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Objectives A skilled workforce is essential to advancing maternal and child health (MCH) in a rapidly changing public health system. Little is known about the MCH workforce's existing capacity to maximize opportunities afforded by ongoing change. We assessed MCH workforce capacity in three areas: Systems Integration, Evidence-Based Decision-Making, and Change Management/Adaptive Leadership. We then examined associations between workforce capacity and modifiable workforce development strategies/resources. Methods Data are from the Public Health Workforce Interests and Needs Survey (PH WINS). The present study was limited to employees working in MCH programs (weighted N = 3062). Workforce capacity was operationalized as self-reported awareness of public health trends and proficiency to perform related skills in the three areas. Survey-weighted generalized estimating equations were used to fit logistic regression models accounting for employee clustering within states. Results While awareness of public health trends was low, the majority of employees (> 70% in each area) reported proficiency to perform skills related to these trends. Capacity was lowest in Systems Integration. Employee engagement in academic partnerships and higher state contributions to MCH program budgets were the strategies/resources most consistently associated with higher capacity. Workplace support was the strongest correlate of capacity in Change Management/Adaptive Leadership. Conclusions for Practice Although employees lacked familiarity with specific public health trends, they were proficient in skills needed to engage in related work. Still, areas for improvement remain. Results provide a baseline against which future training efforts can be evaluated. Academic partnerships and MCH program funding may be useful to prioritize in the context of health transformation., Author(s): Ilana G. Raskind [sup.1] , Theresa Chapple-McGruder [sup.2] , Dara D. Mendez [sup.3] , Michael R. Kramer [sup.4] , Karen D. Liller [sup.5] , Dorothy Cilenti [sup.6] , Martha [...]

Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.02-1.09). Results from our examination of sociodemographic factors of tract populations from which cases were drawn also showed that after controlling for other covariates, statistical significance remained for associations between optimal ascertainment and percentage of Hispanic residents (adjusted odds ratio = 0.93, 95% confidence interval = 0.88-0.99) and percentage of residents with at least a bachelor's degree (adjusted odds ratio = 1.06, 95% confidence interval = I.01 -- I.II). We identified sociodemographic factors associated with autism spectrum disorder prevalence estimates including race, ethnicity, education, and income. Determining which specific factors influence disparities is complicated; however, it appears that even in the presence of education, racial and ethnic disparities are still apparent. These results suggest disparities in access to autism spectrum disorder assessments and special education for autism spectrum disorder among ethnic groups may impact subsequent surveillance. [ABSTRACT FROM AUTHOR]