Type 2 diabetes in a Senegalese rural area(3)

Results show that actually only BMI was associated with FBG ≥ 126 mg/dL. Indeed, increased BMI is associated with increased risks of diabetes (Table 2).Furthermore, age and BMI were independently associated with IFG. Variables concerning central obesity(WC and WHR) were no longer associated with FBG after adjustment for age, sex and education level.

Finally, among individuals with FBG ≥ 126 mg/dL,5 (23.8%) were aware of their diabetic condition, 2(9.5%) of the diabetics were treated, and 0 diabetic individuals under treatment had controlled FBG (i.e.,FBG ＜ 126 mg/dL) (Figure 1).

DIsCUssION

The present study is to our knowledge one of the first to evaluate the prevalence of diabetes and IFG in a rural area in Senegal. The prevalence of diabetes in our sample is 4.2%, and that of IFG, 6.6%, corresponding to the high range of prevalence observed in rural sub-Saharan Africa, ranging from 0.8% to 6% for diabetes[26,27]. Our results thus confirm those obtained in Guinea[10], Nigeria[28] and Mali[29], suggesting that Fulani populations have a high prevalence of reasons for this high prevalence remain unclear. In the Tessekere municipality, Barral et al[30] showed that in 1981, a decreased consumption of cereals and an increased consumption of sugar (with tea, which was introduced recently at that time) and fat was observed since the 1950s, inducing a physiological modification that may have an impact on diabetes or , following the severe droughts in the Sahelian region in the 1970s, local products (millet, leaves,milk, cowpea, etc.), which provided food security were replaced by imported foodstuffs (rice, peanut oil, pasta, bread, etc.) and by small ruminant holdings(sheep, goats) to compensate for economic is more than likely that these rapid changes in diet have gradually led to an increase in diabetes over the past 30 years.

The risk factors identified in our population do not differ from those of other countries[12]. Age and BMI are significant predictors of FBG ≥ 110 mg/dL, but it is noteworthy that only BMI, and not age, is a significant predictor of diabetes in Tessekere. Indeed, it might be associated with two facts. First, in our study, the Fulani population presents a very high proportion of undiagnosed diabetes (76.19%). This result is in line with the results generally obtained in developing countries, where generally half to three-quarters of all cases are undetected[2,12]. But it also means that the condition is usually only diagnosed once patientsare overtly symptomatic or present complications[4].Consequently, the mortality associated with diabetes must be higher among older age groups, which explains the lack of correlation between age and the prevalence of diabetes. Secondly, even if Senegal is one of the five African countries with the most advanced nutrition transition[15], the Fulani population is very isolated (health centers, roads and stores located more than 5 km from camps, without motorized vehicles[31]), one of the poorest in Senegal, and seems to be just at the beginning of demographic,epidemiological and nutritional transitions. These characteristics could explain the lack of relationship between diabetes and age, as the diabetes epidemic appears to be nascent in our population. The same cause could also explain the lack of association between IFG or diabetes and central obesity. Indeed,whereas central obesity[14], depression[18] and material well-being[19] are generally identified risk factors in populations having long experienced diabetes, the recentness of the diabetes epidemic in our population may explain the absence of these risk factors.

Table 2 Odds ratios for fasting blood glucose ≥ 110 mg/dL and fasting blood glucose ≥ 126 mg/dL by sex, age, education level and body mass index in Tessekere (n = 500)aaP ＜ 0.05. 1Education levels ≥ 1 year and individuals ＜ 50 years have been aggregated in order to keep sufficient numbers for statistical tests. HTA:Hypertension; WC: Waist circumference; WHR: Waist-to-hip Categories IFG Diabetes P Odds ratios IC for OR (95%) P Odds ratios IC for OR (95%)Sex (men) Women 0.744 1.153 0.49 - 2.716 0.805 1.141 0.4 - 3.254 Age bracket (≥ 50 yr)1 ＜ 50 yr 0.0271 2.731 1.12 - 6.663 0.228 2.006 0.647 - 6.216 Education level (≥ 1 yr)1 0 yr 0.157 1.832 0.792 - 4.236 0.41 1.55 0.546 - 4.396 HTA (HTA-) HTA + 0.449 0.717 0.304 - 1.695 0.673 0.797 0.277 - 2.289 BMI (continuous) 0.049a 1.095 1 - 1.198 0.018a 1.142 1.023 - 1.274 WHR (obese) Not obese 0.334 1.532 0.645 - 3.635 0.396 1.577 0.551 - 4.508 WC (obese) Not obese 0.927 1.053 0.348 - 3.181 0.688 0.756 0.193 - 2.966

Figure 1 Prevalence of fasting blood glucose ≥ 126 mg/dL, awareness among fasting blood glucose ≥ 126 mg/dL, treatment among the aware, and control among the treated in Tessekere municipality. FBG: Fasting blood glucose.

Finally, the 4.2% prevalence of diabetes found in our study is comparable to the 4.6% observed in rural Senegal by Seck et al[32] but is far below the 8.5% to 12.9% prevalence reported for all other parts of the world[2]. In addition, the prevalence of IFG in our Tessekere sample is significantly lower than the 17.9%[17] or the 10.3%[10] observed respectively in Dakar and in urban Ghana with the same criteria and methods, which make direct comparison results are in line with the majority of the results concerning the urban-rural distribution of diabetes in sub-Saharan Africa[9,12]. Currently, 38% of the population of sub-Saharan Africa live in urban this proportion is predicted to increase to 45%by 2030, with a demographic inflection point to be attained by 2040: More urban than rural residents[33].Due to inherent growth in urban districts and massive migration from rural areas[6], diabetes will certainly rise in the next few years in Senegal, where a focus on actions to optimize lifestyle management is critically important, given that obtaining drugs to treat diabetes is challenging due to cost and availability[34,35].

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