{"doi":"10.1016/j.ihj.2020.09.015","title":"Prevalence and correlates of metabolic syndrome among rural women in Mysore, India","abstract":"AIMS: Metabolic Syndrome (MetS) is a strong predictor of Coronary Heart Disease (CHD). Studies in urban India have found about one-third of Indians suffer from MetS. Less is known about the prevalence of MetS in rural areas, where 70% of the population reside. This study examined the prevalence of Metabolic Syndrome in a population of rural women in India. METHODS: Data were gathered in a community-based study of 500 rural and tribal women residing in the Mysore district, between the age of 30-59 years. The study used the WHO STEPS approach, in which information on demographics and behavioral risk factors were collected. Along with anthropometric measurements, blood pressure, blood glucose, lipids were measured. A harmonized definition of MetS recommended by International Diabetes Federation Task Force on Epidemiology and Prevention was used in this study. RESULTS: Three out of five study participants were found to have MetS (47.1%, n = 223). Of those, 56.5% met 3 of the 5 criteria, 32.2% met 4 criteria, and 11.2% met all 5 criteria. Among the entire sample, low HDL was the most prevalent criterion (88.4%), followed by elevated glucose (57.9%), elevated triglycerides (49.3%), elevated BP (41.5%), and increased waist circumference (15.3%). In this sample, women with METS were generally older (p < 0.001), housewives (p = 0.001), that consumed salty highly processed foods (p = 0.020) and had low physical activity (p = 0.015). CONCLUSIONS: This study showed a high prevalence of MetS in rural women. There is a compelling need for interventions aimed at reducing CHD risk factors in this population.","journal":"Indian Heart Journal","year":2020,"id":71186,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":18,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6772,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":292441,"name":"Prajakta Adsul","orcid":"0000-0003-2860-4378","position":1,"is_corresponding":false},{"id":376440,"name":"Meredith L. Wilcox","orcid":"0000-0001-6696-4935","position":2,"is_corresponding":false},{"id":364229,"name":"Vijaya Srinivas","orcid":"0000-0001-8050-5938","position":3,"is_corresponding":false},{"id":376441,"name":"Elizabeth Frank","orcid":"0000-0002-1823-6455","position":4,"is_corresponding":false},{"id":377681,"name":"Arun Srinivas","orcid":null,"position":5,"is_corresponding":false},{"id":229056,"name":"Purnima Madhivanan","orcid":"0000-0001-7818-3394","position":6,"is_corresponding":false},{"id":364228,"name":"Karl Krupp","orcid":"0000-0001-7001-9194","position":0,"is_corresponding":true}],"reference_count":37,"raw_metadata":null,"created_at":"2026-07-18T21:43:57.004133Z","pmid":"33357649","pmcid":null,"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":[]}