Differences by sex in the prevalence of diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance in sub-Saharan Africa: a systematic review and meta-analysis

Les différences entre les sexes dans la prévalence du diabète sucré, de la glycémie à jeun anormale et de l'intolérance au glucose en Afrique subsaharienne: examen systématique et méta-analyse

Las diferencias entre sexos en la prevalencia de la diabetes mellitus, las alteraciones de la glucemia en ayunas y la intolerancia a la glucosa en África subsahariana: revisión sistemática y metaanálisis

دور الاختلافات حسب الجنس في معدل انتشار داء السكري، واختلال سكر الدم مع الصيام واختلال تحمل الغلوكوز في أفريقيا جنوب الصحراء الكبرى: استعراض منهجي وتحليل وصفي

撒哈拉以南非洲糖尿病、空腹血糖受损和糖耐量异常患病率的性别差异:系统回顾和元分析

Половые различия в распространенности сахарного диабета, нарушенной гликемии натощак и нарушенной переносимости глюкозы в Африке южнее Сахары: систематический обзор и мета-анализ

Esayas Haregot Hilawe Hiroshi Yatsuya Leo Kawaguchi Atsuko Aoyama About the authors

Abstracts

Objective

To assess differences between men and women in the prevalence of diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance in sub-Saharan Africa.

Methods

In September 2011, the PubMed and Web of Science databases were searched for community-based, cross-sectional studies providing sex-specific prevalences of any of the three study conditions among adults living in parts of sub-Saharan Africa (i.e. in Eastern, Middle and Southern Africa according to the United Nations subregional classification for African countries). A random-effects model was then used to calculate and compare the odds of men and women having each condition.

Findings

In a meta-analysis of the 36 relevant, cross-sectional data sets that were identified, impaired fasting glycaemia was found to be more common in men than in women (OR: 1.56; 95% confidence interval, CI: 1.20–2.03), whereas impaired glucose tolerance was found to be less common in men than in women (OR: 0.84; 95% CI: 0.72–0.98). The prevalence of diabetes mellitus – which was generally similar in both sexes (OR: 1.01; 95% CI: 0.91–1.11) – was higher among the women in Southern Africa than among the men from the same subregion and lower among the women from Eastern and Middle Africa and from low-income countries of sub-Saharan Africa than among the corresponding men.

Conclusion

Compared with women in the same subregions, men in Eastern, Middle and Southern Africa were found to have a similar overall prevalence of diabetes mellitus but were more likely to have impaired fasting glycaemia and less likely to have impaired glucose tolerance.


Objectif

Évaluer les différences entre hommes et femmes en termes de prévalence du diabète sucré, de la glycémie à jeun anormale et de l'intolérance au glucose en Afrique subsaharienne.

Méthodes

En septembre 2011, on a recherché dans les bases de données PubMed et Web of Science des études communautaires transversales fournissant les prévalences spécifiques au sexe des trois maladies faisant l'objet de l'étude, chez des adultes vivant dans certaines régions d'Afrique subsaharienne (par exemple en Afrique orientale, centrale et australe, selon la classification sous-régionale des Nations Unies pour les pays africains). Un modèle à effets aléatoires a ensuite été utilisé pour calculer et comparer les cotes des hommes et des femmes affectés par chacune de ces maladies.

Résultats

Dans une méta-analyse des 36 séries de données transversales pertinentes identifiées, on a découvert que la glycémie à jeun anormale était plus fréquente chez les hommes que chez les femmes (RC: 1,56, intervalle de confiance de 95%, IC: 1,20 à 2,03), tandis que la tolérance au glucose s'est révélée moins fréquente chez les hommes que chez les femmes (RC: 0,84, IC de 95%: 0,72 à 0,98). La prévalence du diabète sucré - généralement semblable chez les deux sexes (RC: 1,01, IC de 95%: 0,91 à 1,11) - était plus élevée chez les femmes d'Afrique australe que chez les hommes de la même sous-région, et plus faible chez les femmes d'Afrique orientale et centrale et des pays à faible revenu d'Afrique subsaharienne que chez les hommes des mêmes pays.

Conclusion

Par rapport aux femmes des mêmes sous-régions, on a découvert que la prévalence globale du diabète sucré était similaire chez les hommes d'Afrique orientale, mais que ceux-ci étaient plus susceptibles de souffrir de glycémie à jeun anormale et moins susceptibles d'être affectés par une intolérance au glucose.


Objetivo

Evaluar las diferencias entre hombres y mujeres respecto a la prevalencia de la diabetes mellitus, las alteraciones de la glucemia en ayunas y la intolerancia a la glucosa en África subsahariana.

Métodos

En septiembre de 2011, se realizaron búsquedas en las bases de datos de PubMed y Web of Science a fin de hallar estudios comunitarios transversales que proporcionaran datos sobre las prevalencias específicas de cada sexo de cualquiera de las tres enfermedades de estudio entre los adultos residentes en zonas de África subsahariana (es decir, en el Este, Centro y Sur de África, según la clasificación subregional de las Naciones Unidas para los países africanos). Se empleó un modelo de efectos aleatorios para calcular y comparar las probabilidades por parte de hombres y mujeres de padecer cada una de las enfermedades.

Resultados

En un metaanálisis de los 36 conjuntos de datos de carácter transversal pertinentes que se identificaron, se halló que las alteraciones de la glucemia en ayunas eran más comunes en hombres que en mujeres (OR: 1,56; intervalo de confianza del 95%, IC: 1,20 a 2,03), por el contrario, se descubrió que la intolerancia a la glucosa era menos común en los hombres que en las mujeres (OR: 0,84; IC del 95%: 0,72 a 0,98). La prevalencia de la diabetes mellitus (la cual fue, por lo general, similar en ambos sexos (OR: 1,01; IC 95%: 0,91 a 1,11) fue mayor entre las mujeres del Sur de África que entre los hombres de la misma subregión, y menor entre las mujeres del Este y Centro de África, así como en los países de ingresos bajos de África subsahariana, que entre los hombres correspondientes.

Conclusión

En comparación con las mujeres de las mismas subregiones, se halló que los hombres del Este, Centro y Sur de África tienen una prevalencia general similar de la diabetes mellitus, pero son más propensos a padecer alteraciones de la glucemia en ayunas y menos propensos a padecer intolerancia a la glucosa.


الغرض

تقيمم الاختلافات بين الرجال والنساء في معدل انتشار داء السكري، واختلال سكر الدم مع الصيام واختلال تحمل الغلوكوز في أفريقيا جنوب الصحراء الكبرى.

الطريقة

في أيلول/سبتمبر 2011، تم البحث في قواعد بيانات PubMed وWeb of Science عن الدراسات المجتمعية متعددة القطاعات التي تقدم معدلات انتشار لأي من حالات الدراسة الثلاث بين البالغين الذين يسكنون مناطق من أفريقيا جنوب الصحراء الكبرى (أي في أفريقيا الشرقية والوسطى والجنوبية وفقاً لتصنيف المنطقة دون الإقليمية للبلدان الأفريقية حسب الأمم المتحدة). وتم استخدام نموذج التأثيرات العشوائية لحساب الاحتمالات بين الرجال والنساء في كل حالة.

النتائج

في تحليل وصفي لفئات البيانات متعددة القطاعات ذات الصلة التي تم تحديدها البالغ عددها 36 فئة، تم التوصل إلى أن اختلال سكر الدم مع الصيام أكثر شيوعاً لدى الرجال عنه لدى النساء (نسبة الاحتمال: 1.56؛ فاصل الثقة 95 %: من 1.20 إلى 2.03)، في حين تم التوصل إلى أن اختلال تحمل الغلوكوز أقل شيوعاً لدى الرجال عنه لدى النساء (نسبة الاحتمال: 0.84؛ فاصل الثقة 95 %: من 0.98 إلى 0.72) وكان معدل انتشار داء السكري – الذي تشابه عموماً في كلا الجنسين (نسبة الاحتمال: 1.01؛ فاصل الثقة 95 %: من 0.91 إلى 1.11) – أعلى بين النساء في أفريقيا الجنوبية عنه بين الرجال من نفس المنطقة دون الإقليمية وأقل بين النساء من أفريقيا الشرقية والوسطى ومن بلدان أفريقيا جنوب الصحراء الكبرى المنخفضة الدخل عنه بين الرجال المقابلين لهم.

الاستنتاج

مقارنة بالنساء من نفس المناطق دون الإقليمية، تم التوصل إلى أن الرجال في أفريقيا الشرقية والوسطى والجنوبية لديهم معدل انتشار عام مشابه لداء السكري غير أنه ازدادت لديهم احتمالية الإصابة باختلال سكر الدم مع الصيام في حين قلت لديهم احتمالية الإصابة باختلال تحمل الغلوكوز.


目的

评估撒哈拉以南非洲糖尿病、空腹血糖受损和糖耐量异常患病率的男女差异。

方法

在2011 年9 月,搜索PubMed和Web of Science数据库,查找基于社区、提供撒哈拉以南非洲区域(即根据联合国对非洲国家的亚区分类:东非、中非和南非)居住的成年人当中三种研究状况中任一种状况的特定性别患病率的横断面研究。然后使用随机效果模型计算和比较患有各种病情的男女差别。

结果

在所识别的36 个相关的横断面数据集的元分析中,较之女性,在男性中空腹血糖受损更常见(OR:1.56;95%置信区间,CI:1.20–2.03),而女性的糖耐量受损比男性更常见(OR:0.84;95% CI:0.72–0.98)。对于两性之间大致差不多(OR:1.01;95% CI:0.91–1.11)的糖尿病患病率,南非女性比同一亚区男性高,东非和中非以及撒哈拉以南非洲低收入国家则是男高女低。

结论

与同一亚区女性比较,东非、中非和南非的男性的糖尿病总体患病率相似,但是空腹血糖受损患病率更高,糖耐量受损患病率更低。


Цель

Оценить различия между мужчинами и женщинами в распространенности сахарного диабета, нарушенной гликемии натощак и нарушенной переносимости глюкозы в Африке южнее Сахары.

Методы

В сентябре 2011 года был осуществлен поиск в базах данных PubMed и Web of Science территориальных поперечных исследований, предоставляющих данные в половом разрезе о распространенности любого из трех исследуемых заболеваний среди взрослых, живущих в Африке южнее Сахары (то есть в Восточной, Средней и Южной Африке, согласно субрегиональной классификации африканских стран Организацией Объединенных Наций). Затем для расчета и сопоставления риска мужчин и женщин подвергнуться каждому из заболеваний была использована модель случайных эффектов.

Результаты

Мета-анализ идентифицированных 36 релевантных поперечных наборов данных показал, что нарушение гликемии натощак чаще встречается у мужчин, чем у женщин (соотношение риска, СР: 1,56; 95% доверительный интервал, ДИ: 1,20–2,03), в то время как нарушенная переносимость глюкозы у мужчин встречается реже, чем у женщин (СР: 0,84; 95% ДИ: 0.72–0.98). Распространенность сахарного диабета, которая в целом была аналогична у обоих полов (СР: 1,01; 95% ДИ: 0,91–1,11), в Южной Африке была выше среди женщин, чем среди мужчин из того же субрегиона, и ниже среди женщин из стран Восточной и Центральной Африки, а также из малообеспеченных стран Африки южнее Сахары, чем среди мужчин из той же выборки.

Вывод

У мужчин в Восточной, Средней и Южной Африке была обнаружена аналогичная с женщинами в тех же субрегионах общая распространенность сахарного диабета, но чаще встречались нарушения гликемии натощак и реже – нарушенная толерантность к глюкозе.


Introduction

Increasing urbanization and the accompanying changes in lifestyle are leading to a burgeoning epidemic of chronic noncommunicable diseases in sub-Saharan Africa.1Dalal S, Beunza JJ, Volmink J, Adebamowo C, Bajunirwe F, Njelekela M et al. Non-communicable diseases in sub-Saharan Africa: what we know now. Int J Epidemiol 2011;40:885–901. doi: http://dx.doi.org/10.1093/ije/dyr050 PMID:21527446
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,2Maher D, Smeeth L, Sekajugo J. Health transition in Africa: practical policy proposals for primary care. Bull World Health Organ 2010;88:943–8. doi: http://dx.doi.org/10.2471/BLT.10.077891 PMID:21124720
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At the same time, the prevalence of many acute communicable diseases is decreasing.1Dalal S, Beunza JJ, Volmink J, Adebamowo C, Bajunirwe F, Njelekela M et al. Non-communicable diseases in sub-Saharan Africa: what we know now. Int J Epidemiol 2011;40:885–901. doi: http://dx.doi.org/10.1093/ije/dyr050 PMID:21527446
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,2Maher D, Smeeth L, Sekajugo J. Health transition in Africa: practical policy proposals for primary care. Bull World Health Organ 2010;88:943–8. doi: http://dx.doi.org/10.2471/BLT.10.077891 PMID:21124720
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In consequence, the inhabitants of sub-Saharan Africa are generally living longer and this increasing longevity will result in a rise in the future incidence of noncommunicable diseases in the region.1Dalal S, Beunza JJ, Volmink J, Adebamowo C, Bajunirwe F, Njelekela M et al. Non-communicable diseases in sub-Saharan Africa: what we know now. Int J Epidemiol 2011;40:885–901. doi: http://dx.doi.org/10.1093/ije/dyr050 PMID:21527446
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3BeLue R, Okoror TA, Iwelunmor J, Taylor KD, Degboe AN, Agyemang C et al. An overview of cardiovascular risk factor burden in sub-Saharan African countries: a socio-cultural perspective. Global Health 2009;5:10. doi: http://dx.doi.org/10.1186/1744-8603-5-10 PMID:19772644
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Diabetes mellitus is one of the most prominent noncommunicable diseases that are undermining the health of the people in sub-Saharan Africa and placing additional burdens on health systems that are often already strained.4Gill GV, Mbanya J-C, Ramaiya KL, Tesfaye S. A sub-Saharan African perspective of diabetes. Diabetologia 2009;52:8–16. doi: http://dx.doi.org/10.1007/s00125-008-1167-9 PMID:18846363
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In 2011, 14.7 million adults in the African Region of the World Health Organization (WHO) were estimated to be living with diabetes mellitus.6Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract 2011;94:311–21. doi: http://dx.doi.org/10.1016/j.diabres.2011.10.029 PMID:22079683
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Of all of WHO's regions, the African Region is expected to have the largest proportional increase (90.5%) in the number of adult diabetics by 2030.6Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract 2011;94:311–21. doi: http://dx.doi.org/10.1016/j.diabres.2011.10.029 PMID:22079683
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Sex-related differences in lifestyle may lead to differences in the risk of developing diabetes mellitus and, in consequence, to differences in the prevalence of this condition in women and men.3BeLue R, Okoror TA, Iwelunmor J, Taylor KD, Degboe AN, Agyemang C et al. An overview of cardiovascular risk factor burden in sub-Saharan African countries: a socio-cultural perspective. Global Health 2009;5:10. doi: http://dx.doi.org/10.1186/1744-8603-5-10 PMID:19772644
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However, the relationship between a known risk factor for diabetes mellitus – such as obesity – and the development of symptomatic diabetes mellitus may not be simple. For example, in many countries of sub-Saharan Africa, women are more likely to be obese or overweight than men and might therefore be expected to have higher prevalences of diabetes mellitus.3BeLue R, Okoror TA, Iwelunmor J, Taylor KD, Degboe AN, Agyemang C et al. An overview of cardiovascular risk factor burden in sub-Saharan African countries: a socio-cultural perspective. Global Health 2009;5:10. doi: http://dx.doi.org/10.1186/1744-8603-5-10 PMID:19772644
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Compared with the corresponding men, women in Cameroon8Mbanya JC, Ngogang J, Salah JN, Minkoulou E, Balkau B. Prevalence of NIDDM and impaired glucose tolerance in a rural and an urban population in Cameroon. Diabetologia 1997;40:824–9. doi: http://dx.doi.org/10.1007/s001250050755 PMID:9243104
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were indeed found to have higher prevalences of diabetes mellitus. However, women in Ghana,1111 Amoah AGB, Owusu SK, Adjei S. Diabetes in Ghana: a community based prevalence study in Greater Accra. Diabetes Res Clin Pract 2002;56:197–205. doi: http://dx.doi.org/10.1016/S0168-8227(01)00374-6 PMID:11947967
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and rural areas of the United Republic of Tanzania1414 McLarty DG, Swai AB, Kitange HM, Masuki G, Mtinangi BL, Kilima PM et al. Prevalence of diabetes and impaired glucose tolerance in rural Tanzania. Lancet 1989;1:871–5. doi: http://dx.doi.org/10.1016/S0140-6736(89)92866-3 PMID:2564951
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were found to have lower prevalences of diabetes mellitus than the men in the same study areas. No significant differences between men and women in the prevalence of diabetes mellitus were detected in studies in Guinea,1515 Baldé N-M, Diallo I, Baldé M-D, Barry I-S, Kaba L, Diallo M-M et al. Diabetes and impaired fasting glucose in rural and urban populations in Futa Jallon (Guinea): prevalence and associated risk factors. Diabetes Metab 2007;33:114–20. doi: http://dx.doi.org/10.1016/j.diabet.2006.10.001 PMID:17363316
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Mali,1616 Fisch A, Pichard E, Prazuck T, Leblanc H, Sidibe Y, Brücker G. Prevalence and risk factors of diabetes mellitus in the rural region of Mali (West Africa): a practical approach. Diabetologia 1987;30:859–62. PMID:3446552 Sudan1717 Elbagir MN, Eltom MA, Elmahadi EM, Kadam IM, Berne C. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 1996;19:1126–8. doi: http://dx.doi.org/10.2337/diacare.19.10.1126 PMID:8886561
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and urban areas of the United Republic of Tanzania,1818 Njelekela MA, Mpembeni R, Muhihi A, Mligiliche NL, Spiegelman D, Hertzmark E et al. Gender-related differences in the prevalence of cardiovascular disease risk factors and their correlates in urban Tanzania. BMC Cardiovasc Disord 2009;9:30. doi: http://dx.doi.org/10.1186/1471-2261-9-30 PMID:19615066
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or in a meta-analysis of data collected in several studies in West Africa.1919 Abubakari AR, Lauder W, Jones MC, Kirk A, Agyemang C, Bhopal RS. Prevalence and time trends in diabetes and physical inactivity among adult West African populations: the epidemic has arrived. Public Health 2009;123:602–14. doi: http://dx.doi.org/10.1016/j.puhe.2009.07.009 PMID:19748643
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Although wide variations in the distribution of diabetes mellitus by sex have been documented in several review articles,3BeLue R, Okoror TA, Iwelunmor J, Taylor KD, Degboe AN, Agyemang C et al. An overview of cardiovascular risk factor burden in sub-Saharan African countries: a socio-cultural perspective. Global Health 2009;5:10. doi: http://dx.doi.org/10.1186/1744-8603-5-10 PMID:19772644
https://doi.org/10.1186/1744-8603-5-10...
5Tuei VC, Maiyoh GK, Ha C-E. Type 2 diabetes mellitus and obesity in sub-Saharan Africa. Diabetes Metab Res Rev 2010;26:433–45. doi: http://dx.doi.org/10.1002/dmrr.1106 PMID:20641142
https://doi.org/10.1002/dmrr.1106...
,7Imoisili OE, Sumner AE. Preventing diabetes and atherosclerosis in sub-Saharan Africa: should the metabolic syndrome have a role? Curr Cardiovasc Risk Rep 2009;3:161–7. doi: http://dx.doi.org/10.1007/s12170-009-0026-7 PMID:22368728
https://doi.org/10.1007/s12170-009-0026-...
,2020 Mbanya JCN, Motala AA, Sobngwi E, Assah FK, Enoru ST. Diabetes in sub-Saharan Africa. Lancet 2010;375:2254–66. doi: http://dx.doi.org/10.1016/S0140-6736(10)60550-8 PMID:20609971
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the possible causes of this heterogeneity have never been examined in detail.

Like obesity, impaired fasting glycaemia and impaired glucose tolerance appear to be risk factors in the development of diabetes mellitus.2121 Nathan DM, Davidson MB, DeFronzo RA, Heine RJ, Henry RR, Pratley R et al.; American Diabetes Association. Impaired fasting glucose and impaired glucose tolerance: implications for care. Diabetes Care 2007;30:753–9. doi: http://dx.doi.org/10.2337/dc07-9920 PMID:17327355
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,2222 Unwin N, Shaw J, Zimmet P, Alberti KGMM. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708–23. doi: http://dx.doi.org/10.1046/j.1464-5491.2002.00835.x PMID:12207806
https://doi.org/10.1046/j.1464-5491.2002...
According to the International Diabetes Federation, the estimated age-adjusted prevalence of impaired fasting glycaemia in WHO's African Region was substantially higher in 2011 than the corresponding global mean value – 9.7% versus 6.5%, respectively – and is expected to have risen further by 2030.2323 IDF Diabetes Atlas, 5th edition [Internet]. Africa (AFR). Brussels: International Diabetes Federation; 2012. Available from: http://www.idf.org/diabetesatlas/5e/africa [accessed 23 April 2013].
http://www.idf.org/diabetesatlas/5e/afri...

Impaired fasting glycaemia and impaired glucose tolerance are reported to be metabolically distinct entities that affect different subpopulations, albeit with some degree of overlap.2222 Unwin N, Shaw J, Zimmet P, Alberti KGMM. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708–23. doi: http://dx.doi.org/10.1046/j.1464-5491.2002.00835.x PMID:12207806
https://doi.org/10.1046/j.1464-5491.2002...
,2424 Williams JW, Zimmet PZ, Shaw JE, de Courten MP, Cameron AJ, Chitson P et al. Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter? Diabet Med 2003;20:915–20. doi: http://dx.doi.org/10.1046/j.1464-5491.2003.01059.x PMID:14632717
https://doi.org/10.1046/j.1464-5491.2003...
In Mauritius, the prevalence of impaired fasting glycaemia was found to be significantly higher in men than in women, whereas the prevalence of impaired glucose tolerance was found to be higher in women than in men.2424 Williams JW, Zimmet PZ, Shaw JE, de Courten MP, Cameron AJ, Chitson P et al. Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter? Diabet Med 2003;20:915–20. doi: http://dx.doi.org/10.1046/j.1464-5491.2003.01059.x PMID:14632717
https://doi.org/10.1046/j.1464-5491.2003...
,2525 Shaw JE, Zimmet PZ, de Courten M, Dowse GK, Chitson P, Gareeboo H et al. Impaired fasting glucose or impaired glucose tolerance. What best predicts future diabetes in Mauritius? Diabetes Care 1999;22:399–402. doi: http://dx.doi.org/10.2337/diacare.22.3.399 PMID:10097917
https://doi.org/10.2337/diacare.22.3.399...

Differences between men and women in the prevalence of diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance in much of sub-Saharan Africa have yet to be reviewed. Given the variation in health care, culture, environment, human behaviour and other determinants of health across sub-Saharan Africa,2626 De-Graft Aikins A, Marks D. Health, disease and healthcare in Africa. J Health Psychol 2007;12:387–402. doi: http://dx.doi.org/10.1177/1359105307076228
https://doi.org/10.1177/1359105307076228...
the conclusions drawn from a recent meta-analysis of data from West Africa1919 Abubakari AR, Lauder W, Jones MC, Kirk A, Agyemang C, Bhopal RS. Prevalence and time trends in diabetes and physical inactivity among adult West African populations: the epidemic has arrived. Public Health 2009;123:602–14. doi: http://dx.doi.org/10.1016/j.puhe.2009.07.009 PMID:19748643
https://doi.org/10.1016/j.puhe.2009.07.0...
should not be assumed to apply to the whole of sub-Saharan Africa. The sex-specific prevalence of at least one risk factor for diabetes mellitus – obesity – is known to differ across different parts of sub-Saharan Africa.7Imoisili OE, Sumner AE. Preventing diabetes and atherosclerosis in sub-Saharan Africa: should the metabolic syndrome have a role? Curr Cardiovasc Risk Rep 2009;3:161–7. doi: http://dx.doi.org/10.1007/s12170-009-0026-7 PMID:22368728
https://doi.org/10.1007/s12170-009-0026-...
,2727 Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ et al.; Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group (Body Mass Index). National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. Lancet 2011;377:557–67. doi: http://dx.doi.org/10.1016/S0140-6736(10)62037-5 PMID:21295846
https://doi.org/10.1016/S0140-6736(10)62...

The main aims of the present systematic review were to examine differences between men and women in the prevalence of three conditions – diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance – in Eastern, Middle and Southern Africa (i.e. all in sub-Saharan Africa according to the United Nations subregional classification for African countries),2828 Composition of macro geographical (continental) regions, geographical sub-regions, and selected economic and other groupings [Internet]. New York: United Nations; 2011. Available from: http://unstats.un.org/unsd/methods/m49/m49regin.htm [accessed 23 April 2013].
http://unstats.un.org/unsd/methods/m49/m...
and to explore the possible causes of any variation observed. We followed the Meta-analysis of Observational Studies in Epidemiology (MOOSE) group's guidelines for the reporting of systematic reviews of observational studies.2929 Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D et al.; Meta-analysis of Observational Studies in Epidemiology (MOOSE) Group. Meta-analysis of observational studies: a proposal for reporting. JAMA 2000;283:2008–12. doi: http://dx.doi.org/10.1001/jama.283.15.2008 PMID:10789670
https://doi.org/10.1001/jama.283.15.2008...

Methods

Data sources

In September 2011, we searched PubMed and Web of Science for studies that presented the sex-specific prevalences of diabetes mellitus, impaired fasting glycaemia and/or impaired glucose tolerance in Eastern, Middle and/or Southern Africa (Table 1). The medical subject headings (MeSH) and search terms we used are described in Box 1. We limited our search to human studies but placed no restrictions on the language of publication. We also used Google, Google Scholar and WHO's InfoBase to search the “grey” literature for relevant studies and reports. The citations in articles that appeared to be relevant were examined for other articles that might hold useful data. When it seemed possible that relevant data had been recorded but not published, the authors of published study reports were contacted via e-mail to see if they could provide such data.

Table 1
Countries comprising sub-Saharan Africa, by African subregiona
Box 1  Strategy followed in searching PubMed and the Web of Science

Various medical subject headings (MeSH) and search terms, including “prevalence”, “incidence”, “epidemiology”, “proportion”, “rate”, “diabetes mellitus”, “hyperglycaemia”, “abnormal* blood glucose”, “glucose intolerance”, “dysglycaemia”, “insulin resistance”, “metabolic* syndrome”, “insulin resistance syndrome X”, “cardiovascular syndrome”, “hypertension”, “increase* blood pressure”, “obesity”, “overweight”, “hypercholesterolaemia”, “hyperlipidaemia”, “dyslipidaemia”, “physical inactivity”, “smoking”, “cardiovascular diseases risk factors” and “Africa South of the Sahara” – and alternative spellings such as “hyperglycemia” were used. Searches were combined with the names of each country in Eastern, Middle and Southern Africa (Table 1) – except Cameroon, which was included in a previous study on West Africa1919 Abubakari AR, Lauder W, Jones MC, Kirk A, Agyemang C, Bhopal RS. Prevalence and time trends in diabetes and physical inactivity among adult West African populations: the epidemic has arrived. Public Health 2009;123:602–14. doi: http://dx.doi.org/10.1016/j.puhe.2009.07.009 PMID:19748643
https://doi.org/10.1016/j.puhe.2009.07.0...
– by using the Boolean operators “OR” or “AND”.

Inclusion and exclusion criteria

Data were included in the meta-analysis if they came from studies that fulfilled all of the following criteria:

  • community-based;

  • cross-sectional;

  • reported prevalence of diabetes mellitus, impaired fasting glycaemia and/or impaired glucose tolerance;

  • reported either odds ratios (ORs) for differences between men and women in the prevalence of diabetes mellitus, impaired fasting glycaemia and/or impaired glucose tolerance or data that allowed the computation of such ORs;

  • conducted in apparently healthy, non-pregnant subjects;

  • most subjects are adults (i.e. aged ≥ 15 years) and residing in the UN-designated Eastern, Middle or Southern subregions of Africa;

  • both men and women investigated;

  • employed any of WHO's diagnostic criteria – or the equivalent criteria of the American Diabetic Association – for diabetes mellitus, impaired fasting glycaemia and/or impaired glucose tolerance;3030 WHO Expert Committee on Diabetes Mellitus: second report. Geneva: World Health Organization; 1980. Available from: whqlibdoc.who.int/trs/WHO_TRS_646.pdf [accessed 23 April 2031].
    whqlibdoc.who.int/trs/WHO_TRS_646.pdf...
    3838 Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997;20:1183–97. PMID:9203460

  • reported results either in English or in another language with an abstract in English.

When multiple reports of the same study were retrieved, only the most informative report was selected. Clinic-, hospital- and laboratory-based studies, anonymous reports, letters, commentaries, case studies and reviews were excluded.

Data abstraction

After reading each article that appeared relevant and met the inclusion criteria, one of the authors (EHH) made notes of the year of study and publication, sampling method, sample size, response rate, study design, diagnostic criteria, study area, mean age and/or age range of the subjects, mean blood glucose level, the recorded prevalences of diabetes mellitus, impaired fasting glycaemia and/or impaired glucose tolerance, and, if available, the OR and corresponding 95% confidence intervals (CIs) that indicated the type and significance of any differences in these prevalences by sex. When articles presented data separately for urban and rural subjects, information for these two groups of subjects was extracted separately. When articles presented data stratified by subject age, only the data for subjects aged 15 years or older were included in the analysis. All of the extracted data were independently reviewed by a second author (HY).

Quality appraisal

A checklist – adopted from one created by the University of Wisconsin3939 Quality criteria checklists [Internet]. Green Bay: University of Wisconsin; 2005. Available from: http://www.uwgb.edu/laceyk/NutSci486/EA%20Quality%20Criteria%20Checklists.doc [accessed 1 April 2013].
http://www.uwgb.edu/laceyk/NutSci486/EA%...
– was used to assess the quality of the included studies. The checklist had eight questions relating to the research question, selection of study subjects, comparability of study groups, handling of withdrawals, measurement of outcomes, statistical analyses, results and conclusions, and funding or sponsorship. If the answers to five or more of these questions were positive, the study involved was categorized as “positive” and considered to be of good quality. If the answers to five or more of these questions were negative, the study involved was categorized as “negative” and considered to be of poor quality. All other studies were categorized as “neutral”.

Statistical analysis

ORs were used as “effect estimates” to quantify the relationship between sex and the prevalence of diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance. If no OR had been reported, it was calculated from the raw data. Since the studies included in the meta-analysis used different standard populations, crude prevalences were preferred to the age-adjusted values when both were available. The DerSimonian and Laird random-effects model was used to estimate the mean OR for all of the studies included in the meta-analysis.4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009.

Statistical heterogeneity across the studies was evaluated using both the Q and I2 statistics.4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009. In the Q-tests, a P-value of < 0.1 was considered indicative of statistically significant heterogeneity. We performed subgroup analyses to assess the potential influence of the following study-level covariates on the OR for any sex-specific differences: area of residence (urban or rural), subregion of residence in sub-Saharan Africa (i.e. Eastern, Middle or Southern Africa), study year, ethnicity of the study subjects, and the World-Bank-determined income level of the study country.4141 World Bank list of economies (April 2012) [Internet]. Washington: World Bank; 2012. Available from: http://data.worldbank.org/about/country-classifications/country-and-lending-groups [accessed 1 April 2013].
http://data.worldbank.org/about/country-...
Random-effects univariate meta-regression analysis4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009. was also performed as an extension of the subgroup analyses.

The potential influence of each individual study on the overall summary estimates was assessed by rerunning the meta-analysis while omitting one study at a time. Sensitivity analysis was performed to assess the impact of the quality of the studies on the overall effect estimates. For those studies that reported both crude and age-adjusted prevalences, we also assessed if the effect estimates would have been substantially altered if the age-adjusted values had been used instead of the crude ones.

Publication bias4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009. was assessed using a funnel plot to examine the relationship between the effect size and study precision. Begg and Mazumdar's rank-correlation test4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009. was then used to test this relationship statistically. Finally, Duval and Tweedie's “trim and fill” analysis was used to assess the possible impact of publication bias on the effect size.4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009.

Version 2 of the Comprehensive Meta-Analysis software package (Biostat, Englewood, United States of America) was used for all of the statistical analyses. All statistical tests were two-sided. A P-value of < 0.05 was generally considered indicative of statistical significance.

Results

Literature search

Although the PubMed and Web of Science searches revealed 5129 potentially useful reports, only 25 of these reports were found to satisfy all of the inclusion criteria (Fig. 1). Four additional reports that met all of the inclusion criteria were identified via a Google search (n = 2), a search of the WHO InfoBase (n = 1) or contact with authors (n = 1). The meta-analysis therefore included data from 29 reports that, together, covered 36 studies in which cross-sectional data were collected.1414 McLarty DG, Swai AB, Kitange HM, Masuki G, Mtinangi BL, Kilima PM et al. Prevalence of diabetes and impaired glucose tolerance in rural Tanzania. Lancet 1989;1:871–5. doi: http://dx.doi.org/10.1016/S0140-6736(89)92866-3 PMID:2564951
https://doi.org/10.1016/S0140-6736(89)92...
,1717 Elbagir MN, Eltom MA, Elmahadi EM, Kadam IM, Berne C. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 1996;19:1126–8. doi: http://dx.doi.org/10.2337/diacare.19.10.1126 PMID:8886561
https://doi.org/10.2337/diacare.19.10.11...
,4242 Tibazarwa K, Ntyintyane L, Sliwa K, Gerntholtz T, Carrington M, Wilkinson D et al. A time bomb of cardiovascular risk factors in South Africa: results from the Heart of Soweto Study “Heart Awareness Days”. Int J Cardiol 2009;132:233–9. doi: http://dx.doi.org/10.1016/j.ijcard.2007.11.067 PMID:18237791
https://doi.org/10.1016/j.ijcard.2007.11...
6868 Mollentze WF, Moore AJ, Steyn AF, Joubert G, Steyn K, Oosthuizen GM et al. Coronary heart disease risk factors in a rural and urban Orange Free State black population. S Afr Med J 1995;85:90–6. PMID:7597541

Fig. 1

Flow diagram of the study selection procedure

Study characteristics

Table 2 (available at: http://www.who.int/bulletin/volumes/91/9/12-113415) provides detailed descriptive information for the 36 studies included in the meta-analysis. These studies involved 75 928 subjects and were conducted between 1983 and 2009 in Angola, the Democratic Republic of the Congo, Kenya, Malawi, Mauritius, Mozambique, Seychelles, South Africa, Sudan, Uganda, the United Republic of Tanzania, Zambia or Zimbabwe. Most (92%) of the studies included in the meta-analysis employed probability- or census-sampling techniques and had response rates of 62–99%. Sex-specific prevalences of diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance were included in the reports of 35, 21 and 11 of the studies, respectively. Almost half (45%) of the studies were conducted in both urban and rural areas. The other studies were conducted exclusively in urban (26%), rural (23%) or periurban (6%) areas. In terms of quality, the studies were categorized as either “positive” (n = 31) or “neutral” (n = 5)4242 Tibazarwa K, Ntyintyane L, Sliwa K, Gerntholtz T, Carrington M, Wilkinson D et al. A time bomb of cardiovascular risk factors in South Africa: results from the Heart of Soweto Study “Heart Awareness Days”. Int J Cardiol 2009;132:233–9. doi: http://dx.doi.org/10.1016/j.ijcard.2007.11.067 PMID:18237791
https://doi.org/10.1016/j.ijcard.2007.11...
,4949 Nsakashalo-Senkwe M, Siziya S, Goma FM, Songolo P, Mukonka V, Babaniyi O. Combined prevalence of impaired glucose level or diabetes and its correlates in Lusaka urban district, Zambia: a population based survey. Int Arch Med 2011;4:2. doi: http://dx.doi.org/10.1186/1755-7682-4-2 PMID:21226931
https://doi.org/10.1186/1755-7682-4-2...
,5858 Evaristo-Neto AD, Foss-Freitas MC, Foss MC. Prevalence of diabetes mellitus and impaired glucose tolerance in a rural community of Angola. Diabetol Metab Syndr 2010;2:63. PMID:21040546,6161 Charlton KE, Schloss I, Visser M, Lambert EV, Kolbe T, Levitt NS et al. Waist circumference predicts clustering of cardiovascular risk factors in older South Africans. Cardiovasc J S Afr 2001;12:142–50. PMID:11533736,6363 National survey Zimbabwe non-communicable disease risk factors – (ZiNCoDs). Preliminary report. Harare: Ministry of Health and Child Welfare; 2005. Available from: http://www.who.int/chp/steps/STEPS_Zimbabwe_Data.pdf [accessed 1 April 2013].
http://www.who.int/chp/steps/STEPS_Zimba...
(Appendix A, available at: http://www.med.nagoya-u.ac.jp/intnl-h/swfu/d/auto-UZzMJC.pdf).

Table 2
Descriptions of the cross-sectional data sets included in the meta-analysis

Sex-specific prevalences

The prevalence of diabetes mellitus was 5.7% (95% CI: 4.8–6.8) overall, with a slight difference between the men (5.5%; 95% CI: 4.1–7.2) and women (5.9%; 95% CI: 4.6–7.6) included in the meta-analysis. The prevalence of impaired fasting glycaemia was 4.5% (95% CI: 3.3–6.1) overall – 5.7% (95% CI: 3.7–8.6) among the men and 3.5% (95% CI: 2.1–5.8) among the women – whereas the prevalence of impaired glucose tolerance was 7.9% (95% CI: 6.7–9.2) overall – 7.3% (95% CI: 6.0–8.8) among the men and 8.5% (95% CI: 6.7–10.7) among the women.

Odds ratios

The prevalence of diabetes mellitus among men was not significantly different from that among women (OR: 1.01; 95% CI: 0.91–1.11). However, impaired fasting glycaemia appeared to be significantly more common among men than among women (OR: 1.56; 95% CI: 1.20–2.03), whereas impaired glucose tolerance appeared to be significantly less common among men than among women (OR: 0.84; 95% CI: 0.72–0.98) (Fig. 2). These significant differences between the sexes were still observed when the analysis was restricted to those studies in which the prevalences of both impaired fasting glycaemia and impaired glucose tolerance were determined in the same study cohorts (data not shown). A moderate to substantial level of heterogeneity between studies was detected in the data for diabetes mellitus (I2 = 54.62%; P < 0.001 in Q-test), impaired fasting glycaemia (I2 = 85.38%; P < 0.001 in Q-test) and impaired glucose tolerance (I2 = 74.13%; P < 0.001 in Q-test).

Fig. 2

Forest plot of main meta-analysis results, showing sex-specific odds ratios for diabetes mellitus, impaired fasting glycaemia and impaired glucose tolerance in sub-Saharan Africa

Subgroup analyses

Table 3 summarizes the results of the subgroup analyses. Significant heterogeneity in the OR for diabetes mellitus was observed by area of residence (i.e. urban or rural), subregion of residence in Africa, ethnicity of the study subjects, and country income level – each of which gave a P- value of < 0.05 in a Q-test. The prevalence of diabetes mellitus was found to be significantly higher in men than in women in studies conducted in a mix of urban and rural areas, in Middle or Eastern Africa or in low-income countries. However, in studies conducted in Southern Africa or among subjects of Indian ethnicity, the prevalence of diabetes mellitus was significantly higher among women than among the corresponding men.

Table 3
Pooled odds ratios (ORs)a for diabetes mellitus and two associated risk factors

Significant heterogeneity in the OR for impaired fasting glycaemia was observed by subregion of residence in Africa (P = 0.02) and country income level (P = 0.006). In studies conducted in Eastern Africa or upper-middle-income countries, impaired fasting glycaemia appeared to be significantly more common among men than among women.

With impaired glucose tolerance, significant heterogeneity in the OR was observed by area of residence (P < 0.001), subregion of residence in Africa (P = 0.001), ethnicity (P = 0.002), and country income level (P = 0.03). The odds of impaired glucose tolerance were found to be higher in men than in women in studies conducted on urban residents or subjects of Indian ethnicity.

Meta-regression

In general, the univariate random-effects meta-regression revealed similar associations – between the OR and study-level covariates – as seen in the subgroup analyses (Appendix A). For example, the OR for the sex-specific prevalences of diabetes mellitus appeared to be significantly affected by area of residence (rural versus urban; P = 0.018), subregion of residence in Africa (Southern and Middle Africa versus Eastern Africa; P < 0.001), ethnicity of the study subjects (multi-ethnic versus Indian; P = 0.013), study year (1990s versus 2000s; P = 0.039), and country income level (low versus upper middle; P < 0.001). Subregion of residence (Eastern versus Southern Africa; P = 0.047) and country income level (low versus upper-middle; P = 0.006) also had a significant effect on the OR for impaired fasting glycaemia, whereas subregion of residence (Eastern versus Southern Africa; P < 0.001), ethnicity of study subjects (multi-ethnic versus Indian; P < 0.001), country income level (low versus upper-middle; P < 0.001), and area of residence – both rural versus urban (P < 0.001) and rural versus urban and rural combined (P = 0.003) – had significant effects on the OR for impaired glucose tolerance.

Sensitivity and influence analyses

No meaningful change in the OR was evident when the meta-analysis was rerun either with the data from the five studies of “neutral” quality omitted or using age-adjusted prevalences instead of the crude values (data not shown).

The results of the influence analysis indicated that the omission of the data from any of seven studies – described in five reports4343 Söderberg S, Zimmet P, Tuomilehto J, de Courten M, Dowse GK, Chitson P et al. Increasing prevalence of Type 2 diabetes mellitus in all ethnic groups in Mauritius. Diabet Med 2005;22:61–8. doi: http://dx.doi.org/10.1111/j.1464-5491.2005.01366.x PMID:15606693
https://doi.org/10.1111/j.1464-5491.2005...
,4444 Wanjihia VW, Kiplamai FK, Waudo JN, Boit MK. Post-prandial glucose levels and consumption of omega 3 fatty acids and saturated fats among two rural populations in Kenya. East Afr Med J 2009;86:259–66. PMID:20358787,4747 Christensen DL, Friis H, Mwaniki DL, Kilonzo B, Tetens I, Boit MK et al. Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya. Diabetes Res Clin Pract 2009;84:303–10. doi: http://dx.doi.org/10.1016/j.diabres.2009.03.007 PMID:19361878
https://doi.org/10.1016/j.diabres.2009.0...
,4848 Elbagir MN, Eltom MA, Elmahadi EM, Kadam IMS, Berne C. A high prevalence of diabetes mellitus and impaired glucose tolerance in the Danagla community in northern Sudan. Diabet Med 1998;15:164–9. doi: http://dx.doi.org/10.1002/(SICI)1096-9136(199802)15:2<164::AID-DIA536>3.0.CO;2-A PMID:9507920
https://doi.org/10.1002/(SICI)1096-9136(...
,5757 Kasiam Lasi On’Kin JB, Longo-Mbenza B, Okwe N, Kabangu NK, Mpandamadi SD, Wemankoy O et al. Prevalence and risk factors of diabetes mellitus in Kinshasa hinterland. Int J Diabetes & Metab 2008;16:97–106. – could eliminate the statistical significance of the overall differences between men and women in the prevalence of impaired glucose tolerance. However, even when the data from one of these studies were omitted, women still showed a higher prevalence of impaired glucose tolerance than the corresponding men, with a P-value of > 0.05 but < 0.1. The pooled results for diabetes or impaired fasting glycaemia were not substantially affected by the omission of the data from any one study.

Publication bias

The funnel plots for diabetes mellitus and impaired fasting glycaemia were asymmetric, indicating possible publication bias. However, the corresponding results from Begg and Mazumdar's rank-correlation tests – P-values of 0.93 and 0.64, respectively – were not statistically significant. Duval and Tweedie's “trim and fill” analysis indicated that the meta-analysis would have benefitted from the inclusion of data from more studies – nine for diabetes mellitus and one for impaired fasting glycaemia – and that, if the asymmetry seen in the funnel plots was the result of publication bias, the summary estimates of the sex-specific (i.e. men versus women) OR for diabetes mellitus and impaired fasting glycaemia should be 1.09 (95% CI: 0.98–1.20) and 1.65 (95% CI: 1.27–2.14), respectively (Appendix A).

There were no indications of publication bias in the data on impaired glucose tolerance.

Discussion

To our knowledge, this study is the first systematic review of possible associations between sex and the prevalences of impairments in glucose tolerance and fasting glycaemia in Eastern, Middle and Southern Africa. Previous narrative reviews have reported on the prevalence of diabetes mellitus and, briefly, on the variation in the sex distribution of this illness in sub-Saharan Africa.3BeLue R, Okoror TA, Iwelunmor J, Taylor KD, Degboe AN, Agyemang C et al. An overview of cardiovascular risk factor burden in sub-Saharan African countries: a socio-cultural perspective. Global Health 2009;5:10. doi: http://dx.doi.org/10.1186/1744-8603-5-10 PMID:19772644
https://doi.org/10.1186/1744-8603-5-10...
5Tuei VC, Maiyoh GK, Ha C-E. Type 2 diabetes mellitus and obesity in sub-Saharan Africa. Diabetes Metab Res Rev 2010;26:433–45. doi: http://dx.doi.org/10.1002/dmrr.1106 PMID:20641142
https://doi.org/10.1002/dmrr.1106...
,7Imoisili OE, Sumner AE. Preventing diabetes and atherosclerosis in sub-Saharan Africa: should the metabolic syndrome have a role? Curr Cardiovasc Risk Rep 2009;3:161–7. doi: http://dx.doi.org/10.1007/s12170-009-0026-7 PMID:22368728
https://doi.org/10.1007/s12170-009-0026-...
,2020 Mbanya JCN, Motala AA, Sobngwi E, Assah FK, Enoru ST. Diabetes in sub-Saharan Africa. Lancet 2010;375:2254–66. doi: http://dx.doi.org/10.1016/S0140-6736(10)60550-8 PMID:20609971
https://doi.org/10.1016/S0140-6736(10)60...
However, there appears to have been only one previous meta-analysis of data on the prevalence of diabetes mellitus in sub-Saharan Africa and that was limited to data collected in West Africa.1919 Abubakari AR, Lauder W, Jones MC, Kirk A, Agyemang C, Bhopal RS. Prevalence and time trends in diabetes and physical inactivity among adult West African populations: the epidemic has arrived. Public Health 2009;123:602–14. doi: http://dx.doi.org/10.1016/j.puhe.2009.07.009 PMID:19748643
https://doi.org/10.1016/j.puhe.2009.07.0...

The present results reveal considerable between-country variation in the prevalence of diabetes mellitus among adults. However, the relatively high value recorded for all of the studies combined (5.7%) is a reflection of the rapid transition – from a predominance of communicable disease to one of noncommunicable disease – that much of sub-Saharan Africa is facing. In this vast area of Africa, important risk factors for diabetes mellitus, such as impaired glucose tolerance, appear to be increasing in prevalence while humans are tending to live longer. The prevalence of diabetes mellitus in sub-Saharan Africa will therefore probably rise further unless prevention efforts are intensified. 2323 IDF Diabetes Atlas, 5th edition [Internet]. Africa (AFR). Brussels: International Diabetes Federation; 2012. Available from: http://www.idf.org/diabetesatlas/5e/africa [accessed 23 April 2013].
http://www.idf.org/diabetesatlas/5e/afri...

In the present meta-analysis – as in most2222 Unwin N, Shaw J, Zimmet P, Alberti KGMM. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708–23. doi: http://dx.doi.org/10.1046/j.1464-5491.2002.00835.x PMID:12207806
https://doi.org/10.1046/j.1464-5491.2002...
,2424 Williams JW, Zimmet PZ, Shaw JE, de Courten MP, Cameron AJ, Chitson P et al. Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter? Diabet Med 2003;20:915–20. doi: http://dx.doi.org/10.1046/j.1464-5491.2003.01059.x PMID:14632717
https://doi.org/10.1046/j.1464-5491.2003...
,6969 Færch K, Borch-Johnsen K, Vaag A, Jørgensen T, Witte DR. Sex differences in glucose levels: a consequence of physiology or methodological convenience? The Inter99 study. Diabetologia 2010;53:858–65. doi: http://dx.doi.org/10.1007/s00125-010-1673-4 PMID:20182862
https://doi.org/10.1007/s00125-010-1673-...
– but not all7070 Ramachandran A, Snehalatha C, Satyavani K, Vijay V. Impaired fasting glucose and impaired glucose tolerance in urban population in India. Diabet Med 2003;20:220–4. doi: http://dx.doi.org/10.1046/j.1464-5491.2003.00904.x PMID:12675667
https://doi.org/10.1046/j.1464-5491.2003...
– previous studies on this risk factor for diabetes mellitus – impaired fasting glucose was found to be significantly more common among men than among women, irrespective of the subgroup that was investigated. One possible explanation for this difference is that men tend to have lower hepatic sensitivity to insulin and may, in consequence, have generally higher fasting levels of plasma glucose.6969 Færch K, Borch-Johnsen K, Vaag A, Jørgensen T, Witte DR. Sex differences in glucose levels: a consequence of physiology or methodological convenience? The Inter99 study. Diabetologia 2010;53:858–65. doi: http://dx.doi.org/10.1007/s00125-010-1673-4 PMID:20182862
https://doi.org/10.1007/s00125-010-1673-...
Another possible explanation or contributing factor is that, within sub-Saharan Africa, men are more likely to smoke than women7171 Townsend L, Flisher AJ, Gilreath T, King G. A systematic literature review of tobacco use among adults 15 years and older in sub-Saharan Africa. Drug Alcohol Depend 2006;84:14–27. doi: http://dx.doi.org/10.1016/j.drugalcdep.2005.12.008 PMID:16442750
https://doi.org/10.1016/j.drugalcdep.200...
and smoking appears to increase the risk of impaired fasting glucose, by decreasing insulin sensitivity.7272 Færch K, Vaag A, Witte DR, Jørgensen T, Pedersen O, Borch-Johnsen K. Predictors of future fasting and 2-h post-OGTT plasma glucose levels in middle-aged men and women – the Inter99 study. Diabet Med 2009;26:377–83. doi: http://dx.doi.org/10.1111/j.1464-5491.2009.02688.x PMID:19388967
https://doi.org/10.1111/j.1464-5491.2009...
7474 Rafalson L, Donahue RP, Dmochowski J, Rejman K, Dorn J, Trevisan M. Cigarette smoking is associated with conversion from normoglycemia to impaired fasting glucose: the Western New York Health Study. Ann Epidemiol 2009;19:365–71. doi: http://dx.doi.org/10.1016/j.annepidem.2009.01.013 PMID:19345115
https://doi.org/10.1016/j.annepidem.2009...

In earlier research, impaired glucose tolerance has generally been found to be more common among women than among men.2222 Unwin N, Shaw J, Zimmet P, Alberti KGMM. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708–23. doi: http://dx.doi.org/10.1046/j.1464-5491.2002.00835.x PMID:12207806
https://doi.org/10.1046/j.1464-5491.2002...
,2424 Williams JW, Zimmet PZ, Shaw JE, de Courten MP, Cameron AJ, Chitson P et al. Gender differences in the prevalence of impaired fasting glycaemia and impaired glucose tolerance in Mauritius. Does sex matter? Diabet Med 2003;20:915–20. doi: http://dx.doi.org/10.1046/j.1464-5491.2003.01059.x PMID:14632717
https://doi.org/10.1046/j.1464-5491.2003...
,6969 Færch K, Borch-Johnsen K, Vaag A, Jørgensen T, Witte DR. Sex differences in glucose levels: a consequence of physiology or methodological convenience? The Inter99 study. Diabetologia 2010;53:858–65. doi: http://dx.doi.org/10.1007/s00125-010-1673-4 PMID:20182862
https://doi.org/10.1007/s00125-010-1673-...
The same difference between the sexes was detected in most of the subgroups that were investigated in the present meta-analysis. In general, women have a smaller mass of muscle than men and therefore less muscle available for the uptake of the fixed glucose load (75 g) used in the oral glucose-tolerance test.6969 Færch K, Borch-Johnsen K, Vaag A, Jørgensen T, Witte DR. Sex differences in glucose levels: a consequence of physiology or methodological convenience? The Inter99 study. Diabetologia 2010;53:858–65. doi: http://dx.doi.org/10.1007/s00125-010-1673-4 PMID:20182862
https://doi.org/10.1007/s00125-010-1673-...
,7575 Sicree RA, Zimmet PZ, Dunstan DW, Cameron AJ, Welborn TA, Shaw JE. Differences in height explain gender differences in the response to the oral glucose tolerance test – the AusDiab study. Diabet Med 2008;25:296–302. doi: http://dx.doi.org/10.1111/j.1464-5491.2007.02362.x PMID:18307457
https://doi.org/10.1111/j.1464-5491.2007...
Women also have relatively high levels of estrogen and progesterone, both of which can reduce whole-body insulin sensitivity.7676 van Genugten RE, Utzschneider KM, Tong J, Gerchman F, Zraika S, Udayasankar J et al.; American Diabetes Association GENNID Study Group. Effects of sex and hormone replacement therapy use on the prevalence of isolated impaired fasting glucose and isolated impaired glucose tolerance in subjects with a family history of type 2 diabetes. Diabetes 2006;55:3529–35. doi: http://dx.doi.org/10.2337/db06-0577 PMID:17130501
https://doi.org/10.2337/db06-0577...
Physical inactivity7777 Assah FK, Ekelund U, Brage S, Mbanya JC, Wareham NJ. Free-living physical activity energy expenditure is strongly related to glucose intolerance in Cameroonian adults independently of obesity. Diabetes Care 2009;32:367–9. doi: http://dx.doi.org/10.2337/dc08-1538 PMID:19017776
https://doi.org/10.2337/dc08-1538...
and unhealthy diet7878 Faerch K, Vaag A, Holst JJ, Hansen T, Jørgensen T, Borch-Johnsen K. Natural history of insulin sensitivity and insulin secretion in the progression from normal glucose tolerance to impaired fasting glycemia and impaired glucose tolerance: the Inter99 study. Diabetes Care 2009;32:439–44. doi: http://dx.doi.org/10.2337/dc08-1195 PMID:19056613
https://doi.org/10.2337/dc08-1195...
have also both been associated with impaired glucose tolerance. In many countries in sub-Saharan Africa, women are more likely to be physically inactive than the corresponding men.7979 Guthold R, Ono T, Strong KL, Chatterji S, Morabia A. Worldwide variability in physical inactivity a 51-country survey. Am J Prev Med 2008;34:486–94. doi: http://dx.doi.org/10.1016/j.amepre.2008.02.013 PMID:18471584
https://doi.org/10.1016/j.amepre.2008.02...
,8080 Kruger A, Wissing MP, Towers GW, Doak CM. Sex differences independent of other psycho-sociodemographic factors as a predictor of body mass index in black South African adults. J Health Popul Nutr 2012;30:56–65. doi: http://dx.doi.org/10.3329/jhpn.v30i1.11277 PMID:22524120
https://doi.org/10.3329/jhpn.v30i1.11277...

The differences in the sex distribution of both impaired fasting glycaemia and impaired glucose tolerance in sub-Saharan Africa need to be considered in evaluating the probability that individuals will develop diabetes mellitus and in efforts to prevent the disease. Impairments in glucose tolerance and in fasting glycaemia are not metabolically equivalent, and the people classified as having each condition are different as well.2222 Unwin N, Shaw J, Zimmet P, Alberti KGMM. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708–23. doi: http://dx.doi.org/10.1046/j.1464-5491.2002.00835.x PMID:12207806
https://doi.org/10.1046/j.1464-5491.2002...
,8181 Abdul-Ghani MA, DeFronzo RA. Pathophysiology of prediabetes. Curr Diab Rep 2009;9:193–9. doi: http://dx.doi.org/10.1007/s11892-009-0032-7 PMID:19490820
https://doi.org/10.1007/s11892-009-0032-...
If screening programmes were based only on the measurement of “fasting plasma glucose”, most individuals with impaired glucose tolerance would go undetected and the population identified as being at risk would probably be biased towards males. The glycated haemoglobin (HbA1c) assay6969 Færch K, Borch-Johnsen K, Vaag A, Jørgensen T, Witte DR. Sex differences in glucose levels: a consequence of physiology or methodological convenience? The Inter99 study. Diabetologia 2010;53:858–65. doi: http://dx.doi.org/10.1007/s00125-010-1673-4 PMID:20182862
https://doi.org/10.1007/s00125-010-1673-...
may offer a way of evaluating the risk of diabetes mellitus that is relatively sex-neutral, although this assay is currently too expensive for routine use in Africa and it can also be affected by disorders such as malaria.8282 Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus. Geneva: World Health Organization; 2011. Screening for both impaired fasting glycaemia and impaired glucose tolerance might eliminate most of the sex bias in the identification of those who are at risk of developing diabetes mellitus. Even then, the dose of glucose used in the oral glucose-tolerance test may have to be made lower for women than for men – or tailored to the height of the individual to be tested – to allow for the lower mean muscle mass in women and so prevent the over-diagnosis of impaired glucose tolerance in women.7272 Færch K, Vaag A, Witte DR, Jørgensen T, Pedersen O, Borch-Johnsen K. Predictors of future fasting and 2-h post-OGTT plasma glucose levels in middle-aged men and women – the Inter99 study. Diabet Med 2009;26:377–83. doi: http://dx.doi.org/10.1111/j.1464-5491.2009.02688.x PMID:19388967
https://doi.org/10.1111/j.1464-5491.2009...

In the present meta-analysis, despite the differences seen by sex in impaired fasting glycaemia and impaired glucose tolerance, the overall prevalence of diabetes mellitus in men was found to be very similar to that in women. However, subgroup analyses revealed that diabetes mellitus was more common in the men who lived in Middle and Eastern Africa than in the women who lived in the same African subregions, whereas the women who lived in Southern Africa were more likely to have diabetes mellitus than the corresponding men. Such differences between the sexes were not seen in the earlier study on diabetes mellitus in West Africa.1919 Abubakari AR, Lauder W, Jones MC, Kirk A, Agyemang C, Bhopal RS. Prevalence and time trends in diabetes and physical inactivity among adult West African populations: the epidemic has arrived. Public Health 2009;123:602–14. doi: http://dx.doi.org/10.1016/j.puhe.2009.07.009 PMID:19748643
https://doi.org/10.1016/j.puhe.2009.07.0...
Some of these differences may be related to differences between the sexes in the prevalence of central obesity, which, as a risk factor for diabetes mellitus, is more predictive than peripheral obesity.8383 Lee CMY, Huxley RR, Wildman RP, Woodward M. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol 2008;61:646–53. doi: http://dx.doi.org/10.1016/j.jclinepi.2007.08.012 PMID:18359190
https://doi.org/10.1016/j.jclinepi.2007....
Central obesity has been found to be more common in men than in women in Eastern Africa8484 Christensen DL, Eis J, Hansen AW, Larsson MW, Mwaniki DL, Kilonzo B et al. Obesity and regional fat distribution in Kenyan populations: impact of ethnicity and urbanization. Ann Hum Biol 2008;35:232–49. doi: http://dx.doi.org/10.1080/03014460801949870 PMID:18428015
https://doi.org/10.1080/0301446080194987...
,8585 Msamati BC, Igbigbi PS. Anthropometric profile of urban adult black Malawians. East Afr Med J 2000;77:364–8. PMID:12862154 and more common in women than men in Southern Africa.8686 Puoane T, Steyn K, Bradshaw D, Laubscher R, Fourie J, Lambert V et al. Obesity in South Africa: the South African demographic and health survey. Obes Res 2002;10:1038–48. doi: http://dx.doi.org/10.1038/oby.2002.141 PMID:12376585
https://doi.org/10.1038/oby.2002.141...
However, such obesity cannot be used to explain why the men of Middle Africa are more likely to have diabetes mellitus than the women, as central obesity is more common among the women in this area than among the men.8787 Kasiam Lasi On’kin JB, Longo-Mbenza B, Nge Okwe A, Kangola Kabangu N. Survey of abdominal obesities in an adult urban population of Kinshasa, Democratic Republic of Congo. Cardiovasc J Afr 2007;18:300–7. PMID:17985031 Behavioural risk factors, such as smoking and alcohol use, which are more common among the men of sub-Saharan Africa than among the women,3BeLue R, Okoror TA, Iwelunmor J, Taylor KD, Degboe AN, Agyemang C et al. An overview of cardiovascular risk factor burden in sub-Saharan African countries: a socio-cultural perspective. Global Health 2009;5:10. doi: http://dx.doi.org/10.1186/1744-8603-5-10 PMID:19772644
https://doi.org/10.1186/1744-8603-5-10...
,7171 Townsend L, Flisher AJ, Gilreath T, King G. A systematic literature review of tobacco use among adults 15 years and older in sub-Saharan Africa. Drug Alcohol Depend 2006;84:14–27. doi: http://dx.doi.org/10.1016/j.drugalcdep.2005.12.008 PMID:16442750
https://doi.org/10.1016/j.drugalcdep.200...
might contribute to the prevalence of diabetes mellitus among the men of Middle Africa.

In the present meta-analysis, the income level of the country of residence – a proxy indicator of the economic status of the people in the country – appeared to contribute to the heterogeneity seen in the association between sex and the prevalence of diabetes mellitus. Women of low socioeconomic status in Australia,8888 Kavanagh A, Bentley RJ, Turrell G, Shaw J, Dunstan D, Subramanian SV. Socioeconomic position, gender, health behaviours and biomarkers of cardiovascular disease and diabetes. Soc Sci Med 2010;71:1150–60. doi: http://dx.doi.org/10.1016/j.socscimed.2010.05.038 PMID:20667641
https://doi.org/10.1016/j.socscimed.2010...
Canada,8989 Tang M, Chen Y, Krewski D. Gender-related differences in the association between socioeconomic status and self-reported diabetes. Int J Epidemiol 2003;32:381–5. doi: http://dx.doi.org/10.1093/ije/dyg075 PMID:12777423
https://doi.org/10.1093/ije/dyg075...
Germany9090 Rathmann W, Haastert B, Icks A, Giani G, Holle R, Meisinger C et al.; KORA Study Group. Sex differences in the associations of socioeconomic status with undiagnosed diabetes mellitus and impaired glucose tolerance in the elderly population: the KORA Survey 2000. Eur J Public Health 2005;15:627–33. doi: http://dx.doi.org/10.1093/eurpub/cki037 PMID:16051657
https://doi.org/10.1093/eurpub/cki037...
and the United States of America9191 Robbins JM, Vaccarino V, Zhang H, Kasl SV. Socioeconomic status and type 2 diabetes in African American and non-Hispanic white women and men: evidence from the Third National Health and Nutrition Examination Survey. Am J Public Health 2001;91:76–83. doi: http://dx.doi.org/10.2105/AJPH.91.1.76 PMID:11189829
https://doi.org/10.2105/AJPH.91.1.76...
appear to be at markedly higher risk of diabetes mellitus than the corresponding men. In a recent meta-analysis, the incidence of Type 2 diabetes mellitus among adults with low socioeconomic status was found to be generally higher in women than in men; it was suggested that the women who lived in impoverished areas were more likely to be obese, physically inactive and under high levels of psychosocial stress than the men in the same areas.9292 Agardh E, Allebeck P, Hallqvist J, Moradi T, Sidorchuk A. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol 2011;40:804–18. doi: http://dx.doi.org/10.1093/ije/dyr029 PMID:21335614
https://doi.org/10.1093/ije/dyr029...
In contrast, the results of the present meta-analysis indicated that men who lived in the low-income countries of sub-Saharan Africa were more likely to be diagnosed with diabetes mellitus than the corresponding women. This difference between the sexes may be a consequence of differences between men and women in the distribution of risk factors for diabetes mellitus (e.g. obesity, physical inactivity, poor diet and smoking, etc.) in low-income countries. Another possibility is that women in low-income countries have particularly poor access to health-care services and therefore little chance of being diagnosed with diabetes.8888 Kavanagh A, Bentley RJ, Turrell G, Shaw J, Dunstan D, Subramanian SV. Socioeconomic position, gender, health behaviours and biomarkers of cardiovascular disease and diabetes. Soc Sci Med 2010;71:1150–60. doi: http://dx.doi.org/10.1016/j.socscimed.2010.05.038 PMID:20667641
https://doi.org/10.1016/j.socscimed.2010...
,8989 Tang M, Chen Y, Krewski D. Gender-related differences in the association between socioeconomic status and self-reported diabetes. Int J Epidemiol 2003;32:381–5. doi: http://dx.doi.org/10.1093/ije/dyg075 PMID:12777423
https://doi.org/10.1093/ije/dyg075...
,9191 Robbins JM, Vaccarino V, Zhang H, Kasl SV. Socioeconomic status and type 2 diabetes in African American and non-Hispanic white women and men: evidence from the Third National Health and Nutrition Examination Survey. Am J Public Health 2001;91:76–83. doi: http://dx.doi.org/10.2105/AJPH.91.1.76 PMID:11189829
https://doi.org/10.2105/AJPH.91.1.76...
,9292 Agardh E, Allebeck P, Hallqvist J, Moradi T, Sidorchuk A. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol 2011;40:804–18. doi: http://dx.doi.org/10.1093/ije/dyr029 PMID:21335614
https://doi.org/10.1093/ije/dyr029...
In addition, as Africa is one of the most inequitable parts of the world in terms of income,9393 Briefing notes for AfDB' s long-term strategy. Briefing note 5: Income inequality in Africa [Internet]. Abidjan: African Development Bank Group; 2012. Available from: http://www.afdb.org/fileadmin/uploads/afdb/Documents/Policy-Documents/FINAL%20Briefing%20Note%205%20Income%20Inequality%20in%20Africa.pdf [accessed 1 April 2013].
http://www.afdb.org/fileadmin/uploads/af...
the income level recorded for an African country might not correlate with the socioeconomic status of a study cohort in that country. There appear to be no published data sets that would allow sex-based differences in the relationship between individual socioeconomic status and diabetes mellitus in sub-Saharan Africa to be investigated.

The present meta-analysis had several limitations. First, the studies that provided the data for the meta-analysis were conducted under different circumstances in different countries and the prevalences of diabetes mellitus, impaired fasting glycaemia and/or impaired glucose tolerance were not the primary outcomes of some of the studies. A random-effects model was therefore employed to embrace this considerable heterogeneity.4040 Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons, Ltd; 2009. Second, the studies had to be cross-sectional in design to be included in the meta-analysis and may therefore have been affected by confounding and biases. However, we attempted to minimize selection bias by employing predefined study selection criteria and a quality appraisal checklist. Potential sources of heterogeneity were also assessed in subgroup and meta-regression analyses. Third, since our subgroup and meta-regression analyses were entirely observational in nature, the relationships recorded – across all of the studies – between some study-level characteristics and the effect estimate could be subject to confounding by other study-level characteristics. Unfortunately, the studies included in the meta-analysis were too few to allow for a reasonable assessment of interactions between the study-level covariates. Fourth, we used the income levels of the countries of residence to stratify the studies because of a general lack of information on the socioeconomic status of study participants. The relationships that we observed between a country's income level and the sex-specific prevalences of interest may therefore not reflect the relationships between the socioeconomic status of the subjects and their risks of impaired fasting glycaemia, impaired glucose tolerance or diabetes mellitus. Finally, our conclusions may have been affected by publication bias. The asymmetric funnel plots were indicative of possible publication bias in the data for diabetes mellitus and impaired fasting glucose. Furthermore, our study selection criteria excluded reports that did not have an abstract in English and may have excluded some reports that were not recorded in the PubMed or Web of Science databases, although we did try to search the “grey” literature for relevant data. The results of the “trim and fill” analyses indicated that the impact of any publication bias on our conclusions was probably trivial.

In summary, our meta-analysis demonstrated that, compared with the corresponding women, the men in Eastern, Middle and Southern Africa had a significantly higher prevalence of impaired fasting glycaemia and a lower prevalence of impaired glucose tolerance. Although the overall prevalence of diabetes mellitus did not significantly differ by sex, the prevalence of diabetes mellitus was found to be lower or higher in women than in men when analysed by African subregion. Sex-based differences in the relationship between individual socioeconomic status and impaired fasting glycaemia, impaired glucose tolerance and diabetes mellitus still need to be investigated in sub-Saharan Africa. Our observations may help in the targeting of appropriate – and perhaps sex-specific – interventions to prevent diabetes mellitus in sub-Saharan Africa.

We are grateful to the authors of the articles included in the meta-analysis, many of whom kindly provided us with additional information regarding their studies.

Competing interests:

  • None declared.

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Publication Dates

    History

    • Received
      13 Nov 2012
    • Reviewed
      21 Feb 2013
    • Accepted
      25 Mar 2013
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