CARDIOVASCULAR JOURNAL OF AFRICA • Vol 23, No 1, February 2012
10
AFRICA
Malay, European and African ancestry,
29
and is relatively poor.
However, the INTERHEART and Heart of Soweto studies have
shown that the common risk factors for heart diseases in Africans
resemble those observed in Western societies.
19,37
Until such time
as a validated and recalibrated equation has been developed, this
predictive risk calculator may provide a rough estimate of CVD
risk in the absence of any reliable tool.
As indicated, approximately a third of the study group (mainly
those under 35 years) were self-selected. However given the
relatively low incidence and ignorance of CVD risk, particularly
in this age group, it is unlikely to have biased the findings of
this study.
Conclusion
Although the estimated CVD risk was highest in those with
hyperglycaemia, it was also evident in normal-weight, normo-
glycaemic and younger individuals. Results from this pilot
study have important public health implications as CVD is often
underestimated in the young. A significant number of partici-
pants were unaware of their diabetic status, pointing to the need
to identify this group as a potentially high-risk CVD group.
Due to inter-convertibility of lipids and BMI in the risk-esti-
mation equation, CVD risk can easily be estimated in a primary
healthcare setting. In South Africa, there has been mounting
pressure for the reorganisation of the primary healthcare system
to develop an approach for the management of chronic diseases.
In addition to improving the primary healthcare system, another
approach would be the inclusion of CVD education in school and
university curricula, as is currently being done for HIV/AIDS.
This may also assist in reducing the prevalence of obesity and
the metabolic syndrome, which we recently reported in South
African children.
43
We thank the Bellville South community for participating in the study. This
research was supported by a grant from the University Research Fund of the
Cape Peninsula University of Technology, South Africa.
References
1.
Levitt NS, Katzenellenbogen JM, Bradshaw D, Hoffman MN, Bonnici
F. The prevalence and identification of risk factors for NIDDM in
urban Africans in Cape Town, South Africa.
Diabetes Care
1993;
16
:
601–607.
2.
Erasmus RT, Blanco Blanco E, Okesina AB, Matsha T, Gqweta Z, Mesa
JA. Prevalence of diabetes mellitus and impaired glucose tolerance in
factory workers from Transkei, South Africa.
S Afr Med J
2001;
91
:
157–160.
3.
Motala AA, Pirie FJ, Gouws E, Amod A, Omar MA. High incidence of
type 2 diabetes mellitus in South African Indians: a 10-year follow-up
study.
Diabet Med
2003;
20
: 23–30.
4.
Gu K, Cowie CC, Harris MI. Mortality in adults with and without
diabetes in a national cohort of the US population, 1971–1993.
Diabetes Care
1998;
21
: 1138–1145.
5.
Bradshaw D, Groenewald P, Laubscher R, Nannan N, Nojilana B,
Norman R,
et al
. Initial burden of disease estimates for South Africa,
2000.
S Afr Med J
2003;
93
: 682–688.
6.
Bradshaw D, Norman R, Pieterse D, Levitt NS; South African
Comparative Risk Assessment Collaborating Group. Estimating the
burden of disease attributable to diabetes in South Africa in 2000.
S Afr
Med J
2007;
97
: 700–706.
7.
DECODE study group. Is the current definition for diabetes relevant to
mortality risk from all causes and cardiovascular and noncardiovascular
diseases?
Diabetes Care
2003;
26
: 688–696.
8.
Bartnik M, Rydén L, Ferrari R, Malmberg K, Pyörälä K, Simoons M,
et al
; Euro Heart Survey investigators. The prevalence of abnormal
glucose regulation in patients with coronary artery disease across
Europe. The Euro Heart Survey on diabetes and the heart.
Eur Heart J
2004; 25: 1880–1890.
9.
Temelkova-Kurktschiev TS, Koehler C, Henkel E, Leonhardt W,
Fuecker K, Hanefeld M. Postchallenge plasma glucose and glycemic
spikes are more strongly associated with atherosclerosis than fasting
glucose or HbA1c level.
Diabetes Care
2000;
23
: 1830–1834.
10. Petersen JL, McGuire DK. Impaired glucose tolerance and impaired
fasting glucose--a review of diagnosis, clinical implications and
management.
Diab Vasc Dis Res
. 2005;
2
: 9–15.
11. Anderson KM, Odell PM, Wilson PW, Kannel WB. Cardiovascular
disease risk profiles.
Am Heart J
1991;
121
: 293–298.
12. Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer
G,
et al
; SCORE project group. Estimation of ten-year risk of fatal
cardiovascular disease in Europe: the SCORE project.
Eur Heart J
2003;
24
: 987–1003.
13. D’Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M,
Massaro JM, Kannel WB. General cardiovascular risk profile for use
in primary care: the Framingham Heart Study.
Circulation
2008;
117
:
743–753.
14. Coleman R, Stevens R, Holman R. The Oxford Risk Engine: a cardio-
vascular risk calculator for individuals with or without type 2 diabetes.
Diabetes
2007;
56
( Suppl 1): A170.
15. Simmons RK, Coleman RL, Price HC, Holman RR, Khaw KT,
Wareham NJ, Griffin SJ. Performance of the UK Prospective Diabetes
Study Risk Engine and the Framingham Risk Equations in Estimating
Cardiovascular Disease in the EPIC- Norfolk Cohort.
Diabetes Care
2009;
32
: 708–713.
16. Pencina MJ, D’Agostino RB Sr, Larson MG, Massaro JM, Vasan RS.
Predicting the 30-year risk of cardiovascular disease: the framingham
heart study.
Circulation
2009;
119
: 3078–3084.
17. Hobbs FD, Jukema JW, Da Silva PM, McCormack T, Catapano AL.
Barriers to cardiovascular disease risk scoring and primary prevention
in Europe.
Q J Med
2010 Aug 4. [Epub ahead of print].
18. D’Agostino RB Sr, Grundy S, Sullivan LM, Wilson P; CHD risk
prediction group. Validation of the Framingham coronary heart disease
prediction scores: results of a multiple ethnic groups investigation. J
Am Med Assoc 2001;
286
: 180–187.
19. Steyn K, Sliwa K, Hawken S, Commerford P, Onen C, Damasceno A,
et al
; INTERHEART investigators in Africa. Risk factors associated
with myocardial infarction in Africa: the INTERHEART Africa study.
Circulation
2005;
112
: 3554–3561.
20. Mayosi BM, Flisher AJ, Lalloo UG, Sitas F, Tollman SM, Bradshaw
D. The burden of non-communicable diseases in South Africa.
Lancet
2009;
374
: 934–947.
21. City of Cape Town Census 2001
(21 June
2007).
22. Ewing JA. Detecting alcoholism: The CAGE questionnaire.
J Am Med
Assoc
1984;
252
: 1905–1907.
23. Bradshaw D, Bourne D, Schneider M, Sayed R. Mortality patterns of
chronic diseases of lifestyle in South Africa. In: Fourie J, Steyn K,
eds.
Chronic Diseases of Lifestyle in South Africa.
Medical Research
Council (MRC) Technical Report. Tygerberg: MRC, 1995; 5–31.
24. World Health Organization (WHO). International Society of
Hypertension Guidelines for the Management of Hypertension.
J
Hypertens
1999;
17
: 151–183.
25. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of
diabetes mellitus and its complications. Part 1: diagnosis and classifi-
cation of diabetes mellitus provisional report of a WHO consultation
.
Diabet Med
1998;
15
: 539–553.
26. Narayan KM, Boyle JP, Thompson TJ, Gregg EW, Williamson DF.
Effect of BMI on lifetime risk for diabetes in the US.
Diabetes Care
2007;
30
:1562–1566.
27. Fox CS, Pencina MJ, Wilson PW, Paynter NP, Vasan RS, D’Agostino
RB Sr. Lifetime risk of cardiovascular disease among individuals with
and without diabetes stratified by obesity status in the Framingham
heart study.
Diabetes Care
2008;
31
: 1582–1584.
