Prevalence of gestational diabetes according to commonly used data sources: an observational study

Abstract

BackgroundIt is well recognized that prevalence of gestational diabetes mellitus (GDM) varies depending on the population studied and the diagnostic criteria used. The data source used also can lead to substantial differences in the reporting of GDM prevalence but is considered less frequently. Accurate estimation of GDM prevalence is important for service planning and evaluation, policy development, and research. We aimed to determine the prevalence of GDM in a cohort of New Zealand women using a variety of data sources and to evaluate the agreement between different data sources.MethodsA retrospective analysis of prospectively collected data from the Growing Up in New Zealand Study, consisting of a cohort of 6822 pregnant women residing in a geographical area defined by three regional health boards in New Zealand. Prevalence of GDM was estimated using four commonly used data sources. Coded clinical data on diabetes status were collected from regional health boards and the Ministry of Health’s National Minimum Dataset, plasma glucose results were collected from laboratories servicing the recruitment catchment area and coded according to the New Zealand Society for the Study of Diabetes diagnostic criteria, and self-reported diabetes status collected via interview administered questionnaires. Agreement between data sources was calculated using the proportion of agreement with 95% confidence intervals for both a positive and negative diagnosis of GDM.ResultsPrevalence of GDM combining data from all sources in the Growing Up in New Zealand cohort was 6.2%. Estimates varied from 3.8 to 6.9% depending on the data source. The proportion of agreement between data sources for presence of GDM was 0.70 (95% CI 0.65, 0.75). A third of women who had a diagnosis of GDM according to medical data reported having no diabetes in interview administered questionnaires.ConclusionPrevalence of GDM varies considerably depending on the data source used. Health services need to be aware of this and to understand the limitations of local data sources to ensure service planning and evaluation, policy development and research are appropriate for the local prevalence. Improved communication of the diagnosis may assist women’s self-management of GDM.

Dietary Patterns and Dietary Adaptations in Women With and Without Gestational Diabetes: Evidence From the Growing Up in New Zealand Study

“…The methods used to identify women with GDM in the cohort have been described previously [23]. Briefly, participant NHIs were used to obtain data on diabetes status during pregnancy from the Ministry of Health's National Minimum Dataset, the three regional health boards, and laboratories servicing the recruitment catchment area.…”

“…Globally, reported prevalence of GDM ranges between 1% and 45% of pregnancies [20][21][22]. In New Zealand, GDM has been estimated to affect approximately 6% of pregnancies [23].…”

Gestational diabetes – Diagnostic and therapeutic novelties

“…Fetal macrosomia occurs in 15-45 % of diabetic pregnancies. Also, large-for-gestational-age infants should be screened for hypoglycemia (5).…”

“…Therefore, these women should be informed and educated about these risks, about the need for optimal glycemic control before the preconception phase, and the contraceptive and family planning options. Preconception counselling improved maternal and fetal outcomes in women with pre-existing diabetes (5,6).…”

Mureş County Women’s Behaviour Associated with Pregnancy Risk Factors

“…(2,3) Moreover, problems related to body mass index, obesity, gestational diabetes and lack of folic acid supplementation of women before and during pregnancy were associated with an increased risk of pre-eclampsia, neurological, cardiac and orofacial defects, newborn overweight and premature birth. (4,5,6) Several studies have evaluated the knowledge and behaviour of women of childbearing age and pregnant women regarding some individual risk factors in pregnancy, such as smoking (7), oral health (8) and obesity. (9) However, very few studies have examined several risk factors simultaneously and across ethnic groups.…”