Dyslipidemias and cardiovascular risk scores in urban and rural populations in north-western Tanzania and southern Uganda
Autoři:
Bazil Kavishe aff001; Fiona Vanobberghen aff001; David Katende aff003; Saidi Kapiga aff001; Paula Munderi aff003; Kathy Baisley aff002; Samuel Biraro aff003; Neema Mosha aff001; Gerald Mutungi aff004; Janneth Mghamba aff005; Peter Hughes aff003; Liam Smeeth aff002; Heiner Grosskurth aff001; Robert Peck aff001
Působiště autorů:
Mwanza Intervention Trials Unit, National Institute for Medical Research, Mwanza, Tanzania
aff001; MRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, United Kingdom
aff002; Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Research Unit, Entebbe, Uganda
aff003; Ministry of Health, Kampala, Uganda
aff004; Ministry of Health Community Development Gender Elderly and Children, Dar es Salaam, Tanzania
aff005; Weill Bugando School of Medicine, Mwanza, Tanzania
aff006; Weill Cornell Medical College, New York, NY, United States of America
aff007
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223189
Souhrn
Background
Dyslipidemia is a leading risk factor for atherosclerotic cardiovascular disease. There are few published epidemiological data regarding dyslipidemia in Africa. We determined full lipid and apolipoprotein profiles and investigated factors associated with lipid levels in urban and rural populations of north-western Tanzania and southern Uganda.
Methods
We conducted a cross-sectional survey of randomly-selected, community-dwelling adults (≥18yrs) including five strata per country: one municipality, two district towns and two rural areas. Participants were interviewed and examined using the World Health Organization STEPwise survey questionnaire. Serum levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and apolipoproteins were measured. Factors associated with mean lipid levels were assessed by multivariable linear regression. Framingham 10-year cardiovascular risk scores were calculated with and without lipids.
Results
One-third of adults in the study population had dyslipidemia. Low high-density lipoprotein cholesterol affected 32–45% of rural adults. High total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B were found in <15% of adult population in all strata, but were more common in urban adults. Factors independently associated with higher mean low-density lipoprotein cholesterol and apolipoprotein B were female gender, older age, higher education, higher income, obesity, and hypertension. Framingham cardiovascular risk scores with and without lipids yielded similar results and 90% of study subjects in all strata were classified as “low risk”. Among older adults (>55 years), 30% were classified as “high” or “very high” risk.
Conclusions
Dyslipidemias are common among adults in north-western Tanzania and southern Uganda affecting one third of adult population. Overall, cardiovascular risk scores are low but high risk scores are common with older adults. Health services designed and equipped to diagnose and treat dyslipidemia are urgently needed.
Klíčová slova:
Cholesterol – Lipids – Obesity – Rural areas – Tanzania – Uganda – Apolipoproteins
Zdroje
1. Steyn K, Sliwa K, Hawken S, Commerford P, Onen C, Damasceno A, et al. Risk factors associated with myocardial infarction in Africa: The INTERHEART Africa Study. Circulation. 2005;112(23):3554–61. doi: 10.1161/CIRCULATIONAHA.105.563452 16330696
2. O'Donnell MJ, Xavier D, Liu L, Zhang H, Chin SL, Rao-Melacini P, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet. 2010;376(9735):112–23. doi: 10.1016/S0140-6736(10)60834-3 20561675
3. Forouzanfar MH, Afshin A, Alexander LT, Anderson HR, Bhutta ZA, Biryukov S, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1659–724. doi: 10.1016/S0140-6736(16)31679-8 27733284
4. Danaei G, Singh GM, Paciorek CJ, Lin JK, Cowan MJ, Finucane MM, et al. The global cardiovascular risk transition: associations of four metabolic risk factors with national income, urbanization, and Western diet in 1980 and 2008. Circulation. 2013;127(14):1493–502. doi: 10.1161/CIRCULATIONAHA.113.001470 23481623
5. Sliwa K, Lecour S, Carrington MJ, Raal FJ, Stewart S, Lyons JG, et al. Different lipid profiles according to ethnicity in the Heart of Soweto study cohort of de novo presentations of heart disease: cardiovascular topics. Cardiovasc J Afr. 2012;23(7):389–95. doi: 10.5830/CVJA-2012-036 22914997
6. Karaye KM, Habib AG. Dyslipidaemia in patients with established cardiovascular disease in Sub-Saharan Africa: a systematic review and meta-analysis. Eur J Prev Cardiol. 2014;21(6):682–91. doi: 10.1177/2047487312460018 22952291
7. Bimenya G, Okot J, Nangosa H, Anguma S, Byarugaba W. Plasma cholesterol and related lipid levels of seemingly healthy public service employees in Kampala, Uganda. Afr Health Sci. 2006;6(3):139–44. doi: 10.5555/afhs.2006.6.3.139 17140334
8. Mondo CK, Otim MA, Musoke R, Orem J, Akol G. The prevalence and distribution of non-communicable diseases and their risk factors in Kasese district, Uganda. Cardiovasc J Afr. 2013;24(3):52–7. doi: 10.5830/CVJA-2012-081 23736126
9. Asiki G, Murphy GA, Baisley K, Nsubuga RN, Maher D, Karabarinde A, et al. Prevalence of dyslipidaemia and associated risk factors in a rural population in South-Western Uganda: a community based survey. PloS ONE. (2017) Correction;12(2): e0173133. doi: 10.1371/journal.pone.0173133 28235105
10. Njelekela M, Kuga S, Nara Y, Ntogwisangu J, Masesa Z, Mashalla Y, et al. Prevalence of obesity and dyslipidemia in middle-aged men and women in Tanzania, Africa: relationship with resting energy expenditure and dietary factors. J Nutr Sci Vitaminol. 2002;48(5):352–8. doi: 10.3177/jnsv.48.352 12656207
11. Sabir A, Isezuo S, Ohwovoriole A, Fasanmade O, Abubakar S, Iwuala S, et al. Rural-urban difference in plasma lipid levels and prevalence of dyslipidemia in Hausa-Fulani of north-western Nigeria. Ethn Dis. 2013;23(3):374–8. 23914426
12. Mbalilaki J, Hellènius M-L, Masesa Z, Høstmark A, Sundquist J, Strømme S. Physical activity and blood lipids in rural and urban Tanzanians. Nutr Metab Cardiovasc Dis. 2007;17(5):344–8. doi: 10.1016/j.numecd.2006.03.003 17134959
13. Delisle H, Ntandou G, Sodjinou R, Couillard C, Després J-P. At-risk serum cholesterol profile at both ends of the nutrition spectrum in West African adults? The Benin study. Nutrients. 2013;5(4):1366–83. doi: 10.3390/nu5041366 23603997
14. Steyn K, Rossouw J, Weight M, Fourie J, Benade A, Jooste P, et al. Apolipoprotein B levels and related factors in a rural white South African community-the CORIS study. S Afr Med J. 1996;86(4):359–64. 8693373
15. Gomo ZA. Concentrations of lipids, lipoprotein, and apolipoproteins in serum of Zimbabwean Africans. Clin Chem. 1985;31(8):1390–2. 3926349
16. Kesteloot H, Oviasu VO, Obasohan AO, Olomu A, Cobbaert C, Lissens W. Serum lipid and apolipoprotein levels in a Nigerian population sample. Atherosclerosis. 1989;78(1):33–8. doi: 10.1016/0021-9150(89)90156-1 2502993
17. Kavishe B, Biraro S, Baisley K, Vanobberghen F, Kapiga S, Munderi P, et al. High prevalence of hypertension and of risk factors for non-communicable diseases (NCDs): a population based cross-sectional survey of NCDS and HIV infection in Northwestern Tanzania and Southern Uganda. BMC Med. 2015;13(126):1–21.
18. Tanzania National Bureau of Statistics. 2012 Population and Housing Census—Population Distribution by Administrative Areas. Dar es Salaam: National Bureau of Statistics; 2013.
19. Uganda Bureau of Statistics. National Population and Housing Census 2014—Main Report. Kampala: Uganda Bureau of Statistics; 2016.
20. World Health Organisation. Noncommunicable diseases and their risk factors [homepage on the Internet] [cited 2012 Jan 12 ]. Available from: http://www.who.int/ncds/surveillance/steps/instrument/en/.
21. Saunders JB, Aasland OG, Babor TF, De la Fuente JR, Grant M. Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption‐II. Addiction. 1993;88(6):791–804. doi: 10.1111/j.1360-0443.1993.tb02093.x 8329970
22. National Cholesterol Education Program Expert Panel. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Final Report. Circulation. 2002;106(25):3145–421.
23. Kinosian B, Glick H, Garland G. Cholesterol and coronary heart disease: predicting risks by levels and ratios. Ann Intern Med. 1994;121(9):641–7. doi: 10.7326/0003-4819-121-9-199411010-00002 7944071
24. Roche method manual for COBAS INTEGRA® 400/700/800 2006–10,V4EN
25. Roche method manual for COBAS INTEGRA® 400/700/800 2007–09,V5EN
26. World Health Organisation. Waist Circumference and Waist–Hip Ratio: Report of a WHO Expert Consultation Geneva, 8–11 December 2008. Geneva, Switzerland: 2011.
27. Klug EQ, Raal F, Marais A, Taskinen M, Dalby A, Schamroth C, et al. South African Dyslipidaemia Guideline Consensus Statement: A joint statement from the South African Heart Association (SA Heart) and the Lipid and Atherosclerosis Society of Southern Africa (LASSA). JEMDSA. 2012;17(3):155–65.
28. World Health Organisation. Prevention of Cardiovascular Disease. Geneva, Switzerland: WHO, 2007.
29. Framingham Heart Study. Cardiovascular Disease (10-year risk) [homepage on the Internet] [cited 2015 September 23]. Available from: https://www.framinghamheartstudy.org/fhs-risk-functions/cardiovascular-disease-10-year-risk/.
30. Victora CG, Huttly SR, Fuchs SC, Olinto M. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol. 1997;26(1):224–7. doi: 10.1093/ije/26.1.224 9126524
31. Peer N, Steyn K, Lombard C, Gwebushe N, Levitt N. A high burden of hypertension in the urban black population of Cape Town: The Cardiovascular Risk in Black South Africans (CRIBSA) Study. PLoS ONE. 2013;8(11):e78567. doi: 10.1371/journal.pone.0078567 24250798
32. Murphy GA, Asiki G, Ekoru K, Nsubuga RN, Nakiyingi-Miiro J, Young EH, et al. Sociodemographic distribution of non-communicable disease risk factors in rural Uganda: a cross-sectional study. Int J Epidemiol. 2013;42(6):1740–53. doi: 10.1093/ije/dyt184 24191304
33. Carroll MD, Lacher DA, Sorlie PD, Cleeman JI, Gordon DJ, Wolz M, et al. Trends in serum lipids and lipoproteins of adults, 1960–2002. Jama. 2005;294(14):1773–81. doi: 10.1001/jama.294.14.1773 16219880
34. Coban N, Onat A, Guclu-Geyik F, Can G, Erginel-Unaltuna N. Sex- and Obesity-specific Association of Aromatase (CYP19A1) Gene Variant with Apolipoprotein B and Hypertension. Arch Med Res. 2015;46(7):564–71. doi: 10.1016/j.arcmed.2015.09.004 26415088
35. Albarrati AM, Alghamdi MSM, Nazer RI, Alkorashy MM, Alshowier N, Gale N. Effectiveness of Low to Moderate Physical Exercise Training on the Level of Low-Density Lipoproteins: A Systematic Review. Biomed Res Int. 2018 Nov 1. 2018:5982980. doi: 10.1155/2018/5982980 30515408
36. Te Morenga LA, Howatson AJ, Jones RM, Mann J. Dietary sugars and cardiometabolic risk: systematic review and meta-analyses of randomized controlled trials of the effects on blood pressure and lipids. Am J Clin Nutr. 2014;100(1):65–79. doi: 10.3945/ajcn.113.081521 24808490
37. Gould AL, Rossouw JE, Santanello NC, Heyse JF, Furberg CD. Cholesterol reduction yields clinical benefit: impact of statin trials. Circulation. 1998;97(10):946–52. doi: 10.1161/01.cir.97.10.946 9529261
38. Raal F, Schamroth C, Blom D, Marx J, Rajput M, Haus M, et al. CEPHEUS SA: a South African survey on the undertreatment of hypercholesterolaemia: cardiovascular topics. Cardiovasc J Afr. 2011;22(5):234–40. doi: 10.5830/CVJA-2011-044 21922121
39. Peck R, Mghamba J, Vanobberghen F, Kavishe B, Rugarabamu V, Smeeth L, et al. Preparedness of Tanzanian health facilities for outpatient primary care of hypertension and diabetes: a cross-sectional survey. Lancet Glob Health. 2014;2(5):e285–e92. doi: 10.1016/S2214-109X(14)70033-6 24818084
40. Katende D, Mutungi G, Baisley K, Biraro S, Ikoona E, Peck R, et al. Readiness of Ugandan health services for the management of outpatients with chronic diseases. Trop Med Int Health. 2015;20(10):1385–95. doi: 10.1111/tmi.12560 26095069
41. Gyakobo M, Amoah AG, Martey-Marbell D-A, Snow RC. Prevalence of the metabolic syndrome in a rural population in Ghana. BMC Endocr Disord. 2012;12(1):25.
42. Emerging Risk Factors Collaboration. Major lipids, apolipoproteins, and risk of vascular disease. Jama. 2009;302(18):1993–2000. doi: 10.1001/jama.2009.1619 19903920
43. Toure M, Sall M, Gauthier F, Weill J, Mouray H, Fall M. Apolipoprotein A1 as an early index of protein-energy malnutrition. Eur J Clin Nutr. 1991;45(10):511–4. 1782923
44. Gaziano TA, Abrahams-Gessel S, Denman CA, Montano CM, Khanam M, Puoane T, et al. An assessment of community health workers' ability to screen for cardiovascular disease risk with a simple, non-invasive risk assessment instrument in Bangladesh, Guatemala, Mexico, and South Africa: an observational study. Lancet Glob Health. 2015;3(9):e556–e63. doi: 10.1016/S2214-109X(15)00143-6 26187361
45. Ortegón M, Lim S, Chisholm D, Mendis S. Cost effectiveness of strategies to combat cardiovascular disease, diabetes, and tobacco use in sub-Saharan Africa and South East Asia: mathematical modelling study. Br Med J. 2012;e607:1–15.
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