Incidence of mental health conditions following pediatric hospital admissions: analysis of a national database.

Introduction: Despite increasing survival of children following hospitalization, hospitalization may increase iatrogenic risk for mental health (MH) disorders, including acute stress, post-traumatic stress, anxiety, or depression. Using a population-based retrospective cohort study, we assessed the rates of new MH diagnoses during the 12 months after hospitalization, including the moderating effects of ICU exposure. Study design/methods: This was a retrospective case control study using the Truven Health Analytics insurance database. Inclusion criteria included children aged 3-21 years, insurance enrollment for >12 months before and after hospital admission. We excluded children with hospitalization 2 years prior to index hospitalization and those with prior MH diagnoses. We extracted admission type, ICD-10 codes, demographic, clinical, and service coordination variables from the database. We established age- and sex-matched cohorts of non-hospitalized children. The primary outcome was a new MH diagnosis. Multivariable regression methods examined the risk of incident MH disorder(s) between hospitalized and non-hospitalized children. Among hospitalized children, we further assessed effect modification from ICU (vs. non-ICU) stay, admission year, length of stay, medical complexity, and geographic region. Results: New MH diagnoses occurred among 19,418 (7%) hospitalized children, 3,336 (8%) ICU-hospitalized children and 28,209 (5%) matched healthy controls. The most common MH diagnoses were anxiety (2.5%), depression (1.9%), and stress/trauma (2.2%) disorders. Hospitalization increased the odds of new MH diagnoses by 12.3% (OR: 1.123, 95% CI: 1.079-1.17) and ICU-hospitalization increased these odds by 63% (OR: 1.63, 95% CI: 1.483-1.79) as compared to matched, non-hospitalized children. Children with non-complex chronic diseases (OR: 2.91, 95% CI: 2.84-2.977) and complex chronic diseases (OR: 5.16, 95% CI: 5.032-5.289) had a substantially higher risk for new MH diagnoses after hospitalization compared to patients with acute illnesses. Conclusion: Pediatric hospitalization is associated with higher, long-term risk of new mental health diagnoses, and ICU hospitalization further increases that risk within 12 months of the acute episode. Acute care hospitalization confers iatrogenic risks that warrant long-term mental and behavioral health follow-up.

Linear hair growth rates in preschool children.

BACKGROUND: Human scalp hair is a validated bio-substrate for monitoring various exposures in childhood including contextual stressors, environmental toxins, prescription or non-prescription drugs. Linear hair growth rates (HGR) are required to accurately interpret hair biomarker concentrations. METHODS: We measured HGR in a prospective cohort of preschool children (N = 266) aged 9-72 months and assessed demographic factors, anthropometrics, and hair protein content (HPC). We examined HGR differences by age, sex, race, height, hair pigment, and season, and used univariable and multivariable linear regression models to identify HGR-related factors. RESULTS: Infants below 1 year (288 ± 61 µm/day) had slower HGR than children aged 2-5 years (p = 0.0073). Dark-haired children (352 ± 52 µm/day) had higher HGR than light-haired children (325 ± 50 µm/day; p = 0.0019). Asian subjects had the highest HGR overall (p = 0.016). Younger children had higher HPC (p = 0.0014) and their HPC-adjusted HGRs were slower than older children (p = 0.0073). Age, height, hair pigmentation, and HPC were related to HGR in multivariable regression models. CONCLUSIONS: We identified age, height, hair pigment, and hair protein concentration as significant determinants of linear HGRs. These findings help explain the known hair biomarker differences between children and adults and aid accurate interpretation of hair biomarker results in preschool children. IMPACT: Discovery of hair biomarkers in the past few decades has transformed scientific disciplines like toxicology, pharmacology, epidemiology, forensics, healthcare, and developmental psychology. Identifying determinants of hair growth in children is essential for accurate interpretation of hair biomarker results in pediatric clinical studies. Childhood hair growth rates define the time-periods of biomarker incorporation into growing hair, essential for interpreting the biomarkers associated with environmental exposures and the mind-brain-body connectome. Our study describes age-, sex-, and height-based distributions of linear hair growth rates and provides determinants of linear hair growth rates in a large population of children. Age, height, hair pigmentation, and hair protein content are determinants of hair growth rates and should be accounted for in child hair biomarkers studies. Our findings on hair protein content and linear hair growth rates may provide physiological explanations for differences in hair growth rates and biomarkers in preschool children as compared to adults.

Longitudinal Trajectories of Hair Cortisol: Hypothalamic-Pituitary-Adrenal Axis Dysfunction in Early Childhood.

The objective of this study was to examine if longitudinal trajectories of hair cortisol concentrations (HCC) measured at two or three yearly time points can identify 1-3 year old children at risk for altered hypothalamic-pituitary-adrenal (HPA)-axis function due to early life stress (ELS). HCC was measured (N = 575) in 265 children using a validated enzyme-linked immunosorbent assay. Hair was sampled in Clinic Visits (CV) centered at years 1, 2, and 3 (n = 45); 1 and 2 (n = 98); 1 and 3 (n = 27); 2 and 3 (n = 95). Log-transformed HCC values were partitioned using latent class mixed models (LCMM) to minimize the Bayesian Information Criterion. Multivariable linear mixed effects models for ln-HCC as a function of fixed effects for age in months and random effects for participants (to account for repeated measures) were generated to identify the factors associated with class membership. Children in Class 1 (n = 69; 9% Black) evidenced declining ln-HCC across early childhood, whereas Class 2 members (n = 196; 43% Black) showed mixed trajectories. LCMM with only Class 2 members revealed Class 2A (n = 17, 82% Black) with sustained high ln-HCC and Class 2B (n = 179, 40% Blacks) with mixed ln-HCC profiles. Another LCMM limited to only Class 2B members revealed Class 2B1 (n = 65, 57% Black) with declining ln-HCC values (at higher ranges than Class 1), and Class 2B2 (n = 113, 30% Black) with sustained high ln-HCC values. Class 1 may represent hair cortisol trajectories associated with adaptive HPA-axis profiles, whereas 2A, 2B1, and 2B2 may represent allostatic load with dysregulated profiles of HPA-axis function in response to varying exposures to ELS. Sequential longitudinal hair cortisol measurements revealed the allostatic load associated with ELS and the potential for developing maladaptive or dysregulated HPA-axis function in early childhood.

The social ecology of childhood and early life adversity.

An increasing prevalence of early childhood adversity has reached epidemic proportions, creating a public health crisis. Rather than focusing only on adverse childhood experiences (ACEs) as the main lens for understanding early childhood experiences, detailed assessments of a child's social ecology are required to assess "early life adversity." These should also include the role of positive experiences, social relationships, and resilience-promoting factors. Comprehensive assessments of a child's physical and social ecology not only require parent/caregiver surveys and clinical observations, but also include measurements of the child's physiology using biomarkers. We identify cortisol as a stress biomarker and posit that hair cortisol concentrations represent a summative and chronological record of children's exposure to adverse experiences and other contextual stressors. Future research should use a social-ecological approach to investigate the robust interactions among adverse conditions, protective factors, genetic and epigenetic influences, environmental exposures, and social policy, within the context of a child's developmental stages. These contribute to their physical health, psychiatric conditions, cognitive/executive, social, and psychological functions, lifestyle choices, and socioeconomic outcomes. Such studies must inform preventive measures, therapeutic interventions, advocacy efforts, social policy changes, and public awareness campaigns to address early life adversities and their enduring effects on human potential. IMPACT: Current research does not support the practice of using ACEs as the main lens for understanding early childhood experiences. The social ecology of early childhood provides a contextual framework for evaluating the long-term health consequences of early life adversity. Comprehensive assessments reinforced with physiological measures and/or selected biomarkers, such as hair cortisol concentrations to assess early life stress, may provide critical insights into the relationships between early adversity, stress axis regulation, and subsequent health outcomes.