To characterize bladder and bowel toileting skill acquisition in children with fragile X syndrome and to identify associated demographic, behavioral, and clinical factors.
Using baseline data from the Fragile X Online Registry With Accessible Research Database (FORWARD), bivariate analyses and logistic regression models were used to identify differences between subjects who were and were not bowel and/or bladder trained by the age of 10 years. Cox proportional hazard models were used to assess the rate of completion of toilet training (TT) as a function of sex and autism spectrum disorder (ASD) diagnosis.
In bivariate analyses, male sex, lower language level, inability to write one's name, more impaired intellectual level, ASD, and more severe behavioral deficits all predicted lack of bladder training (n = 313, p < 0.001) and bowel training (n = 300, p = 0.0004–0.0001) by the age of 10 years. In logistic regression models, lower level of language acquisition (p < 0.001) and higher Aberrant Behavior Checklist Irritability scores (p < 0.04) were associated with lower odds of bladder training by the age of 10 years. Lower level of language acquisition (p < 0.001) and ASD (p < 0.025) were associated with lower odds of bowel training by the age of 10 years. For both bladder and bowel training, Cox proportional hazard models indicated that delayed training was associated with male sex, lower levels of language acquisition, and ASD for both bladder training (n = 486; p < 0.001) and bowel training (n = 472; p < 0.001).
These findings emphasize the importance of both slower language development and ASD diagnosis in predicting bowel and bladder training delays and can be used to develop and evaluate targeted approaches to TT based on sex, ASD diagnosis, and other clinical features identified in this study.
*Departments of Pediatrics, Neurological Sciences, and Biochemistry, Rush University Medical Center, Chicago, IL;
†School of Nursing, University of California, San Francisco, CA;
‡Department of Pediatrics, Duke Health Center, Lenox Baker Children's Hospital, Durham, NC;
§Mental Health Data Science Division, New York State Psychiatric Institute, New York, NY;
‖Developmental Pediatrics, University of Colorado School of Medicine, Children's Hospital Colorado, Aurora, CO;
¶Morgridge College of Education, University of Denver, Denver, CO;
**California School of Professional Psychology, Alliant International University, Alhambra, CA;
††Biostatistics Department, Columbia University Mailman School of Public Health, New York, NY.
Address for reprints: Elizabeth Berry-Kravis, MD, PhD, Departments of Pediatrics, Neurological Sciences, and Biochemistry, Rush University Medical Center, 1725 West Harrison, Suite 718, Chicago, IL 60612; e-mail: Elizabeth_berryfirstname.lastname@example.org.
Work on this publication was supported by cooperative agreements #U01DD000231, #U19DD000753, and #U01DD001189, funded by the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the Department of Health and Human Services.
Disclosure: The authors declare no conflict of interest.
Received March 24, 2019
Accepted August 06, 2019