{"doi":"10.1093/ije/dyac014","title":"Cohort Profile: The Center for cArdiometabolic Risk Reduction in South Asia (CARRS)","abstract":"South Asians comprise nearly 2 billion people worldwide and are at high risk of cardiometabolic disease, even at young ages and low body weights. The CARRS cohort, a population-based representative sample of Chennai and Delhi in India and of Karachi in Pakistan, ages ≥20 years, was assembled in two waves [CARRS-1 (2010–12), n = 16 287, 13 720 with biospecimens; and CARRS-2 (2014–16), n = 14 587, 13 709 with biospecimens]. CARRS-1 has completed five follow-up assessments after the baseline visit. CARRS-2 has completed one follow-up assessment after the baseline visit. The cohort had high participation rates at recruitment (∼90% in both waves). The CARRS Cohort has followed 30 874 individuals (27 429 with biospecimens) and accrued ∼115 000 person-years of follow-up, including a biorepository (n = 360 000 aliquots) in India. CARRS provides scientific infrastructure and data for measuring incidence and secular trends of cardiometabolic diseases (CMD) and risk factors. Researchers interested in the collaborative project can contact Dr KM Venkat Narayan [[email protected]] or Dr Dorairaj Prabhakaran [[email protected]]. Emerging data, largely from the diaspora and largely cross-sectional, indicate that South Asians exhibit high rates of cardiovascular disease (CVD), diabetes, atypical dyslipidaemia profiles, and hepatic steatosis1–7 at lower body weight and younger ages relative to populations with European and other ancestries.8–10 It is hypothesized that these differences are rooted in some combination of distinctive pathophysiology, risk factor, phenotypic and socioeconomic characteristics.11–13 In addition, South Asia exhibits differences in health service use, health care costs and quality of care compared with high-income countries (HICs).14 Well-characterized prospective epidemiological cohorts help study the natural history of diseases and the evolution of care in the region. This can advance the knowledge and science of cardiometabolic diseases and provide the infrastructure for interdisciplinary and dynamic scientific explorations.15 The Center for cArdiometabolic Risk Reduction in South Asia (CARRS) is a population-based representative sociodemographically diverse cohort of 30 874 adults with prospective follow-up in three major cities in South Asia—Chennai and Delhi in India and Karachi in Pakistan.16 The cohort was representatively drawn from the adult populations aged 20 and older in Delhi (North India, population 20 million), Chennai (South India, population 8 million)17 and Karachi (Pakistan, population 16 million),18 three megacities with a cumulative population of 44 million individuals. We used a population-based, multistage, cluster random sampling design based on local administrative boundaries to recruit adult men and women to be representative of each city. In 2010–12, CARRS-1 was recruited as a probability sample of n = 16 287 adults aged 20 years and older. In 2014–16, CARRS-2 was established as an independent probability sample of 14 587 newly recruited individuals, using methods identical to CARRS-1. Pregnant women and seriously ill individuals were excluded. Seriously ill individuals included bedridden individuals because of the difficulty in taking anthropometric measurements and future follow-up, as blood and other biological samples were collected in a camp. Wards were the primary sampling units for Chennai and Delhi, and clusters were the primary sampling units for Karachi. In Chennai and Delhi, 20 wards were randomly selected from urban districts. Five Census enumeration blocks (CEBs) were randomly selected from each of the 20 randomly selected wards to get 100 CEBs from Chennai and Delhi. Finally, 20 households were selected per CEB in CARRS-1 (25 households in CARRS-2). In Karachi, 80 clusters were randomly selected and 25 households were randomly selected from each cluster. Two eligible participants, one man and one woman, aged 20 years or older, were selected from each household based on the ‘Kis","journal":"International Journal of Epidemiology","year":2022,"id":240624,"datarank":0.7692746264032494,"base_score":3.8066624897703196,"endowment":3.8066624897703196,"self_citation_contribution":0.5709993734655481,"citation_network_contribution":0.1982752529377013,"self_endowment_contribution":0.5709993734655481,"citer_contribution":0.1982752529377013,"corpus_percentile":73.86091127098321,"corpus_rank":3380,"citation_count":44,"citer_count":14,"citers_with_citation_signal":9,"citers_with_endowment":9,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9138,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":337637,"name":"Shivani A. Patel","orcid":"0000-0003-0082-5857","position":1,"is_corresponding":false},{"id":22946,"name":"Mohammed K. Ali","orcid":"0000-0001-7266-2503","position":2,"is_corresponding":false},{"id":257194,"name":"Deepa Mohan","orcid":null,"position":3,"is_corresponding":false},{"id":868662,"name":"Garima Rautela","orcid":"0000-0002-3773-5903","position":4,"is_corresponding":false},{"id":478824,"name":"Unjali P. Gujral","orcid":"0000-0002-0352-813X","position":5,"is_corresponding":false},{"id":417669,"name":"Roopa Shivashankar","orcid":"0000-0002-4361-9423","position":6,"is_corresponding":false},{"id":344913,"name":"Ranjit Mohan Anjana","orcid":"0000-0002-4843-1374","position":7,"is_corresponding":false},{"id":519592,"name":"Ruby Gupta","orcid":"0000-0002-8487-6004","position":8,"is_corresponding":false},{"id":868663,"name":"Deksha Kapoor","orcid":"0000-0001-9999-4153","position":9,"is_corresponding":false},{"id":417670,"name":"Vamadevan S. Ajay","orcid":"0000-0002-4102-0505","position":10,"is_corresponding":false},{"id":337639,"name":"Sailesh Mohan","orcid":"0000-0003-1853-3596","position":11,"is_corresponding":false},{"id":365392,"name":"Muhammad Masood Kadir","orcid":null,"position":12,"is_corresponding":false},{"id":38951,"name":"Viswanathan Mohan","orcid":"0000-0001-5038-6210","position":13,"is_corresponding":false},{"id":22843,"name":"Nikhil Tandon","orcid":"0000-0003-4604-1986","position":14,"is_corresponding":false},{"id":23230,"name":"Dorairaj Prabhakaran","orcid":"0000-0002-3172-834X","position":15,"is_corresponding":false},{"id":245134,"name":"K.M. Venkat Narayan","orcid":"0000-0001-8621-5405","position":16,"is_corresponding":false},{"id":344911,"name":"Dimple Kondal","orcid":"0000-0002-1417-9510","position":0,"is_corresponding":true}],"reference_count":56,"raw_metadata":null,"created_at":"2026-07-19T00:22:51.435773Z","pmid":"35138386","pmcid":"PMC9749725","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}