The incidence of gestational diabetes mellitus (GDM) has increased significantly in the last few decades in the US. Understanding its risk factors is imperative for the prevention of GDM and its sequelae, but the roles of behavioural risk factors such as stressful events and smoking on GDM are generally not well understood. Using data obtained from the New York State (NYS) Pregnancy Risk Assessment Monitoring System survey for 2004-06 and the NYS birth certificates, we examined relationships between GDM, stressful events and smoking among 2690 women who had live singleton births and did not have pre-pregnancy diabetes. After adjustment for risk factors such as maternal age, race/ethnicity, pre-pregnancy body mass index, hypertension, as well as smoking exposure, education, parity, and gestation at first visit for prenatal care, we found that having five or more stressful events 12 months before the baby was born was significantly associated with GDM (OR = 2.49, [95% CI 1.49, 4.16]). In another model, having any stressful event(s) other than 'moved to a new address' 12 months before the baby was born was also moderately associated with GDM (OR = 1.38, [95% CI 1.04, 1.85]). Smoking exposure, assessed by combining maternal smoking and second-hand smoke exposure into six levels, had no significant association with GDM, and did not show a dose-response pattern. The present study suggests that stressful events during pregnancy may be an independent risk factor for GDM. Future studies of GDM should include this common, but potentially modifiable risk factor in analyses.

This study examined agreement (concordance or convergent validity) between self-report and birth certificate for gestational diabetes. Study population was 2,854 women who had live births 2-6 months earlier and responded to a questionnaire from the New York State Pregnancy Risk Assessment Monitoring System (PRAMS) survey, 2004-2006. Agreement between self-report and birth certificate was assessed for the study population overall, and for subgroups defined by race, age, education, marital status, number of previous live births, time of first prenatal care, and birth weight of the newborn. A total of 258 women self-reported gestational diabetes, while birth certificates indicated that 138 women had gestational diabetes. For the study population overall, percent agreement was 93.8% and Kappa was 0.53. Due to the moderate bias index (68.2% overall, ranged from 33.3 to 100% in subgroups) and the high skewed prevalence index (91.8% overall, ranged from 70.7 to 97.5% in subgroups), we determined Prevalence-Adjusted and Bias-Adjusted Kappa (PABAK) was a better measure of agreement. PABAK was 0.88 overall, indicating very good agreement. PABAK was uniformly high in all subgroups. The highest PABAK was found among women aged 25 years and younger (0.93), and the lowest PABAK was among Asian women (0.79). Although the absence of a gold standard for gestational diabetes hinders assessment of criterion validity, high PABAK measures suggest that self-reporting by PRAMS respondents is feasible for identifying cases of gestational diabetes for surveillance and population-based epidemiologic research.

A study by Colley et al., [3] showed that Pregnancy risk assessment monitoring system (PRAMS) is a unique and valuable maternal and child health data source. Petersen et al.'s, [4] study results show that Context: Prenatal care is commonly understood to have a benefi cial impact on pregnancy outcome. Child survival is directly dependent on good maternal health and nutrition. Aim: To study the variation in counseling of prenatal care measures at different sources of care. Materials and Methods: A cohort of 5,380 observations from the New York State Pregnancy Risk Assessment Monitoring System were analyzed to study the relationship between site/source of prenatal care and quality/ content of prenatal care, and the infl uence of maternal characteristics therewith. Statistical Analysis Software, version 8 (SAS-V8) was used for analysis. Results: The most common source of care was doctor of medicine/health managed care organization (75.89%) followed by hospital clinic (11.22%), community health center (6.5%), health department clinic (4.05%), and others (2.3%). Health department clinic showed a greater prevalence proportion for counseling in all of the fi ve prenatal care measures (talked about breastfeeding, illegal drugs, nutrition, baby's growth, and smoking) when compared with the remaining four sources of care. Majority of private clinic attendees were whites (87.8%), older mothers (20.7%), and/or high income groups (67.8%). Young mothers preferred visiting health department clinic (22.5%). Average income mothers preferred accessing healthcare from the community health center (26.9%). Conclusion: Variation in quality of care among various sources of care is likely to occur. Maternal characteristics could also infl uence the selection of source of care.

Objectives This study aimed to assess changes in paid maternity leave before and after New York’s (NY) Paid Family Leave (PFL) law went into effect (1/1/2018) and changes in disparities by maternal characteristics. Methods We used specific data collected on maternity leaves by women who gave birth in 2016–2018 in NY State (outside NY City) participating in the Pregnancy Risk Assessment Monitoring System survey. Multiple logistic regressions were conducted to evaluate the effect of the PFL law on prevalence of paid leave taken by women after childbirth. Results After NY’s PFL law went into effect, there was a 26% relative increase in women taking paid leave after childbirth. Use of paid leave after childbirth increased among all racial and ethnic groups. The increases were greater among Black non-Hispanic or other race non-Hispanic women, compared to white non-Hispanic women, suggesting that NY’s law was associated with more equitable use of paid leave following childbirth. Conclusions for Practice Wider implementation and greater utilization of paid maternity leave policies would promote health equity and help reduce racial/ethnic disparities in maternal and child health outcomes.