Sex-based prevalence of growth faltering in an urban pediatric population.
OBJECTIVE
To determine the sex-based prevalence of growth faltering in a pediatric primary care setting.


METHODS
A total of 33 476 children attending 4 urban pediatric primary care practices affiliated with a tertiary pediatric hospital between July 2002 and June 2005 were studied. Growth faltering was defined as height <5th percentile or a drop in height z-score by >or= 1.5 standard deviations (SD) before age 18 months or by >or= 1 SD thereafter. The growth-faltering and nonfaltering groups were compared in terms of sex, race, age, number of clinic visits, and insurance, and by US census tract, socioeconomic status and parental education. Similar comparisons were made for children with height z-scores below -2.25 SD.


RESULTS
Growth faltering was present in 3007 of the children studied (9%). Univariate and multivariate logistic regression analyses identified significant associations between growth faltering and younger age (P< .0001), Caucasian race (P< .0001), fewer clinic visits (P< .0001), and Medicaid insurance (P< .005), but not with sex nor by residential census tract, median income or proportion with less than high school education. Height below -2.25 SD was associated with male sex (P< .01), Medicaid insurance (P< .01), and more primary care visits (P< .0005).


CONCLUSIONS
The sex disparity in subspecialty growth center referrals (2:1 male:female) is not due to male predominance in growth faltering among children in the urban primary care setting.
Grimberg
Adda
A
Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. Grimberg@email.chop.edu
Ramos
Mark
M
Grundmeier
Robert
R
Feemster
Kristen A
KA
Pati
Susmita
S
Cucchiara
Andrew J
AJ
Stallings
Virginia A
VA
D003951:Diagnostic Errors / Q000517:prevention & control; D005260:Female; D006130:Growth Disorders / Q000175:diagnosis / Q000453:epidemiology* / Q000208:ethnology; D006297:Health Services Accessibility; D054624:Health Status Disparities; D006801:Humans; D019458:Insurance Coverage; D016015:Logistic Models; D008297:Male; D008484:Medicaid; D015999:Multivariate Analysis; D015143:Philadelphia / Q000453:epidemiology; D011203:Poverty; D015995:Prevalence; D011320:Primary Health Care; D012017:Referral and Consultation / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D017678:Sex Distribution; D014481:United States; D014505:Urban Population