Abstract
BackgroundThe diabetes prevalence increases at an alarming rate around the world and understanding disparities in occurrence, care management, and health outcomes may be a starting point towards achieving more effective strategies to prevent and manage it. The aims of this study are to compare immigrants and Italians in terms of the differences in diabetes prevalence and to evaluate inequalities in disease management and glycaemic control by using information included in Reggio Emilia diabetes register.MethodsWe retrieved from the diabetes register subjects aged 20–74 on December 31st, 2009. Using citizenship, we created three main groups: Italy, High Developed Countries (HDC), and High Migration Pressure Countries (HMPC). These were split into sub-regions of origin. We calculated age-adjusted prevalence by gender and sub-region. Using logistic regression model, we analyzed the association between area of origin and following indicators: 1) not being in care of diabetes clinics; 2) not having glycated haemoglobin (HbA1c) test in 2010; 3) among those tested, having a HbA1c value > = 9% (75 mmol/mol).ResultsWe found 15,889 Italian and 1,295 HMPC citizens with diabetes. HMPC citizens had higher age-adjusted prevalence of diabetes than Italians (females 5.0% vs 3.6%; males 6.5% vs 5.5%). The excess was mostly due to a strong excess in immigrants from Southern Asia (females 9.7%, males 10.2%) and Northern Africa (females 9.3%, males 5.9%). HMPC citizens were cared for by diabetes clinics in a similar proportion than Italians (OR: 1.08; 95% CI: 0.93-1.25), but had a greater odds of not being tested for HbA1c (OR: 1.51; 95% CI: 1.34-1.71), as well as of having HbA1c values equal to or over 9% (OR: 2.06; 95% CI: 1.80-3.14). The outcomes were poorer in HMPC females for the first two outcomes, while there was no difference for the HbA1c values (Wald test for heterogeneity p = 0.0850; p = 0.0156; p = 0.6635, respectively).ConclusionsOur findings highlight the need for gender-oriented actions for prevention and early diagnosis of the diabetes to contrast the higher risk in Northern Africans and Southern Asians. Further studies are required to determine whether the protocols in use are adequate for different immigrant groups.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-1403-4) contains supplementary material, which is available to authorized users.
Highlights
The diabetes prevalence increases at an alarming rate around the world and understanding disparities in occurrence, care management, and health outcomes may be a starting point towards achieving more effective strategies to prevent and manage it
We computed the mean age with confidence intervals and we reported the number and percentage of subjects not treated with anti-diabetic drugs, not in care of diabetes clinics, without Glycated haemoglobin (HbA1c) test in 2010, and, among those tested, with latest HbA1c assay > = 9% (75 mmol/mol)
Foreigners were younger than Italians (Table 1), and the lowest age means were found among men and women from sub-Saharan Africa (F: mean 44.6 years, 95% Confidence interval (CI): 41.4-47.9; M: mean 44.9 years, 95% confidence intervals (95% CI): 43.2-46.7)
Summary
The diabetes prevalence increases at an alarming rate around the world and understanding disparities in occurrence, care management, and health outcomes may be a starting point towards achieving more effective strategies to prevent and manage it. We created three main groups: Italy, High Developed Countries (HDC), and High Migration Pressure Countries (HMPC). These were split into sub-regions of origin. Understanding disparities in occurrence, care management, and health outcomes may be a starting point towards achieving more effective strategies to prevent and manage diabetes. Studies have shown that immigrants with diabetes are undermanaged [12-14], and some ethnic groups have a lower probability of testing glycaemic index and reaching the recommended levels of glycated haemoglobin (HbA1c) [15-18]. The relationship between diabetes and migration can be difficult to disentangle as the former is influenced by ethnic, socioeconomic, lifestyle, individual factors, and the latter by the country of origin, reasons for migration, age at arrival, and duration of stay in the host country
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