Gestational diabetes mellitus prevalence in Maela refugee camp on the Thai-Myanmar Border: a clinical report.
Gilder ME., Zin TW., Wai NS., Ner M., Say PS., Htoo M., Say S., Htay WW., Simpson JA., Pukrittayakamee S., Nosten F., McGready R.
Background Individuals in conflict-affected areas rarely get appropriate care for chronic or non-infectious diseases. The prevalence of gestational diabetes mellitus (GDM) is increasing worldwide, and new evidence shows conclusively that the negative effects of hyperglycemia occur even at mild glucose elevations and that these negative effects can be attenuated by treatment. Scientific literature on gestational diabetes in refugee camp settings is critically limited. Methods A 75 g 2-hour glucose tolerance test was administered to 228 women attending the antenatal care (ANC) clinic in Maela refugee camp on the Thai-Myanmar border. Prevalence of GDM was determined using the HAPO trial cut-offs [≥92 mg/dL (fasting),≥180 (1 hour), and≥153 (2 hour)] and the WHO criteria [≥126 mg/dL (fasting), and 140 mg/dL (2 hour)]. Results From July 2011 to March 2012, the prevalence of GDM was 10.1% [95% confidence interval (CI): 6.2-14.0] when the cut-off determined by the HAPO trial was applied. Applying the older WHO criteria yielded a prevalence of 6.6% (95% CI 3.3-9.8). Age, parity, and BMI emerged as characteristics that may be significantly associated with GDM in this population. Other risk factors that are commonly used in screening guidelines were not applicable in this diabetes-naïve population. Discussion The prevalence of GDM is lower in this population compared with other populations, but still complicates 10% of pregnancies. New evidence regarding gestational diabetes raises new dilemmas for healthcare providers in resource-poor settings. Efforts to identify and treat patients at risk for adverse outcomes need to be balanced with awareness of the risks and burdens associated with over diagnosis and unnecessary interventions. Screening approaches based on risk factors or using higher cut-off values may help minimize this burden and identify those most likely to benefit from intervention.