Background: Cardiovascular diseases and diabetes are among the leading causes of premature adult deaths in India. Innovative approaches such as clinical decision support (CDS) software could play a major role in improving the quality of hypertension/diabetes care in primary care settings. Objective: To describe the steps and processes in the development of mWellcare, a complex intervention based on mobile health (mHealth) technology. Methods: The Medical Research Council framework was used to develop mWellcare in four steps: (1) identify gaps in usual care through literature review and health facility assessments; (2) identify the components of the intervention through discussions and consultations with experts; (3) develop intervention (clinical algorithms and mHealth system); and (4) evaluate acceptability and feasibility through pilot testing in five community health centers. Results: Lack of evidence-based, integrated, and systematic management of chronic conditions were major gaps identified. Experts in information technology, clinical fields, and public health professionals identified intervention components to address these gaps. Thereafter, clinical algorithm contextualized to primary care settings were prepared and the mWellcare intervention was developed. During the 2-month pilot, 631 patients diagnosed with hypertension and/or diabetes were registered, with a follow-up rate of 36.2%. The major barrier was resistance to follow mWellcare recommended patient workflow, and to overcome it, we emphasized onsite training and orientation program to cover all health care team member in each CHC. Conclusion: A pilot-tested mWellcare intervention is an mHealth system with important components, i.e. integrated management of chronic conditions, evidence-based CDS, longitudinal health data and automated short-messaging service to reinforce compliance to drug intake and follow-up visit, which will be used by nurses at primary health care settings in India. The effectiveness and cost-effectiveness of the intervention will be tested through a cluster randomized trial (trial registration number NCT02480062).

Background: The growing burden of hypertension and diabetes is one of the major public health challenges being faced by the health system in India. Clinical Decision Support Systems (CDSS) that assist with tailoring evidence-based management approaches combined with task-shifting from more specialized to less specialized providers may together enhance the impact of a program. We sought to integrate a technology “CDSS” and a strategy “Task-shifting” within the Government of India’s (GoI) Non-Communicable Diseases (NCD) System under the Comprehensive Primary Health Care (CPHC) initiative to enhance the program’s impact to address the growing burden of hypertension and diabetes in India. Methods: We developed a model of care “I-TREC” entirely calibrated for implementation within the current health system across all facility types (Primary Health Centre, Community Health Centre, and District Hospital) in a block in Shaheed Bhagat Singh (SBS) Nagar district of Punjab, India. We undertook an academic-community partnership to incorporate the combination of a CDSS with task-shifting into the GoI CPHC-NCD system, a platform that assists healthcare providers to record patient information for routine NCD care. Academic partners developed clinical algorithms, a revised clinic workflow, and provider training modules with iterative collaboration and consultation with government and technology partners to incorporate CDSS within the existing system. Discussion: The CDSS-enabled GoI CPHC-NCD system provides evidence-based recommendations for hypertension and diabetes; threshold-based prompts to assure referral mechanism across health facilities; integrated patient database, and care coordination through workflow management and dashboard alerts. To enable efficient implementation, modifications were made in the patient workflow and the fulcrum of the use of technology shifted from physician to nurse. Conclusion: Designed to be applicable nationwide, the I-TREC model of care is being piloted in a block in the state of Punjab, India. Learnings from I-TREC will provide a roadmap to other public health experts to integrate and adapt their interventions at the national level. Trial registration: CTRI/2020/01/022723.

Consumer knowledge is understood to play a role in managing risk factors associated with cardiovascular disease and may be influenced by level of education. The association between population knowledge, behaviours and actual salt consumption was explored overall, and for more-educated compared to less-educated individuals. A cross-sectional survey was done in an age-and sex-stratified random sample of 1395 participants from urban and rural areas of North and South India. A single 24-h urine sample, participants’ physical measurements and questionnaire data were collected. The mean age of participants was 40 years, 47% were women and mean 24-h urinary salt excretion was 9.27 (8.87–9.69) g/day. Many participants reported favourable knowledge and behaviours to minimise risks related to salt. Several of these behaviours were associated with reduced salt intake—less use of salt while cooking, avoidance of snacks, namkeens, and avoidance of pickles (all p < 0.003). Mean salt intake was comparable in more-educated (9.21, 8.55–9.87 g/day) versus less-educated (9.34, 8.57–10.12 g/day) individuals (p = 0.82). There was no substantively different pattern of knowledge and behaviours between more-versus less-educated groups and no clear evidence that level of education influenced salt intake. Several consumer behaviours related to use of salt during food preparation and consumption of salty products were related to actual salt consumption and therefore appear to offer an opportunity for intervention. These would be a reasonable focus for a government-led education campaign targeting salt.

Introduction: Cardiovascular diseases (CVDs) are the leading cause of death in India. The CVD risk approach is a cost-effective way to identify those at high risk, especially in a low resource setting. As there is no validated prognostic model for an Indian urban population, we have re-calibrated the original Framingham model using data from two urban Indian studies. Methods: We have estimated three risk score equations using three different models. The first model was based on Framingham original model; the second and third are the recalibrated models using risk factor prevalence from CARRS (Centre for cArdiometabolic Risk Reduction in South-Asia) and ICMR (Indian Council of Medical Research) studies, and estimated survival from WHO 2012 data for India. We applied these three risk scores to the CARRS and ICMR participants and estimated the proportion of those at high-risk (>30% 10 years CVD risk) who would be eligible to receive preventive treatment such as statins. Results: In the CARRS study, the proportion of men with 10 years CVD risk > 30% (and therefore eligible for statin treatment) was 13.3%, 21%, and 13.6% using Framingham, CARRS and ICMR risk models, respectively. The corresponding proportions of women were 3.5%, 16.4%, and 11.6%. In the ICMR study the corresponding proportions of men were 16.3%, 24.2%, and 16.5% and for women, these were 5.6%, 20.5%, and 15.3%. Conclusion: Although the recalibrated model based on local population can improve the validity of CVD risk scores our study exemplifies the variation between recalibrated models using different data from the same country. Considering the growing burden of cardiovascular diseases in India, and the impact that the risk approach has on influencing cardiovascular prevention treatment, such as statins, it is essential to develop high quality and well powered local cohorts (with outcome data) to develop local prognostic models.

Evidence to date suggests that high sodium intake affects health adversely, yet the role of a population-level strategy to reduce sodium intake is often contested. This review focuses on current available evidence on regional sodium intake levels, health implications of sodium intake, and population-level strategies implemented worldwide. The limitations in evidence, the difficulties in implementing population-wide strategies to reduce sodium intake, and the need for such strategies are critically reviewed. Evidence clearly shows that sodium has an adverse effect on blood pressure, cardiovascular disease, and mortality. However, whether reduced sodium intake benefits all individuals or only hypertensive individuals is still unclear. Methodological issues and publication bias in current evidence are other matters of concern in sodium-related research. While it is essential to continue working toward the World Health Organization’s target of 30% reduction in sodium intake, due consideration should be given to improving the quality of research, reducing bias in publications, and reviewing evidence more critically.

Aim: To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population. Methods: We conducted a cross-sectional survey among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019. Multimorbidity was defined as the coexistence of ≥two conditions using a 14-condition tool validated in India. We also calculated a multimorbidity-weighted index (MWI), which provides a weight to each disease based on its impact on physical functioning. Logistic regression was conducted to evaluate the association with sociodemographic variables, mental health (PHQ-9), physical functioning (ADL scale), and self-rated health (SRH). Results: We analyzed data from 3213 adults [Mean age 51.5 (±13), 54% women]. Prevalence of single chronic condition, multimorbidity, and MWI was 28.6, 18% and − 1.9 respectively. Age, higher wealth index and ever use alcohol were significantly associated with multimorbidity. Overall, 2.8% of respondents had limited physical functioning, 2.1% had depression, and 61.5% reported low SRH. Poorer health outcomes were more prevalent among the elderly, women, less educated, and those having lower wealth index and multimorbidity, were found to be significantly associated with poor health outcomes. Conclusions: The burden of multimorbidity was high in this young rural population, which portends significant adverse effects on their health and quality of life. The Indian health system should be reconfigured to address this emerging health priority holistically, by adopting a more integrated and sustainable model of care.