A population-based survey of prevalence of diabetes and correlates in an urban slum community in Nairobi, Kenya

BMC Public Health

Kenneth K Mutai³  Erastus K Njeru²  C Fredrick Otieno¹  Elijah K Njau¹  Rosemary Wanjiru¹  Mark D Joshi¹  Richard Ayah² 

[1] School of Medicine, College of Health Sciences, University of Nairobi, Nairobi, Kenya;School of Public Health, College of Health Sciences, University of Nairobi, P.O. BOX 19676–00202, KNH, Nairobi, Kenya;University of Nairobi Partnership for Advanced Care and Treatment (PACT), Centre of Excellence, Nairobi, Kenya

关键词: Epidemiological transition;    Diabetes correlates;    Sub-Saharan Africa;    Urban slum;    Diabetes mellitus/epidemiology;   

Others  :  1162310
DOI  :  10.1186/1471-2458-13-371

 received in 2012-10-14, accepted in 2013-04-04,  发布年份 2013

【 摘 要 】

Background

Urban slum populations in Africa continue to grow faster than national populations. Health strategies that focus on non-communicable diseases (NCD) in this segment of the population are generally lacking. We determined the prevalence of diabetes and associated cardiovascular disease (CVD) risk factors correlates in Kibera, Nairobi’s largest slum.

Methods

We conducted a population-based household survey utilising cluster sampling with probability proportional to size. Households were selected using a random walk method and consenting residents aged 18 years and above were recruited. The WHO STEPS instrument was administered. A random capillary blood sugar (RCBS) was obtained; known persons with diabetes and subjects with a RCBS >11.1 had an 8 hours fasting blood sugar (FBS) drawn. Diabetes was defined as a RCBS of ≥ 11.1 mmol/l and a FBS of ≥ 7.0 mmol/l, or a prior diagnosis or receiving diabetes drug treatment.

Results

Out of 2061 enrolled; 50.9% were males, mean age was 33.4 years and 87% had a minimum of primary education. Only 10.6% had ever had a blood sugar measurement. Age adjusted prevalence of diabetes was 5.3% (95% CI 4.2-6.4) and prevalence increased with age peaking at 10.5% (95% CI 6.8-14.3%) in the 45–54 year age category. Diabetes mellitus (DM) correlates were: 13.1% smoking, 74.9% alcohol consumption, 75.7% high level of physical activity; 16.3% obese and 29% overweight with higher rates in women.

Among persons with diabetes the odds of obesity, elevated waist circumference and hypertension were three, two and three fold respectively compared to those without diabetes. Cardiovascular risk factors among subjects with diabetes were high and mirrored that of the entire sample; however they had a significantly higher use of tobacco.

Conclusions

This previously unstudied urban slum has a high prevalence of DM yet low screening rates. Key correlates include cigarette smoking and high alcohol consumption. However high levels of physical activity were also reported. Findings have important implications for NCD prevention and care. For this rapidly growing youthful urban slum population policy makers need to focus their attention on strategies that address not just communicable diseases but non communicable diseases as well.

【 授权许可】

   
2013 Ayah et al.; licensee BioMed Central Ltd.

【 参考文献 】

• [1]World Health Organization: Chronic diseases: a vital investment. Geneva: World Health Organization; 2005.
• [2]Murray CJL, Lopez AD (Eds): The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020. Boston, Mass: Harvard, School of Public Health; (Global burden of disease and injuries Vol 1); 1996.
• [3]World Health Organization: World Health Report 2000: health systems: improving performance. Geneva: World Health Organization; 2000.
• [4]Shaw JE, Sicree RA, Zimmet PZ: Global estimates for the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010, 87:4-14.
• [5]Millar WJ, Wigle DT: Socio-economic disparities in risk factors for cardiovascular diseases. CAN MED ASSOC J 1986, 134:127-132.
• [6]Ismail AA, Beeching GV, Gill GV, Bellis MA: Capture-recapture-adjusted prevalence rates of type 2 diabetes are related to social deprivation. Q J Med 1999, 92:707-710.
• [7]Walker JJ, Walker JJ, Livingstone SJ, Colhoun HM, Lindsay RS, McKnight JA, Morris AD, Petrie JR: Effect of socioeconomic status on mortality among people with type 2 diabetes: a study from the Scottish diabetes research network epidemiology group. Diabetes Care 2011, 34(5):1127-1132.
• [8]Robbins JM, Vaccarino V, Zhang H, Kasl SV: Excess type 2 diabetes in African-American women and men aged 40–74 and socioeconomic status: evidence from the third national health and nutrition examination survey. J Epidemiol Community Health 2000, 54(11):839-845.
• [9]Anand K, Shah B, Yadav K, Singh R, Mathur P: Are the urban poor vulnerable to non-communicable diseases? A survey of risk factors for non-communicable diseases in urban slums of Faridabad. Natl Med J India 2007, 28(3):115-120.
• [10]Mbanya NJC, Ayesha AM, Sobngwi E, Assah FK, Enoru S: Diabetes in sub-Saharan Africa. Lancet 2010, 375:2254-2266.
• [11]Levitt NS: Diabetes in Africa: epidemiology, management and health care challenges. Heart 2008, 94:1376-1382.
• [12]Christensen DI, Friss H, Mwaniki DL, Kilonzo B, Tetens I, Boit MK, Omondi B, Kaduka L, Borch-Johnsen K: Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya. Diabetes Res ClinPract 2009, 84(3):303-310.
• [13]Yusuf S, Reddy S, Ounpuu S, Anand S: Global burden of cardiovascular diseases. Part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation 2001, 104:2746-2753.
• [14]UNFPA: UNFPA state of world population 2007: unleashing the potential of urban growth. New York: UNFPA; 2007.
• [15]Kenya National Bureau of Statistics (KNBS): Kenya population and housing census. Nairobi: Kenya National Bureau of Statistics; 2009.
• [16]United Nations Human Settlements Programme (UN-HABITAT): Nairobi urban sector profile. Nairobi: UN-HABITAT; 2006.
• [17]Department of Economic and Social Affairs United Nations: Designing Household Survey Samples: Practical Guidelines (Series F) No.98. United Nations. Statistics Division, ed. New York: United Nations, Department of Economic and Social Affairs; 2008.
• [18]World Health Organization (WHO): STEP wise approach to surveillance (STEPS). Geneva: World Health Organization; Available from: URL: http://www.who.int/chp/steps/en/ webcite (accessed May 1 2010)
• [19]World Health Organization (WHO): Diabetes mellitus: report of a WHO study group (Technical Report Series no 727). Geneva: World Health Organization; 1985.
• [20]Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr: National high blood pressure education program coordinating committee. Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension 2003, 42:1206-1252.
• [21]Ahmad OB, Boschi-Pinto C, Lopez AD, Murray CJL, Lozano R, Inoue M: Age Standardisation of rates: a New WHO standard. Global program on evidence for health policy discussion paper series: No 31. Geneva: World Health Organisation; 2001.
• [22]Connolly V, Unwin N, Sherriff P, Bilous R, Kelly W: Diabetes prevalence and socioeconomic status: a population based study showing increased prevalence of type II diabetes in the deprived areas. J Epidemiol Community Health 2000, 54:173-177.
• [23]Misra A, Pandy RM, Devi JR, Shama R, Vikram N: High prevalence of diabetes, obesity and dyslipidaemia in an urban slum population in Northern India. Int J Obes 2001, 25:1722-1729.
• [24]Ezeamama AE, Viali S, Tuitele J, McGarvey ST: The influence of socioeconomic factors on cardiovascular disease risk factors in the context of economic development in the Samoan archipelago. Natl Med J India 2006, 63(10):2533-2545.
• [25]International Diabetes Federation (IDF): Diabetes atlas. 3rd edition. Brussels: International Diabetes Federation; 2006.
• [26]Hall V, Thomsen RW, Henriksen O, Lohse N: Diabetes in Sub Saharan Africa 1999–2011: epidemiology and public health implications. A systematic review. BMC Publ Health 2011, 11:564. BioMed Central Full Text
• [27]Kilele AKM: Adult literacy in Kenya, Presentation on the results of the Kenya National Adult and Literacy Survey (KNALS). 2006. http://www.knbs.or.ke/downloads/pdf/KNALS2007.pdf webcite, Accessed on 26th February 2013
• [28]Jeon CY, Murray MB: Diabetes mellitus increases the risk of active tuberculosis: a systematic review of 13 observational studies. PLoS Med 2008, 5(7):e152.
• [29]Stevenson CR, Forouhi NG, Roglic G, Williams BG, Lauer JA, Dye C, Unwin N: Diabetes and tuberculosis: the impact of the diabetes epidemic on tuberculosis incidence. BMC Publ Health 2007, 7:234. BioMed Central Full Text
• [30]Wild S, Richard S, Gojka A, Aders G, Hilary K: Global prevalence of diabetes. Estimates for the year 2000 and projections for 2030. Diabetes Care 2004, 27:1047-1053.
• [31]Mathenge W, Foster A, Kuper H: Urbanization, ethnicity and cardiovascular risk in a population in transit in Nakuru, Kenya: a population based survey. BMC Publ Health 2010, 10:569-581. BioMed Central Full Text
• [32]Sobhana R, Rao PR, Lavanya A, Williams R, Vijay V, Ramchandran A: Expenditure on health care incurred by diabetic subjects in a developing country-a study from southern India. Diabetes Res ClinPract 2000, 48:37-42.
• [33]Desgroppes A, Sophie T: Kibera: The Biggest Slum in Africa? Les Cahiers de l'Afrique de l'Est 2011, 44:23-34.
• [34]Agyei-Mensah S, Aikins ADG: Epidemiological transition and the double burden of disease in Accra, Ghana. J Urban Health 2010, 87:879-897.