Aim To determine the glycosylated haemoglobin (HbA1c) cut-points for diabetes and impaired fasting glucose (IFG) among Asian Indians. Methods Participants (n = 525) were a random sample selected from the India Health Study. Based on history and fasting plasma glucose (FPG), participants were classified into known diabetes, newly diagnosed diabetes (NDD), impaired fasting glucose (IFG) [ADA and WHO criteria] or normal fasting glucose (NFG). Receiver Operating Characteristic curves were used to identify the optimum sensitivity and specificity for defining HbA1c cut-points for NDD and IFG against the FPG criteria. Results There were 64 participants with a known history of diabetes. Of the remaining 461, IFG was present in 44.7% (ADA) and 18.2% (WHO), and 10.4% were NDD. Mean HbA1c were 5.4 (±0.04)% for NFG; 5.7 (±0.06)% among IFG-ADA, 5.8 (±0.09)% among IFG-WHO; 7.5 (±0.33)% for NDD and 8.4 (±0.32)% for known diabetes. Optimal HbA1c cut-point for NDD was 5.8% (sensitivity = 75%, specificity = 75.5%, AUC = 0.819). Cut-point for IFG (ADA) was 5.5% (sensitivity = 59.7%, specificity = 59.9%, AUC = 0.628) and for IFG (WHO) was 5.6% (sensitivity = 60.7%, specificity = 65.1%, AUC = 0.671). Conclusion In this study population from north and south regions of India, the HbA1c cut-point that defines NDD (≥5.8%) was much lower than that proposed by an international expert committee and the American Diabetes Association (≥6.5%). A cut-point of ≥5.5% or ≥5.6% defined IFG, and was slightly lower than the ≥5.7% for high risk proposed, but accuracy was less than 70%.

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. Methods 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.

Background: India is experiencing an epidemic of obesity-hyperglycaemia, which coincides with child bearing age for women. The epidemic can be sustained and augmented through transgenerational transmission of adiposity and glucose intolerance in women. This presents an opportunity for exploring a clear strategy for the control of this epidemic in India. We conducted a study between November 2013 and May 2015 to inform the design of a large pregnancy cohort study. Based on the findings of this pilot, we developed the protocol for the proposed birth cohort of 5000 women, the recruitment for which will start in April 2016. The protocol of the study documents the processes which aim at advancing the available knowledge, linking several steps in the evolution of obesity led hyperglycemia. Methods: Maternal Antecedents of Adiposity and Studying the Transgenerational role of Hyperglycemia and Insulin (MAASTHI) is a cohort study in the public health facilities in Bangalore, India. The objective of MAASTHI is to prospectively assess the effects of glucose levels in pregnancy on the risk of adverse infant outcomes, especially in predicting the possible risk markers of later chronic diseases. The primary objective of the proposed study is to investigate the effect of glucose levels in pregnancy on skinfold thickness (adiposity) in infancy as a marker of future obesity and diabetes in offspring. The secondary objective is to assess the association between psychosocial environment of mothers and adverse neonatal outcomes including adiposity. The study aims to recruit 5000 pregnant women and follow them and their offspring for a period of 4 years. The institutional review board at The Indian Institute of Public Health (IIPH)-H, Bangalore, Public Health Foundation of India has approved the protocol. All participants are required to provide written informed consent. Discussion: The findings from this study may help to address important questions on screening and management of high blood sugar in pregnancy. It may provide critical information on the specific determinants driving the underweight-obesity-T2DM epidemic in India. The study can inform the policy regarding the potential impact of screening and management protocols in public healthcare facilities. The public health implications include prioritising issues of maternal glycemic control and weight management and better understanding of the lifecourse determinants in the development of T2DM.

Social networks are believed to affect health-related behaviors and health. Data to examine the links between social relationships and health in low- and middle-income country settings are limited. We provide guidance for introducing an instrument to collect social network data as part of epidemiological surveys, drawing on experience in urban India. We describe development and fielding of an instrument to collect social network information relevant to health behaviors among adults participating in a large, population-based study of non-communicable diseases in Delhi, India. We discuss basic characteristics of social networks relevant to health including network size, health behaviors of network partners (i.e., network exposures), network homogeneity, network diversity, strength of ties, and multiplexity. Data on these characteristics can be collected using a short instrument of 11 items asked about up to 5 network members and 3 items about the network generally, administered in approximately 20 minutes. We found high willingness to respond to questions about social networks (97% response). Respondents identified an average of 3.8 network members, most often relatives (80% of network ties), particularly blood relationships. Ninety-one percent of respondents reported that their primary contacts for discussing health concerns were relatives. Among all listed ties, 91% of most frequent snack partners and 64% of exercise partners in the last two weeks were relatives. These results demonstrate that family relationships are the crux of social networks in some settings, including among adults in urban India. Collecting basic information about social networks can be feasibly and effectively done within ongoing epidemiological studies.