). MEASUREMENTS: A variety of cognitive tests were administered during two pretests and chosen for their appropriateness for measuring cognition in older adults in India and suitability for calibration with the core LASI survey and the Harmonized Cognitive Assessment Protocol. RESULTS: We evaluated the factor structure of the test battery and its conformity with a classical CHC factor model that incorporated measurement models for general cognition, five broad domains (orientation, executive functioning, language/fluency, memory, and visuospatial), and five narrow domains (reasoning, attention/speed, immediate memory, delayed memory, and recognition memory) of cognitive performance. Model fit was adequate (root mean square error of approximation = 0.051; comparative fit index = 0.916; standardized root mean squared residual = 0.060). CONCLUSION: We demonstrated configural factorial invariance of a cognitive battery in the Indian LASI-DAD using CHC theory. Broad domain factors may be used in future research to rank individuals with respect to cognitive performance and classify cognitive impairment. J Am Geriatr Soc 68:S11-S19, 2020.

Design and Methodology of the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD).

BACKGROUND/OBJECTIVES: To provide high-quality data on older adults in India that will enable an in-depth study of late-life cognition and dementia in India and cross-country analysis of risk factors for cognitive aging and dementia. DESIGN: The Longitudinal Aging Study in India (LASI) is a nationally representative survey of health, economic, and social well-being of the Indian population aged 45 and older. Its large sample of more than 70,000 older adults represents not only the country as a whole but also each state. LASI-Diagnostic Assessment of Dementia (DAD) is an in-depth study of late-life cognition and dementia, drawing a subsample of over 3,000 LASI respondents aged 60 and older. SETTING: Participants were interviewed at home or in a participating hospital according to their preferences. PARTICIPANTS: Adults aged 60 and older (N = 3,224), along with 3,191 informants. MEASUREMENTS: Respondents underwent a battery of cognitive tests, and informants were interviewed about their cognitive and health conditions. A common set of cognitive tests was selected to enable international comparisons, and additional cognitive tests suitable for illiterate and innumerate populations were also selected. Rich data on risk factors of dementia were collected through health examination, venous blood assays, and genotyping. RESULTS: The response rate was 82.9%, varying across sex, education, and urbanicity. Data are available to other researchers. CONCLUSION: LASI-DAD provides an opportunity to study late-life cognition and dementia and their risk factors in the older population in India and to gain further insights through cross-country analysis by pooling data from its international sister studies. J Am Geriatr Soc 68:S5-S10, 2020.

Methodological considerations in designing and implementing the harmonized diagnostic assessment of dementia for longitudinal aging study in India (LASI-DAD).

The Harmonized Diagnostic Assessment of Dementia for Longitudinal Aging Study in India (LASI-DAD) is a population-representative, prospective cohort study of late-life cognition and dementia. It is part of an ongoing international research collaboration that aims to measure and understand cognitive impairment and dementia risk by collecting a set of cognitive and neuropsychological assessments and informant reports, referred to as the Harmonized Cognitive Assessment Protocol (HCAP). LASI-DAD provides nationally representative data drawn from a subsample of the ongoing Longitudinal Aging Study in India (LASI). One of LASI-DAD's distinctive features is its rich geriatric assessment, including the collection of venous blood samples and brain imaging data for a subsample of respondents. In this paper, we discuss the methodological considerations of developing and implementing the HCAP protocol in India. The lessons we learned from translating and applying the HCAP protocol in an environment where illiteracy and innumeracy are high will provide important insights to researchers interested in measuring and collecting data on late-life cognition and dementia in developing countries. We further developed an innovative blood management system that enables us to follow the collection, transportation, assay, and storage of samples. Such innovation can benefit other population surveys collecting biomarker data.

LASI-DAD study: a protocol for a prospective cohort study of late-life cognition and dementia in India.

INTRODUCTION: Alzheimer's disease and related dementias can be considered the epidemic of the 21st century. Particularly, the predicted growth in the size of elderly populations in low-income and middle-income countries is expected to produce a dramatic surge in dementia prevalence and incidence. Although a rising burden of dementia presents an urgent challenge for India, previous efforts to study dementia in the country have relied on non-representative samples in geographically restricted regions. The Harmonised Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) will provide rich, population-representative data on late-life cognition and dementia and their risk factors for the first time in India. METHODS: The LASI-DAD will recruit a sample of 3000 people aged 60+ years. Their family members or friends, whom respondents nominate as informants, participate in the computer-assisted personal interview. The study sample is drawn from the ongoing, nationally representative Longitudinal Aging Study in India, a multipurpose panel survey of aging. We aim to collect rich data on cognitive and neuropsychological tests, informant reports, and epidemiological data through a comprehensive geriatric assessment, and venous blood collection and assays. For a subsample, we collect neuroimaging data. Data collection is currently in progress in 14 States and Union Territories of India. Clinicians will provide clinical consensus diagnosis based on the Clinical Dementia Rating. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Indian Council of Medical Research and all collaborating institutions. Anonymised data will be available for the larger research community through a secured website hosted by the Gateway to Global Aging Data platform. Research findings from the LASI-DAD team will be disseminated through journal publications and presentations at professional conferences.

TB Risk Perceptions among Medical Residents at a Tertiary Care Center in India.

SETTING: Government tertiary health care center in India. OBJECTIVE: To understand the perceptions of medical residents about their risk of developing TB in the workplace. DESIGN: Cross-sectional study in which a semistructured questionnaire which included an open-ended question to assess their main concerns regarding TB in workplace was used to collect data. RESULTS: Out of 305 resident doctors approached, 263 (94%) completed a structured questionnaire and 200 of these responded to an open-ended question. Daily exposure to TB was reported by 141 (64%) residents, 13 (5%) reported a prior history of TB, and 175 (69%) respondents were aware of TB infection control guidelines. A majority reported concerns about acquiring TB (78%) and drug-resistant TB (88%). The key themes identified were concerns about developing drug-resistant TB (n = 100; 50%); disease and its clinical consequences (n = 39; 20%); social and professional consequences (n = 37; 19%); exposure to TB patients (n = 32; 16%); poor infection control measures (n = 27; 14%); and high workload and its health consequences (n = 16; 8%). CONCLUSION: Though many resident doctors were aware of TB infection control guidelines, only few expressed concern about lack of TB infection control measures. Doctors need to be convinced of the importance of these measures which should be implemented urgently.