Assessment of diabetes and prediabetes prevalence and predictors by HbA1c in a population from sub-Saharan Africa with a high proportion of anemia: a prospective cross-sectional study

Abstract

IntroductionEpidemiological data about diabetes mellitus (DM) for sub-Saharan Africa (SSA) are scarce and the utility of glycated hemoglobin (HbA1c) to diagnose DM is uncertain in African populations with a high proportion of anemia.Research design and methodsIn a cross-sectional study, age-adjusted prevalence rates and predictors for DM and pre-DM were prospectively assessed by HbA1c in a semirural walk-in population of Tanzania (n=992). Predictors for DM were calculated by logistic regression. Correlations between HbA1c, hemoglobin, and blood glucose levels were done by Pearson’s correlation.ResultsOverall, DM and pre-DM prevalence rates were 6.8% (95% CI 5.3 to 8.5) and 25% (95% CI 22.8 to 28.3), respectively. There was an increase in DM prevalence in patients 50–59 (14.9%; 95% CI 9.1 to 22.5), ≥60 years old (18.5%; 95% CI 12.2 to 26.2) and in patients with overweight (9.3%; 95% CI 5.9 to 13.7), obesity (10.9%; 95% CI 6.9 to 16) compared with patients 18–29 years old (2.2%; 95% CI 0.9 to 4.4) (p<0.001) and to normal-weight patients (3.6%; 95% CI 2.1 to 5.6) (p<0.01), respectively. Age (OR 1.08, 95% CI 1.05 to 1.12; p<0.001), body mass index (BMI) (OR 1.10, 95% CI 1.04 to 1.16; p<0.001), and acute infection (OR 3.46, 95% CI 1.02 to 10.8; p=0.038) were predictors for DM. Comparing patients with a BMI of 20 kg/m2 and a BMI of 35 kg/m2, the relative risk for DM increases in average by 2.12-fold (range 1.91–2.24) across the age groups. Comparing patients 20 years old with patients 70 years old, the relative risk for DM increases in average 9.7-fold (range 8.9–10.4) across the BMI groups. Overall, 333 patients (36%) suffered from anemia. Pearson’s correlation coefficients (r) between HbA1c and hemoglobin was −0.009 (p=0.779), and between HbA1c and fasting blood glucose and random blood glucose, it was 0.775 and 0.622, respectively (p<0.001).ConclusionWe observed a high prevalence of DM and pre-DM, mainly triggered by increasing age and BMI, and provide evidence that HbA1c is suitable to assess DM also in populations of SSA with high proportions of anemia.Trial registration numberNCT03458338.

Prevalence of prediabetes and associated factors among community members in Rural Isingiro district

“…In the present study we found an overall of Prediabetes of 9.19%. This was within the estimated global prevalence range of 4.8%-11.9% but slightly higher than that of sub-Saharan Africa alone [14].However another study that assessed the prevalence of Prediabetes based on correlation with HbA1c in sub Saharan Africa found a prevalence of 25% by the ADA criteria [12]. The ADA criteria on the other hand is known to estimate higher prevalence of Prediabetes than the WHO criteria that we used in the current study.…”

Elderly Person with HIV and Antiretroviral Therapy: Prevalence of Dysglycemia and Risk Factors

“…In Africa, few studies were carried out on the subject, with prevalences of 3.5 to 26.5% for T2DM and 20.2 to 43.5% for PD, among adults with HIV on ART [24]. In Sub-Saharan Africa, data on T2DM are scarce and the high prevalence of anemia compromises the usefulness of glycated hemoglobin in the diagnosis of dysglycemia [25]. The prevalence of T2DM and PD in our study was higher than that found in the literature, probably because it is a sample with a CA equal to or greater than 60 years and the majority presenting premature aging [26].…”

HIV infection and anaemia do not affect HbA1c for the detection of diabetes in black South Africans: Evidence from the Durban Diabetes Study

“…Recent studies examining the relation between HbA 1c and anaemia have generally focused on anaemia classified solely using haemoglobin levels, or iron-deficiency anaemia (defined using additional measures including ferritin and transferrin)-which commonly causes microcytic anaemia 9,16,[20][21][22] [S3-S5]. The majority of these studies have reported inverse associations or correlations between HbA 1c levels and such measures that are generally small in magnitude 9,16 [S3, S4].…”

“…Importantly, few studies have been based in African populations, with mixed evidence regarding the presence, direction and magnitude of associations between anaemia and HbA 1c . [20][21][22] This points to the need for further, comprehensive evidence from this region. The exact mechanisms by which different types of anaemia may affect HbA 1c are not clear, with multiple proposed hypotheses regarding pathways.…”

“…Furthermore, our study was based on validated laboratory measurement of HbA 1c , PG, HIV infection and haematological indices performed on samples from all participants, and analyses were adjusted for a range of potential confounders. Additionally, we provide evidence from a randomly selected general population in South Africa, whereas most SSA-based studies identified here examining the relation between HbA 1c and anaemia 21,22 or HIV status 29,30 have been facility-based. Furthermore, to our knowledge, ours is one of very few SSAbased studies directly comparing diabetes defined by HbA 1c with OGTT (including both FPG and 2hPG measures), the other identified study being clinic-based.…”