Validity of Montreal Cognitive Assessment to Detect Cognitive Impairment in Individuals with Type 2 Diabetes.

INTRODUCTION: Guidelines recommend screening older people (> 60-65 years) with type 2 diabetes (T2D) for cognitive impairment, as it has implications in the management of diabetes. The Montreal Cognitive Assessment (MoCA) is a sensitive test for the detection of mild cognitive impairment (MCI) in the general population, but its validity in T2D has not been established. METHODS: We administered MoCA to patients with T2D (age ≥ 60 years) and controls (no T2D), along with a culturally validated neuropsychological battery and functional activity questionnaire. MCI was defined as performance in one or more cognitive domains ≥ 1.0 SD below the control group (on two tests representing a cognitive domain), with preserved functional activities. The discriminant validity of MoCA for the diagnosis of MCI at different cut-offs was ascertained. RESULTS: We enrolled 267 patients with T2D and 120 controls; 39% of the participants with T2D met the diagnostic criteria for MCI on detailed neuropsychological testing. At the recommended cut-off on MoCA (< 26), the sensitivity (94.2%) was high, but the specificity was quite low (29.5%). The cut-off score of < 23 showed an optimal trade-off between sensitivity (69.2%), specificity (71.8%), and diagnostic accuracy (70.8%). The cut-off of < 21 exhibited the highest diagnostic accuracy (74.9%) with an excellent specificity (91.4%), a good positive and negative predictive value (78.5% and 73.7%, respectively). CONCLUSIONS: The recommended screening cut-off point on MoCA of < 26 has a suboptimal specificity and may increase the referral burden in memory clinics. A lower cut-off of < 21 on MoCA maximizes the diagnostic accuracy. Interactive Visual Abstract available for this article.

Type 2 diabetes (T2D) is a risk factor for cognitive dysfunction which potentially impacts diabetes self-management skills. Guidelines recommend screening older adults with diabetes for early detection of cognitive impairment. For screening cognitive impairment in busy endocrine clinics, we need a test that is easy and rapid to administer, sensitive enough to pick the cognitive deficits of T2D and at the same time gives less false-positive outcomes. The Montreal Cognitive Assessment (MoCA) scale is a widely available cognitive screening tool, but there are no studies evaluating its discriminant properties in people with diabetes. We evaluated the performance metrics of MoCA in this population. We found mild cognitive impairment in four out of ten participants with T2D at or above 60 years of age. At the recommended cut-off on MoCA (< 26), the sensitivity was high, but the specificity quite low. We found better diagnostic accuracy at lower cut-offs (20/21), with high specificity but a lower sensitivity. At this cut-off, approximately one out of five people screened using MoCA would require detailed neuropsychological testing, and four out of five who undergo detailed evaluation would have true cognitive impairment.

Association of collaborative care intervention features with depression and metabolic outcomes in the INDEPENDENT study: A mixed methods study.

AIMS: The INtegrating DEPrEssioN and Diabetes treatmENT (INDEPENDENT) trial tested a collaborative care model including electronic clinical decision support (CDS) for treating diabetes and depression in India. We aimed to assess which features of this clinically and cost-effective intervention were associated with improvements in diabetes and depression measures. METHODS: Post-hoc analysis of the INDEPENDENT trial data (189 intervention participants) was conducted to determine each intervention feature's effect: 1. Collaborative case reviews between expert psychiatrists and the care team; 2. Patient care-coordinator contacts; and 3. Clinicians' CDS prompt modifications. Primary outcome was baseline-to-12-months improvements in diabetes control, blood pressure, cholesterol, and depression. Implementer interviews revealed barriers and facilitators of intervention success. Joint displays integrated mixed methods' results. RESULTS: High baseline HbA1c≥ 74.9 mmol/mol (9%) was associated with 5.72 fewer care-coordinator contacts than those with better baseline HbA1c (76.8 mmol/mol, 9.18%, p < 0.001). Prompt modification proportions varied from 38.3% (diabetes) to 1.3% (LDL). Interviews found that providers' and participants' visit frequencies were preference dependent. Qualitative data elucidated patient-level factors that influenced number of clinical contacts and prompt modifications explaining their lack of association with clinical outcomes. CONCLUSION: Our mixed methods approach underlines the importance of the complementarity of different intervention features. Qualitative findings further illuminate reasons for variations in fidelity from the core model.

National Estimates of the Adult Diabetes Care Continuum in India, 2019-2021.

Importance: Diabetes is widespread and treatable, but little is known about the diabetes care continuum (diagnosis, treatment, and control) in India and how it varies at the national, state, and district levels. Objective: To estimate the adult population levels of diabetes diagnosis, treatment, and control in India at national, state, and district levels and by sociodemographic characteristics. Design, Setting, and Participants: In this cross-sectional, nationally representative survey study from 2019 to 2021, adults in India from 28 states, 8 union territories, and 707 districts were surveyed for India's Fifth National Family Health Survey (NFHS-5). The survey team collected data on blood glucose among all adults (18-98 years) who were living in the same household as eligible participants (pregnant or nonpregnant female individuals aged 15-49 years and male individuals aged 15-54 years). The overall sample consisted of 1 895 287 adults. The analytic sample was restricted to those who either self-reported having diabetes or who had a valid measurement of blood glucose. Exposures: The exposures in this survey study were district and state residence; urban vs rural residence; age (18-39 years, 40-64 years, or ≥65 years); sex; and household wealth quintile. Main Outcomes and Measures: Diabetes was defined by self-report or high capillary blood glucose (fasting: ≥126 mg/dL [to convert to mmol/L, multiply by 0.0555]; nonfasting: ≥220 mg/dL). Among respondents who had previously been diagnosed with diabetes, the main outcome was the proportion treated based on self-reported medication use and the proportion controlled (fasting: blood glucose <126 mg/dL; nonfasting: ≤180 mg/dL). The findings were benchmarked against the World Health Organization (WHO) Global Diabetes Compact targets (80% diagnosis; 80% control among those diagnosed). The variance in indicators between and within states was partitioned using variance partition coefficients (VPCs). Results: Among 1 651 176 adult respondents (mean [SD] age, 41.6 [16.4] years; 867 896 [52.6%] female) with blood glucose measures, the proportion of individuals with diabetes was 6.5% (95% CI, 6.4%-6.6%). Among adults with diabetes, 74.2% (95% CI, 73.3%-75.0%) were diagnosed. Among those diagnosed, 59.4% (95% CI, 58.1%-60.6%) reported taking medication, and 65.5% (95% CI, 64.5%-66.4%) achieved control. Diagnosis and treatment were higher in urban areas, older age groups, and wealthier households. Among those diagnosed in the 707 districts surveyed, 246 (34.8%) districts met the WHO diagnosis target, while 76 (10.7%) districts met the WHO control target. Most of the variability in diabetes diagnosis (VPC, 89.1%), treatment (VPC, 85.9%), and control (VPC, 95.6%) were within states, not between states. Conclusions and Relevance: In this survey study, the diabetes care continuum in India is represented by considerable district-level variation, age-related disparities, and rural-urban differences. Surveillance at the district level can guide state health administrators to prioritize interventions and monitor achievement of global targets.

Cost-effectiveness of a multicomponent quality improvement care model for diabetes in South Asia: The CARRS randomized clinical trial.

OBJECTIVES: To assess the cost-effectiveness of a multicomponent strategy versus usual care in people with type 2 diabetes in South Asia. DESIGN: Economic evaluation from healthcare system and societal perspectives. SETTING: Ten diverse urban clinics in India and Pakistan. PARTICIPANTS: 1146 people with type 2 diabetes (575 in the intervention group and 571 in the usual care group) with mean age of 54.2 years, median diabetes duration: 7 years and mean HbA1c: 9.9% (85 mmol/mol) at baseline. INTERVENTION: Multicomponent strategy comprising decision-supported electronic health records and non-physician care coordinator. Control group received usual care. OUTCOME MEASURES: Incremental cost-effectiveness ratios (ICERs) per unit achievement in multiple risk factor control (HbA1c <7% (53 mmol/mol) and SBP <130/80 mmHg or LDLc <2.58 mmol/L (100 mg/dL)), ICERs per unit reduction in HbA1c, 5-mmHg unit reductions in systolic BP, 10-unit reductions in LDLc (mg/dl) (considered as clinically relevant) and ICER per quality-adjusted life years (QALYs) gained. ICERs were reported in 2020 purchasing power parity-adjusted international dollars (INT$). The probability of ICERs being cost-effective was considered depending on the willingness to pay (WTP) values as a share of GDP per capita for India (Int$ 7041.4) and Pakistan (Int$ 4847.6). RESULTS: Compared to usual care, the annual incremental costs per person for intervention group were Int$ 1061.9 from a health system perspective and Int$ 1093.6 from a societal perspective. The ICER was Int$ 10,874.6 per increase in multiple risk factor control, $2588.1 per one percentage point reduction in the HbA1c, and $1744.6 per 5 unit reduction in SBP (mmHg), and $1271 per 10 unit reduction in LDLc (mg/dl). The ICER per QALY gained was $33,399.6 from a societal perspective. CONCLUSIONS: In a trial setting in South Asia, a multicomponent strategy for diabetes care resulted in better multiple risk factor control at higher costs and may be cost-effective depending on the willingness to pay threshold with substantial uncertainty around cost-effectiveness for QALYs gained in the short term (2.5 years). Future research needs to confirm the long-term cost-effectiveness of intensive multifactorial intervention for diabetes care in diverse healthcare settings in LMICs.

Cost-Effectiveness of a Collaborative Care Model Among Patients With Type 2 Diabetes and Depression in India.

OBJECTIVE: To assess the cost-effectiveness of collaborative versus usual care in adults with poorly controlled type 2 diabetes and depression in India. RESEARCH DESIGN AND METHODS: We performed a within-trial cost-effectiveness analysis of a 24-month parallel, open-label, pragmatic randomized clinical trial at four urban clinics in India from multipayer and societal perspectives. The trial randomly assigned 404 patients with poorly controlled type 2 diabetes (HbA1c ≥8.0%, systolic blood pressure ≥140 mmHg, or LDL cholesterol ≥130 mg/dL) and depressive symptoms (9-item Patient Health Questionnaire score ≥10) to collaborative care (support from nonphysician care coordinators, electronic registers, and specialist-supported case review) for 12 months, followed by 12 months of usual care or 24 months of usual care. We calculated incremental cost-effectiveness ratios (ICERs) in Indian rupees (INR) and international dollars (Int'l-$) and the probability of cost-effectiveness using quality-adjusted life-years (QALYs) and depression-free days (DFDs). RESULTS: From a multipayer perspective, collaborative care costed an additional INR309,558 (Int'l-$15,344) per QALY and an additional INR290.2 (Int'l-$14.4) per DFD gained compared with usual care. The probability of cost-effectiveness was 56.4% using a willingness to pay of INR336,000 (Int'l-$16,654) per QALY (approximately three times per-capita gross domestic product). The willingness to pay per DFD to achieve a probability of cost-effectiveness >95% was INR401.6 (Int'l-$19.9). From a societal perspective, cost-effectiveness was marginally lower. In sensitivity analyses, integrating collaborative care in clinical workflows reduced incremental costs by ∼47% (ICER 162,689 per QALY, cost-effectiveness probability 89.4%), but cost-effectiveness decreased when adjusting for baseline values. CONCLUSIONS: Collaborative care for patients with type 2 diabetes and depression in urban India can be cost-effective, especially when integrated in clinical workflows. Long-term cost-effectiveness might be more favorable. Scalability across lower- and middle-income country settings depends on heterogeneous contextual factors.

Anxiety and depression among adult tobacco users during the COVID-19 restrictions in India.

Background: The world witnessed a highly contagious and deadly disease, COVID-19, toward the end of 2019. India is one of the worst affected countries. We aimed to assess anxiety and depression levels among adult tobacco users and people who recently quit tobacco during COVID-19 lockdown in India. Materials and methods: The study was conducted across two Indian cities, Delhi and Chennai (July-August, 2020) among adult tobacco users (n = 801). Telephonic interviews were conducted using validated mental health tools (Patient Health Questionnaire-PHQ-9 and Generalized Anxiety Disorder-GAD-7) to assess the anxiety and depression levels of the participants. Descriptive analysis and multiple logistic regression were used to study the prevalence and correlates of depression and anxiety. Results: We found that 20.6% of tobacco users had depression symptoms (3.9% moderate to severe); 20.7% had anxiety symptoms (3.8% moderate to severe). Risk factors associated with depression and anxiety included food, housing, and financial insecurity. Conclusion: During COVID-19 lockdown, mental health of tobacco users (primarily women) was associated with food, housing and financial insecurity. The Indian Government rightly initiated several health, social and economic measures to shield the most vulnerable from COVID-19, including a ban on the sale of tobacco products. It is also necessary to prioritize universal health coverage, expanded social security net, tobacco cessation and mental health services to such vulnerable populations during pandemic situations.

A model for national assessment of barriers for implementing digital technology interventions to improve hypertension management in the public health care system in India.

BACKGROUND: There is substantial interest in leveraging digital health technology to support hypertension management in low- and middle-income countries such as India. The potential for healthcare infrastructure and broader context to support such initiatives in India has not been examined. We evaluated existing healthcare infrastructure to support digital health interventions and examined epidemiologic, socioeconomic, and geographical contextual correlates of healthcare infrastructure in 544 districts covering 29 states and union territories across India. METHODS: The study was a cross-sectional analysis of India's Fourth District Level Household and Facility Survey (DLHS-4; 2012-2014), the most up-to-date nationally representative district-level healthcare infrastructure data. Facilities were the unit of analysis, and analyses accounted for clustering within states. The main outcome was healthcare system infrastructural context to implement hypertension management programs. Domains included diagnostics (functional BP instrument), medications (anti-hypertensive medication in stock), essential clinical staff (e.g., staff nurse, medical officer, pharmacist), and IT specific infrastructure (regular power supply, internet connection, computer availability). Descriptive analysis was conducted for infrastructure indicators based on the Indian Public Health Standards, and logistic regression was conducted to estimate the association between epidemiologic and geographical context (exposures) and the composite measure of healthcare system. RESULTS: Data from 32,215 government facilities were analyzed. Among lowest-tier subcenters, 30% had some IT infrastructure, while at the highest-tier district hospitals, 92% possessed IT infrastructure. At mid-tier primary health centres and community health centres, IT infrastructure availability was 28 and 51%, respectively. For all but sub-centres, the availability of essential staff was lower than the availability of IT infrastructure. For all but district hospitals, higher levels of blood pressure, body mass index, and urban residents were correlated with more favorable infrastructure. By region, districts in Western India tended towards having the best prepared health facilities. CONCLUSIONS: IT infrastructure to support digital health interventions is more frequently lacking at lower and mid-tier healthcare facilities compared with apex facilities in India. Gaps were generally larger for staffing than physical infrastructure, suggesting that beyond IT infrastructure, shortages in essential staff impose significant constraints to the adoption of digital health interventions. These data provide early benchmarks for state- and district-level planning.

Assessment of Studies of Quality Improvement Strategies to Enhance Outcomes in Patients With Cardiovascular Disease.

Importance: Clinical care quality improvement (QI) strategies are critical to prevent and control cardiovascular disease (CVD). However, there is limited evidence regarding which components of the health system-, clinician-, and patient-based QI strategies contribute to their impact on CVD. Objectives: To identify, map, and organize evidence on the effectiveness and implementation of cardiovascular QI strategies that seek to improve outcomes in patients with CVD. Evidence Review: Eight electronic databases (MEDLINE, EMBASE, CINAHL, PsycINFO, the Cochrane Library, ProQuest, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform) were searched for studies published between January 1, 2009, and October 25, 2019. Eligible study designs included randomized trials and preintervention and postintervention evaluations. Descriptive findings of included studies were reported using several frameworks to map the intervention components stratified by target population, setting, outcomes, and overall results. Findings: From 8066 screened titles and abstracts, 456 unique studies with 150 148 unique patients (38.1% women and 61.9% men; mean [SD] age, 64.6 [7.1] years) were identified, including 427 randomized trials, 21 quasi-randomized studies, and 8 preintervention and postintervention studies. Of 336 studies from 45 countries that were classified, 255 (75.9%) were from high-income countries; 68 (20.2%), upper-middle-income countries; 13 (3.9%), lower-middle-income countries; and 0, low-income countries, with diverse clinical settings and target patient populations (post-myocardial infarction, stroke, heart failure). Patient support (311 studies), information communication technology (ICT) for health (78 studies), community support (18 studies), supervision (15 studies), and high-intensity training (14 studies) were the most commonly evaluated QI strategies. Other strategies were group problem-solving (7 studies), printed information (5 studies), strengthening infrastructure (4 studies), and financial incentives (3 studies). Patient support, ICT for health, training, and community support were strategies that had been evaluated the most for clinical end points and showed modest associations with several clinical outcomes. The other strategies did not have outcome-driven evaluations reported. Group problem-solving was associated with improved patient self-care and quality of life. Strengthening infrastructure was associated with improved treatment satisfaction. Printed information and financial incentives showed no meaningful effect. Conclusions and Relevance: This systematic review found that substantial variations exist in the types, effectiveness, and implementation of QI strategies for patients with CVD. A comprehensive map of QI strategies created by this study would be useful for researchers to identify where new knowledge is needed to improve cardiovascular outcomes. Outcome-driven evaluations and long-term studies are needed, particularly in low-income settings, to better understand the effects of QI strategies on prevention and control of CVD.

Health, psychosocial, and economic impacts of the COVID-19 pandemic on people with chronic conditions in India: a mixed methods study.

BACKGROUND: People with chronic conditions are disproportionately prone to be affected by the COVID-19 pandemic but there are limited data documenting this. We aimed to assess the health, psychosocial and economic impacts of the COVID-19 pandemic on people with chronic conditions in India. METHODS: Between July 29, to September 12, 2020, we telephonically surveyed adults (n = 2335) with chronic conditions across four sites in India. Data on participants' demographic, socio-economic status, comorbidities, access to health care, treatment satisfaction, self-care behaviors, employment, and income were collected using pre-tested questionnaires. We performed multivariable logistic regression analysis to examine the factors associated with difficulty in accessing medicines and worsening of diabetes or hypertension symptoms. Further, a diverse sample of 40 participants completed qualitative interviews that focused on eliciting patient's experiences during the COVID-19 lockdowns and data analyzed using thematic analysis. RESULTS: One thousand seven hundred thirty-four individuals completed the survey (response rate = 74%). The mean (SD) age of respondents was 57.8 years (11.3) and 50% were men. During the COVID-19 lockdowns in India, 83% of participants reported difficulty in accessing healthcare, 17% faced difficulties in accessing medicines, 59% reported loss of income, 38% lost jobs, and 28% reduced fruit and vegetable consumption. In the final-adjusted regression model, rural residence (OR, 95%CI: 4.01,2.90-5.53), having diabetes (2.42, 1.81-3.25) and hypertension (1.70,1.27-2.27), and loss of income (2.30,1.62-3.26) were significantly associated with difficulty in accessing medicines. Further, difficulties in accessing medicines (3.67,2.52-5.35), and job loss (1.90,1.25-2.89) were associated with worsening of diabetes or hypertension symptoms. Qualitative data suggest most participants experienced psychosocial distress due to loss of job or income and had difficulties in accessing in-patient services. CONCLUSION: People with chronic conditions, particularly among poor, rural, and marginalized populations, have experienced difficulties in accessing healthcare and been severely affected both socially and financially by the COVID-19 pandemic.

Lifetime risk of diabetes in metropolitan cities in India.

AIMS/HYPOTHESIS: We aimed to estimate the lifetime risk of diabetes and diabetes-free life expectancy in metropolitan cities in India among the population aged 20 years or more, and their variation by sex, age and BMI. METHODS: A Markov simulation model was adopted to estimate age-, sex- and BMI-specific lifetime risk of developing diabetes and diabetes-free life expectancy. The main data inputs used were as follows: age-, sex- and BMI-specific incidence rates of diabetes in urban India taken from the Centre for Cardiometabolic Risk Reduction in South Asia (2010-2018); age-, sex- and urban-specific rates of mortality from period lifetables reported by the Government of India (2014); and prevalence of diabetes from the Indian Council for Medical Research INdia DIABetes study (2008-2015). RESULTS: Lifetime risk (95% CI) of diabetes in 20-year-old men and women was 55.5 (51.6, 59.7)% and 64.6 (60.0, 69.5)%, respectively. Women generally had a higher lifetime risk across the lifespan. Remaining lifetime risk (95% CI) declined with age to 37.7 (30.1, 46.7)% at age 60 years among women and 27.5 (23.1, 32.4)% in men. Lifetime risk (95% CI) was highest among obese Indians: 86.0 (76.6, 91.5)% among 20-year-old women and 86.9 (75.4, 93.8)% among men. We identified considerably higher diabetes-free life expectancy at lower levels of BMI. CONCLUSIONS/INTERPRETATION: Lifetime risk of diabetes in metropolitan cities in India is alarming across the spectrum of weight and rises dramatically with higher BMI. Prevention of diabetes among metropolitan Indians of all ages is an urgent national priority, particularly given the rapid increase in urban obesogenic environments across the country. Graphical abstract.

The Integrated Tracking, Referral, and Electronic Decision Support, and Care Coordination (I-TREC) program: scalable strategies for the management of hypertension and diabetes within the government healthcare system of India.

BACKGROUND: Hypertension and diabetes are among the most common and deadly chronic conditions globally. In India, most adults with these conditions remain undiagnosed, untreated, or poorly treated and uncontrolled. Innovative and scalable approaches to deliver proven-effective strategies for medical and lifestyle management of these conditions are needed. METHODS: The overall goal of this implementation science study is to evaluate the Integrated Tracking, Referral, Electronic decision support, and Care coordination (I-TREC) program. I-TREC leverages information technology (IT) to manage hypertension and diabetes in adults aged ≥30 years across the hierarchy of Indian public healthcare facilities. The I-TREC program combines multiple evidence-based interventions: an electronic case record form (eCRF) to consolidate and track patient information and referrals across the publicly-funded healthcare system; an electronic clinical decision support system (CDSS) to assist clinicians to provide tailored guideline-based care to patients; a revised workflow to ensure coordinated care within and across facilities; and enhanced training for physicians and nurses regarding non-communicable disease (NCD) medical content and lifestyle management. The program will be implemented and evaluated in a predominantly rural district of Punjab, India. The evaluation will employ a quasi-experimental design with mixed methods data collection. Evaluation indicators assess changes in the continuum of care for hypertension and diabetes and are grounded in the Reach, Effectiveness, Adoption Implementation, and Maintenance (RE-AIM) framework. Data will be triangulated from multiple sources, including community surveys, health facility assessments, stakeholder interviews, and patient-level data from the I-TREC program's electronic database. DISCUSSION: I-TREC consolidates previously proven strategies for improved management of hypertension and diabetes at single-levels of the healthcare system into a scalable model for coordinated care delivery across all levels of the healthcare system hierarchy. Findings have the potential to inform best practices to ultimately deliver quality public-sector hypertension and diabetes care across India. TRIAL REGISTRATION: The study is registered with Clinical Trials Registry of India (registration number CTRI/2020/01/022723 ). The study was registered prior to the launch of the intervention on 13 January 2020. The current version of protocol is version 2 dated 6 June 2018.

Healthcare utilisation and expenditure patterns for cardio-metabolic diseases in South Asian cities: the CARRS Study.

OBJECTIVE: To estimate average annual expenditures per person, total economic burden and distress health financing associated with the treatment of five cardio-metabolic diseases (CMDs-hypertension, diabetes, heart disease (angina, myocardial infarction and heart failure), stroke and chronic kidney disease) in three metropolitan cities in South Asia. DESIGN: Cross-sectional surveys. SETTING: We analysed community-based baseline data from the Centre for cArdio-metabolic Risk Reduction in South Asia (CARRS) Study collected in 2010-2011 representing Chennai and New Delhi (India), and Karachi (Pakistan). PARTICIPANTS: We used data from non-pregnant adults (≥20 years) from the aforementioned cities that responded to a cost-of-illness questionnaire. We estimated health utilisation and expenditures among those reporting taking treatment(s) for the aforementioned CMDs in the last 1 year. We converted all costs to International Dollars (Int$ 2011) and inflated to 2018 values. The annual costs per person were stratified by city, sociodemographic characteristics, contributor of costs and financing methods. The total economic burden of CMDs for each city was projected using age-standardised prevalence and per-person costs of diseases reported in CARRS, applying these to population data from the most recent census. We also calculated distress financing (DF) as having to borrow or sell assets to pay for CMD treatment and identified sociodemographic groups at most risk of DF using multiple regression. RESULTS: Of 16 287 CARRS participants, 2883 (17.7%) reported receiving treatment for CMDs. The total annual expenditures reported per patient for CMDs ranged from Int$358 to Int$2425. Medications constituted 46% of total direct expenditures and out-of-pocket (OOP) expenditures accounted for nearly 80% of financing these health expenditures. Total economic burdens of CMDs were Int$0.42 billion, Int$3.4 billion and Int$1.4 billion in Chennai, New Delhi and Karachi, respectively. Overall, 36.1% experienced DF, and women (OR=4.4), unemployed (OR=10.7) and uninsured (OR=8.1) adults experienced higher odds of DF. CONCLUSION: CMDs are associated with large economic burdens in South Asia. Due to most payments coming from OOP expenditures and limited insurance, the odds of DF are high.

Proposed guidelines for screening of hyperglycemia in patients hospitalized with COVID-19 in low resource settings.

BACKGROUND AND AIMS: The coronavirus disease 2019 (COVID-19) pandemic has immensely strained healthcare systems worldwide. Diabetes has emerged as a major comorbidity in a large proportion of patients infected with COVID-19 and is associated with poor health outcomes. We aim to provide a practical guidance on screening of hyperglycemia in persons without known diabetes in low resource settings. METHODS: We reviewed the available guidelines on this subject and proposed an algorithm based on simple measures of blood glucose (BG) which can be implemented by healthcare workers with lesser expertise in low resource settings. RESULTS: We propose that every hospitalized patient with COVID-19 infection undergo a paired capillary BG assessment (pre-meal and 2-h post-meal). Patients with pre-meal BG < 7.8 mmol/L (140 mg/dL) and post-meal BG < 10.0 mmol/L (180 mg/dL) may not merit further monitoring. On the other hand, those with one or more value above these thresholds should undergo capillary BG monitoring (pre-meals and 2 hours after dinner) for the next 24 hours. When two or more (≥50%) such values are significantly elevated [pre-meal ≥8.3 mmol/L (150 mg/dL) and post-meal ≥11.1 mmol/L (200 mg/dL)], pharmacotherapy should be immediately initiated. On the other hand, in patients with modest elevation of one or more values [pre-meal 7.8-8.3 mmol/L (140-150 mg/dL) and post-meal 10.0-11.1 mmol/L (180-200 mg/dL)], dietary modifications should be initiated and pharmacotherapy considered only if BG control remains suboptimal. CONCLUSION: We highlight strategies for screening of hyperglycemia in persons without known diabetes treated for COVID-19 infection in low resource settings. This guidance may well be applied to other settings in the near future.

Prevalence and correlates of household food insecurity in Delhi and Chennai, India.

India is home to nearly 200 million undernourished people, yet little is known about the characteristics of those experiencing food insecurity, especially among urban households. The objectives of this study were: (1) to report the prevalence of food insecurity in two large, population-based representative samples in urban India, (2) to describe socio-economic correlates of food insecurity in this context, and (3) to compare the dietary intake of adults living in food insecure households to that of adults living in food secure households. Data are from 4334 households participating in an ongoing population-based cohort study of a representative sample of Delhi and Chennai, India. The most recent wave of data (2017-2018) were analysed. Food insecurity was measured using the 9-item Household Food Insecurity Access Scale (HFIAS) and dietary intake using a 33-item semi-quantitative food frequency questionnaire. The overall prevalence of food insecurity was 8.5% (95% confidence interval [CI], 6.8-10.2); 15.2% (95% CI 12.0-18.4) of the poorest households (lowest wealth index tertile) were food insecure compared to 1.7% (95% CI 1.0-2.3) of the wealthiest households (highest wealth index tertile). Participants experiencing food insecurity were significantly younger and more likely to be from Delhi compared to Chennai. After adjustment for socio-economic factors (city, age, sex, education, wealth index, fuel used for cooking, and source of drinking water), participants experiencing food insecurity had significantly higher meat, poultry, roots and tubers (potato), and sugar sweetened beverage intakes, and lower vegetables, fruit, dairy, and nut intakes. Food insecurity is highly prevalent among the poorest households in urban India and is associated with intake of a number of unhealthy dietary items.

Strategies for Stakeholder Engagement and Uptake of New Intervention: Experience From State-Wide Implementation of mHealth Technology for NCD Care in Tripura, India.

BACKGROUND: Appropriate strategies and key stakeholder engagement are the keys to successful implementation of new health care interventions. OBJECTIVES: The study sought to articulate the key strategies used for scaling up a research-based intervention, mPower Heart electronic Clinical Decision Support System (e-CDSS), for state-wide implementation at health facilities in Tripura. METHODS: Multiple strategies were used for statewide implementation of mPower Heart e-CDSS at noncommunicable diseases clinics across the government health facilities in Tripura: formation of a technical coordination-cum-support unit, change management, enabling environment, adapting the intervention with user focus, and strengthening the Health Information System. RESULTS: The effective delivery of a new health system intervention requires engagement at multiple levels including political leadership, health administrators, and health professionals, which can be achieved by forming a technical coordination-cum-support unit. It is important to specify the role and responsibilities of existing manpower and provide a structured training program. Enabling environment at health facilities (providing essential equipment, space and time, etc.) is also crucial. Successful implementation also requires that patients, health care providers, the health system, and leadership recognize the immediate and long-term benefits of the new intervention and have a buy-in in the intervention. With constant encouragement and nudge from administrative authorities and by using multiple strategies, 40 government health facilities adopted the mPower Heart e-CDSS. From its launch in May 2017 until November 20, 2018, a total of 100,810 eligible individuals were screened and enrolled, with 35,884 treated for hypertension, 9,698 for diabetes, and 5,527 for both hypertension and diabetes. CONCLUSIONS: Multiple strategies, based on implementation principles, are required for successful scaling up of research-based interventions.

Concordance of glycaemic and cardiometabolic traits between Indian women with history of gestational diabetes mellitus and their spouses: an opportunity to target the household.

AIMS/HYPOTHESIS: The aim of this study was to investigate the concordance of dysglycaemia (prediabetes or diabetes) and cardiometabolic traits between women with a history of gestational diabetes mellitus (GDM) and their spouses. METHODS: Using hospital medical records, women with GDM (diagnosed between 2012 and 2016) and their spouses were invited to participate in the study and to attend a scheduled hospital visit in a fasting state. Sociodemographic, anthropometric and medical data were collected, and a 75 g OGTT with serum insulin estimation, HbA1c measurement and fasting lipid profile were performed at the visit. Prediabetes and diabetes were defined using ADA criteria and the metabolic syndrome was defined using IDF criteria. RESULTS: A total of 214 couples participated in the study. Women were tested at a mean ± SD age of 32.4 ± 4.6 years and median (quartile [q]25-q75) of 19.5 (11-44) months following the index delivery, while men were tested at a mean ± SD age of 36.4 ± 5.4 years. A total of 72 (33.6%) couples showed concordance for dysglycaemia, while 99 (46.3%) and 51 (23.8%) couples were concordant for overweight/obesity and the metabolic syndrome, respectively. A total of 146 (68.2%) couples showed concordance for any of the above three factors. The presence of dysglycaemia in one partner was associated with an increased risk of dysglycaemia in the other partner (OR 1.80 [95% CI 1.04, 3.11]). Similarly, being overweight/obese (OR 2.19 [95% CI 1.22, 3.93]) and presence of the metabolic syndrome (OR 2.01 [95% CI 1.16, 3.50]) in one partner was associated with an increased risk of these conditions in the other partner. Both women and men were more likely to have dysglycaemia if they had a partner with dysglycaemia. Women with a partner with dysglycaemia had a significantly higher BMI, waist circumference and diastolic BP, and a significantly higher probability of low HDL-cholesterol (<1.29 mmol/l) and the metabolic syndrome compared with women with a normoglycaemic partner. No such differences were observed for men with or without a partner with dysglycaemia. CONCLUSIONS/INTERPRETATION: The high degree of spousal concordance found in this study suggests social clustering of glycaemic and cardiometabolic traits among biologically unrelated individuals. This provides us with an opportunity to target the behavioural interventions at the level of the 'married couple', which may be a novel and cost-effective method of combating the current diabetes epidemic.

Rationale and protocol for estimating the economic value of a multicomponent quality improvement strategy for diabetes care in South Asia.

BACKGROUND: Economic dimensions of implementing quality improvement for diabetes care are understudied worldwide. We describe the economic evaluation protocol within a randomised controlled trial that tested a multi-component quality improvement (QI) strategy for individuals with poorly-controlled type 2 diabetes in South Asia. METHODS/DESIGN: This economic evaluation of the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) randomised trial involved 1146 people with poorly-controlled type 2 diabetes receiving care at 10 diverse diabetes clinics across India and Pakistan. The economic evaluation comprises both a within-trial cost-effectiveness analysis (mean 2.5 years follow up) and a microsimulation model-based cost-utility analysis (life-time horizon). Effectiveness measures include multiple risk factor control (achieving HbA1c < 7% and blood pressure < 130/80 mmHg and/or LDL-cholesterol< 100 mg/dl), and patient reported outcomes including quality adjusted life years (QALYs) measured by EQ-5D-3 L, hospitalizations, and diabetes related complications at the trial end. Cost measures include direct medical and non-medical costs relevant to outpatient care (consultation fee, medicines, laboratory tests, supplies, food, and escort/accompanying person costs, transport) and inpatient care (hospitalization, transport, and accompanying person costs) of the intervention compared to usual diabetes care. Patient, healthcare system, and societal perspectives will be applied for costing. Both cost and health effects will be discounted at 3% per year for within trial cost-effectiveness analysis over 2.5 years and decision modelling analysis over a lifetime horizon. Outcomes will be reported as the incremental cost-effectiveness ratios (ICER) to achieve multiple risk factor control, avoid diabetes-related complications, or QALYs gained against varying levels of willingness to pay threshold values. Sensitivity analyses will be performed to assess uncertainties around ICER estimates by varying costs (95% CIs) across public vs. private settings and using conservative estimates of effect size (95% CIs) for multiple risk factor control. Costs will be reported in US$ 2018. DISCUSSION: We hypothesize that the additional upfront costs of delivering the intervention will be counterbalanced by improvements in clinical outcomes and patient-reported outcomes, thereby rendering this multi-component QI intervention cost-effective in resource constrained South Asian settings. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01212328.

Strategic Opportunities for Leveraging Low-cost, High-impact Technological Innovations to Promote Cardiovascular Health in India.

Accelerated epidemiological transition in India over the last 40 years has resulted in a dramatic increase in the burden of cardiovascular diseases and the related risk factors of diabetes and hypertension. This increase in disease burden has been accompanied by pervasive health disparities associated with low disease detection rates, inadequate awareness, poor use of evidence-based interventions, and low adherence rates among patients in rural regions in India and those with low socioeconomic status. Several research groups in India have developed innovative technologies and care-delivery models for screening, diagnosis, clinical management, remote-monitoring, self-management, and rehabilitation for a range of chronic conditions. These innovations can leverage advances in sensor technology, genomic tools, artificial intelligence, big-data analytics, and so on, for improving access to and delivering quality and affordable personalized medicine in primary care. In addition, several health technology start-ups are entering this booming market that is set to grow rapidly. Innovations outside biomedical space (eg, protection of traditional wisdom in diet, lifestyle, yoga) are equally important and are part of a comprehensive solution. Such low-cost, culturally tailored, robust innovations to promote health and reduce disparities require partnership among multi-sectors including academia, industry, civil society, and health systems operating in a conducive policy environment that fosters adequate public and private investments. In this article, we present the unique opportunity for India to use culturally tailored, low-cost, high-impact technological innovations and strategies to ameliorate the perennial challenges of social, policy, and environmental challenges including poverty, low educational attainment, culture, and other socioeconomic factors to promote cardiovascular health and advance health equity.