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CARDIOVASCULAR JOURNAL OF AFRICA • Volume 31, No 6, November/December 2020

318

AFRICA

this study are those of the authors, and the above-mentioned funding sources

do not accept any liability in regard thereto. The authors acknowledge the

participants and research assistants for their contribution towards the success

of this study. The shopping mall owners are also acknowledged for allowing

data collection on their premises.

References

1.

Agyemang C, Boatemaa S, Frempong GA, Aikins A.

Metabolic

Syndrome

. Switzerland: Springer International, 2015.

2.

Letamo G. The prevalence of, and factors associated with overweight

and obesity in Botswana.

J Biosoc Sci

2011;

43

: 75–84.

3.

Keetile, M, Navaneetham, K, Letamo, G. Patterns and determinants

of overweight and obesity among adults in Botswana. European

Population Conference 2016, Mainz, Germany, 2016.

4.

Tapera R, Merapelo MT, Tumoyagae T, Maswabi TM, Erick P, Letsholo

B,

et al.

The prevalence and factors associated with overweight and

obesity among University of Botswana students.

Cogent Med

2017;

4

(1): 1357249.

5.

Castro AVB, Kolka CM, Kim S, Bergman RN. Obesity, insulin

resistance and comorbidities – Mechanisms of association.

Arq Bras

Endocrinol Metabol

2014;

58

(6): 600–609.

6.

Vazquez G, Duval S, Jacobs DR, Silventoinen K. Comparison of body

mass index, waist circumference, and waist/hip ratio in predicting inci-

dent diabetes: a meta-analysis.

Epidemiol Rev

2007;

29

: 115–128.

7.

Rahman M, Temple JR, Breitkopf CR, Berenson AB. Racial differences

in body fat distribution among reproductive-aged women.

Metabolism

2009;

58

(9): 1329–1337.

8.

Crowther NJ, Norris SA. The current waist circumference cut point used

for the diagnosis of metabolic syndrome in sub-Saharan African women

is not appropriate.

PLoS One

2012;

7

(11): e48883.

9.

Alberti KG, Zimmet P, Shaw J. Metabolic syndrome – a new world-wide

definition. A Consensus Statement from the International Diabetes

Federation.

Diabet Med

2006;

23

(5): 469–480.

10. Carr DB, Utzschneider KM, Hull RL, Kodama K, Retzlaff BM,

Brunzell JD,

et al

. Intra-abdominal fat is a major determinant of the

National Cholesterol Education Program Adult Treatment Panel III

criteria for the metabolic syndrome.

Diabet Med

2006;

23

(5): 469–480.

11. Molarius A, Seidell JC, Sans S, Tuomilehto J, Kuulasmaa K. Varying

sensitivity of waist action levels to identify subjects with overweight

or obesity in 19 populations of the WHO MONICA Project.

J Clin

Epidemiol

1999;

52

: 1213–1224.

12. Tan CE, Ma S, Wai D, Chew SK. Tai ES. Can we apply the National

Cholesterol Education Program Adult Treatment Panel definition of the

metabolic syndrome to Asians?

Diabetes Care

2000;

27

(5): 1182–1186.

13. Okafor CI. The metabolic syndrome in Africa: Current trends.

Indian J

Endocr Metab

2012;

16

(1): 56–66.

14. Prinsloo J, Malan L, de Ridder JH, Potgieter JC, Steyn HS. Determining

the waist circumference cut-off which best predicts the metabolic

syndrome components in urban Africans: The SABPA Study.

Exp Clin

Endocrinol Diabetes

2011;

119

: 599–603.

15. Omuse G, Maina D, Hoffman M, Mwangi J, Wambua C, Kagotho E,

et al

. Metabolic syndrome and its predictors in an urban population in

Kenya: A cross sectional study.

BMC Endocr Disord

2017;

17

(37).

16. Magalhães P, Capingana DP, Mill JG. Prevalence of the metabolic

syndrome and determination of optimal cut-off values of waist circum-

ference in university employees from Angola.

Cardiovasc J Sth Afr

2014;

25

(1): 27–33.

17. Ibrahim MM, Elamragy AA, Girgis H, Nour MA. Cut-off values of

waist circumference and associated cardiovascular risk in Egyptians.

BMC Cardiovasc Disord

2011;

11

(53).

18. Motala A, Esterhuizen T, Pirie FJ, Omar MAK. The prevalence of

metabolic syndrome and determination of the optimal waist circumfer-

ence cut-off points in a rural South African Community.

Diabetes Care

2011;

34

: 1032–1037.

19. Hoebel S, Malan L, de Ridder JH. Determining ethnic-, gender-, and

age-specific waist circumference cut-off points to predict metabolic

syndrome: the Sympathetic Activity and Ambulatory Blood Pressure

in Africans (SABPA) study.

J Endocrinol Metab Diabetes S Afr

2013;

18

(2): 88–96.

20. United Nations, Department of Economics and Social Affairs,

Population Division (2018). World Urbanization Prospects: the 2018

revison, online edition.

21. Ntandou G, ne Delisle HL, Agueh V, Fayomi B. Physical activity and

socioeconomic status explain rural-urban differences in obesity: a cross-

sectional study in Benin (West Africa).

Ecol Food Nutr

2008;

47

(4):

313–337.