thesis on diabetes mellitus in india pdf

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• Published: 19 April 2017

Epidemiology

Prevalence of type 2 diabetes and its complications in India and economic costs to the nation

• R Pradeepa 1 &
• V Mohan 1  

European Journal of Clinical Nutrition volume  71 ,  pages 816–824 ( 2017 ) Cite this article

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• Endocrine system and metabolic diseases
• Health care

Diabetes, a major lifestyle disorder, has become a global burden, and the prevalence rates are rising steeply in developing economies. Rapid socioeconomic transition with urbanization and industrialization are the main causes for the global diabetes epidemic. Among developing economies, the highest increase in number of people with diabetes is in China followed by India. In India, the epidemic of diabetes continue to increase and is experiencing a shift in diabetes prevalence from urban to rural areas, the affluent to the less privileged and from older to younger people. Diabetes is a progressive disorder leading to complications, which are broadly divided into small vessel or microvascular disease and large vessel or macrovascular disease. Microvascular complications affect the inner part of the eye—the retina known as diabetic retinopathy, the kidney termed as diabetic nephropathy and the peripheral nerves termed as diabetic neuropathy. The macrovascular complications affect the heart, the brain and the peripheral arteries termed as cardiovascular disease, cerebrovascular disease and peripheral vascular disease, respectively. Given the lifelong expenditure associated with diabetes and its complications, individuals, families and the society are unable to cope with the economic, emotional and social disease burden due to diabetes. The economic burden of diabetes can be reduced by providing universal healthcare coverage, access to affordable medicines and early detection and treatment of the disorder. This emphasizes the need for a multi-prolonged strategy to minimize the burden of diabetes and its complications.

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Predictors of microvascular complications in patients with type 2 diabetes mellitus at regional referral hospitals in the central zone, tanzania: a cross-sectional study.

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International Diabetes Federation IDF Diabetes Atlas, 7 edn. International Diabetes Federation: Brussels, Belgium, 2015.

Anjana RM, Pradeepa R, Deepa M, Datta M, Sudha V, Unnikrishnan R 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. Diabetologia 2011; 54 : 3022–3027.

Article   CAS   PubMed   Google Scholar  

Zabetian A, Sanchez IM, Narayan KM, Hwang CK, Ali MK . Global rural diabetes prevalence: a systematic review and meta-analysis covering 1990-2012. Diabetes Res Clin Pract 2014; 104 : 206–213.

Article   PubMed   Google Scholar  

Rahman S, Rahman T, Ismail AA, Rashid AR . Diabetes-associated macrovasculopathy: pathophysiology and pathogenesis. Diabetes Obes Metab 2007; 9 : 767–780.

Anjana RM, Ali MK, Pradeepa R, Deepa M, Datta M, Unnikrishnan R et al . The need for obtaining accurate nationwide estimates of diabetes prevalence in India - rationale for a national study on diabetes. Indian J Med Res 2011; 133 : 369–380.

CAS   PubMed   PubMed Central   Google Scholar  

International Diabetes Federation. Diabetes Atlas . International Diabetes Federation: Brussels, Belgium, 2000.

Allgot B, Gan D, King H, Lefebvre P, Mbanya JC, Silink M et al Diabetes Atlas . International Diabetes Federation: Brussels, Belgium, 2003.

Google Scholar  

Sicree R, Shaw J, Zimmet P Diabetes and impaired glucose tolerance. In: Gan D (ed). Diabetes Atlas , 3rd edn. International Diabetes Federation: Brussels, Belgium, 2006, pp 15–103.

Unwin N, Whiting D, Gan D, Jacqmain O, Ghyoot G Diabetes Atlas , 4th edn. International Diabetes Federation: Brussels, Belgium, 2009; pp 1–27.

International Diabetes Federation. IDF Diabetes Atlas , 5th edn. International Diabetes Federation: Brussels, Belgium, 2011.

International Diabetes Federation. IDF Diabetes Atlas , 6th edn. International Diabetes Federation: Brussels, Belgium, 2013.

Chakravarthy A . A study of diabetes and its treatment with special reference to Bengalees and their diet. Indian Med Rec 1938; 58 : 65.

Datta SN, Prasad BG, Jain SP . An epidemiological study of diabetes mellitus in defence population in Lucknow Cantonment. J Indian Med Assoc 1973; 61 : 23–27.

CAS   PubMed   Google Scholar  

Deepa M, Grace M, Binukumar B, Pradeepa R, Roopa S, Khan HM et al . CARRS Surveillance Research Group. High burden of prediabetes and diabetes in three large cities in South Asia: The Center for cArdio-metabolic Risk Reduction in South Asia (CARRS) Study. Diabetes Res Clin Pract 2015; 110 : 172–182.

Article   PubMed   PubMed Central   Google Scholar  

Ahuja MMS . Epidemiological studies on diabetes mellitus in India Ahuja MMS (ed) Epidemiology of Diabetes in Developing Countries . Interprint: New Delhi, India, 1979; 29–38.

Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V et al . High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 2001; 44 : 1094–1101.

Sadikot SM, Nigam A, Das S, Bajaj S, Zargar AH, Prasannakumar KM et al . The burden of diabetes and impaired glucose tolerance in India using the WHO 1999 criteria: prevalence of diabetes in India study (PODIS). Diabetes Res Clin Pract 2004; 66 : 301–307.

Mohan V, Mathur P, Deepa R, Deepa M, Shukla DK, Menon GR et al . Urban rural differences in prevalence of self-reported diabetes in India–the WHO-ICMR Indian NCD risk factor surveillance. Diabetes Res Clin Pract 2008; 80 : 159–168.

Ajay VS, D Prabhakaran D, Jeemon P, Thankappan KR, Mohan V, Ramakrishnan L et al . Prevalence and determinants of diabetes mellitus in the Indian industrial population. Diabet Med 2008; 25 : 1187–1194.

Anjana RM, Pradeepa R, Deepa M, Datta M, Sudha V, Unnikrishnan R et al . The Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study: methodological details. J Diabetes Sci Technol 2011; 5 : 906–914.

Mohan V, Deepa M, Deepa R, Shanthirani CS, Farooq S, Ganesan A et al . Secular trends in the prevalence of diabetes and impaired glucose tolerance in urban South India—the Chennai Urban Rural Epidemiology Study (CURES-17). Diabetologia 2006; 49 : 1175–1178.

Xu Y, Wang L, He J, Bi Y, Li M, Wang T et al . 2010 China Noncommunicable Disease Surveillance Group. Prevalence and control of diabetes in Chinese adults. JAMA 2013; 310 : 948–959.

Chowdhury MA, Uddin MJ, Khan HM, Haque MR . Type 2 diabetes and its correlates among adults in Bangladesh: a population based study. BMC Public Health 2015; 15 : 1070.

Article   PubMed   PubMed Central   CAS   Google Scholar  

Katulanda P, Constantine GR, Mahesh JG, Sheriff R, Seneviratne RD, Wijeratne S et al . Prevalence and projections of diabetes and pre-diabetes in adults in Sri Lanka–Sri Lanka Diabetes, Cardiovascular Study (SLDCS). Diabet Med 2008; 25 : 1062–1069.

Mohan V, Deepa M, Anjana RM, Lanthorn H, Deepa R . Incidence of diabetes and pre-diabetes in a selected urban south Indian population (CUPS-19). J Assoc Physicians India 2008; 56 : 152–157.

Anjana RM, Shanthi Rani CS, Deepa M, Pradeepa R, Sudha V, Divya Nair H et al . Incidence of diabetes and prediabetes and predictors of progression among Asian Indians: 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES). Diabetes Care 2015; 38 : 1441–1448.

Deshpande AD, Harris-Hayes M, Schootman M . Epidemiology of diabetes and diabetes-related complications. Phys Ther 2008; 88 : 1254–1264.

Rema M, Ponnaiya M, Mohan V . Prevalence of retinopathy in non-insulin dependent diabetes mellitus at a diabetes centre in Southern India. Diabetes Res Clin Pract 1996; 34 : 29–36.

Pradeepa R, Prabu AK, Jebarani S, Subhashini S, Mohan V . Use of a large diabetes electronic medical record system in India: clinical and research applications. J Diabetes Sci Technol 2011; 5 : 543–552.

Dandona L, Dandona R, Naduvilath TJ, McCarty CA, Rao GN . Population based assessment of diabetic retinopathy in an urban population in southern India. Br J Ophthalmol 1999; 83 : 937–940.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Narendran V, John RK, Raghuram A, Ravindran RD, Nirmalam PK, Thulasiraj RD . Diabetic retinopathy among self reported diabetes in southern India: a population based assessment. Br J Ophthalmol 2002; 86 : 1014–1018.

Rema M, Premkumar S, Anitha B, Deepa R, Pradeepa R, Mohan V . Prevalence of diabetic retinopathy in urban India: The Chennai Urban Rural Epidemiology Study (CURES) Eye Study - 1. Invest Ophthal Vis Sci 2005; 46 : 2328–2333.

Raman R, Rani PK, Reddi Rachepalle S, Gnanamoorthy P, Uthra S, Kumaramanickavel G et al . Prevalence of diabetic retinopathy in India Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study report 2. Ophthalmology 2009; 116 : 311–318.

Sunita M, Desai S, Vinay P, Moolani S, Rai N, Deepen S et al . Aditya Jyot-Diabetic Retinopathy in Urban Mumbai Slums Study (AJ-DRUMSS): study design and methodology - report 1. Ophthalmic Epidemiol 2014; 21 : 51–60.

Namperumalsamy P, Kim R, Vignesh TP, Nithya N, Royes J, Gijo T et al . Prevalence and risk factors for diabetic retinopathy: a population-based assessment from Theni district, south India. Br J Ophthalmol 2009; 93 : 429–434.

Rani PK, Raman R, Chandrakantan A, Pal SS, Perumal GM, Sharma T . Risk factors for diabetic retinopathy in self-reported rural population with diabetes. J Postgrad Med 2009; 55 : 92–96.

Vaz NC, Ferreira A, Kulkarni M, Vaz FS, Pinto N . Prevalence of diabetic complications in rural Goa, India. Indian J Community Med 2011; 36 : 283–289.

Mohan V, Deepa M, Pradeepa R, Prathiba V, Datta M, Sethuraman R et al . Prevention of diabetes in rural India with a telemedicine intervention. J Diabetes Sci Technol 2012; 6 : 1355–1364.

Jonas JB, Nangia V, Khare A, Matin A, Bhojwani K, Kulkarni M et al . Prevalence and associated factors of diabetic retinopathy in rural central India. Diabetes Care 2013; 36 : e69.

Raman R, Ganesan S, Pal SS, Kulothungan V, Sharma T . Prevalence and risk factors for diabetic retinopathy in rural India. Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetic Study III (SN-DREAMS III), report no 2. BMJ Open Diabetes Res Care 2014; 2 : e000005.

Tanuja A, Guruprasad BS, Prashanth K, Prasad I . Prevalence and risk factors of diabetic retinopathy in a rural population of south India. Int J Diabetes Dev Ctries 2015; 35 : 356–361.

Article   Google Scholar  

Moss SE, Klein R, Kessler SD, Richie KA . Comparison between ophthalmoscopy and fundus photography in determining severity of diabetic retinopathy. Ophthalmology 1985; 92 : 62.

Liu Y, Song Y, Tao L, Qiu W, Lv H, Jiang X et al . Prevalence of diabetic retinopathy among 13473 patients with diabetes mellitus in China: a cross-sectional epidemiological survey in six provinces. BMJ Open 2017; 7 : e013199.

Wong TY, Cheung N, Tay WT, Wang JJ, Aung T, Saw SM et al . Prevalence and risk factors for diabetic retinopathy: the Singapore Malay Eye Study. Ophthalmology 2008; 115 : 1869–1875.

Katulanda P, Ranasinghe P, Jayawardena R . Prevalence of retinopathy among adults with self-reported diabetes mellitus: the Sri Lanka diabetes and Cardiovascular Study. BMC Ophthalmol 2014; 14 : 100.

Jee D, Lee WK, Kang S . Prevalence and risk factors for diabetic retinopathy: the Korea National Health and Nutrition Examination Survey 2008–2011. Invest Ophthalmol Vis Sci 2013; 54 : 6827–6833.

Rema M, Pradeepa R . Diabetic retinopathy: an Indian perspective. Indian J Med Res 2007; 125 : 297–310.

Parving HH, Mauer M, Ritz E . Diabetic nephropathy. In: Brenner BM (ed) Brenner & Rector’s The Kidney , 7th edn. Vol. II, Sauders: Philadelphia, 2004; 1777–1818.

Gupta DK, Verma LK, Khosla PK, Dash SC . The prevalence of microalbuminuria in diabetes: a study from north India. Diabetes Res Clin Pract 1991; 12 : 125–128.

Kanakamani J, Ammini AC, Gupta N, Dwivedi SN . Prevalence of microalbuminuria among patients with type 2 diabetes mellitus—a hospital-based study from north India. Diabetes Technol Ther 2010; 12 : 161–166.

Dadhania BP, Aravat AH, Dhruva GA . Study of microalbuminuria in diabetes type 2 patients as a marker of morbidity (a study of 100 cases in Rajkot city). IJBAR 2012; 03 : 763–766.

Viswanathan V, Tilak P, Kumpatla S . Risk factors associated with the development of overt nephropathy in type 2 diabetes patients: a 12 years observational study. Indian J Med Res. 2012; 136 : 46–53.

John L, Sundar Rao PSS, Kanagasabhapathy AS . Prevalence of diabetic nephropathy in non insulin dependant diabetes mellitus. Indian J Med Res 1991; 94 : 24–29.

Yajnik CS, Naik SS, Raut KN, Khade AD, Bhat DS, Nagarkar VD et al . Urinary albumin excretion rate (AER) in newly-diagnosed type 2 Indian diabetic patients is associated with central obesity and hyperglycaemia. Diabetes Res Clin Pract 1992; 17 : 55–60.

Varghese A, Deepa R, Rema M, Mohan V . Prevalence of microalbuminuria in Type 2 diabetes mellitus at a diabetes centre in southern India. Postgrad Med J 2001; 77 : 399–402.

Chowta NK, Pant P, Chowta MN . Microalbuminuria in diabetes mellitus: Association with age, sex, weight, and creatinine clearance. Indian J Nephrol 2009; 19 : 53–56.

Parchwani D, Singh SP . Microalbuminuria in diabetic patients: prevalence and putative risk factors. Natl J Commun Med 2011; 2 : 126–129.

Agarwal RP, Ola V, Bishnoi P, Gothwal S, Sirohi P, Agrawal R . Prevalence of micro and macrovascular complications and their risk factors in type-2 diabetes mellitus. J Assoc Physicians India 2014; 62 : 504–508.

Unnikrishnan RI, Rema M, Pradeepa R, Deepa M, Shanthirani CS, Deepa R et al . Prevalence and risk factors of diabetic nephropathy in an urban south Indian population: the Chennai Urban Rural Epidemiology Study (CURES 45). Diabetes Care 2007; 30 : 2019–2024.

Ambayiram AV, Kalyani P, Felix AJW, Govindarajan PK . Prevalence of microalbuminuria among type II diabetes mellitus patients in urban Chidambaram. Saudi J Med 2016; 1 : 57–62.

Mather HM, Chaturvedi N, Kehely AM . Comparison of prevalence and risk factors for microalbuminuria in South Asians and Europeans with type 2 diabetes mellitus. Diabet Med 1998; 15 : 672–677.

Klein R, Klein BE, Moss SE . Prevalence of microalbuminuria in older-onset diabetes. Diabetes Care 16 : 1325–1330, 1993.

Ramachandran A, Snehalatha C, Satyavani K, Latha E, Sasikala R, Vijay V . Prevalence of vascular complications and their risk factors in type 2 diabetes. J Assoc Physicians India 1999; 47 : 1152–1156.

Ashok S, Ramu M, Deepa R, Mohan V . Prevalence of. neuropathy in type 2 diabetic patients attending a diabetes centre in south India. J Assoc Physicians India 2002; 50 : 546–550.

Dutta A, Naorem S, Singh P, Wangjam K . Prevalence of peripheral neuropathy in newly diagnosed type 2 diabetics. Int J Diabetes Dev Ctries 2005; 25 : 30–33.

Viswanathan V, Thomas N, Tandon N, Asirvatham A, Rajasekar S, Ramachandran A et al . Profile of diabetic foot complications and its associated complications - a multicentric study from India. J Assoc Physicians India 2005; 53 : 933–936.

Chanda A, Ayyar V, Idiculla JM, Bantwal G . Perception of foot problems among diabetic patients: A cross sectional study. Int J Diab Dev Ctries 2006; 26 : 77–80.

Pawde PP, Thampi RR, Renish RK, Resmi RU, Vivek MR . Prevalence and risk factors of diabetic peripheral neuropathy among type-2 diabetic patients presenting to SMIMS hospital, Kulasekharam, Kanyakumari district, Tamil Nadu, India. Int J Med Sci Public Health 2016; 2 : 73–76.

Bansal D, Gudala K, Muthyala H, Esam H, Nayakallu R, Bhansali A . Prevalence and risk factors of development of peripheral diabetic neuropathy in type 2 diabetes mellitus in a tertiary care setting. J Diabetes Investig 2014; 5 : 714–721.

Gill HK, Yadav SB, Ramesh V, Bhatia E . A prospective study of prevalence and association of peripheral neuropathy in Indian patients with newly diagnosed type 2 diabetes mellitus. J Postgrad Med 2014; 60 : 270–275.

D’Souza M, Kulkarni V, Bhaskaran U, Ahmed H, Naimish H, Prakash A et al . Diabetic peripheral neuropathy and its determinants among patients attending a tertiary health care centre in Mangalore, India. J Public Health Res 2015; 4 : 450–454.

Rai OK, Mishra V, Chandra R, Saxena SK, Mangal BD . Diabetic peripheral neuropathy and its metabolic determinants in a north Indian population. NJIRM 2016; 7 : 1–4.

CAS   Google Scholar  

Pradeepa R, Rema M, Vignesh J, Deepa M, Deepa R, Mohan V . Prevalence and risk factors for diabetic neuropathy in an urban south Indian population: the Chennai Urban Rural Epidemiology Study (CURES-55). Diabet Med 2008; 25 : 407–412.

Nagaraj C, Ramakuri M, Konapur KS . Burden of foot problems in diabetic subjects – a community-based study among urban poor in Bangalore, India. J Diabetic Foot Complic 2014; 6 : 60–66.

Meigs JB . Epidemiology of type 2 diabetes and cardiovascular disease: translation from population to prevention: the Kelly West award lecture 2009. Diabetes Care 2010; 33 : 1865–1871.

Joshi P, Islam S, Pais P, Reddy S, Dorairaj P, Kazmi K et al . Risk factors for early myocardial infarction in South Asians compared with individuals in other countries. JAMA 2007; 297 : 286–294.

Mohan V, Premalatha G, Sastry NG . Ischaemic heart disease in South Indian NIDDM patients – a clinic based study on 6597 NIDDM patients. Int J Diabetes Dev Ctries 1995; 15 : 64–67.

Agarwal AK, Singh M, Arya V, Garg U, Singh VP, Jain V . Prevalence of peripheral arterial disease in type 2 diabetes mellitus and its correlation with coronary artery disease and its risk factors. J Assoc Physicians India 2012; 60 : 28–32.

Mohan V, Deepa R, Shanthirani S, Premalatha G . Prevalence of coronary artery disease and its relationship to lipids in a selected population in South India – The Chennai Urban population Study (CUPS No. 5). J Amer Coll Cardiol 2001; 38 : 682–687.

Article   CAS   Google Scholar  

Mohan V, Ravikumar R, ShanthiRani S, Deepa R . Intimal medial thickness of the carotid artery in south Indian diabetic and non diabetic subjects: the Chennai Urban Population Study (CUPS). Diabetologia 2000; 43 : 494–499.

Mohan V, Premalatha G, Shastry NG . Peripheral vascular disease in non-insulin dependent diabetes mellitus in South India. Diabetes Res Clin Pract 1995; 27 : 235–240.

Pendsey S . Peripheral vascular disease (PVD) in diabetics: Indian scenario. Int J Diabetes Dev Ctries 1998; 18 : 31–33.

Eshcol J, Jebarani S, Anjana RM, Mohan V, Pradeepa R . Prevalence, incidence and progression of peripheral arterial disease in Asian Indian type 2 diabetic patients. J Diabetes Complicat 2014; 28 : 627–631.

Premalatha G, Shanthirani S, Deepa R, Markovitz J, Mohan V . Prevalence and risk factors of peripheral vascular disease in a selected South Indian population. The Chennai Urban Population Study (CUPS). Diabetes Care 2000; 23 : 1295–1300.

Pradeepa R, Chella S, Surendar J, Indulekha K, Anjana RM, Mohan V . Prevalence of peripheral vascular disease and its association with carotid intima-media thickness and arterial stiffness in type 2 diabetes: the Chennai urban rural epidemiology study (CURES 111). Diab Vasc Dis Res 2014; 11 : 190–200.

Biller J, Love BB . Diabetes and stroke. Med Clin North Am 1993; 77 : 95–110.

Fernandes M, Keerthiraj B, Mahale AR, Kumar A, Dudekula A . Evaluation of carotid arteries in stroke patients using color Doppler sonography: A prospective study conducted in a tertiary care hospital in South India. Int J Appl Basic Med Res 2016; 6 : 38–44.

International Diabetes Federation IDF Diabetes Atlas, 5th edn. International Diabetes Federation: Brussels, Belgium, 2012. Available at: http://www.indiaenvironmentportal.org.in/files/file/diabetes%20atlas%202012.pdf .

Rayappa PH, Raju KNM, Kapur A, Stefan B, Camilla S, Dilip kumar KM . Economic cost of diabetes care: the Bangalore urban district diabetes study. Int J Diabetes Dev Ctries 1999; 19 : 83.

Shobhana R, Rama Rao P, Lavanya A, Williams R, Vijay V, Ramachandran A . Expenditure on health care incurred by diabetic subjects in a developing country – a study from southern India. Diab Res Clin Pract 2000; 48 : 37–72.

Shobhana R, Rama Rao P, Lavanya A, Williams R, Padma C, Vijay V et al . Costs incurred by families having Type 1 diabetes in a developing country - a study from Southern India. Diabetes Res Clin Pract 2002; 55 : 45–48.

Kapur A, Bjork S, Nair J, Kelkar S, Ramachandran A . Socioeconomic determinants of the cost of diabetes in India. Diabetes Voice 2004; 43 : 18–21.

Grover S, Avasthi A, Bhansali A, Chakrabarti S, Kulhara P . Cost of ambulatory care of diabetes mellitus: a study from north India. Postgrad Med J 2005; 81 : 391–395.

Bjork S, The economic burden of diabetes in India: results from a national survey. Forum 9. National Survey: Mumbai, 2005.

Ramachandran A, Shobhana R, Snehalatha C, Augustine C, Murugesan N, Viswanathan V et al . Increasing expenditure on health care incurred by diabetic subjects in a developing country. Diabetes Care 2007; 30 : 252–256.

Kumar A, Nagpal J, Bhartia A . Direct cost of ambulatory care of type 2 diabetes in the middle and high income group populace of Delhi: The DEDICOM survey. J Assoc Physicians India 2008; 56 : 667–674.

Tharkar S, Satyavani K, Viswanathan V . Cost of medical care among type 2 diabetic patients with a co-morbid condition-Hypertension in India. Diabetes Res Clin Pract 2009; 83 : 263–267.

Tharkar S, Devarajan A, Kumpatla S, Viswanathan V . The socioeconomics of diabetes from a developing country: a population based cost of illness study. Diabetes Res Clin Pract 2010; 89 : 334–340.

Kumpatla S, Kothandan H, Tharkar S, Viswanathan V . The costs of treating long-term diabetic complications in a developing country: a study from India. J Assoc Physicians India 2013; 61 : 102–109.

PubMed   Google Scholar  

Sharma KM, Ranjani H, Zabetian A, Datta M, Deepa M, Anand Moses CR et al . Excess cost burden of diabetes in Southern India: a clinic-based, comparative cost-of-illness study. Global Health Epidemiol Genomics 2016; 1 : e8.

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Pradeepa, R., Mohan, V. Prevalence of type 2 diabetes and its complications in India and economic costs to the nation. Eur J Clin Nutr 71 , 816–824 (2017). https://doi.org/10.1038/ejcn.2017.40

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DOI : https://doi.org/10.1038/ejcn.2017.40

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Epidemiology of type 2 diabetes in India

Rajendra pradeepa.

Madras Diabetes Research Foundation and Dr. Mohan's Diabetes Specialities Centre, IDF Centre of Excellence in Diabetes Care and ICMR Centre for Advanced Research on Diabetes, Chennai, Tamil Nadu, India

Viswanathan Mohan

The burden of diabetes is high and increasing globally, and in developing economies like India, mainly fueled by the increasing prevalence of overweight/obesity and unhealthy lifestyles. The estimates in 2019 showed that 77 million individuals had diabetes in India, which is expected to rise to over 134 million by 2045. Approximately 57% of these individuals remain undiagnosed. Type 2 diabetes, which accounts for majority of the cases, can lead to multiorgan complications, broadly divided into microvascular and macrovascular complications. These complications are a significant cause for increased premature morbidity and mortality among individuals with diabetes, leading to reduced life expectancy and financial and other costs of diabetes leading to profound economic burden on the Indian health care system. The risk for diabetes is largely influence by ethnicity, age, obesity and physical inactivity, unhealthy diet, and behavioral habits in addition to genetics and family history. Good control of blood sugar blood pressure and blood lipid levels can prevent and/or delay the onset of diabetes complications. The prevention and management of diabetes and associated complications is a huge challenge in India due to several issues and barriers, including lack of multisectoral approach, surveillance data, awareness regarding diabetes, its risk factors and complications, access to health care settings, access to affordable medicines, etc. Thus, effective health promotion and primary prevention, at both, individual and population levels are the need of the hour to curb the diabetes epidemic and reduce diabetes-related complications in India.

Diabetes is one of the largest global health emergencies of this century, ranking among the 10 leading causes of mortality together with cardiovascular disease (CVD), respiratory disease, and cancer.[ 1 , 2 ] According to the World Health Organization (WHO), noncommunicable diseases (NCDs) accounted for 74% of deaths globally in 2019, of which, diabetes resulted in 1.6 million deaths, thus becoming the ninth leading cause of death globally.[ 2 ] By the year 2035, nearly 592 million people are predicted to die of diabetes.[ 3 ] Type 2 diabetes, which constitutes 90% of all cases of diabetes, earlier considered to be a disease of the affluent “Western” countries, has now spread globally, and has become a major cause of disability and death affecting even younger age group.[ 1 ] Diabetes has reached epidemic proportions in many developing economies, such as China and India.[ 1 ] According to WHO, the prevalence of diabetes is growing most rapidly in low- and middle-income countries.[ 4 ] The rapid socioeconomic change in conjunction with urbanization and industrialization are the major factors for the global increase in the diabetes epidemic, with other associated risk factors such as population growth, unhealthy eating habits, and a sedentary lifestyle also playing an important role.[ 5 ]

Diabetes is a progressive disorder that leads to serious complications, which are associated with increased costs to the family, community, and healthcare system. Uncontrolled diabetes leads to increased risk of vascular disease and much of the burden of type 2 diabetes is caused by macrovascular (cardiovascular (CV), cerebrovascular, and peripheral artery disease) and microvascular (diabetic retinopathy, nephropathy, and neuropathy) complications.[ 5 , 6 ]

Global Burden of Diabetes

Type 2 diabetes susceptibility varies to a great extent around the globe, with Pacific Islanders, Asian Indians, and Native Americans having a significantly higher risk of developing the disorder. The number of people with type 2 diabetes began to rise globally in the 1990s, and since 2000, the world has seen a dramatic increase in the number of people with diabetes.[ 7 ] According to the International Diabetes Federation (IDF), 8.8% of the adult population have diabetes, with men having slightly higher rates (9.6%) than women (9.0%).[ 1 ] Current global statistics shows that 463 million and 374 million individuals have diabetes and impaired glucose tolerance (IGT), a prediabetic condition. These numbers are estimated to increase to 700 million people with diabetes and 548 million people with IGT by 2045, which represents a 51% increase compared to 2019.[ 1 ]

Among the IDF regions, the Western Pacific has the highest number of people with diabetes (163 million), followed by the South-East Asian region (88 million), Europe (59 million), Middle East and North Africa (55 million), and North America and Caribbean (47.6 million). Currently, the lowest numbers are found in South and Central America (36.1 million) and Africa (19.4 million).[ 1 ] Thus, it is apparent that the affluent regions of Europe and North America are not the only ones dealing with the diabetes epidemic.

According to the IDF in 2019, the top three countries with the highest number of individuals with diabetes are China (116.4 million), India (77.0 million), and the United States of America (31.0 million). This trend is expected to continue in 2030 and 2045, with China (140.5 and 147.2 million) and India (101.0 and 134.2 million) continuing to have the highest burden of diabetes.[ 1 ] This is supported by the Global Burden of Disease Study, which reported that population growth and ageing in the world's largest countries, such as China and India, are driving the absolute increase in the number of people with diabetes.[ 8 ]

According to prevalence estimates by IDF, the diabetes burden is growing faster in low- and middle-income countries (367.8 million) than in high-income countries (95.2 million).[ 1 ] The Global Burden of Disease study conducted in 195 countries and territories provided a detailed overview of the numbers, rates, and rising trends in the diabetes burden between 1990 and 2025.[ 9 ] This study also reported that the low- and middle-income regions had higher burden of diabetes, while the high-income regions had lower burden of diabetes. This study reported that the number of people with incident diabetes increased from 11.3 to 22.9 million between 1990 and 2017 (an increase by 102.9%) and the number of prevalent diabetes increased from 211.2 to 476.0 million (an increase by 129.7%), respectively. Furthermore, modifiable metabolic, environmental, and behavioral factors were found to be the major risk factors for diabetes burden.

Another cause for concern is the high percentage of individuals with undiagnosed diabetes, which is currently more than 50%. This is observed mainly in developing economies due to less developed health care systems. It is estimated that approximately 231.9 million (one in two) of adults with diabetes are undiagnosed worldwide.[ 1 ] Fig. 1 depicts the proportion and number of individuals with undiagnosed diabetes in various IDF regions.[ 1 ] According to reports, nearly 59.7% of people with diabetes in Africa are unaware of their disease (the highest such proportion among all regions), while only 37.8% of people with diabetes in North America and the Caribbean are unaware of their disease (the lowest proportion among all the regions). When compared to other IDF regions, Africa and South and Central America have a lower number of individuals with undiagnosed diabetes (11.6 and 13.3 million, respectively).[ 1 ] According to these estimates, there is an urgent need for improved diabetes screening. They also highlight the importance of identifying undiagnosed diabetes and providing appropriate and timely care as undiagnosed diabetes can have negative consequences such as an increased risk of diabetes related complications, increased healthcare use, and associated costs.[ 10 ]

Proportion and number of individuals with undiagnosed diabetes – International Diabetes Federation (IDF) [ Ref No: 1 ]

Burden of Diabetes in India

Diabetes has steadily increased in India and around the world over the last three decades, with India accounting for a sizable portion of the global burden. India's disease patterns have shown a switch due to an epidemiological transition: thus mortality from communicable, maternal, neonatal, and nutritional diseases (CMNNDs) has decreased significantly, while NCDs and injuries have markedly increased their contribution to overall disease burden and mortality.[ 11 ] In India in 1990, the total disability adjusted life years (DALYs) from CMNNDs were 61%, 30% from NCDs, and 9% from injuries. However, due to major epidemiological transitions in India over the years, total DALYs from CMNNDs have decreased to 33%, while those from NCDs and injuries have increased to 55 and 12%, respectively, in 2016 [ Fig. 2 ]. Across India, the disease burden or DALY rate in 2016 was 4-fold for diabetes, and when looked at the leading individual causes of DALYs in India, most NCDs have risen in rank since 1990, with diabetes showing a dramatic increase, from 35 th place in 1990 to 13 th place in 2016.[ 11 ]

Causes of total deaths in India, 1990 and 2016 (Communicable vs noncommunicable vs injuries) [Ref No: 11 ]

Prevalence of diabetes and trends over time

In India, the burden of diabetes has been increasing steadily since 1990 and leaps and at a faster pace from the year 2000. Fig. 3 shows the increasing trend in diabetes prevalence in India during the past decade in India as per IDF.[ 1 , 12 , 13 , 14 , 15 , 16 ] The prevalence of diabetes in India has risen from 7.1% in 2009 to 8.9% in 2019. Table 1 provides the burden of diabetes in India at a glance. Currently, 25.2 million adults are estimated to have IGT, which is estimated to increase to 35.7 million in the year 2045. India ranks second after China in the global diabetes epidemic with 77 million people with diabetes. Of these, 12.1 million are aged >65 years, which is estimated to increase to 27.5 million in the year 2045. It is also estimated that nearly 57% of adults with diabetes are undiagnosed in India, which is approximately 43.9 million. The mean healthcare expenditure on diabetes per person is 92 US dollars, and total deaths attributable directly to diabetes account for 1 million.

Trends in diabetes prevalence during the past decade in India [Source: Ref 1 , 12 , 13 , 14 , 15 , 16 ]

Burden of diabetes/prediabetes in India (Ref No. 1 )

*USD - US dollars; Source IDF Diabetes Atlas 2019 (Ref No: 1)

The report on the state-level disease burden in India stated that the percent change in diabetes prevalence among all ages in India from 1990 to 2016 was 64.3%, while the age-standardized prevalence was 29.3%.[ 11 ] The India State-Level Disease Burden Initiative Diabetes study collaborators[ 17 ] reported that the prevalence and number of people with diabetes in India increased from 5.5% and 26.0 million in 1990 to 7.7% and 65.0 million in the year 2016. According to this report, Tamil Nadu had the highest prevalence in 2016, followed by Kerala, Delhi, Punjab, Goa, and Karnataka.

Diabetes is becoming more prevalent in India, based on the data obtained from cross-sectional surveys conducted in various parts of the country.[ 18 ] The first study was conducted in Mumbai in 1963 among 18,243 individuals, and the prevalence of diabetes was found to be 1.5% based on urine analysis.[ 19 ] There have been a few national studies on the prevalence of diabetes. The national prevalence of diabetes was reported to be 2.1% in the multicenter ICMR survey conducted between 1972 and 1975 in Ahmedabad, Calcutta, Cuttack, Delhi, Poona, and Trivandrum, as well as neighboring rural areas.[ 20 ] In 2001, the National Urban Diabetes Survey conducted in India's six major cities reported an age-standardized prevalence of 12.1%,[ 21 ] while the Prevalence of Diabetes in India Study, conducted in 40 urban and 37 small towns and rural areas across India in 2004, found that the prevalence of diabetes to be 5.9 and 2.7%, respectively.[ 22 ] The WHO-ICMR NCD Risk Factor Surveillance Study, conducted between 2003 and 2005 in urban and rural areas of six different states, reported a 4.5% prevalence of self-reported diabetes.[ 23 ]

In the Indian Council of Medical Research–India DIABetes study, the largest nationally representative epidemiological survey conducted in India on diabetes and prediabetes, the data from 15 states/UT of the country [ Table 2 ] showed that the prevalence of diabetes ranged from 3.5 to 8.7% in rural to 5.8 to 15.5% in urban areas and the prevalence varied from 4.3% in Bihar to 13.6% in Chandigarh.[ 24 , 25 ] The prevalence of diabetes was higher in urban areas (11.2%) compared to rural areas (5.2%). The prevalence of prediabetes ranged from 5.8 to 14.7% in rural to 7.2 to 16.2% in urban areas. The prevalence of prediabetes exceeded that of diabetes in most states. This indicates the presence of a large number of individuals who may develop type 2 diabetes in the near future. There is also evidence that Asian Indians progress more rapidly through the prediabetes stage as compared to people of other ethnic groups.[ 25 , 26 ] The prevalence of diabetes was higher among states with higher per capita GDP and among individuals belonging to the higher SES. This study demonstrates that there is clear evidence of an epidemiological transition, with a higher prevalence of diabetes in low socioeconomic status of urban areas in more economically developed states.[ 25 ]

Weighted prevalence of diabetes and prediabetes in 15 states/Union territory of India - the ICMR INDIAB Study [Ref Nos: 24 , 25 ]

The National Family Health Survey, four survey[ 27 ] conducted in 15 Indian states/union territories during the year 2014–2015, reported that Andaman and Nicobar Islands had the highest prevalence of diabetes (26 and 14.5% among men and women, respectively), while Haryana had the lowest prevalence of diabetes (8.2%) for men and Bihar (6.1%) for women. The prevalence was higher in urban than in rural areas. The recent Secular Trends in Diabetes in India study which assessed the change in diabetes prevalence between 2006 and 2016 in urban and rural areas of Tamil Nadu reported that the prevalence of diabetes increased from 18.6% in 2006 to 21.9 in 2016 in the city, while in the smaller towns, it increased from 16.4 to 20.3, and in the periurban villages, from 9.2 to 13.4, respectively.[ 28 ]

Data from the population-based representative Center for Cardio-metabolic Risk Reduction in South Asia (CARRS) Study reports that 6 out of 10 adults in South Asian cities have either diabetes or prediabetes.[ 29 ] In Chennai, 22.8%, and in Delhi, 25.2% of the population was estimated to have diabetes. This study also reported a diabetes prevalence of 16.3% in Karachi, Pakistan, which is lower than the two cities in India. In the CARRS cohort, the lifetime diabetes risk for 20-year-old men was 55.5% compared to 64.6% for women and was high among obese women (86.0%) and men (86.9%). With increasing age (at age 60 years), the lifetime risk of diabetes decreased to 37.7% for women and 27.5% for men.[ 30 ] Recent studies contradict previous findings that migrant Indians had higher prevalence rates of type 2 diabetes than their counterparts in India. The prevalence of type 2 diabetes was reported to be higher in Asian Indians living in Chennai (38%) compared to those residing in San Francisco and Chicago, US (24%).[ 31 ] These findings highlight the fact that India's current rapid economic and nutritional transitions increase the risk of type 2 diabetes, and that the “diabetogenic” environment in India is now as bad, if not worse, as in the United States.

Incidence of diabetes

Apart to from the rising prevalence of diabetes in India, the incidence of diabetes are also rising steadily, with a fast transition from euglycemia to prediabetes and diabetes. In India, very few longitudinal studies have been conducted to assess the incidence of diabetes and prediabetes. In the Chennai Urban Population Study cohort, diabetes and prediabetes incidence rates were reported to be 20.2 and 13.1 per 1000 person-years, respectively,[ 32 ] while the follow-up study conducted in the Chennai Urban Rural Epidemiology Study (CURES) cohort reported the incidence rates of diabetes, prediabetes, and any dysglycemia to be 22.2, 29.5, and 51.7 per 1000 person-years, respectively.[ 33 ] The conversion rate to diabetes was reported to be 19.4% among those with normal glucose tolerance and 58.9% among those with prediabetes. Diabetes incidence was reported to be 78.9 per 1000 person-years among those with prediabetes.[ 33 ]

In Kerala, participants of the Study of Life Style Diseases in Central Kerala were followed up over a 10-year period from two semiurban wards of Venmony Panchayat of Alappuzha district. The incidence rate of type 2 diabetes and impaired fasting glucose (IFG) were 24.5 per 1000 person-years and 45.01 per 1000 person-years, respectively. During the follow-up period, nearly 60% of participants with baseline IFG converted to type 2 diabetes.[ 34 ]

In another follow-up study conducted in rural areas of Puducherry, the incidence rate of diabetes was reported to be 21.5 per 1,000 person-years. The incidence rate doubled among males (28.7 per 1000 person-years) compared with females (14.6 per 1000 person-years).[ 35 ]

Morbidity and mortality

Diabetes is well known for its systemic impact on a wide range of diabetes-related complications, including macrovascular and microvascular complications and death among the most feared outcomes. In addition, recently diabetes is also being linked to nontraditional complications such as mental health, cancer, disability, and liver disease.[ 36 ] Diabetic retinopathy is recognized as the most specific complication of diabetes and has been used to guide diabetes diagnostic thresholds. The prevalence of diabetic retinopathy has been estimated to be 17.6% among adults with diabetes in urban South India.[ 37 ] Spectrum of eye disorders in diabetes in India report, pan-India facility-based study, concluded that diabetic retinopathy was prevalent in one-third and sight-threatening diabetic retinopathy in one-fifth of people with type 2 diabetes presenting at 14 eye-care facilities.[ 38 ] The CURES study conducted in urban Southern India reported lower prevalences of retinopathy, nephropathy, neuropathy, and peripheral vascular disease and higher prevalence of coronary artery disease (CAD) compared to those reported for Western populations.[ 37 , 39 , 40 , 41 , 42 ] Data from rural areas indicate that the burden of complications is comparable, if not higher, in rural areas of South India than in urban areas.[ 43 ] The relatively high prevalence of diabetic complications in developing economies like India could be due to delay in diagnosis of diabetes as well as complications, coexisting illness, inadequate health care systems, and high drug cost, particularly insulin leading to poor control of diabetes.

Diabetes, along with its complications, is a leading cause of mortality. The South East Asian region has the second highest number of deaths attributable to diabetes in adults among the IDF Regions, with 1.2 million deaths in 2019, with India contributing the lion's share with more than 1 million estimated deaths accountable to diabetes and related complications.[ 1 ] The Prospective Urban Rural Epidemiology study which compared CV events, all-cause mortality, and CV mortality rates among 143,567 adults with and without diabetes in 21 countries including India with different income levels reported that CVD rates, all-cause mortality, and CV mortality were markedly higher among those with diabetes in low-income countries compared with middle- and high-income countries.[ 44 ] The India State-Level Disease Burden Initiative Diabetes study reported that diabetes contributed to 3.1% of all deaths in India, with an increase in death rates due to diabetes from 1990 to 2016 by 131%.[ 17 ]

There are as yet no large-scale Indian studies on mortality in patients with type 2 diabetes, and most available studies are from clinical settings and therefore have shown different results. In a retrospective study from Srinagar[ 45 ] of 234,776 inpatient admissions, 16,690 died, of whom 4.4% had diabetes. Of the top five causes of death, infections were reported by 41%, chronic renal failure by 33.6%, CAD by 16.9%, cerebrovascular disease by 13.2%, and chronic obstructive pulmonary disease by 6.9%. A follow-up of the CURES cohort reported overall mortality rate to be nearly 4-fold higher in people with diabetes compared to those without diabetes (27.9 per 1000 person-years vs. 8.0 per 1000 person-years). The study also illustrated that ischemic heart disease and diabetes had the highest population-attributable risk for all-cause mortality in the entire study cohort.[ 46 ]

Risk Factors

The etiology of diabetes is believed to be multifactorial. Many individual-level nonmodifiable risk factors like genetic, age, ethnicity, and family history have been prospectively associated with type 2 diabetes, but the increases in prevalence in most populations have probably been driven by a modifiable risk factors including sedentary lifestyle and/or lack of exercise, increasing prevalence of overweight/obesity, unhealthy diets (increased intake of refined grains, fat, sugar, and sweetened beverages and decreased intake of fruits and vegetables) and habits (smoking and alcohol abuse), exposure to environmental pollutants, altered intrauterine environment and mental health (stress/depression), short sleep duration, and the built environment [ Fig. 4 ].

Risk factors for type 2 diabetes

According to the India state-level disease burden report,[ 47 ] in 1990, a tenth of the total disease burden in India was caused by a cluster of risk factors that included unhealthy diet, being overweight/obese, high blood pressure, blood sugar, and cholesterol, all of which contributed to ischemic heart disease, stroke, and diabetes, which increased to a quarter of the total disease burden in India in 2016. Tobacco use, which was accountable for 6% of the total disease burden in India in 2016, is another significant contributor to CVD and diabetes, as well as cancer and some other diseases.[ 47 ] The Global Burden of Disease Study 2016, reported obesity, low-dietary intake of fruits, nuts and seeds, and whole grains, and tobacco use to be the most important risk factors for DALYs and deaths due to diabetes.[ 48 ]

Strategies to Tackle the Epidemic of Diabetes in India

The rising rates of prediabetes, diabetes, and associated complications in urban as well as in rural areas and among the young in India are of great concern. Addressing health issues related to diabetes in India, which is the second-most populous country and has a large and diverse population, poses many challenges. The specific challenges in diabetes prevention/management are (i) lack of strong national partnerships for multisectoral actions, (ii) lack of availability of robust surveillance and research data on diabetes, (iii) abysmally low disease awareness among the public, (iv) lack of access to basic prevention/management of diabetes in the primary health care setting, which includes access to affordable medicines leading to premature deaths, (v) disproportionate fund allocation for diabetes programs, (vi) difficulties in engaging the industry and private sector, (vii) limited human resources, and (viii) inadequate community mobilization and weak coordination among civil societies and between the civil societies and government agencies for diabetes.

Tackling diabetes calls for a fundamental change, from addressing each risk factor separately to collectively addressing a cluster of risk factors in an integrated manner, and from using a biomedical approach to a public health approach. Thus, when planning prevention/control programs, a multifaceted approach is essential for success. Diabetes prevention/control strategies include (i) reduction in exposure to lifestyle risk factors through health promotion and primary prevention, (ii) early detection and timely treatment, and (iii) surveillance to monitor trends in diabetes and associated risk factors. High levels of commitment and multisectoral actions are needed to reduce the growing burden of diabetes in India. Some of the policies that may help to slow down the epidemic of diabetes in India include (i) national food policies targeting availability and accessibility of healthy and nutritious foods, ensuring that the food industry strictly complies with norms of food safety and standards and supporting production and distribution of healthy foods (whole grains, fruit, vegetables, legumes, and nuts), (ii) health policies to reduce harmful behaviors such as smoking, alcohol misuse, use of trans fat, and consumption of junk foods and increase physical activity by the creation of amenities such as public spaces (e.g., parks) for walking, cycling, etc., (iii) prevention policies such as health information and communication to improve population awareness, and (iv) policies to reduce the cost of essential drugs and ensuring reasonable access to care. All these efforts need a healthy collaboration between health, information, education, and agriculture ministries to create awareness and to facilitate a healthy lifestyle among the Indian population.

Diabetes has already become a leading threat to public health globally and the picture becomes grimmer for the low- and middle-income countries like India, where the burden has risen significantly in recent decades and will continue to rise in the coming decades. This could have a great influence on morbidity and mortality associated with diabetes and, thus, on the overall healthcare expenditure in India. To curb the epidemic of diabetes and its associated complications, there is a need for a multipronged strategy involving early diagnosis of diabetes, screening for its complications, and offering optimal therapy at all levels of care for those who already have diabetes and primary prevention of diabetes in those with prediabetes.

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• Introduction
• Conclusions
• Article Information

A, Diabetes prevalence. B, Hypertension prevalence.

a Diabetes prevalence under the assumption that all Annual Health Survey participants had not fasted are shown in eFigure 3 in the Supplement .

A, Diabetes prevalence. B, Hypertension prevalence. Predicted probabilities were obtained from multivariable logistic regressions of diabetes and hypertension on individuals’ sociodemographic characteristics (age group, household wealth quintile, education, marital status, sex, and rural vs urban location), district-level fixed effects, and an interaction term between age group and household wealth quintile. Predicted probabilities assuming that all Annual Health Survey respondents had not fasted are shown in eFigure 6 in the Supplement .

A, Diabetes prevalence. B, Hypertension prevalence. No data were available for Jammu and Kashmir, and Gujarat. The Union Territories of Chandigarh, Daman and Diu, and Puducherry are not visible in the map owing to their small area. Point estimates and 95% CIs for each state are shown in eTable 7 in the Supplement . AP indicates Andhra Pradesh; AR, Arunachal Pradesh; AS, Assam; BR, Bihar; CG, Chhattisgarh; CH, Chandigarh; DD, Daman and Diu; DL, Delhi; GA, Goa; HR, Haryana; HP, Himachal Pradesh; JH, Jharkhand; KA, Karnataka; KL, Kerala; MP, Madhya Pradesh; MH, Maharashtra; MN, Manipur; ML, Meghalaya; MZ, Mizoram; NL, Nagaland; OD, Odisha (Orissa); PB, Punjab; PY, Puducherry; RJ, Rajasthan; SK, Sikkim; TN, Tamil Nadu; TS, Telangana State; TR, Tripura; UP, Uttar Pradesh; UK, Uttarakhand (Uttaranchal); WB, West Bengal.

eMethods 1. Methodology of the AHS and DLHS-4

eFigure 1. States and Union Territories covered by each survey

eMethods 2. Matching Annual Health Survey biomarker data to participants’ socio-demographic data

eMethods 3. Computation of the household wealth index

eMethods 4. Computation of sampling weights

eTable 1. Sample characteristics stratified by whether the blood glucose or blood pressure measurement was missing

eTable 2. National diabetes and hypertension prevalence by age group and sex

eTable 3. National diabetes prevalence assuming all AHS respondents were unfasted

eFigure 2. Hypertension prevalence by five-year age group for India and WHO/NCD-RisC regions

eFigure 3. Prevalence of diabetes by rural vs urban residence, sex, and household wealth quintile assuming all AHS respondents were unfasted

eFigure 4. Prevalence of diabetes and hypertension by rural vs urban residence, sex, and education

eFigure 5. Prevalence of diabetes by rural vs urban residence, sex, and education assuming all AHS respondents were unfasted

eTable 4. Regression results for diabetes assuming all AHS participants were unfasted

eTable 5. Regression results for diabetes among those in whom fasting status could be ascertained (ie, DLHS-4 participants only)

eFigure 6. The predicted probability of diabetes by age group, rural-urban location, and household wealth quintile assuming AHS participants were unfasted

eFigure 7. The predicted probability of diabetes by age group, rural-urban location, and household wealth quintile among those in whom fasting status could be ascertained (ie, DLHS-4 participants only)

eTable 6. State-level age-standardized diabetes and hypertension prevalence estimates by sex

eTable 7. State-level age-standardized diabetes and hypertension prevalence estimates by rural vs urban location

eTable 8. State-level crude diabetes and hypertension prevalence estimates by age group

eTable 9. State-level age-standardized diabetes prevalence estimates by sex assuming all AHS respondents were unfasted

eTable 10. State-level age-standardized diabetes prevalence estimates by rural vs urban location assuming all AHS respondents were unfasted

eTable 11. State-level crude diabetes prevalence estimates by age group assuming all AHS respondents were unfasted

eFigure 8. Association of the state- and district-level age-standardized prevalence of diabetes with mean household wealth quintile

eFigure 9. Association of the state- and district-level age-standardized prevalence of hypertension with mean household wealth quintile

eFigure 10. Comparison of age-standardized national diabetes prevalence reported in different studies

eReferences

• India’s Call to Action—Prioritize Chronic Cardiovascular Disease JAMA Internal Medicine Invited Commentary March 1, 2018 Alka M. Kanaya, MD

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Geldsetzer P , Manne-Goehler J , Theilmann M, et al. Diabetes and Hypertension in India : A Nationally Representative Study of 1.3 Million Adults . JAMA Intern Med. 2018;178(3):363–372. doi:10.1001/jamainternmed.2017.8094

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Diabetes and Hypertension in India : A Nationally Representative Study of 1.3 Million Adults

• 1 Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
• 2 Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
• 3 Department of Economics & Centre for Modern Indian Studies, University of Goettingen, Göttingen, Germany
• 4 MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, Education Campus, University of Witwatersrand, Johannesburg, South Africa
• 5 Centre for Global Health, King's College London, London, England
• 6 Indian Institute of Public Health, Gandhinagar, India
• 7 Public Health Foundation of India, Delhi NCR, India
• 8 Institute of Public Health, Heidelberg University, Heidelberg, Germany
• 9 Africa Health Research Institute, Mtubatuba, South Africa
• Invited Commentary India’s Call to Action—Prioritize Chronic Cardiovascular Disease Alka M. Kanaya, MD JAMA Internal Medicine

Question   How does the prevalence of diabetes and hypertension in India vary by geographical area and sociodemographic characteristics?

Findings   Diabetes and hypertension prevalence varied widely among states (by more than a factor of 6 for diabetes and more than a factor of 2 for hypertension); while household wealth and urban location were positively associated with both conditions, the prevalence of diabetes and hypertension among those older than 40 years in the poorest household wealth quintile in rural areas was nonetheless high (5.9% and 30.0%, respectively).

Meaning   The prevalence of diabetes and hypertension in India varies substantially by age, rural vs urban location, and state—knowledge that could be used to target relevant programs to those most in need.

Importance   Understanding how diabetes and hypertension prevalence varies within a country as large as India is essential for targeting of prevention, screening, and treatment services. However, to our knowledge there has been no prior nationally representative study of these conditions to guide the design of effective policies.

Objective   To determine the prevalence of diabetes and hypertension in India, and its variation by state, rural vs urban location, and individual-level sociodemographic characteristics.

Design, Setting, and Participants   This was a cross-sectional, nationally representative, population-based study carried out between 2012 and 2014. A total of 1 320 555 adults 18 years or older with plasma glucose (PG) and blood pressure (BP) measurements were included in the analysis.

Exposures   State, rural vs urban location, age, sex, household wealth quintile, education, and marital status.

Main Outcomes and Measures   Diabetes (PG level ≥126 mg/dL if the participant had fasted or ≥200 mg/dL if the participant had not fasted) and hypertension (systolic BP≥140 mm Hg or diastolic BP≥90 mm Hg).

Results   Of the 1 320 555 adults, 701 408 (53.1%) were women. The crude prevalence of diabetes and hypertension was 7.5% (95% CI, 7.3%-7.7%) and 25.3% (95% CI, 25.0%-25.6%), respectively. Notably, hypertension was common even among younger age groups (eg, 18-25 years: 12.1%; 95% CI, 11.8%-12.5%). Being in the richest household wealth quintile compared with being in the poorest quintile was associated with only a modestly higher probability of diabetes (rural: 2.81 percentage points; 95% CI, 2.53-3.08 and urban: 3.47 percentage points; 95% CI, 3.03-3.91) and hypertension (rural: 4.15 percentage points; 95% CI, 3.68-4.61 and urban: 3.01 percentage points; 95% CI, 2.38-3.65). The differences in the probability of both conditions by educational category were generally small (≤2 percentage points). Among states, the crude prevalence of diabetes and hypertension varied from 3.2% (95% CI, 2.7%-3.7%) to 19.9% (95% CI, 17.6%-22.3%), and 18.0% (95% CI, 16.6%-19.5%) to 41.6% (95% CI, 37.8%-45.5%), respectively.

Conclusions and Relevance   Diabetes and hypertension prevalence is high in middle and old age across all geographical areas and sociodemographic groups in India, and hypertension prevalence among young adults is higher than previously thought. Evidence on the variations in prevalence by state, age group, and rural vs urban location is critical to effectively target diabetes and hypertension prevention, screening, and treatment programs to those most in need.

In 2011, World Health Organization (WHO) member states signed the Global Action Plan for the Prevention and Control of Noncommunicable Diseases, 1 which aimed to halt the rise of diabetes by 2025 and reduce the prevalence of hypertension by 25% between 2010 and 2025. In 2015, as part of Sustainable Development Goal 3, the United Nations (UN) member states set the target of reducing premature mortality from noncommunicable diseases (NCDs) by one-third by 2030. Given India’s huge population, 2 its achievements are critical to reaching these global targets.

India is in the midst of a rapid epidemiological transition: the estimated proportion of disability-adjusted life-years (DALYs) attributable to NCDs in India has risen from 31% of total DALYs in 1990 to 55% in 2016. 3 An increasing prevalence of diabetes and hypertension is thought to be both an important driver and consequence of this transition. The NCD Risk Factor Collaboration (NCD-RisC) estimates suggest that between 1980 and 2014, the age-standardized diabetes and hypertension prevalence among men in India grew from 3.7% to 9.1% and 24.5% to 26.6%, respectively, and among women from 4.6% to 8.3% and 22.7% to 24.7%, respectively. 4 The prevalence of both conditions is likely to continue increasing in the future given that (1) India’s population is aging and urbanizing rapidly 2 , 5 and (2) standards of living in the country are improving, 6 which tends to be accompanied by an increase in obesity and its associated cardiovascular disease (CVD) risk factors, 7 including diabetes and hypertension. The latter is particularly concerning given that adults of Asian Indian ethnicity are thought to be predisposed to developing CVD when exposed to obesogenic environments and lifestyles. 8

For effective targeting of health system resources and services, it is essential to understand how the prevalence of diabetes and hypertension varies among population groups across this vast country. Yet, to date, there has not been a nationally representative study of diabetes and hypertension in India to provide the evidence needed to inform policymaking. 9 , 10 Pooling data from a nationally representative sample of 1.3 million adults, this study aims to provide a new (and more accurate) diabetes and hypertension prevalence estimate for India, and to examine how the prevalence of these conditions varies by state, rural vs urban location, and individual-level sociodemographic characteristics.

We pooled data from 2 large household surveys in India: The District-Level Household Survey-4 (DLHS-4) and the second update of the Annual Health Survey (AHS), which were both carried out between 2012 and 2014, are representative at the district level and jointly cover all 29 states of India except (1) Jammu and Kashmir and (2) Gujarat. More details on the surveys are provided in eMethods 1, eMethods 2, and eFigure 1 in the Supplement . This analysis of an existing data set in the public domain received a determination of “not human subjects research” by the institutional review board of the Harvard T. H. Chan School of Public Health.

Both the AHS and DLHS-4 measured blood glucose and blood pressure (BP) in men and nonpregnant women 18 years or older. A capillary blood sample (using a finger prick) was taken and blood glucose measured using the SD CodeFree handheld glucometer (Bionsensor Inc), which multiplied capillary glucose readings by 1.11 to display their plasma equivalent. 11 Blood pressure was measured twice in the left upper arm (with the patient sitting) using an electronic BP monitor (Rossmax AW150, Rossmax International Ltd).

Diabetes was defined as having a high plasma glucose reading (≥126 mg/dL [7.0 mmol/L] if patients reported having fasted or ≥200 mg/dL [11.1 mmol/L] if patients reported not fasting per the recommendations of the International Diabetes Federation and WHO 12 ). All participants were asked to fast overnight until the time of the blood glucose measurement in the morning. Fasting status was verified by self-report in the DLHS-4 (58.4% of participants reported to have fasted) but was not recorded in the AHS. The prevalence and regression results in this article assume all AHS respondents to have fasted. However, in the Supplement , we present all prevalence and regression estimates assuming AHS participants had not fasted, as well as regression results among only those respondents in whom fasting status was verified by self-report (ie, DLHS-4 participants only).

Based on the mean of the 2 BP measurements taken in the AHS and DLHS-4, we defined hypertension as systolic BP of at least 140 mm Hg or diastolic BP of at least 90 mm Hg. 13

The independent variables for this study were state, household wealth quintile, education, marital status (currently married or not), and whether the household was located in a rural or urban area. We used household ownership of 12 assets (radio, TV, computer, phone, refrigerator, bike, scooter, car, washing machine, sewing machine, house, and land) and 5 key housing characteristics (water supply, type of toilet and whether it is shared, cooking fuel, housing material, and source of lighting) to generate a household wealth index in a principal component analysis (PCA). Following the methodology developed by Filmer and Pritchett, 14 , 15 we extracted the first component in the PCA separately for urban and rural areas and divided this variable into quintiles (again, separately for rural and urban areas) based on the distribution in the national data set. More details on the computation of the household wealth index are provided in eMethods 3 in the Supplement .

Diabetes and hypertension prevalence was calculated by state, rural vs urban location, sex, age group, and household wealth quintile using sampling weights to account for both the survey design and the pooling of AHS with DLHS-4 data (see eMethods 4 in the Supplement ). Age-standardized prevalence estimates were weighted to the age distribution of the WHO’s standard population. 16 We fitted multivariable linear probability models (LPMs)—run separately for rural and urban areas—to further investigate the association of diabetes and hypertension with individual-level sociodemographic characteristics. Our regressions included a binary indicator (“fixed effect”) for each of 18 126 primary sampling units (PSUs) to filter out area-level effects on diabetes and hypertension. Because there are relatively few observations in each PSU, we fitted LPMs rather than logistic or probit models to avoid the incidental parameter problem. 17 An added advantage of the LPM is the interpretability of the regression coefficients as simple absolute differences in the probability of the outcome. To avoid the possibility of fitted probabilities greater than 1 and less than 0, we use logistic regression (with district-level fixed effects to sidestep the incidental parameter problem) for predicted probability plots. The standard errors in all regression models were adjusted for clustering at the PSU level. Statistical analyses were performed with R software (version 3.3.2; R Foundation), and all figures were created with the ggplot2 package.

A total of 1 618 359 nonpregnant adults were interviewed; 297 804 (18.4%) had a missing value for the plasma glucose measurement or at least 1 of the 2 BP readings, yielding a sample size for analysis of 1 320 555 adults. Table 1 shows the (unweighted) characteristics of the participants; 7.6% of participants had diabetes, 26.5% had hypertension, 43.4% of participants were ages 18 to 35 years, and 47.0% of women and 28.6% of men had not completed primary school. Three quarters of participants were married, and a third (32.5%) were living in urban areas.

The crude (weighted) prevalence of diabetes was 7.3% (95% CI, 7.1%-7.4%) and 7.8% (95% CI, 7.6%-8.0%) among women and men, respectively, and ranged from 2.4% (95% CI, 2.2%-2.5%) among men ages 18 to 25 years to 14.0% (95% CI, 13.5%-14.5%) among men older than 65 years (eTable 2 in the Supplement ). Crude hypertension prevalence was 23.6% (95% CI, 23.3%-23.8%) among women and 27.4% (95% CI, 27.0%-27.7%) among men, ranging from 9.2% (95% CI, 8.9%-9.6%) among women ages 18 to 25 years to 48.6% (95% CI, 47.9%-49.3%) among women older than 65 years.

Stratification of crude prevalence by individuals’ sociodemographic characteristics ( Figure 1 and eFigure 4 in the Supplement ) and multivariable regressions ( Table 2 and Figure 2 ) show that (1) household wealth quintile was positively associated with both conditions, although—compared with the poorest quintile—the richest quintile had only a modestly higher probability of diabetes (rural areas: 2.81 percentage points; 95% CI, 2.53-3.08 and urban areas: 3.47 percentage points; 95% CI, 3.03-3.91) and hypertension (rural areas: 4.15 percentage points; 95% CI, 3.68-4.61 and urban areas: 3.01 percentage points; 95% CI, 2.38-3.65); (2) the differences in the probability of both conditions by educational attainment were generally small (≤2.00 percentage points); (3) for both conditions, prevalence tended to be higher in urban than rural areas; (4) the relative differences in prevalence by urban vs rural location and household wealth quintile were markedly higher for diabetes than for hypertension; (5) the relative differences between household wealth quintiles in the probability of both conditions were higher in rural areas than in urban areas; (6) while for both diabetes and hypertension men had a greater probability of having the condition than women, the absolute difference in the probability by sex was substantially larger for hypertension; and (7) the differences in the probability of both conditions with age group were higher than for any other sociodemographic characteristic.

The age-standardized prevalence of diabetes varied from 2.33% (95% CI, 1.98%-2.75%) among women in Madhya Pradesh to 17.90% (95% CI, 15.37%-20.74%) among men in Goa (eTable 6 in the Supplement ). For hypertension, the age-standardized prevalence ranged from 13.50% (95% CI, 12.19%-14.93%) among women in Chhattisgarh to 43.53% (95% CI, 38.33%-48.87%) among men in Daman and Diu. While diabetes was most prevalent in the South of India (Andhra Pradesh, Goa, Karnataka, Kerala, and Tamil Nadu) as well as in Delhi and West Bengal, hypertension prevalence tended to be highest in the northern states of Punjab and Himachal Pradesh, the southern state of Kerala, and the northeastern states of Sikkim and Nagaland ( Figure 3 ). The state- and district-level prevalence of diabetes and hypertension was positively correlated with each area’s standard of living (as measured by the state- or district-level mean household wealth quintile) (eFigure 8 and eFigure 9 in the Supplement ).

To our knowledge, our study is the first to analyze nationally representative, individual-level blood glucose level and BP data in India—a country that is home to more than a sixth of the world’s population and 22% of the population in low- and middle-income countries 2 —to provide empirical evidence on the prevalence of diabetes and hypertension and its variation among different geographical areas and sociodemographic groups. The age-standardized prevalence of diabetes was 6.1% (95% CI, 6.0%-6.3%) among women and 6.5% (95% CI, 6.4%-6.7%) among men. For comparison, NCD-RisC estimates that the age-standardized prevalence of diabetes in the United States was 6.4% among women and 8.1% among men. 18 For hypertension, the age-standardized prevalence was considerably higher in India than estimates for the United States (20.0% among women in India compared with 10.8% in the United States, and 24.5% among men in India compared with 15.5% in the United States). 19 While we found substantial variation in diabetes and hypertension prevalence among Indian states, we show that diabetes and hypertension are common in middle and older age across all geographical settings and population groups in the country. Specifically, even though household wealth and living in an urban area were positively associated with both diabetes and hypertension, the prevalence of these conditions in middle and old age among the lowest household wealth quintile in rural areas was still high. For instance, among those older than 40 years in the poorest wealth quintile in rural areas, 5.9% (95% CI, 5.5%-6.2%) had diabetes and 30.0% (95% CI, 29.2%-30.7%) had hypertension.

While the key strength of this study is its ability to disaggregate prevalence by state- and individual-level sociodemographic characteristics, we also provide a new diabetes and hypertension prevalence estimate for India. To date, prevalence estimates for both conditions have been obtained by extrapolating findings from subnational studies to the national level. We observed an age-standardized diabetes prevalence of 6.3% (95% CI, 6.2%-6.5%). As depicted in eFigure 14, this figure is lower than the age-standardized estimates provided by the International Diabetes Federation (which has estimated an adult prevalence of 9.3% [95% CI, 7.6%-11.4%] for 2015), 20 NCD-RisC (estimating an adult prevalence of 9.1% [95% CI, 5.2%-14.2%] for 2014), 4 and the Global Burden of Disease Project (estimating an age-standardized prevalence among the entire population of 6.5% [uncertainty range: 6.0%-7.1%] in 2015). 21 The lower value for prevalence in our study is partly because we defined diabetes based on blood glucose level only (because information on diabetes medications or diagnosis was not available in the AHS and DLHS-4). While our prevalence figures are lower than these previous modeled estimates, our state-level prevalence estimates are similar to those obtained using data from the largest subnational study to date. 22

For hypertension, our age-standardized prevalence estimate of 24.5% (95% CI, 24.2%-24.9%) among men and 20.0% (95% CI, 19.7%-20.3%) among women is within the uncertainty intervals of the modeled estimates by WHO/NCD-RisC for India for 2015 (26.5% [95% uncertainty level, 21.2%-32.4%] among men and 24.7% [95% uncertainty level, 19.9%-29.9%] among women), which used the same definition of hypertension as was used in this study. 19 , 23 More strikingly however, as shown in eFigure 2 in the Supplement , we found substantially higher prevalence of hypertension among age groups younger than 45 years than estimated by WHO/NCD-RisC for South Asia (India contributed 76% of the population of South Asia, as defined by WHO/NCD-RisC). 2 , 19 In fact, in younger age groups, our hypertension prevalence estimates for India were higher than those for Central and Eastern Europe—a region that WHO/NCD-RisC identified as having the highest hypertension prevalence globally. 19 , 23 An important finding of our study, therefore, is the unexpectedly high prevalence of hypertension among young adults in India, which—if ineffectively treated—will likely result in longer lifetime exposure to this risk factor and thus higher CVD rates in the future.

Equity concerns have been raised about investing limited resources for health in LMICs into CVD screening and treatment because CVD is generally thought to occur more frequently in wealthier strata of society than in poorer strata. 24 , 25 In this study, we show that the wealth and education gradients in diabetes and hypertension prevalence are relatively minor, especially when compared with age gradients. A limitation of this study, however, is that if wealthier and more educated individuals were more likely to achieve control of their diabetes or hypertension through better access to treatment, then the socioeconomic gradients in diabetes and hypertension in this analysis (which defined these conditions based on blood glucose level and BP only) are flatter than they would have been had these conditions been defined as either reporting to be on treatment or having a high blood glucose level and BP. More generally, prevalence of CVD risk factors by wealth groups can only partially inform equity-focused policy decisions because of 2 main limitations. The first is that prevalence estimates do not take into account that CVD events are likely to have more detrimental effects among the poor than among the wealthy because poorer individuals have lower access to high-quality health care services and have less financial risk protection. 26 - 31 The second limitation is that examining a single risk factor or disease at a time does not provide information on the relative contribution of the disease to the wealth group’s total disease burden. In particular, many areas of India are still facing a substantial infectious disease burden and poor maternal and child health indicators 32 —health problems that disproportionately affect the poor.

Our study has several additional limitations. As in any population-based survey, some adults (18.4%) had a missing value for their blood glucose measurement or at least 1 of the 2 systolic or diastolic BP measurements. Of these, 87.0% had a missing consent variable (basic sociodemographic information on these participants was still collected from the household head), suggesting that missing measurements were mostly due to some adults being absent at the time of the household visit (rather than refusal to consent or data entry errors). Second, a 1-time capillary blood glucose measurement is not recommended for the diagnosis of diabetes in clinical settings. 33 It has, however, been shown to have an acceptable sensitivity and specificity for defining diabetes in population-based research and is the recommended method for monitoring diabetes prevalence in the WHO’s STEPwise Approach to NCD Risk Factor Surveillance. 34 - 36 Third, the study was unable to distinguish between type 1 and type 2 diabetes. The International Diabetes Federation estimates that 72 000 children with type 1 diabetes from birth to age 14 years lived in India in 2015; 0.02% of the country’s population was in this age range. 2 , 20 Extrapolating this percentage to adults would suggest that the proportion of adults with type 1 diabetes in our sample is likely very small. Fourth, in contrast with the DLHS-4, fasting status was not verified through self-report in the AHS. Applying a fasting blood glucose threshold to participants who had not fasted in the AHS (which covers the poorer states of India) may be partially responsible for the high diabetes prevalence among poorer individuals. We addressed this limitation by also providing prevalence estimates assuming that all AHS respondents had not fasted instead of fasted (eTables 3 and 9-11 and eFigures 5 and 6, in the Supplement ). In addition, we show our regression results after restricting the sample to DLHS-4 respondents (eTable 5 and eFigure 7 in the Supplement ) and find that among these participants, for whom fasting status was verified through self-report, the probability of diabetes in the lowest national household wealth quintile was even higher than among AHS respondents (eFigure 7 in the Supplement ).

While we identified important variation in diabetes and hypertension prevalence among states and by rural vs urban location, prevalence levels in India are high across all geographical settings and socioeconomic groups in middle and old age. Major investments in targeted diabetes and hypertension prevention, detection, and treatment programs are needed across the country if India is to avert catastrophic health, social, and economic consequences of these conditions and their sequelae. Given the size, growth, rapid urbanization, and aging of India’s population, 2 , 5 as well as the high levels of impoverishing health care expenditures caused by NCDs, 31 the country’s success in tackling its diabetes and hypertension epidemic will be crucial to achieving Sustainable Development Goals globally.

Corresponding Author: Lindsay M. Jaacks, PhD, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA 02115 ( [email protected] ).

Accepted for Publication: November 24, 2017.

Published Online: January 29, 2018. doi:10.1001/jamainternmed.2017.8094

Author Contributions: Dr Jaacks had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Geldsetzer, Manne-Goehler, Davies, Awasthi, Vollmer, Jaacks, Bärnighausen, Atun.

Acquisition, analysis, or interpretation of data: Geldsetzer, Manne-Goehler, Theilmann, Davies, Awasthi, Jaacks, Bärnighausen, Atun.

Drafting of the manuscript: Geldsetzer.

Critical revision of the manuscript for important intellectual content: Geldsetzer, Manne-Goehler, Theilmann, Davies, Awasthi, Vollmer, Jaacks, Bärnighausen, Atun.

Statistical analysis: Geldsetzer, Theilmann, Vollmer.

Obtained funding: Geldsetzer, Jaacks.

Study supervision: Davies, Jaacks, Bärnighausen, Vollmer, Atun.

Conflict of Interest Disclosures: None reported.

Additional Information: Drs Vollmer, Jaacks, Bärnighausen, and Atun are co–senior authors.

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Open Access

Peer-reviewed

Research Article

Perception and coping mechanisms of patients with diabetes mellitus during the COVID-19 pandemic in Ibadan, Nigeria

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Sociology, University of Wroclaw, Wroclaw, Poland

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Demography and Population Studies, University of Witwatersrand, Johannesburg, South Africa, Department of Public Health, School of Business and Health Studies, York St John University, London, United Kingdom

Roles Writing – original draft, Writing – review & editing

Affiliation Department of Family and Community Health, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana

Affiliation Department of Internal Medicine, College of Medicine, University of Ibadan & University College Hospital, Ibadan, Nigeria

• Olajumoke Ololade Tunji-Adepoju, 
• Obasanjo Afolabi Bolarinwa, 
• Richard Gyan Aboagye, 
• Williams O. Balogun

• Published: August 27, 2024
• https://doi.org/10.1371/journal.pone.0309451
• Peer Review
• Reader Comments

The 2019 coronavirus disease (COVID-19) ushered in a period of fear and uncertainty, resulting in structural instability across the globe. Vulnerable individuals, such as patients with diabetes mellitus, are predispose to have adverse effects and complications of COVID-19 when infected. We explored the perception of diabetes mellitus patients during the COVID-19 pandemic and their coping mechanisms at the University College Hospital, Ibadan.

We employed an exploratory qualitative study design to explore diabetes mellitus patients’ perceptions and coping mechanisms during the COVID-19 pandemic. A purposive sampling technique was used to recruit 32 participants (2 health professionals and 30 diabetes mellitus patients). In-depth interviews were used to collect the data from the participants. All the recorded audio data were transcribed verbatim and exported to NVivo software for thematic data analyses.

Most diabetes mellitus patients were not fearful of the pandemic but were optimistic that it would not affect their health. Mechanisms such as the usage of herbal medicines and adherence to COVID-19 precautionary measures were noticed among patients. The study also revealed that the hospital’s coping mechanism during the COVID-19 pandemic include prolonged appointments, limiting the number of patients attended per clinic day, and the provision of telehealth service. Patients in our study utilised negative coping mechanisms such as reduced drug dosages, subscriptions to cheaper drug brands, and reliance on religious institutions rather than a clinic for health instructions.

Conclusions

The study has shown that diabetes mellitus patients were not fearful of the COVID-19 pandemic. The utilisation of telehealth, encouragement of daily monitoring of sugar levels, provision of avenues for a medication review, and adherence to the safety protocols were coping mechanisms employed by the health system and diabetes mellitus patients. We recommend that the government and other healthcare stakeholders reinforce the resilience of diabetes mellitus patients by alleviating their health burdens during the pandemic. This could be done by subsidizing the prices of drugs, tests, and consultation fees for patients with diabetes mellitus. Also, more efforts should be made to elevate the health system through the reduction in waiting and appointment times in the diabetes clinic and employing more health personnel in the clinic.

Citation: Tunji-Adepoju OO, Afolabi Bolarinwa O, Aboagye RG, Balogun WO (2024) Perception and coping mechanisms of patients with diabetes mellitus during the COVID-19 pandemic in Ibadan, Nigeria. PLoS ONE 19(8): e0309451. https://doi.org/10.1371/journal.pone.0309451

Editor: Sylla Thiam, Sunu Sante Consulting, SENEGAL

Received: June 26, 2023; Accepted: August 12, 2024; Published: August 27, 2024

Copyright: © 2024 Tunji-Adepoju et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data utilised in this research contain potentially identifying or sensitive patient information; data are owned by the Institute for Advanced Medical Research and Training (IAMRAT). Please get in touch with IAMRAT via [email protected] or the first author for data request and access.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: COVID-19, Coronavirus Disease 2019; IDI, In-depth Interview; KII, Key Informant Interview; NCD, Non-Communicable Diseases; NCDC, Nigeria Centre for Disease Control and Prevention; WHO, World Health Organization

Diabetes Mellitus has been an important global health concern even prior to the outbreak of the 2019 coronavirus disease (COVID-19). Diabetes mellitus is a chronic health condition characterized by high blood glucose due to either the inability of the pancreas to produce adequate insulin or the body’s resistance to available insulin [ 1 ]. Poorly managed diabetes mellitus can result in long-term complications such as amputation, cardiovascular disease, vision impairment, and renal disease [ 1 ]. The prevalence of diabetes mellitus is increasing across the globe. Between 1980 and 2014, the number of patients with diabetes mellitus increased from 108 million to 422 million [ 2 ] and over 500 million in 2020 [ 3 , 4 ]. Diabetes mellitus is projected to be the seventh leading cause of death worldwide by 2030 [ 2 ]. The burden of diabetes is greatly increasing in sub-Saharan Africa, and Nigeria has the largest share of this burden [ 5 , 6 ]. Evidence suggests that an estimated 11 million Nigerians have diabetes [ 7 ]. This implies that more than five percent of the Nigerian population is living with the disease, and it is a major cause of death among many Nigerians below 70 years old [ 8 ].

Research has shown that the presence of excess blood glucose, also known as hyperglycemia in diabetes patients, makes them susceptible to COVID-19 [ 9 , 10 ]. In the same vein, a study reported that patients with diabetes are two times more likely to develop severe conditions or die from COVID-19, while people living with uncontrolled diabetes are about 13 times more likely to die from the virus [ 9 ]. This has instilled fear in many patients with diabetes in Nigeria [ 10 ]. Hence, the fact that patients with diabetes need extra health care and attention during the pandemic remains undisputable [ 11 ]. Measures to prevent and control Non-Communicable Diseases (NCDs), such as diabetes, in developing countries, including Nigeria, have not been effectively implemented. The COVID-19 pandemic worsened the accumulated effects of Nigeria’s failure to improve the healthcare structure and system, particularly the care of people with NCDs. The outbreak of COVID-19 in Nigeria on the 27th of February 2020 [ 12 ] also caused dysfunctionality and complications in the Nigerian social structures, requiring sporadic responses.

Predictably, the response to COVID-19 in Nigeria infringed on treating other diseases, including diabetes mellitus [ 13 ]. For instance, many public hospitals were converted to COVID-19 treatment centers resulting in restricted access of other patients to medical care [ 5 , 14 ]. Also, the World Health Organization (WHO) stipulated in its report that the COVID-19 pandemic negatively impacted the equity regarding essential health service delivery in its member states [ 4 , 17 ]. The report further revealed that more than 50% of its member states experienced disruption in delivering health care services on NCDs, cancer, and mental health disorders. Some of the reasons given for this disruption include shortage of staff due to their transfer to COVID-19 care centers, lack of public transport, and cancellation of planned appointments, while the reasons recorded in 20% of the member states were: the shortage of medicines, diagnostics, and other technologies [ 4 ]. Due to the various forms of hardship or discomfort caused by the pandemic, vulnerable individuals, such as people with diabetes mellitus, are likely to perceive the period differently than healthy people. Patients with diabetes are likely to have a negative perception of the COVID-19 condition, which could influence the adoption of harmful coping mechanisms that could further hamper their health outcomes. Although several perception studies have been done on COVID-19 generally in Nigeria, such as that of Osahon and Memudu [ 15 ] on the perception and healthy attitudes of Nigerians to COVID-19, very little data is available about the perception of diabetes patients of the COVID-19 pandemic. This study explored the perceptions of patients with diabetes mellitus during the pandemic and their coping mechanisms during the period. This is important to illuminate the experiences of patients with diabetes mellitus during the pandemic, and the findings could be beneficial to the government and healthcare stakeholders in formulating policies to help improve the health outcomes of patients with diabetes during the pandemic.

Study design

We adopted an explorative qualitative research approach [ 16 ]. This approach is suitable for understanding the perception of diabetes mellitus patients at University College Hospital and the coping mechanisms during the COVID-19 pandemic. This qualitative research approach also guide the collection of in-depth data from the participants in their natural form [ 16 ].

Study setting

The study was conducted in the University College Hospital, Ibadan. University College Hospital is a tertiary health center that serves Oyo state and neighbouring states where patients with diabetes, including those with suspected COVID-19 cases, are seen. According to statistics from the Nigeria Centre for Disease Control and Prevention (NCDC) [ 17 ], Oyo State is among the COVID-19 most infected states in Nigeria, and Ibadan is its capital city. The University College Hospital was founded in November 1952, located at Oritamefa in the Ibadan North Local Government Area. It is the first teaching hospital in Nigeria to provide in-patient and outpatient health care services. It receives referrals from southwestern and other parts of Nigeria and outside the country. The Diabetes clinic runs every Monday, and an average of 50–70 patients visit the clinic daily.

Participant sampling and sample size

Participants in this study were registered diabetes patients who had been visiting the outpatient diabetes clinic at University College Hospital before the pandemic and are still attending the clinic during the pandemic. We used a purposive sampling technique to recruit 30 participants for the study, which was determined using the data saturation method. These participants constituted those who experienced the phenomena under study. Patients who were living with diabetes mellitus disease prior to the pandemic (at least more than a year) and aged 18 years and above were included. However, those accessible during the data collection period were included. The rationale was that this category of patients with diabetes mellitus could tell the difference between their experiences in the clinic before and during the pandemic. Being coherent, healthy, gave informed consent were other inclusion criteria for the study. Patients who did not consent to the study or were no longer interested in participating even while in the middle of it were excluded from the study. Patients diagnosed with diabetes after the outbreak of COVID-19 and/or who did not attend the diabetes clinic during the study period were not included. Also, patients with acute or chronic debilitating comorbidities were not included in the study.

Data collection procedure

Four (4) trained research assistants were used for the data collection. The research assistants were trained anthropologists, who the authors also trained in areas consisting of the consenting process, interviews, asking probing questions, and recording. The authors developed an interview guide as the data collection tool. Data on the participants’ sociodemographic characteristics and the study objectives were collected after obtaining consent. The probe questions were structured to capture responses to the participants’ perceptions of the COVID-19 pandemic. It also covered responses to the coping mechanisms adopted by diabetes mellitus patients during the pandemic. Prior to the data collection, we informed the participants about any possible discomfort, benefits, and compensation associated with the study. Interviews were conducted once the participants agreed to a date, time, and place of convenience to participants. The participants were approached for recruitment at the end of the medical appointments, and those who consented were interviewed at the premises of the hospital. The data collection lasted for an average of 60 minutes per participant. The participants were compensated with an equivalent gift of three US dollars ($3) at the end of the interview.

About 15 interviews were conducted each week for two weeks by one of the authors with four trained anthropologists who had qualitative fieldwork experiences. The anthropologist helped in administering the interview guide. Interviews were conducted with strict adherence to the COVID-19 precautionary measures. The data collection/interviews were done between the 15 th to 22 nd of March 2021 using a pretested interviewer guide. The participants were recruited using a purposive sampling technique. All the interviews were tape-recorded, and field notes were taken and utilised during the transcription and analysis. Data transcription was carried out after every fieldwork, and this helped in identifying questions that may have been left unanswered during the interview or those needing further probing, as well as identifying the point of saturation where no further interviews were conducted. The research assistants helped with field notes, tape recording and data analysis.

Data analysis

All the audio data was transcribed verbatim on the same day the data was collected. After the transcription by the research assistants, After the transcription of the data, the transcripts were vetted and proofread by OOTA, OAB and WOB. Later, the transcripts were made accessible to OAB, who performed the initial independent thematic analysis [ 18 ]. Using the ‘nodes’ function in NVivo-12 software, where codes were assigned to the text data from the transcripts [ 19 ]. During the analysis, all similar recurring codes were categorised to generate themes and, subsequently, sub-themes [ 18 ]. The extracts and quotes from the themes and sub-themes generated were used to support the results of the study. All the authors approved the extracts and quotes. A pretest of the interview guide was done with two (2) potential respondents (male and female) among those who came for medical appointments prior to the actual commencement of the main data collection. The interview guide pretest results show accurate consistency, but the results were not included in the main study.

Rigour and trustworthiness

In every qualitative study, credibility and trustworthiness measures are critical. In achieving this, we allowed two research assistants with experience in qualitative analysis to transcribe and analyze tape-recorded interviews separately. The two research assistants’ themes and sub-themes, as well as the authors, were compared to ascertain their consistency. To strengthen the credibility of the results, direct quotations and precise summaries of participant remarks were used. A week after the transcription and preliminary data analysis, we conducted member-checking with three of the participants to demonstrate trustworthiness. This allowed the participants to attest that the transcripts accurately captured the content of the interviews. Nobody offered changes or voiced complaints about the interviews’ calibre or content in terms of clearly expressing their viewpoints. The participants’ nonverbal cues, their concerns, and the interviewers’ observations were all documented in the field notes that were taken following each interview and consulted throughout the research. The authors who carried out the interviews are qualified healthcare researchers with expertise in conducting IDIs.

Ethical issues

Ethical clearance was sought from the Ibadan/University College Hospital Ethics Committee (UI/UCH EC) with approval number UI/EC/21/0064. In this study, we complied with all the ethical guidelines pertaining to using human participants and peculiar to qualitative studies. We anonymized all the transcripts and audio files by giving them pseudonyms to remove any personal information that may be used to identify the study participants. The participants in the study were given an information sheet that included information on the objectives, methods, potential risks and advantages, compensations, who to contact, and an affirmation of confidentiality, privacy, and autonomy. The participants gave written consent by signing the consent form for participating, and for recording the interviews. Later, the participants’ signed informed consent was requested. This demonstrated that they had read and understood the terms of reference before deciding to participate freely in our study. We also encrypted a passcode and locked the audio files and transcripts to prevent unauthorised individuals from accessing the material.

In-depth interviews were held with thirty patients with diabetes mellitus in the outpatient ward of the endocrinology clinic. Each interview lasted for about an hour.

Demographic characteristics of participants

A total of thirty participants were recruited for the study, consisting of approximately two-thirds females and one-third males. Most participants were elderly, with the oldest being an 84-year-old female and the youngest a 21-year-old male. More than half were Christians, with the remainder being Muslims. All males, except the youngest, were married. Among the females, most were married, with two widows, one single and one separated.

Over half of the participants had tertiary education, a few had secondary education, and a small number had primary education. Only a few females had no formal education, whereas all males had some level of formal education.

Most males were retired, with three employed and one unemployed (the youngest male). Among females, more than two-thirds were employed, three were unemployed, and two were retired. Participants’ socio-economic status ranged from average to low.

Concerning diabetes type awareness, seven out of ten female participants did not know their type, while all but one male participant was aware. Most participants had type 2 diabetes, except for one male and one female in their twenties who had type 1 diabetes.

Emerging themes from the study

Table 1 presents the major themes and sub-themes that emerged from the study. While analyzing data, two key themes emerged: The perception of Diabetes Patients during the COVID-19 Pandemic and the coping mechanisms employed by diabetes mellitus patients during the pandemic.

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https://doi.org/10.1371/journal.pone.0309451.t001

Perception of diabetes mellitus patients during the COVID-19 pandemic

This theme contains three sub-themes (clinic appointments, effects of the COVID-19 pandemic on diabetes patients, and adherence to COVID-19 protocols).

Clinic appointments.

Data from the key informant interviews revealed that the pandemic was perceived as a period that has negatively affected appointments, clinic attendance, and the management of diabetes in the clinic. A participant stated that

Yes, like I just told you, it has affected it a lot because I have been coming for months now, and I have not been able to see the doctor (IDI, Participant 10, Female, 45 years). The pandemic has affected my clinic attendance because, presently, I only come to the clinic when the doctor gives me appointments. Prior to the pandemic, asides from my appointment dates, I come to the clinic every first Monday of the month because we diabetes patients usually hold meetings in the diabetes association office; however, since the emergence of the pandemic, we have stopped holding the meeting (IDI, Participant 9, Male, 21 years)

Effects of the COVID-19 pandemic on patients with diabetes mellitus.

This sub-theme has ten codes, which include the vulnerable groups during the pandemic. The participants revealed a clear understanding of the fact that diabetes patients are vulnerable during the pandemic. A number of the patients demonstrated a clear knowledge of the category of people who are vulnerable to COVID-19 infection. They perceived this category of people as the aged, those who defy preventive measures, and people with comorbidities. However, some of the participants were unaware of who could be susceptible to the virus.

Some of the diabetic patients who were not observing the COVID-19 precautionary measures are vulnerable to the virus, as encapsulated in the excerpt below:

Anybody can contract it, especially those who fail to wash their hands and follow the preventive measures (IDI, Participant 2, Male , 75 years). Those who fail to adhere to the necessary precautions , those who talk with their whole mouth open without using their nose masks and those who stay too close to other people (IDI , Participant 9 , Male , 21 years) . The elderly / people with underlying diseases Yes, people that are already sick before and the elderly ones (IDI, Participant 10, female, 45 years). It cannot have any negative impact on diabetes patients if they take their medications regularly and follow necessary precautions (IDI , Participant 9 , Male 21 years) .

Some participants, however, did not know who could get infected with the virus, as evidenced in the below excerpt:

I can’t say (IDI, Participant 1, female , 74 years). Only God knows (IDI , Participant 4 , female , 84years)

They posited that the COVID-19 virus could have severe impacts on them. The opinion of one participant in this regard is captured in the excerpt below:

The diabetes patient could get infected and the person might not get cured of it. It could even kill such a person (IDI, Participant 8 , Female, 52years).

A few others were of the opinion that COVID-19 cannot have any deadly implications on patients with diabetes since one can be treated if infected.

The impact it can have is for one to get infected, and even if one gets infected, since it can be treated. I don’t think it can bring about any deadly impact except for someone whose time is up on this planet earth already (IDI, Participant 12 , Female 28 years).

Patients with diabetes are not vulnerable in as much as they follow their diabetes regimen:

I don ’ t think there should be any effects if they use their drugs regularly, exercise as well and take away the fear of contracting the disease (IDI , Participant 2 , Male 75 years) .

The in-depth interview further revealed that most of the participants were not afraid of the COVID-19 virus. The submission of a participant is clear on this, as evident in the statement below:

Ehn … It did not make me scared because I firstly did not believe it was real but as time went on and I started hearing that people were really contracting it, it was then I believed that COVID-19 is real. However, till now, I have not seen anyone who has contracted it in my vicinity. As such, that is one of the reasons I did not really get scared about it (IDI, Participant 12, Female 28years).

Patients with diabetes mellitus noted that they were not fearful of the pandemic because they trusted in the Supreme Being, their object of worship (God). The results further showed that a couple of patients with diabetes mellitus were not afraid during the pandemic due to their trust in their medications, the quality of health care provided in the University College Hospital diabetes clinic and their proper adherence to the COVID-19 precautionary measures. The excerpts below capture this:

I’m unruffled. I know we have problems all over the world but I’m a Christian and I’m unruffled (IDI, Participant 2 , Male 75 years). I was not afraid , I don’t believe in it . I have Jesus (IDI , Participant 21 , Male 65 years) .

On the contrary, a few participants perceived that the COVID-19 pandemic was a fearful one, and they perceived it to be the end of their life. This is evident in the excerpts below:

A fearful period

I was thinking I was going to die (IDI, Participant 14 , Female 30years). I was very scared , but God’s grace is sufficient (IDI , Participant 1 , Male 74 years) .

Adherence to COVID-19 protocols.

This sub-theme encompassed the physical presentation of patients only when necessary and allowance of physical presentation of patients with strict adherence to COVID-19 protocols.

Findings from the interviews revealed that the clinic avoided unnecessary physical presentation of diabetes mellitus patients during the pandemic by prolonging appointments. Patients were advised to call doctors on the clinic lines except when there is a pressing health concern that requires a physical presentation of the patient in the clinic. Also, the opinion of a participant revealed that patients are informed to adhere to the COVID-19 precautionary measures whenever they need to be physically present in the clinic. These opinions are encapsulated in the opinions below:

Adherence to the COVID-19 safety protocols through prolonged appointments

They did well before the pandemic, and they answered us on our appointed dates, but since the pandemic started, I’m just coming to see the doctor, it’s over a year already. I’ve been coming in the previous weeks but I was sent back home saying that only when the doctor calls me is when I can come. All these were not there before the pandemic; they kept to their appointments then ((IDI, Participant 18 , Female 80 years). Yes , I am faithful but here , they are not faithful . The staff , attendants and the records officials are not faithful . Sometimes , when I come on my appointment dates , on getting here , they would tell me they have rescheduled my appointment because of COVID-19 (IDI , Participant 10 , Female 45 years) . I didn’t visit the hospital when the pandemic began , but when the hospital was open , I came , and we were told to use our drugs , and I haven’t been able to see the doctor again . It’s been a year I saw a doctor; I just saw the doctor on the first of March this year since all these while . Whenever I have appointments , I use to come , but University College Hospital is not helping matters cause most times I will come , they will say they’ve re-scheduled my appointment many times (IDI , Participant 22 , Female , 72 years) .

One of the diabetes mellitus patients indicated that the COVID-19 precautionary measures were mandatory for all patients in the clinic.

They make sure we use our nose mask, they do temperature checks before you come in, even at the gate, they tell you to put your mask on (IDI, Participants 20 , Male 75 years).

Coping mechanisms adopted by patients with diabetes mellitus

Coping mechanisms emerged as the second theme. The sub-themes were mechanisms adopted by the clinic, coping mechanisms adopted by the patients with diabetes mellitus, reasons for low subscription to telehealth, and dangerous coping mechanisms used by the patients with diabetes mellitus.

Mechanisms adopted by the clinic.

Under this sub-theme, the patients with diabetes mellitus mentioned that the coping mechanisms put in place at the diabetes clinic include the adoption of an online database, provision of avenues to review prescriptions, encouragement of daily monitoring of blood sugar, telehealth, and awareness creation. The following narrative quotes to support this sub-theme;

Now that they’re using technology, things are improving, so little by little, I hope they will do better (IDI, Participants 11 , Female 65 years). They treat me well each time I come. I am always instructed to get an exercise book to write my blood sugar level when I check it every morning and night every day. Once I come to the clinic, I do show the doctor the book. If it is normal, the doctor will not increase my medications, but if it is high, my medications will be increased. That is the way I am attended to (IDI, Participant 12, Female 28 years)

Telehealth.

Participants shared their experiences with the communication services provided by the clinic:

They have call center, they introduced a call center that patients can call and speak to the doctors and nurses, errm I think it’s not 24 hours, but its during working hours (IDI, Participants 17, Male 77 years). I am only aware of the fact that I got a message from the clinic during the early period of the pandemic that I should call some numbers in case an emergency issue arises concerning my health (IDI, Participant 8, Female 52 years).

Coping mechanisms adopted by patients with diabetes mellitus.

The patients utilized positive coping mechanisms such as adherence to preventive measures and reliance on the media for COVID-19 updates. This is captured in the responses below by a number of the participants:

Adherence to the COVID-19 precautionary measures was one of the coping mechanisms the patients with diabetes mellitus adopted in preventing themselves from COVID-19 infection.

They make sure we use our nose mask, they do temperature check before you come in, even at the gate they tell you to put your mask on (IDI, Participants 20 , Male 75 years). I simply follow the laid preventive measures and I keep myself clean in the house’ (IDI , Participant 4 , Female 84 years) . I was just doing what I was supposed to do and didn’t do what i wasn’t supposed to . For example , I have been avoiding crowded places . I have not attended Jumat service since the pandemic began rather , my family and I observe our prayers together at home (IDI , Participant 3 , Male 63 years) .

A couple of the patients with diabetes mellitus relied on the frequent updates on COVID-19 from the mass media as a coping mechanism against the pandemic.

I listened to health programs on the radio and I adhered to their health advices and I also took precautions. It was the precautionary messages and COVID-19 jingles delivered by newscasters on the radio I listened and adhered to (IDI, Participants 8, Female , 52 years).

A few of the participants averred that though they were aware of the telehealth service provided by the clinic, they did not utilize it as a coping mechanism. This is vivid in the opinion of some participants.

During the COVID I received text messages inviting me to come for my check up. But I didn’t come ooo!. But they’re trying (IDI Participants 11, Female 65 years). I didn’t because there was no reason for me to call them ( IDI , Participants 3 , Male 63 years) .

One of the patients opined that they were not aware of the telehealth service provided by the clinic. The provision of the telehealth service was helpful as it came as a timely intervention for some patients who utilized it. This is evident in the response of one of the participants, who opined thus:

Yes during the pandemic when we wanted to see the doctor, we were told to call him on the phone, when I called the doctor I was told the drugs to buy (IDI, Participants 30 , Female 44 years).

Reasons for low subscription to telehealth.

The findings of the study revealed that despite the provision of telehealth service as a coping mechanism, there are however some limitations to its use among patients with diabetes mellitus in University College Hospital.

One of the diabetes mellitus patients opined that he did not use it because a need to utilize the service did not arise. The excerpt below encapsulates this.

I didn’t because there was no reason for me to call them (IDI, Participants 3, Male 63 years)

Also, a level of full awareness regarding telehealth has not been reached among diabetes mellitus patients in the clinic; as such, a few patients did not utilize the service because they were unaware of it.

No, I did not. I wasn’t aware of that service (IDI, Participants 4, Female 84 years). No, I am not aware of it (IDI, Participants 12, Female 28 years).

Dangerous mechanisms employed by patients with diabetes mellitus in the clinic.

The study revealed the employment of negative mechanisms by diabetes mellitus patients in the clinic. This is evident in the excerpts below:

The use of herbal medicines

I used some traditional herbs to also compliment my medications. I drank the juice from boiled mango leaves and ginger. I also took my injections. I stayed indoors and maintain social distancing the few times I go out. Most times even if I feel like going out, my parents will not allow me go out because they know that I am more vulnerable to COVID-19 ( IDI, Participants 12, female, 28 years). I do a lot of steaming , herbal steaming , I cook dongoyaro leaves and the bark , we boil it , and we drink on the first day and subsequent days we just steam . Everybody in my house steams , we use menthol , we add menthol to it and we take a lot of supplements , vitamin C and D , that’s all we’ve done so far ( IDI , Participants 17 , Male 77 years) .

Usage of old prescriptions

I continued buying the drug that was prescribed to me since the last time I came to the clinic. By the time my health deteriorated recently and I have been coming to the clinic, the prescription was changed, but I was already used to my old prescription (IDI, Participant 12, Female, 28 years).

Inconsistency in clinic attendance

Many at times, most of us do not come to the clinic because we do not have money (IDI, Participant 9, Male 21 years).

Suggested coping mechanisms for the management of the University college hospital clinic and the government.

The patients with diabetes mellitus gave some recommendations on how the management of the University College Hospital Diabetes Clinic and the government can assist in easing the stressful conditions of diabetes mellitus patients during the COVID-19 pandemic. They are captured in the excerpts below:

Some participants want their medications to be subsidized and be easy to get.

What I think can be done is….You see, there is a saying that someone who has diabetes and does not want to die early needs money because it is not easy if I would be honest with you. I think what they can do is if they can help us subsidize our drugs. If we are given free drugs once in a while even if it is one drug, it would go a long way. What can be done is if they can help us that way once in a while then if they can help us find means through which our medications will not be scarce to get and they should help us such that it would not be too expensive than what we can bear. See… if it is not too expensive, there is nobody that does not want to use their medications and be healthy but the inability to afford the drugs makes one not to be faithful with the medications. Those are the ways I think they can help us ( IDI, Participant 12, Female 28 years). They can make the drugs cheaper, some can’t afford it and it led to their death(IDI, Participant 18, Female 52years) They should provide free drugs for us . Many at times , most of us do not come to the clinic because we do not have money ( IDI , Participant 9 , Male 21 years) .

Some patients with diabetes mellitus mentioned that the consultation fees should be reduced and this is captured in the narratives below.

One thing they can do is to reduce the consultation fees. Sometimes after paying the money, there won’t be anything left anymore. And sometimes, if we pay and the doctor is not around, the hospital won’t refund the money; that one is gone ( IDI, Participants 30, Female 44 years). We are not equal and not all buoyant . The consultation fee can be reduced and some things can be given for free , even if it is a few drugs ( IDI , Participants 13 , Female 49 years) .

Reduction of waiting time was one of the recommendations suggested by patients with diabetes for the management of University College Hospital. This is supported by the quote below;

Ah the major thing is that they should answer us in time. I understand that they will first do ward round but immediately they come back they should answer us ( IDI, Participants 11, Female 65 years).

One of the participants opined that there should be continuous or regular meetings which can be held in an open space within the clinic in other for them to be updated on their next line of action such as receiving medications, medication review, and adherence to COVID-19 protocols. The except below summarises this assertion.

We have an association but University College Hospital is not allowing us to hold meetings now, and its affecting a lot, through the association, we have had numerous lectures from physiotherapist and dieticians, to teach us more about our condition but our venue is small and due to COVID-19 regulations, those meetings can’t hold but we have pleaded with the management to allow us to do it outside in the open. Because the absence of those meetings is affecting some of us who have no clue as to go about something regarding our ailment ( IDI, Participants 26, Female 68 years).

Other suggested coping mechanisms include: opening more call lines to ensure efficient telehealth services, ensuring patients are treated politely in the clinic, and provision of hygienic toilet facilities.

This study explored the perception and coping mechanisms employed by patients with diabetes mellitus during the COVID-19 pandemic. We found that most participants were not fearful due to the pandemic; rather, they were optimistic while they played their part in ensuring they were safe. This is consistent with the findings of a study conducted in India [ 20 ], which revealed that most of the participants in their study were not so anxious about the pandemic but were rather optimistic. Also, the participants in this study demonstrated a clear understanding of those vulnerable to COVID-19, as some posited that anybody who defies the COVID-19 precautionary measures, people with underlying diseases such as diabetes, are susceptible to the virus. This attests to the supposition that COVID-19 sensitization and training were done in communities and health facilities. Also, surveillance mechanisms were improved in communities in Nigeria [ 20 ].

Literature has revealed that some health facilities had to shut down the entire clinic, including diabetes outpatients, to protect the health care providers and patients from contracting the virus [ 21 ]. Similarly, our findings show that the vulnerable nature of the patients informed why all appointments in the University College Hospital diabetes clinic were cancelled during the early period of the pandemic, after which they were rescheduled till January 2021. Furthermore, our study confirms compliance with WHO’s [ 4 ] recommendation on the use of telemedicine in other to bridge the health access gap caused by the pandemic. Hence, the physical presentation of patients during the pandemic was only encouraged when necessary. However, the study also revealed that patients who attend the diabetes clinic have been adhering to the COVID-19 precautionary protocols such as wearing masks and social distancing most especially when they attend the clinic since it reopened.

Contrary to the assertion made by Ahmed [ 5 ] that most of the public hospitals have been converted to COVID-19 treatment centers, which made lots of patients with comorbidities stranded when they needed medical attention, this study found that the University College Hospital diabetes clinic was only closed during the early period of the pandemic in order to ensure the safety of its staff and patients. In addition, the study revealed that the patients were not left stranded by the clinic as telehealth was provided as an alternative was provided. Patients also had access to healthcare personnel on an appointment basis after the clinic reopened in January 2021. Interestingly, the study revealed that patients were encouraged by the clinic to monitor their blood glucose daily by keeping records of it in a book. Another measure instituted was reducing the crowd in the outpatient clinic by extending patients’ appointment dates. This had the negative effect of limiting access to healthcare personnel during the pandemic. As a result, many patients with diabetes have had their routine screening deferred [ 11 ].

The findings of this study revealed that COVID-19 precautionary measures were strictly adhered to in the clinic, and patients have been compliant. This is, therefore, consistent with the recommendations of the WHO that preventive measures such as social distancing, the use of masks, and hand sanitisers should be adhered to [ 4 ]. Awareness of the availability of the telehealth service was high among the participants. However, awareness goes beyond knowing that a service exists. It is concerned with understanding and utilizing that knowledge [ 22 ].

Contrary to the findings of Hartmann-Boyce [ 23 ], which showed that many patients could not utilize the telehealth service because of their inability to afford the equipment needed for the process, findings from the in-depth interviews revealed that most patients did not utilize telehealth because they did not have reasons to use it. However, very few participants who claimed to utilize the service in this study reported that it was helpful.

The religious nature of Nigerian society is evident in the findings of this study, as most of the participants found succor from the worries and fears of the pandemic in the “Supreme Being”. This is consistent with the supposition that most patients with diabetes eased their fear during the pandemic by trusting the divine being and seeking supernatural protection from the same [ 24 ]. Reliance on the media for sensitization and updates on the pandemic was noted in the study. This affirms the views of Effiong et al. [ 25 ] in Nigeria, where the media was utilized to disseminate messages to the masses on how the virus can be spread and how it can be prevented. Some patients coped by being regular on their medications. This finding is consistent with similar studies [ 26 , 27 ], as it also revealed that some patients with diabetes in University College Hospital were able to cope when the clinic was closed during the early period of the pandemic by using their last prescriptions before the pandemic to procure more drugs.

Furthermore, the use of traditional herbs alongside medications was shown in the study. This is consistent with the findings from the key informant interviews. This confirms that most non-COVID-19 patients relied more on local medications and homemade remedies to cater for their health during the pandemic [ 28 ]. Evidence shows that the burden of diabetes management is more on patients with diabetes mellitus in Nigeria, as about 74.5% of the health care expenditure is self-financed by patients while the government provides only 25.5% [ 29 ]. This study found that interventions such as subsidisation, availability of drugs, and reduction of consultation fees would help patients cope better during the pandemic. In addition, approval of the resumption of the University College Hospital diabetes association meeting, shortening waiting time in clinics, creation of more call lines, polite treatment of patients, increased sensitization, and the provision of hygienic toilet facilities would help alleviate the stress of the pandemic on diabetes patients in University College Hospital.

Strengths and limitations

The study’s main strength is that it examined the perception and coping mechanisms of patients with diabetes mellitus in a tertiary health center during the COVID-19 pandemic. The qualitative nature of the study only permitted a small number of participants in the hospital to be interviewed; therefore, it is important to evaluate our findings carefully before extrapolating them to the entire country.

Implications for public health research

Based on the study’s findings, it is imperative for health professionals to routinely conduct psychological assessments for diabetes mellitus patients. Also, the health service managers can design a guidance and assistance programme for patients with diabetes mellitus intended to improve their ability to adopt coping mechanisms.

The study has shown that patients with diabetes mellitus were not fearful of the COVID-19 pandemic despite their status as diabetes mellitus patients. Diabetes mellitus patients were found to be adherent to the COVID-19 precautionary protocols. The health systems’ coping mechanisms to avert the pandemic’s negative implications were telehealth, encouragement of daily monitoring of sugar levels, and the provision of avenues for a medication review. Additionally, the patients relied on mass media advice and adherence to safety protocols to cope with COVID-19. Based on the study’s outcomes, the government and other healthcare stakeholders must reinforce the resilience of diabetes mellitus patients by alleviating their health burdens during the pandemic. This could be done by subsidizing the prices of drugs, tests, and consultation fees, improving the waiting and appointment system in the clinic, creating an online presence for the University College Hospital Diabetes Association Office, and employing more health personnel in the clinic.

Supporting information

S1 checklist. strengthening the reporting of observational studies in epidemiology statement checklist..

https://doi.org/10.1371/journal.pone.0309451.s001

S1 File. Study questionnaire.

https://doi.org/10.1371/journal.pone.0309451.s002

Acknowledgments

The authors express their appreciation to the University College Hospital, Ibadan, for the privilege of conducting the study within its diabetes clinic. We also thank everyone for their various contributions and assistance during the study.

• 1. Organization WH. Global report on diabetes: World Health Organization; 2016.
• 2. Organization WH. Diabetes 2022 [3rd November, 2022]. Available from: http://www.who.int/mediacentre/factsheets/fs312/en/ .
• 3. Programme UND. The Impact of the COVID-19 Pandemic in Nigeria: A Socio-Economic Analysis 2020 [4th November, 2022].
• 4. Organization WH. Rapid assessment of continuity of essential health services (EHS) during the COVID-19 pandemic 2020 [3rd November, 2022].
• View Article
• Google Scholar
• PubMed/NCBI
• 17. (NCDC). NCfDCaP. NCDC COVID-19 report dashboard 2020 [cited 2020 July 1, 2020]. Available from: https://covid19.ncdc.gov.ng/ .