Show simple item record

Differential risk factor profile of diabetes and atherosclerosis in rural, sub- urban and urban regions of South India: The KMCH- Non- communicable disease studies

dc.contributor.authorVelmurugan, Ganesan
dc.contributor.authorMohanraj, Sundaresan
dc.contributor.authorDhivakar, Mani
dc.contributor.authorVeerasekar, Ganesh
dc.contributor.authorBrag‐gresham, Jennifer
dc.contributor.authorHe, Kevin
dc.contributor.authorAlexander, Thomas
dc.contributor.authorCherian, Mathew
dc.contributor.authorSaran, Rajiv
dc.contributor.authorPradeep, Thalappil
dc.contributor.authorSwaminathan, Krishnan
dc.date.accessioned2021-06-02T21:05:25Z
dc.date.available2022-07-02 17:05:24en
dc.date.available2021-06-02T21:05:25Z
dc.date.issued2021-06
dc.identifier.citationVelmurugan, Ganesan; Mohanraj, Sundaresan; Dhivakar, Mani; Veerasekar, Ganesh; Brag‐gresham, Jennifer ; He, Kevin; Alexander, Thomas; Cherian, Mathew; Saran, Rajiv; Pradeep, Thalappil; Swaminathan, Krishnan (2021). "Differential risk factor profile of diabetes and atherosclerosis in rural, sub- urban and urban regions of South India: The KMCH- Non- communicable disease studies." Diabetic Medicine (6): n/a-n/a.
dc.identifier.issn0742-3071
dc.identifier.issn1464-5491
dc.identifier.urihttps://hdl.handle.net/2027.42/167761
dc.description.abstractAimsSouth Asia has emerged rapidly as an epicentre of non- communicable diseases (NCDs) specifically diabetes and cardiovascular diseases. The prevalence rate, risk factors and aetiology of NCDs in different socio- demographic settings are not clearly understood. This study was performed to assess the prevalence of diabetes and atherosclerosis and their risk factors in urban, sub- urban and rural communities of South India.MethodsThree communities [Nallampatti (rural), Thadagam (sub- urban) and Kalapatti (urban)] in South India were selected for participation in the KMCH- NCD Studies. Study volunteers were administered a detailed questionnaire, underwent anthropometric measurements, clinical measurements including blood pressure, glycated haemoglobin (HbA1c), non- fasting lipid profile and serum creatinine. Carotid intima- media thickness was measured using B- mode ultrasound. Multiple logistic regression analyses were performed to understand the association of risk factors with diabetes and atherosclerosis.ResultsA total of 2976 native participants, - ¥20 years of age were screened. The prevalence of diabetes was 16%, 26% and 23% respectively in the rural, sub- urban and urban study populations. Association of obesity with diabetes was observed in only urban population while hypertension and dyslipidaemia showed association in both urban and semi- urban populations. Association of diabetes with atherosclerosis was observed in urban and semi- urban populations. Hypertension in semi- urban and obesity and dyslipidaemia in urban population showed association with atherosclerosis.ConclusionsDiabetes and atherosclerosis burden reported in the three different communities were higher than previous reports, especially in rural and sub- urban regions. No traditional risk factor is identified to be associated with prevalence of diabetes and atherosclerosis in rural population. These findings suggest an urgent need for investigation into the role of non- traditional risk factors like environmental or occupational exposures may help to better understand the aetiology of diseases in non- urbanized communities.
dc.publisherIHME
dc.publisherWiley Periodicals, Inc.
dc.subject.otherrural health
dc.subject.otheratherosclerosis
dc.subject.otherdiabetes
dc.subject.othernon- communicable diseases
dc.subject.otherpublic health
dc.subject.otherrisk factors
dc.titleDifferential risk factor profile of diabetes and atherosclerosis in rural, sub- urban and urban regions of South India: The KMCH- Non- communicable disease studies
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167761/1/dme14466_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167761/2/dme14466.pdf
dc.identifier.doi10.1111/dme.14466
dc.identifier.sourceDiabetic Medicine
dc.identifier.citedreferenceCheema A, Adeloye D, Sidhu S, Sridhar D, Chan KY. Urbanization and prevalence of type 2 diabetes in Southern Asia: a systematic analysis. J Glob Health. 2014; 4 ( 1 ): 010404.
dc.identifier.citedreferenceInstitute for Health Metrics and Evaluation (IHME ). Findings from the Global Burden of Disease Study 2017. Seattle, WA: IHME; 2018.
dc.identifier.citedreferenceWorld Health Organization. Global report on Diabetes; 2016.
dc.identifier.citedreferenceInternational Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels, Belgium: International Diabetes Federation, 2019. https://www.diabetesatlas.org
dc.identifier.citedreferenceFall CH. Non- industrialised countries and affluence. Br Med Bull. 2001; 60: 33 - 50.
dc.identifier.citedreferenceEbrahim S, Kinra S, Bowen L, et al. The effect of rural- to- urban migration on obesity and diabetes in India: a cross- sectional study. PLoS Med. 2010; 8 ( 5 ): 10.
dc.identifier.citedreferenceAnjana RM, Pradeepa R, Das AK, et al; ICMR- INDIAB Collaborative Study Group. Physical activity and inactivity patterns in India - results from the ICMR- INDIAB study (Phase- 1) [ICMR- INDIAB- 5]. Int J Behav Nutr Phys Act. 2014; 11 ( 1 ): 26.
dc.identifier.citedreferenceKinra S, Bowen LJ, Lyngdoh T, et al. Sociodemographic patterning of non- communicable disease risk factors in rural India: a cross sectional study. BMJ. 2010; 341.
dc.identifier.citedreferenceJoshi R, Cardona M, Iyengar S, et al. Chronic diseases now a leading cause of death in rural India- mortality data from the Andhra Pradesh Rural Health Initiative. Int J Epidemiol. 2006; 35: 1522 - 1529.
dc.identifier.citedreferenceGajalakshmi V, Peto R. Verbal autopsy of 80,000 adult deaths in Tamilnadu, South India. BMC Public Health. 2004; 4: 47.
dc.identifier.citedreferenceRamachandran A, Snehalatha C, Baskar AD, et al. Temporal changes in prevalence of diabetes and impaired glucose tolerance associated with lifestyle transition occurring in the rural population in India. Diabetologia. 2004; 47: 860 - 865.
dc.identifier.citedreferenceDehghan M, Mente A, Zhang X, et al. Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): a prospective cohort study. Lancet. 2017; 10107: 2050 - 2062.
dc.identifier.citedreferenceAnjana RM, Pradeepa R, Deepa M, et al; ICMR- INDIAB Collaborative Study Group. Prevalence of diabetes and prediabetes (impaired fasting glucose and/or impaired glucose tolerance) in urban and rural India: phase I results of the Indian Council of Medical Research- INdia DIABetes (ICMR- INDIAB) study.
dc.identifier.citedreferenceSwaminathan K, Thangavel G. Pesticides and human diabetes: a pilot project to explore a possible link. Practical Diabetes. 2015; 32 ( 3 ): 111 - 113.
dc.identifier.citedreferenceVelmurugan G, Ramprasath T, Swaminathan K, et al. Gut microbial degradation of organophosphate insecticides- induces glucose intolerance via gluconeogenesis. Genome Biol. 2017; 18: 8.
dc.identifier.citedreferenceSwaminathan K, Veerasekar G, Kuppusamy S, et al. Noncommunicable disease in rural India: are we seriously underestimating the risk? The Nallampatti noncommunicable disease study. Ind J Endocrinol Metab. 2017; 21: 90 - 95.
dc.identifier.citedreferenceVelmurugan G, Swaminathan K, Veerasekar G, et al. Metals in urine in relation to prevalence of pre- diabetes, diabetes and atherosclerosis in rural India. Occup Environ Med. 2018; 75: 661 - 667.
dc.identifier.citedreferenceVelmurugan G, Swaminathan K, Mohanraj S, et al. Association of co- accumulation of arsenic and organophosphate insecticides with diabetes and atherosclerosis in a rural agricultural community: KMCH- NNCD- I study. Acta Diabetol. 2020; https://doi.org/10.1007/s00592- 020- 01516
dc.identifier.citedreferenceSwaminathan K, Sundaram M, Prakash P, Subbiah S. Diabetic ketoacidosis: an uncommon manifestation of pesticide poisoning. Diabetes Care. 2013; 36 ( 1 ): e4.
dc.identifier.citedreferenceGinsberg BH. Factors affecting blood glucose monitoring: sources of errors in measurement. J Diabetes Sci Technol. 2009; 3 ( 4 ): 903 - 913.
dc.identifier.citedreferenceAmerican Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014; 37 ( Suppl 1 ): S81 - S90.
dc.identifier.citedreferenceInternational Expert Committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care. 2009; 32 ( 7 ): 1327 - 1334.
dc.identifier.citedreferenceMohan V, Vijayachandrika V, Gokulakrishnan K, et al. A 1c cut points to define various glucose intolerance groups in Asian Indians. Diabetes Care. 2010; 33 ( 3 ): 515 - 519.
dc.identifier.citedreferenceSkinder BM, Pandit AK, Sheikh AQ, Ganai BA. Brick kilns: Cause of Atmospheric Pollution. J Pollut Eff Cont. 2014; 2 ( 112 ): https://doi.org/10.4172/2375- 4397.1000112
dc.identifier.citedreferenceEze IC, Hemkens LG, Bucher HC, et al. Association between ambient air pollution and diabetes mellitus in Europe and North America: systematic review and meta- analysis. Environ Health Perspect. 2015; 123 ( 5 ): 381 - 389.
dc.identifier.citedreferenceLi C, Fang D, Xu D, et al. Main air pollutants and diabetes- associated mortality: a systematic review and meta- analysis. Eur J Endocrinol. 2014; 171 ( 5 ): R183 - R190.
dc.identifier.citedreferenceRahimi R, Abdollahi M. A review on the mechanisms involved in hyperglycemia induced by organophosphorus pesticides. Pestic Biochem Physiol. 2007; 88 ( 2 ): 115 - 121.
dc.identifier.citedreferenceVelmurugan G, Ramprasath T, Mithieux G, Swaminathan K, Ramasamy S. Gut microbiota, endocrine disrupting chemicals and diabetes epidemic. Trends Endocrinol Metab. 2017; 28: 614 - 628.
dc.identifier.citedreferenceTseng CH. The potential biological mechanisms of arsenic- induced diabetes mellitus. Toxicol Appl Pharmacol. 2004; 197: 67 - 83.
dc.identifier.citedreferenceYang A, Cheng N, Pu H, et al. Occupational metal exposures, smoking and risk of diabetes and prediabetes. Occup Med. 2016; 67: 217 - 223.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.