Interpretation
The increasing prevalence of GDM over a 15-year period aligns with findings from various prior studies, which have consistently reported rising GDM rates since 1989, utilizing diverse data sources and reporting methods (9, 19, 23, 24, 25, 26). According to CDC data, GDM prevalence surged by 56% from 2000 to 2010 and by an additional 30% from 2006 to 2019 (19, 26). As of 2020, Kansas reported a GDM prevalence of 8.7% (19). Simultaneously, the prevalence of maternal obesity has seen a significant increase, mirroring earlier literature and the broader adult obesity trend, which, in 2022, stood at 36%, with severe obesity poised to become the most common BMI category among women (1, 11, 12, 17, 21, 27). In 2020, Kansas exhibited a 34% obesity rate among women, showcasing a higher-than-average trend (20, 27). The parallel rise in maternal obesity and GDM rates highlights a growing concern, as these trends are expected to continue increasing.
This study sheds light on the rural-urban disparities among pregnant women with GDM from 2005 to 2019. The observed higher prevalence of GDM cases in the sample population and a slightly elevated risk of GDM among women residing in rural areas align with previous findings specific to GDM in rural areas within the United States (13). However, it's worth noting that there are few studies comparing GDM prevalence based on rurality in the US. The trend analysis of GDM rates in rural versus urban areas consistently shows higher rates in rural areas at most time points, with anticipated increases over time. These geographic disparities further highlight the elevated risk of adverse pregnancy outcomes for women in rural areas which has health implications for both the mother and child (14, 15, 16, 18, 28). Notably, one adverse outcome of GDM is the increased risk of developing type 2 diabetes (5). These findings contribute to the broader concerns about health disparities, health equity, barriers to care, and the challenges of maternal care deserts in our state that affect factors such as access to quality care, and effective GDM prevention, screening, and management, including appropriate nutrition, which persist in rural areas (15, 16, 18, 29). Recent data from Kansas reveals that nearly 20% of infants are born to women residing in rural counties, many of which are classified as maternity care deserts (22). Concerning travel distances in Kansas, women, on average, travel 10 miles to the nearest birthing hospital, while some may need to travel nearly 63 miles in counties with the longest travel times (22). Moreover, women in 45% of Kansas counties face a very high or high vulnerability to adverse outcomes (22).
Highlighting health disparities within specific demographic characteristics is further emphasized by the findings of the study. Asians, American Indians or Alaskan Natives, and Hispanics faced the highest GDM risk, aligning with previous research highlighting racial and ethnic disparities in GDM rates. American Indians or Alaskan Natives, in particular, exhibited elevated GDM rates, pre-pregnancy diabetes, and overweight or obesity, with a higher likelihood of inadequate prenatal care and various disparities linked to social determinants of health (30). Surprisingly, despite their lower BMIs, Asians consistently demonstrated the highest GDM prevalence, possibly due to cultural and socioeconomic factors (13, 19, 24, 26, 31, 32, 33). Hispanics also showed higher GDM rates in comparison to non-Hispanic Whites (24, 26, 34). In contrast, Black pregnant women had a lower GDM risk but a heightened risk of developing type 2 diabetes compared to other racial and ethnic groups (10, 19, 26, 31).
The well-established association between advanced maternal age and a markedly elevated risk of GDM is reaffirmed in the study, aligning with previous research. Maternal age has consistently been shown to have a direct relationship with GDM risk, with studies revealing a higher likelihood of GDM occurrence in older mothers, along with other adverse pregnancy outcomes. This positive association between advanced maternal age and the development of GDM has solidified maternal age as a robust risk factor for GDM (1, 19, 33, 35, 36).
This study initiates an exploration into the connection between socioeconomic status (SES) and GDM risk. The association between maternal education level and GDM development, particularly in the US, requires further investigation to establish a clear connection. One study demonstrated demonstrates no significant association between maternal education level and GDM development (11). Similar gaps exist for employment, as this study reveals an increased GDM risk in unemployed individuals, with limited prior research on the precise correlation between employment and GDM. SES examined concerning GDM, hasn't comprehensively considered education and employment. Previous studies have linked low SES to a higher GDM risk, while others suggest a gradient-like relationship between these variables (9, 37, 38, 39, 40). Therefore, further exploration into the impact of socioeconomic status on GDM, encompassing education and employment, is essential, given that SES consistently emerges as a robust predictor of disease onset and progression. Unexamined variables, such as income, may mediate the relationship between education and employment on GDM. Income, while not directly assessed, can be approximated using insurance source, revealing a higher GDM risk among Medicaid users, a crucial source of funding for nearly half of US births, particularly in rural areas (18). Low-income pregnant women with Medicaid encounter challenges in accessing consistent and timely care, receiving less prenatal care, having fewer deliveries, and exhibiting a higher likelihood of obesity and smoking (18, 29). Pregnant women covered by Medicaid also face elevated rates of severe maternal morbidity and mortality, emphasizing the need for targeted interventions and access to quality care (18). Approximately 36% of GDM-related medical costs are covered by government programs, primarily Medicaid (25). Furthermore, expanded coverage of emergency Medicaid for prenatal care has been associated with a significant increase in the use of antidiabetic medications during pregnancy among Latina patients with GDM or preexisting diabetes (41). In summary, the relationship between SES and GDM, while requiring further examination, highlights the importance of addressing these complex interactions in maternal healthcare.
Strengths and Limitations
The strengths of this study include a large 15-year data set and, to our knowledge, the first analysis to assess Kansas specific GDM prevalence via rurality, and associated risk among demographic variables. This analysis included a cohort of all live births in Kansas from 2005 to 2019. This study has limitations, including the omission of factors such as parity, history of GDM, smoking, alcohol use, nutrition, and physical activity, which are recognized risk factors for GDM but were not the primary focus (4, 7, 42, 43). Furthermore, the analysis did not account for variations in GDM screening and diagnosis criteria, making it challenging to determine accurate prevalence. In the US, different diagnostic criteria yield GDM diagnosis rates ranging from 5–20%, and changes in screening recommendations in 2014 may contribute to differences in prevalence over time or across jurisdictions (3, 25). Additionally, there is the potential for underreporting of GDM, with birth certificate and hospital discharge data showing sensitivity ranging from 46–83% and often failing to adequately capture diabetes-complicated births (44). This underreporting of health conditions, particularly in birth certificate data, could lead to an underestimation of both preexisting and gestational diabetes prevalence (3, 19).