Type 2 diabetes in a Senegalese rural area(2)

Variables studied

The socioeconomic and demographic variables collected were age (20-29/30-39/40-49/50 and over),gender (male/female) and educational level - defined in accordance with the educational system in Senegal- (0/1-5/6-9/10-12/over 12 years of school).

The following question was used as an indicator of economic conditions: “Given your household income,do you feel you … (1) live well? (2) live okay? (3)live okay, but you have to be careful? and (4) have difficulty making ends meet”? This question, taken directly from Razafindrakoto and Roubaud’s study[21],has demonstrated validity and relevance in eight African capitals, including Dakar, to measure economic conditions in the context of subjective well-being. For the analyses, the answers were coded from 1 (poor) to 4 (prosperous). The Mini International Neuropsychiatric Interview (MINI) was used to diagnose major depressive episodes at the time of the interview[22,23].

The biological health variables collected were dysglycemia, blood pressure (BP), body mass index(BMI), waist circumference (WC) and waist-to-hip ratio(WHR). For dysglycemia, subjects were examined during the morning after fasting since the previous evening meal. The day before the investigation, subjects were informed of the need to have nothing to drink or eat in order to measure capillary whole blood glucose. Capillary whole blood (glucose) was obtained from a finger prick and was immediately analyzed using a Hemocue blood glucose analyzer?. The participants were then divided into three categories according to international standards[24]: Fasting plasma glucose＜ 110 mg/dL; IFG: Fasting plasma glucose levels between 110 and 125 mg/dL; those with diabetes,who had either been previously diagnosed diabetics or had capillary whole blood glucose value greater than or equal to 126 mg/dL.

In order to measure BP, we used an OMRON M5-I digital automatic blood pressure monitor (OMRON?,s’Hertogenbosch, The Netherlands). Measurements were taken on the upper right arm using an appropriate sized cuff while the participant was sitting and had rested for 5 min. Three readings were taken during the interview. The first was discarded, and the mean of the last two readings were used in the (HTA) was defined as a systolic BP ≥ 140 mmHg (SBP) and/or a diastolic BP ≥ 90 mmHg (DBP)or reported treatment for hypertension.

Finally, overweight was defined as 25 ≤ BMI ＜ 30;obesity corresponded to a BMI of ≥ 30; underweight to a BMI of ＜ 18.5. WC of ≥ 102 cm in men and of ≥88 cm in women was considered central obesity. Lastly,a WHR of ＞ 0.9 in men and a WHR of ＞ 0.8 in women were considered central obesity[25].

Statistical analysis

Files compiled on the basis of the 496 questionnaires were processed and coded in Excel (2013). We used χ2 tests to measure the presence, strength,and independence of statistical association of sociodemographic and biological variables and also carried out binary logistic regression analyses to estimate the risk factors for diabetes. All analyses were performed using SPSS software, version 20. A two-sided P-value of less than 0.05 was considered significant.

REsULTs

In our sample, more than two-thirds of the participants were aged ＜ 40 years. Almost three-quarters had not attended school and the majority was not of men and women were balanced, as the proportions of people with good and poor material well-being. Most individuals were not hypertensive and not obese by WC, whereas 40% of individuals had central obesity measured by WHR. Prevalence of diabetes and IFG in our sample was 4.2% (95%CI:2.44%-5.96%) and 6.6% (95%CI: 4.42%-8.78%)respectively.

Table 1 shows that in Tessekere, only mean BMI is significantly higher among diabetic individuals and among those having FBG ≥ 110 mg/dL. Furthermore,IFG is significantly more prevalent in individuals aged 50 and over and in individuals with central obesity (by WC and WHR).

The previously identified relationship between FBG,sociodemographic and biological health variables wastested by binary logistic regression. The results of the binary logistic regression are presented in Table 2.

Table 1 Fasting blood glucose levels by sex, age, education, material well-being, Mini International Neuropsychiatric Interview, hypertension,waist circumference, waist-to-hip ratio, body mass index, systolic blood pressure and diastolic blood pressure in Dakar (n = 500)Education levels ＞ 5 years have been aggregated in order to keep sufficient numbers for statistical tests. MINI: Mini International Neuropsychiatric Interview; HTA: Hypertension; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BMI: Body mass index; WC: Waist circumference; WHR: Waistto-hip Categories ＜ 126 mg/dL≥ 126 mg/dL Test ＜ 110 mg/dL≥ 110 mg/dL Test Total Total 475 21 463 33 496 Sex Men 233 8 χ2 = 0.967; 228 13 χ2 = 1.196; 241 Women 242 13 P = 0.326 235 20 P = 0.274 255 Education 0 358 15 χ2 = 0.204; 350 23 χ2 = 3.044; 373 level 1-5 82 4 P = 0.903 81 5 P = 0.218 86 6-9 18 0 16 2 18 10-12 11 2 10 3 13＞ 12 6 0 6 0 6 Age 20-29 193 7 χ2 = 3.026; 189 11 χ2 = 11.893; 200 bracket 30-39 112 3 P = 0.553 111 4 P = 0.018 115 40-49 73 4 72 5 77≥ 50 97 7 91 13 104 Material Well 71 1 χ2 = 5.554; 69 3 χ2 = 2.351; 72 well-being Okay 145 11 P = 0.135 142 14 P = 0.503 156 Okay but careful 203 6 197 12 209 Difficulties 56 3 55 4 59 MINI Not depressive 438 20 χ2 = 0.261; 426 32 χ2 = 1.072; 458 Depressive 37 1 P = 0.610 37 1 P = 0.301 38 HTA HTA - 327 13 χ2 = 0.449; 319 21 χ2 = 0.396; 340 HTA + 148 8 P = 0.503 144 12 P = 0.529 156 WC Non obese 421 16 χ2 = 2.970; 412 25 χ2 = 5.143; 437 Obese 54 5 P = 0.085 51 8 P = 0.023 59 WHR Non obese 271 8 χ2 = 2.937; 266 13 χ2 = 4.082; 279 Obese 204 13 P = 0.087 197 20 P = 0.043 217 BMI Mean 20.8396 23.8 t = 3.303; P = 0.001 20.8 23.1 t = 3.155; P = 0.002 20.9 SBP Mean 125.3 127.8 t = 0.400; P = 0.693 125.2 127.5 t = 0.470; P = 0.641 125.4 DBP Mean 82.1 80.6 t = 0.579; P = 0.563 82.1 81.5 t = 0.301; P = 0.763 82.1

文章来源：《人类学学报》 网址: http://www.rlxxb.cn/qikandaodu/2021/0105/484.html