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.

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.

Protocol on a multicentre statistical and economic modelling study of risk-based stratified and personalised screening for diabetes and its complications in India (SMART India).

INTRODUCTION: The aim of this study is to develop practical and affordable models to (a) diagnose people with diabetes and prediabetes and (b) identify those at risk of diabetes complications so that these models can be applied to the population in low-income and middle-income countries (LMIC) where laboratory tests are unaffordable. METHODS AND ANALYSIS: This statistical and economic modelling study will be done on at least 48 000 prospectively recruited participants aged 40 years or above through community screening across 20 predefined regions in India. Each participant will be tested for capillary random blood glucose (RBG) and complete a detailed health-related questionnaire. People with known diabetes and all participants with predefined levels of RBG will undergo further tests, including point-of-care (POC) glycated haemoglobin (HbA1c), POC lipid profile and POC urine test for microalbuminuria, retinal photography using non-mydriatic hand-held retinal camera, visual acuity assessment in both eyes and complete quality of life questionnaires. The primary aim of the study is to develop a model and assess its diagnostic performance to predict HbA1c diagnosed diabetes from simple tests that can be applied in resource-limited settings; secondary outcomes include RBG cut-off for definition of prediabetes, diagnostic accuracy of cost-effective risk stratification models for diabetic retinopathy and models for identifying those at risk of complications of diabetes. Diagnostic accuracy inter-tests agreement, statistical and economic modelling will be performed, accounting for clustering effects. ETHICS AND DISSEMINATION: The Indian Council of Medical Research/Health Ministry Screening Committee (HMSC/2018-0494 dated 17 December 2018 and institutional ethics committees of all the participating institutions approved the study. Results will be published in peer-reviewed journals and will be presented at national and international conferences. TRIAL REGISTRATION NUMBER: ISRCTN57962668 V1.0 24/09/2018.

Association of Household Wealth Index, Educational Status, and Social Capital with Hypertension Awareness, Treatment, and Control in South Asia.

OBJECTIVE: Hypertension control rates are low in South Asia. To determine association of measures of socioeconomic status (wealth, education, and social capital) with hypertension awareness, treatment, and control among urban and rural subjects in these countries we performed the present study. METHODS: We enrolled 33,423 subjects aged 35-70 years (women 56%, rural 53%, low-education status 51%, low household wealth 25%, low-social capital 33%) in 150 communities in India, Pakistan, and Bangladesh during 2003-2009. Prevalence of hypertension and its awareness, treatment, and control status and their association with wealth, education, and social capital were determined. RESULTS: Age-, sex-, and location-adjusted prevalence of hypertension in men was 31.5% (23.9-40.2%) and women was 32.6% (24.9-41.5%) with variations in prevalence across study sites (urban 30-56%, rural 11-43%). Prevalence was significantly greater in urban locations, older subjects, and participants with more wealth, greater education, and lower social capital index. Hypertension awareness was in 40.4% (urban 45.9, rural 32.5), treatment in 31.9% (urban 37.6, rural 23.6), and control in 12.9% (urban 15.4, rural 9.3). Control was lower in men and younger subjects. Hypertension awareness, treatment, and control were significantly lower, respectively, in lowest vs. highest wealth index tertile (26.2 vs. 50.6%, 16.9 vs. 44.0%, and 6.9 vs. 17.3%, P < 0.001) and lowest vs. highest educational status tertile (31.2 vs. 48.4%, 21.8 vs. 42.1%, and 7.8 vs. 19.2%, P < 0.001) while insignificant differences were observed in lowest vs. highest social capital index (38.2 vs. 36.1%, 35.1 vs. 27.8%, and 12.5 vs. 9.1%). CONCLUSIONS: This study shows low hypertension awareness, treatment, and control in South Asia. Lower wealth and educational status are important in low hypertension awareness, treatment, and control.

Use of capillary blood glucose for screening for gestational diabetes mellitus in resource-constrained settings.

AIMS: The aim of the study was to evaluate usefulness of capillary blood glucose (CBG) for diagnosis of gestational diabetes mellitus (GDM) in resource-constrained settings where venous plasma glucose (VPG) estimations may be impossible. METHODS: Consecutive pregnant women (n = 1031) attending antenatal clinics in southern India underwent 75-g oral glucose tolerance test (OGTT). Fasting, 1- and 2-h VPG (AU2700 Beckman, Fullerton, CA) and CBG (One Touch Ultra-II, LifeScan) were simultaneously measured. Sensitivity and specificity were estimated for different CBG cut points using the International Association of Diabetes in Pregnancy Study Groups (IADPSG) criteria for the diagnosis of GDM as gold standard. Bland-Altman plots were drawn to look at the agreement between CBG and VPG. Correlation and regression equation analysis were also derived for CBG values. RESULTS: Pearson's correlation between VPG and CBG for fasting was r = 0.433 [intraclass correlation coefficient (ICC) = 0.596, p < 0.001], for 1H, it was r = 0.653 (ICC = 0.776, p < 0.001), and for 2H, r = 0.784 (ICC = 0.834, p < 0.001). Comparing a single CBG 2-h cut point of 140 mg/dl (7.8 mmol/l) with the IADPSG criteria, the sensitivity and specificity were 62.3 and 80.7 %, respectively. If CBG cut points of 120 mg/dl (6.6 mmol/l) or 110 mg/dl (6.1 mmol/l) were used, the sensitivity improves to 78.3 and 92.5 %, respectively. CONCLUSIONS: In settings where VPG estimations are not possible, CBG can be used as an initial screening test for GDM, using lower 2H CBG cut points to maximize the sensitivity. Those who screen positive can be referred to higher centers for definitive testing, using VPG.

High burden of prediabetes and diabetes in three large cities in South Asia: The Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) Study.

AIM: To estimate the prevalence of, and assess factors associated with, diabetes and prediabetes in three South Asian cities. METHODS: Using a multi-stage cluster random sample representative of each city, 16,288 subjects aged ≥20 years (Chennai: 6906, Delhi: 5365 and Karachi: 4017) were recruited to the Centre for cArdio-metabolic Risk Reduction in South-Asia (CARRS) Study. Fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c) were measured in 13720 subjects. Prediabetes was defined as FPG 100-125 mg/dl (5.6-6.9 mmol/l) and/or HbA1c 5.7-6.4% (39-46 mmol/mol) and diabetes as self-report and/or drug treatment for diabetes and/or FPG≥126 mg/dl (≥7.0 mmol/l) and/or HbA1c≥6.5% (48 mmol/mol). We assessed factors associated with diabetes and prediabetes using polytomous logistic regression models. RESULTS: Overall 47.3-73.1% of the population had either diabetes or prediabetes: Chennai 60.7% [95%CI: 59.0-62.4%] (diabetes - 22.8% [21.5-24.1%], prediabetes - 37.9% [36.1-39.7%]); Delhi 72.7% [70.6-74.9%] (diabetes - 25.2% [23.6-26.8%], prediabetes - 47.6% [45.6-49.5%]); and Karachi 47.4% [45.7-49.1%]; (diabetes - 16.3% [15.2-17.3%], prediabetes - 31.1% [29.5-32.8%], respectively). Proportions of self-reported diabetes were 55.1%, 39.0%, and 48.0% in Chennai, Delhi, and Karachi, respectively. City, age, family history of diabetes, generalized obesity, abdominal obesity, body fat, high cholesterol, high triglyceride, and low HDL cholesterol levels were each independently associated with prediabetes, while the same factors plus waist-to-height ratio and hypertension were associated with diabetes. CONCLUSION: Six in ten adults in large South Asian cities have either diabetes or prediabetes. These data call for urgent action to prevent diabetes in South Asia.

Physical activity and inactivity patterns in India - results from the ICMR-INDIAB study (Phase-1) [ICMR-INDIAB-5].

BACKGROUND: The rising prevalence of diabetes and obesity in India can be attributed, at least in part, to increasing levels of physical inactivity. However, there has been no nationwide survey in India on physical activity levels involving both the urban and rural areas in whole states of India. The aim of the present study was to assess physical activity patterns across India - as part of the Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study. METHODS: Phase 1 of the ICMR-INDIAB study was conducted in four regions of India (Tamilnadu, Maharashtra, Jharkhand and Chandigarh representing the south, west, east and north of India respectively) with a combined population of 213 million people. Physical activity was assessed using the Global Physical Activity Questionnaire (GPAQ) in 14227 individuals aged ≥ 20 years [urban- 4,173; rural- 10,054], selected from the above regions using a stratified multistage design. RESULTS: Of the 14227 individuals studied, 54.4% (n=7737) were inactive (males: 41.7%), while 31.9% (n=4537) (males: 58.3%) were active and 13.7% (n=1953) (males: 61.3%) were highly active. Subjects were more inactive in urban, compared to rural, areas (65.0% vs. 50.0%; p<0.001). Males were significantly more active than females (p<0.001). Subjects in all four regions spent more active minutes at work than in the commuting and recreation domains. Absence of recreational activity was reported by 88.4%, 94.8%, 91.3% and 93.1% of the subjects in Chandigarh, Jharkhand, Maharashtra and Tamilnadu respectively. The percentage of individuals with no recreational activity increased with age (Trend χ(2): 199.1, p<0.001). CONCLUSIONS: The study shows that a large percentage of people in India are inactive with fewer than 10% engaging in recreational physical activity. Therefore, urgent steps need to be initiated to promote physical activity to stem the twin epidemics of diabetes and obesity in India.

Increased risk of type 2 diabetes with ascending social class in urban South Indians is explained by obesity: The Chennai urban rural epidemiology study (CURES-116).

AIM: The aim of this study is to determine the factors responsible for differences in the prevalence of diabetes mellitus (DM) in subjects of different social class in an urban South Indian population. MATERIALS AND METHODS: Analyses were based on the cross-sectional data from the Chennai Urban Rural Epidemiology Study of 1989 individuals, aged ≥20 years. Entered in the analyses were information obtained by self-report on (1) household income; (2) family history of diabetes; (3) physical activity; (4) smoking status; (5) alcohol consumption. Biochemical, clinical and anthropometrical measurements were performed and included in the analyses. Social class was classified based on income as low (Rs. <2000) intermediate (Rs. 2000-5000`) and high (Rs. 5000-20000). RESULTS: The prevalence rates of DM were 12.0%, 18.4% and 21.7% in low, intermediate and high social class, respectively (P < 0.001). A significant increase in the risk of diabetes was found with ascending social class (Intermediate class: Odds ratio [OR], 1.7 [confidence interval [CI], 1.2-2.3]; High class: OR, 2.0 [CI-1.4-2.9]). The multivariable adjusted logistic regression analysis revealed that the effect of social class on the risk of diabetes remained significant (P = 0.016) when age, family history of diabetes and blood pressure were included. However, with the inclusion of abdominal obesity in the model, the significant effect of social class disappeared (P = 0.087). CONCLUSION: An increased prevalence of DM was found in the higher social class in this urban South Indian population, which is explained by obesity.

CARRS Surveillance study: design and methods to assess burdens from multiple perspectives.

BACKGROUND: Cardio-metabolic diseases (CMDs) are a growing public health problem, but data on incidence, trends, and costs in developing countries is scarce. Comprehensive and standardised surveillance for non-communicable diseases was recommended at the United Nations High-level meeting in 2011. AIMS: To develop a model surveillance system for CMDs and risk factors that could be adopted for continued assessment of burdens from multiple perspectives in South-Asian countries. DESIGN: Hybrid model with two cross-sectional serial surveys three years apart to monitor trend, with a three-year prospective follow-up of the first cohort.Sites: Three urban settings (Chennai and New Delhi in India; Karachi in Pakistan), 4000 participants in each site stratified by gender and age.Sampling methodology: Multi-stage cluster random sampling; followed by within-household participant selection through a combination of Health Information National Trends Study (HINTS) and Kish methods.Culturally-appropriate and methodologically-relevant data collection instruments were developed to gather information on CMDs and their risk factors; quality of life, health-care utilisation and costs, along with objective measures of anthropometric, clinical and biochemical parameters. The cohort follow-up is designed as a pilot study to understand the feasibility of estimating incidence of risk factors, disease events, morbidity, and mortality. RESULTS: The overall participant response rate in the first cross-sectional survey was 94.1% (Chennai 92.4%, n = 4943; Delhi 95.7%, n = 4425; Karachi 94.3%, n = 4016). 51.8% of the participants were females, 61.6% < 45years, 27.5% 45-60years and 10.9% >60 years. DISCUSSION: This surveillance model will generate data on prevalence and trends; help study the complex life-course patterns of CMDs, and provide a platform for developing and testing interventions and tools for prevention and control of CMDs in South-Asia. It will also help understanding the challenges and opportunities in establishing a surveillance system across countries.

Level of urbanization and noncommunicable disease risk factors in Tamil Nadu, India.

OBJECTIVE: To investigate the poorly understood relationship between the process of urbanization and noncommunicable diseases (NCDs) through the application of a quantitative measure of urbanicity. METHODS: We constructed a measure of the urban environment for seven areas using a seven-item scale based on data from the Census of India 2001 to develop an "urbanicity" scale. The scale was used in conjunction with data collected from 3705 participants in the World Health Organization's 2003 STEPwise risk factor surveillance survey in Tamil Nadu, India, to analyse the relationship between the urban environment and major NCD risk factors. Linear and logistic regression models were constructed examining the relationship between urbanicity and chronic disease risk. FINDINGS: Among men, urbanicity was positively associated with smoking (odds ratio: 3.54; 95% confidence interval, CI: 2.4-5.1), body mass index (OR: 7.32; 95% CI: 4.0-13.6), blood pressure (OR: 1.92; 95% CI: 1.4-2.7) and low physical activity (OR: 3.26; 95% CI: 2.5-4.3). Among women, urbanicity was positively associated with low physical activity (OR: 4.13; 95% CI: 3.0-5.7) and high body mass index (OR: 6.48; 95% CI: 4.6-9.2). In both sexes urbanicity was positively associated with the mean number of servings of fruit and vegetables consumed per day (P < 0.05). CONCLUSION: Urbanicity is associated with the prevalence of several NCD risk factors in Tamil Nadu, India.