Scientific papers

@article{Kengne2017,

title = {Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies},

author = {Andre Pascal Kengne and James Bentham and Bin Zhou and Nasheeta Peer and Tandi E. Matsha and Honor Bixby and Mariachiara Di Cesare and Kaveh Hajifathalian and Yuan Lu and Cristina Taddei and Pascal Bovet and Catherine Kyobutungi and Charles Agyemang and Hajer Aounallah-Skhiri and Felix K. Assah and Amina Barkat and Habiba Ben Romdhane and Queenie Chan and Nishi Chaturvedi and Albertino Damasceno and Hélène Delisle and Francis Delpeuch and Kouamelan Doua and Eruke E. Egbagbe and Jalila El Ati and Paul Elliott and Reina Engle-Stone and Rajiv T. Erasmus and Heba M. Fouad and Dickman Gareta and Oye Gureje and Marleen Elisabeth Hendriks and Leila Houti and Mohsen M. Ibrahim and Han C G Kemper and Japhet Killewo and Sudhir Kowlessur and Herculina S. Kruger and Fatima Zahra Laamiri and Youcef Laid and Naomi S. Levitt and Nuno Lunet and Dianna J. Magliano and Bernard Maire and Yves Martin-Prevel and Sounnia Mediene-Benchekor and Mostafa K. Mohamed and Charles K. Mondo and Kotsedi Daniel Monyeki and Aya Mostafa and Martin Nankap and Ellis Owusu-Dabo and Tobias F Rinke Wit and Olfa Saidi and Constance Schultsz and Aletta E. Schutte and Idowu O. Senbanjo and Jonathan E. Shaw and Liam Smeeth and Eugène Sobngwi and Charles Sossa Jérome and Karien Stronks and Frank Tanser and Félicité Tchibindat and Pierre Traissac and Lechaba Tshepo and Fikru Tullu and Flora A M Ukoli and Bharathi Viswanathan and Alisha N. Wade and Goodarz Danaei and Gretchen A. Stevens and Leanne M. Riley and Majid Ezzati and Jean Claude N. Mbanya},

url = {https://academic.oup.com/ije/article/46/5/1421/3861188},

doi = {10.1093/ije/dyx078},

issn = {0300-5771},

year  = {2017},

date = {2017-01-01},

journal = {International Journal of Epidemiology},

volume = {46},

issue = {5},

pages = {1421-1432},

abstract = {Background: The 2016 Dar Es Salaam Call to Action on Diabetes and Other noncommunicable diseases (NCDs) advocates national multi-sectoral NCD strategies and action plans based on available data and information from countries of sub-Saharan Africa and beyond. We estimated trends from 1980 to 2014 in age-standardized mean body mass index (BMI) and diabetes prevalence in these countries, in order to assess the coprogression and assist policy formulation. Methods: We pooled data from African and worldwide population-based studies which measured height, weight and biomarkers to assess diabetes status in adults aged ≥18 years. A Bayesian hierarchical model was used to estimate trends by sex for 200 countries and territories including 53 countries across five African regions (central, eastern, northern, southern and western), in mean BMI and diabetes prevalence (defined as either fasting plasma glucose of ≥ 7.0 mmol/l, history of diabetes diagnosis, or use of insulin or oral glucose control agents). Results: African data came from 245 population-based surveys (1.2 million participants) for BMI and 76 surveys (182 000 participants) for diabetes prevalence estimates. Countries with the highest number of data sources for BMI were South Africa (n=17), Nigeria (n=15) and Egypt (n=13); and for diabetes estimates, Tanzania (n=8), Tunisia (n=7), and Cameroon, Egypt and South Africa (all n=6). The age-standardized mean BMI increased from 21.0 kg/m2 (95% credible interval: 20.3-21.7) to 23.0 kg/m2 (22.7-23.3) in men, and from 21.9 kg/m2 (21.3-22.5) to 24.9 kg/m2 (24.6-25.1) in women. The agestandardized prevalence of diabetes increased from 3.4% (1.5-6.3) to 8.5% (6.5-10.8) in men, and from 4.1% (2.0-7.5) to 8.9% (6.9-11.2) in women. Estimates in northern and southern regions were mostly higher than the global average; those in central, eastern and western regions were lower than global averages. A positive association (correlation coefficient ≃ 0.9) was observed between mean BMI and diabetes prevalence in both sexes in 1980 and 2014. Conclusions: These estimates, based on limited data sources, confirm the rapidly increasing burden of diabetes in Africa. This rise is being driven, at least in part, by increasing adiposity, with regional variations in observed trends. African countries' efforts to prevent and control diabetes and obesity should integrate the setting up of reliable monitoring systems, consistent with the World Health Organization's Global Monitoring System Framework.},

keywords = {Adiposity, Africa, Body mass index, Diabetes, Prevalence, Trends},

pubstate = {published},

tppubtype = {article}

}

@article{Katte2014,

title = {Coincidence of diabetes mellitus and hypertension in a semi-urban Cameroonian population: a cross-sectional study},

author = {Jean-Claude Katte and Anastase Dzudie and Eugene Sobngwi and Eta N. Mbong and Gerard Tama Fetse and Charles Kouam Kouam and Andre-Pascal Kengne},

url = {http://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-14-696},

doi = {10.1186/1471-2458-14-696},

issn = {1471-2458},

year  = {2014},

date = {2014-01-01},

journal = {BMC Public Health},

volume = {14},

issue = {1},

pages = {696},

abstract = {Hypertension and diabetes mellitus are increasingly common in population within Africa. We determined the rate of coincident diabetes and hypertension and assessed the levels of co-awareness, treatment and control in a semi-urban population in Cameroon. Methods. A total of 1702 adults (967 women) self-selected from the community were consecutively recruited in Bafoussam (West region of Cameroon) during November 2012. Existing diabetes and hypertension and treatments were investigated and blood pressure and fasting blood glucose measured. Multinomial logistic regressions models were used to investigate the determinants of prevalent diabetes and hypertension. Results: Age-standardized prevalence rates (95% confidence intervals) men vs. women were 40.4% (34.7 to 46.1) and 23.8% (20.4 to 27.2) for hypertension alone; 3.3% (1.5 to 5.1) and 5.6% (3.5 to 7.7) for diabetes alone; and 3.9% (2.6 to 5.2) and 5.0% (3.5 to 6.5) for hypertension and diabetes. The age-standardized awareness, treatment and control rates for hypertension alone were 6.5%, 86.4% and 37.2% for men, and 24.3%, 52.1% and 51.6% in women. Equivalent figures for diabetes alone were 35.4%, 65.6% and 23.1% in men and 26.4%, 75.5% and 33.7% in women; and those for hypertension and diabetes were 86.6%, 3.3% and 0% in men, and 74.7%, 22.6% and 0% in women. Sex, age and adiposity were the main determinants of the three conditions. Conclusions: Coincident diabetes and hypertension is as high as diabetes alone in this population, driven by sex, age and adiposity. Awareness, treatment and control remain unacceptably low. © 2014 Katte et al.; licensee BioMed Central Ltd.},

keywords = {Cameroon, Coincidence, diabetes mellitus, hypertension, Prevalence, Sub-Saharan Africa},

pubstate = {published},

tppubtype = {article}

}

@article{Al-Quwaidhi2014,

title = {Comparison of type 2 diabetes prevalence estimates in Saudi Arabia from a validated Markov model against the International Diabetes Federation and other modelling studies},

author = {Abdulkareem J. Al-Quwaidhi and Mark S. Pearce and Eugene Sobngwi and Julia A. Critchley and Martin O’Flaherty},

url = {http://dx.doi.org/10.1016/j.diabres.2013.12.036 https://linkinghub.elsevier.com/retrieve/pii/S0168822713004701},

doi = {10.1016/j.diabres.2013.12.036},

issn = {01688227},

year  = {2014},

date = {2014-01-01},

journal = {Diabetes Research and Clinical Practice},

volume = {103},

issue = {3},

pages = {496-503},

publisher = {Elsevier Ireland Ltd},

abstract = {Aims: To compare the estimates and projections of type 2 diabetes mellitus (T2DM) prevalence in Saudi Arabia from a validated Markov model against other modelling estimates, such as those produced by the International Diabetes Federation (IDF) Diabetes Atlas and the Global Burden of Disease (GBD) project. Methods: A discrete-state Markov model was developed and validated that integrates data on population, obesity and smoking prevalence trends in adult Saudis aged ≥25 years to estimate the trends in T2DM prevalence (annually from 1992 to 2022). The model was validated by comparing the age- and sex-specific prevalence estimates against a national survey conducted in 2005. Results: Prevalence estimates from this new Markov model were consistent with the 2005 national survey and very similar to the GBD study estimates. Prevalence in men and women in 2000 was estimated by the GBD model respectively at 17.5% and 17.7%, compared to 17.7% and 16.4% in this study. The IDF estimates of the total diabetes prevalence were considerably lower at 16.7% in 2011 and 20.8% in 2030, compared with 29.2% in 2011 and 44.1% in 2022 in this study. Conclusion: In contrast to other modelling studies, both the Saudi IMPACT Diabetes Forecast Model and the GBD model directly incorporated the trends in obesity prevalence and/or body mass index (BMI) to inform T2DM prevalence estimates. It appears that such a direct incorporation of obesity trends in modelling studies results in higher estimates of the future prevalence of T2DM, at least in countries where obesity has been rapidly increasing. © 2013 Elsevier Ireland Ltd.},

keywords = {Diabetes, Modelling, Prevalence, Saudi Arabia},

pubstate = {published},

tppubtype = {article}

}

@article{Kengne2012,

title = {Metabolic syndrome in type 2 diabetes: comparative prevalence according to two sets of diagnostic criteria in sub-Saharan Africans},

author = {Andre P. Kengne and Serge N. Limen and Eugene Sobngwi and Cathérine F. T. Djouogo and Christophe Nouedoui},

url = {https://dmsjournal.biomedcentral.com/articles/10.1186/1758-5996-4-22},

doi = {10.1186/1758-5996-4-22},

issn = {1758-5996},

year  = {2012},

date = {2012-01-01},

journal = {Diabetology & Metabolic Syndrome},

volume = {4},

issue = {1},

pages = {22},

abstract = {Background: Available definition criteria for metabolic syndrome (MS) have similarities and inconsistencies. The aim of this study was to determine the prevalence of MS in a group of Cameroonians with type 2 diabetes, according to the International Diabetes Federation (IDF) and the National Cholesterol Education Programme Adult Treatment Panel III (NCEP-ATP III) criteria, and to assess the concordance between both criteria, and the implications of combining them. Methods: We collected clinical and biochemical data for 308 patients with type 2 diabetes (men 157) at the National Obesity Center of the Yaounde Central Hospital, Cameroon. Concordance was assessed with the use of the Kappa statistic. Results: Mean age (standard deviation) was 55.8 (10.5) years and the median duration of diagnosed diabetes (25th75th percentiles) was 3 years (0.55.0), similarly among men and women. The prevalence of MS was 71.7% according to the IDF criteria and 60.4% according to NCEP-ATP III criteria. The prevalence was significantly higher in women than in men independently of the criteria used (both p<0.001). Overall concordance between both definitions was low to average 0.51 (95% confidence interval: 0.410.61). Combining the two sets of criteria marginally improved the yield beyond that provided by the IDF criteria alone in men, but not in the overall population and in women. Conclusions: The IDF and NCEP-ATP III criteria do not always diagnose the same group of diabetic individuals with MS and combining them merely increases the yield beyond that provided by the IDF definition alone. This study highlights the importance of having a single unifying definition for MS in our setting. © 2012 Kengne et al.; licensee BioMed Central Ltd.},

keywords = {Cameroon, Concordance, diabetes mellitus, Metabolic syndrome, Prevalence, Sub-Saharan Africa},

pubstate = {published},

tppubtype = {article}

}