RESUMO
BACKGROUND: The glycated haemoglobin A1c (HbA1c) level may be used for screening for type 2 diabetes and prediabetes instead of a more burdensome oral glucose tolerance test (OGTT). However, among the high-risk South Asian population, little is known about the overlap of the methods or about the metabolic profiles of those disconcordantly diagnosed. METHODS: We included 944 South Asians (18-60 years old), whom we screened with the HbA1c level and the OGTT in The Hague, the Netherlands. We calculated the area under the receiver-operator characteristic curve (AUROC) with a 95% confidence interval of HbA1c using the American Diabetes Association classifications, and determined the sensitivity and specificity with 95% confidence intervals at different thresholds. Moreover, we studied differences in metabolic characteristics between those identified by HbA1c and by the OGTT alone. RESULTS: The overlap between HbA1c and OGTT classifications was partial, both for diabetes and prediabetes. The AUROC of HbA1c for OGTT defined diabetes was 0.86 (0.79-0.93). The sensitivity was 0.46 (0.29-0.63); the specificity 0.98 (0.98-0.99). For prediabetes, the AUROC was 0.73 (0.69-0.77). Each of the 31 individuals with diabetes and 353 with prediabetes identified with the HbA1c level had a high body mass index, large waist circumference, high blood pressure, and low insulin sensitivity, all of which were similar to the values shown by those among the 19 with diabetes or 62 with prediabetes who only met the OGTT criteria, but not the HbA1c criteria. CONCLUSIONS: The HbA1c level identified a partially different group than the OGTT did. However, both those identified with the HbA1c level and those identified with the OGTT alone were at increased metabolic risk. TRIAL REGISTRATION: Dutch Trial Register: NTR1499.
Assuntos
Estatura , Inquéritos Nutricionais , Índice de Massa Corporal , Peso Corporal , Criança , HumanosRESUMO
OBJECTIVE: The Netherlands host three population-based cancer screening programmes: for cervical, breast, and colorectal cancer. For screening programmes to be effective, high participation rates are essential, but participation in the Netherlands' programmes is starting to fall below the minimal effective rate. We aimed to produce a systematic overview of the current known determinants of (non-)attendance at the Dutch cancer screening programmes. METHODS: A literature search was conducted in the electronic databases Academic Search Premier, Cochrane Library, Embase, EMCare, PubMed, PsycINFO, Web of Science, and also in grey literature, including all articles published before February 2018. The I-Change model was used to categorize the identified determinants of cancer screening attendance. RESULTS: In total, 19/1232 identified studies and 6 grey literature reports were included. Fifteen studies reported on predisposing factors. Characteristics such as social economic status, country of birth, and residency were most often reported, and correlate with cancer screening attendance. Thirteen studies addressed information factors. Factors on awareness, motivation, ability, and barriers were less often studied. CONCLUSION: Current studies tend to describe the general characteristics of (non-)attendance and (non-)attenders, but rarely provide in depth information on other factors of (non-)participation. The I-Change model proved to be a useful tool in mapping current knowledge on cancer screening attendance and revealed knowledge gaps regarding determinants of (non-)participation in the screening programmes. More research is needed to fully understand determinants of participation, in order to influence and optimize attendance rates over the long term.