Francis J Meaney
- Part-Time Faculty
- Ph.D. Biological Anthropology
- The University of Arizona, Tucson, Arizona, United States
- Factors influencing the physical growth of Tucson school children
- The University of Arizona, Tucson, Arizona (2008 - Ongoing)
- The University of Arizona, Tucson, Arizona (2007 - 2008)
Epidemiology of developmental disabilitiesEpidemiology of genetic disorders and diseases
Human GeneticsHistory of Genetics
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- Duncan, B. R., Andrews, J. G., Pottinger, H. L., & Meaney, F. J. (2017). Developmental Disabilities. In Nutrition and Health in a Developing World(pp 526-558). Switzerland: Springer Nature. doi:10.1007/978-3-319-43739-2
- Meaney, F. J., Duncan, B. R., Andrews, J. G., & Pottinger, H. L. (2017). Developmental disabilities. In Nutrition and Health in a Developing World, 3rd Edition(pp 523-558). New York: Humana Press, Springer International Publishing AG,.
- Meaney, F. J. (2018). Recognition of clinical characteristics for population-based surveillance of fetal alcohol syndrome. Birth Defects Research, 110(10), 851-862.
- Meaney, F. J. (2017). The Niemann-Pick C1 gene interacts with a high-fat diet to promote weight gain through dysregulation of central energy metabolism pathways. American Journal of Physiology-Endocrinology and Metabolism, 313(2), E183-E194.
- Meaney, F. J., Pettygrove, S. D., & Andrews, J. G. (2016). DSM criteria that best differentiate intellectual disability from Autism Spectrum Disorder. Child Psychiatry and Human Development, Online publication, 9.More infoAbstract: Clinical characteristics of autism spectrum disorder(ASD) and intellectual disability (ID) overlap, creatingpotential for diagnostic confusion. Diagnostic andstatistical manual of mental disorders (DSM) criteria thatbest differentiate children with ID and some ASD featuresfrom those with comorbid ID and ASD were identified.Records-based surveillance of ASD among 8-year-oldchildren across 14 US populations ascertained 2816 childrenwith ID, with or without ASD. Area under the curve(AUC) was conducted to determine discriminatory powerof DSM criteria. AUC analyses indicated that restrictedinterests or repetitive behaviors best differentiated betweenthe two groups. A subset of 6 criteria focused on socialinteractions and stereotyped behaviors was most effectiveat differentiating the two groups (AUC of 0.923), whilecommunication-related criteria were least discriminatory.Matching children with appropriate treatments requiresdifferentiation between ID and ASD. Shifting to DSM-5may improve differentiation with decreased emphasis onlanguage-related behaviors.
- Pandya, S., Andrews, J., Campbell, K., & Meaney, F. J. (2016). Rehabilitative technology use among individuals with Duchenne/Becker muscular dystrophy. Journal of pediatric rehabilitation medicine, 9(1), 45-53.More infoTo document use of rehabilitative technology among individuals with Duchenne/Becker muscular dystrophy (DBMD) among sites of the Muscular Dystrophy Surveillance, Tracking, and Research network (MD STARnet).
- Fox, D. J., Pettygrove, S. D., Cunniff, C. M., O'Leary, L. A., Gilboa, S. M., Bertrand, J., Druschel, C. M., Breen, A., Robinson, L., Ortiz, L., Frias, J. L., Ruttenber, M., Klumb, D., & Meaney, F. J. (2015). Fetal Alcohol Syndrome Among Children Aged 7–9 Years — Arizona, Colorado, and New York, 2010. Morbidity and Mortality Weekly Report (MMWR), 64(03), 54-57.
- Fox, D. J., Pettygrove, S., Cunniff, C., O'Leary, L. A., Gilboa, S. M., Bertrand, J., Druschel, C. M., Breen, A., Robinson, L., Ortiz, L., Frías, J. L., Ruttenber, M., Klumb, D., Meaney, F. J., & , C. f. (2015). Fetal alcohol syndrome among children aged 7-9 years - Arizona, Colorado, and New York, 2010. MMWR. Morbidity and mortality weekly report, 64(3), 54-7.More infoFetal alcohol syndrome (FAS) is a serious birth defect and developmental disorder caused by in utero exposure to alcohol. Assessment of the public health burden of FAS through surveillance has proven difficult; there is wide variation in reported prevalence depending on the study population and surveillance method. Generally, records-based birth prevalence studies report estimates of 0.2-1.5 per 1,000 live births, whereas studies that use in-person, expert assessment of school-aged children in a community report estimates of 6-9 per 1,000 population. The Fetal Alcohol Syndrome Surveillance Network II addressed some of the challenges in records-based ascertainment by assessing a period prevalence of FAS among children aged 7‒9 years in Arizona, Colorado, and New York. The prevalence across sites ranged from 0.3 to 0.8 per 1,000 children. Prevalence of FAS was highest among American Indian/Alaska Native children and lowest among Hispanic children. These estimates continue to be much lower than those obtained from studies using in-person, expert assessment. Factors that might contribute to this discrepancy include 1) inadequate recognition of the physical and behavioral characteristics of FAS by clinical care providers; 2) insufficient documentation of those characteristics in the medical record; and 3) failure to consider prenatal alcohol exposure with diagnoses of behavioral and learning problems. Addressing these factors through training of medical and allied health providers can lead to practice changes, ultimately increasing recognition and documentation of the characteristics of FAS.
- O'Leary, L. A., Ortiz, L., Montgomery, A., Fox, D. J., Cunniff, C., Ruttenber, M., Breen, A., Pettygrove, S., Klumb, D., Druschel, C., Frías, J. L., Robinson, L. K., Bertrand, J., Ferrara, K., Kelly, M., Gilboa, S. M., Meaney, F. J., & , F. (2015). Methods for surveillance of fetal alcohol syndrome: The Fetal Alcohol Syndrome Surveillance Network II (FASSNetII) - Arizona, Colorado, New York, 2009 - 2014. Birth defects research. Part A, Clinical and molecular teratology, 103(3), 196-202.More infoSurveillance of fetal alcohol syndrome (FAS) is important for monitoring the effects of prenatal alcohol exposure and describing the public health burden of this preventable disorder. Building on the infrastructure of the Fetal Alcohol Syndrome Surveillance Network (FASSNet, 1997-2002), in 2009 the Centers for Disease Control and Prevention awarded 5-year cooperative agreements to three states, Arizona, Colorado, and New York, to conduct population-based surveillance of FAS. The Fetal Alcohol Syndrome Surveillance Network II (FASSNetII, 2009-2014) developed a surveillance case definition based on three clinical criteria: characteristic facial features, central nervous system abnormalities, and growth deficiency. FASSNetII modified the FASSNet methods in three important ways: (1) estimation of a period prevalence rather than birth prevalence; (2) surveillance of FAS among school-age children (ages 7-9 years) to better document the central nervous system abnormalities that are not apparent at birth or during infancy; and (3) implementation of an expert clinical review of abstracted data for probable and confirmed cases classified through a computerized algorithm. FASSNetII abstracted data from multiple sources including birth records, medical records from child development centers or other specialty clinics, and administrative databases such as hospital discharge and Medicaid. One challenge of FASSNetII was its limited access to non-medical records. The FAS prevalence that could be estimated was that of the population identified through an encounter with the healthcare system. Clinical and public health programs that identify children affected by FAS provide critical information for targeting preventive, medical and educational services in this vulnerable population.
- Hansen, C., Adams, M., Fox, D. J., O'Leary, L. A., Frías, J. L., Freiman, H., & Meaney, F. J. (2014). Exploring the feasibility of using electronic health records in the surveillance of fetal alcohol syndrome. Birth defects research. Part A, Clinical and molecular teratology, 100(2), 67-78.More infoExplore the use of electronic health records (EHRs) in fetal alcohol syndrome (FAS) surveillance systems.
- Davis, M. F., Scherer, K., Miller, T. M., & Meaney, F. J. (2010). Measuring disease severity in Duchenne and Becker Muscular Dystrophy. Journal of Methods and Measurement in the Social Sciences, 1(1), 8-18.