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. 2022 Jun 9;93(2):300–307. doi: 10.1038/s41390-022-02137-1

Table 1.

Study characteristics of multivariable prediction models for cognitive outcomes in childhood.

Authors Camargo-Figuera et al.20 Camacho et al.21 Eriksen et al.22
Journal BMC Pediatrics Paediatric Perinatal Epidemiology PLoS One
Continent South America Europe Europe
Sample Pelotas Birth Cohort Millennium Cohort Study Lifestyle During Pregnancy Study (sampled from the Danish National Birth Cohort)
Design Prospective cohort Prospective cohort Prospective cohort
Sample size 3312 9487 1782
Year of recruitment 2004 2000–2002 1997–2003a
Exclusion criteria Conditions associated with very low IQ, e.g., severe mental retardation Nil Multiple pregnancies, language barrier, impaired hearing or vision, congenital disabilities implying mental retardation
Age at cognitive assessment 6 3 5
Cognitive assessment Wechsler Primary and Preschool Scales of Intelligence -III Bracken School Readiness Assessment Wechsler Primary and Preschool Scales of Intelligence – Revised
Cognitive outcome variable Binary Binary Continuous
Low IQ defined by a z-score <−1 Not school ready defined by score <1 standard deviation below mean
Number of risk factors at outset 32 29 27
Rationale given for candidate variables Yes—selected based on previous literature and availability Yes—selected based on previous literature and availability No–but broad range (>20) selected
Statistical model Multivariable logistic regression Multivariable logistic regression Multivariable linear regression
Method of initial screening of candidate variables Forward and backward stepwise selection Forward and backward stepwise selection Univariable association p ≥ 0.10
Interaction terms fitted No No No
Multicollinearity addressed/discussed No Yes Yes
No. predictors in final model 13 13 9
Validation performed Yes Yes No
Internal and external validation performed Internal validation only
Predictive value measured External validation Internal validation R squared 0.29
Area under receiver operating curve (AUROC) 0.75 AUROC 0.80
Sensitivity 70.3% Sensitivity 72%
Specificity 68% Specificity 74%
Predictors in final model Child—gender, height-for-age deficit; head circumference-for-age deficit Child—gender, ethnicity, developmental milestones Child—gender, birth weight, height, head circumference
Parental—breastfeeding, parental smoking, maternal perception of child’s health, skin colour Parental—maternal age, maternal mental health, breastfeeding Parental—maternal BMI, breastfeeding
Socioenvironmental—parental employment status, maternal education, income, number of siblings, number of persons per room Socioenvironmental—socioeconomic class, maternal education, income, number of children, employment status, housing type Socioenvironmental—maternal IQ, parental education

aIn 2003, a prospective follow-up of 1750 mother–child pairs was initiated, sampled on the basis of maternal alcohol drinking patterns from The Danish National Birth Cohort (DNBC).