The Role of Chemical and Nonchemical Stressors on

The Role of Chemical and Nonchemical Stressors on Children’s Neurocognitive Development – from Pregnancy through Early Childhood Jazmin Ruiz ID# 20540 1 ORISE 1, 2, James J. 2 Quackenboss , Nicolle S. 2 Tulve Post-Doctoral Fellow, and 2 U. S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, NC Jazmin Ruiz, Ph. D l ruiz. jazmin@epa. gov l 919 -541 -3902 Abstract Background: Early childhood (0 -6 years old) is a time of significant brain growth and foundational skills development essential for school readiness and academic achievement. Maximizing a child’s learning potential can be achieved only with complete knowledge of stressors that impact learning. Many studies attempt to identify associations between individual exposure factors and neurocognitive development. However, extending from pregnancy to a child’s first day of school, numerous stressors (e. g. , chemicals, prenatal stress, behaviors, family violence) may influence children’s neurocognitive development and health and well-being. Additionally, community-level decisions related to land use, transportation, buildings and infrastructure, and waste and materials management may also influence a child’s health and well-being by impacting their home and learning environments. Purpose: Examine stressors related to neurocognitive health in children ages 3 -6 years to (1) identify and characterize individual stressors associated with neurocognitive development and (2) develop a conceptual model that identifies key stressors and their possible interactions. Methods: A literature review was performed across multiple databases (e. g. , Pub. Med, Web of Science, Psych. Info) utilizing the search string “neurodevelopment or cognition and children”. The search was limited to articles written in English and published within the past 10 years that assessed neurocognitive health in children 6 years old or younger. Assessment of the quality of the study and its applicability to the general population was conducted to identify key stressors associated with neurocognitive health and to develop a conceptual model using a multi-level systems approach. Results: Key exposure factors were identified for each developmental lifestage from pregnancy to 3 -6 years old. These factors were grouped three different ways according to (1) the type of occurrence (e. g. , individual, home, school, community), (2) characterization as an individual health, social, environmental or economic determinant, and (3) how decisions regarding land use, buildings and infrastructure, waste and materials management, and transportation have impacted them. These elements were incorporated into the conecptual model and the results suggest that some childhood exposures (e. g. , SES, parent-child interaction, diet, built environment) not only present as key factors, but act as effect modifiers of stressors experienced during pregnancy and infancy (e. g. , lead, pesticides, prenatal stress). Conclusion: Evidence from the literature suggests that individually these factors play an important role in determining the trajectory of neurocognitive health. However, the plasticity of a child’s developing brain indicates that the effect of a single factor can possibly be modified due to exposure(s) to additional factors, over time or concurrently. This presentation will highlight the myriad of chemical and nonchemical stressors identified during the literature search, discuss key exposure factors identified, and explain why certain exposure factors should be considered key exposure factors. This work can help inform future research in this area in order to better create environments which enhance childhood development and learning. Methods Figure 1. Flow Diagram showing the Study Selection/Screening Process of Available Data Title/Abstract Review, Duplicates Removed After Review of Study Design /Methods Excluded: 606 Excluded: 7164 Total Identified with Keyword search: 7756 Web of Science: 2068 Pub. Med: 2790 Psych. Info: 2898 + Included: 592 Summary of Results to Date Justification Included in Literature Review and Considered for Analysis: 262 Data Extraction & Analysis of 153 exposure variables Additional Included: 276 Title/Abstract of Top ten related articles reviewed Table 1. Inclusion Criteria for Extant Studies Identified During the Literature Review -Observational studies, randomized control trials, review or meta-analysis -Time of exposure to a factor ranged from in utero to the time at which the health outcome is assessed -Health outcome was measured in children < 18 years old -Cognitive outcome was measured using current and earlier versions of evidence based assessments of cognitive functioning classified as well established (Campbell et al. , J Pediatr Psychol (2008)) and expressed as continuous variable or categorized as a low score (<85 or < 70) -Study included a measure of association and statistical significance -Majority of study participants were healthy children without any existing developmental disabilities, neonatal morbidities, cerebral pathologies associated with cognitive deficits, rare disorders (congenital or genetic) or receiving rare treatments/procedures Early childhood (0 to 6 years old) is a critical period of time in which early cognitive skills (e. g. , sensorimotor skills, shape recognition and relative quantities; Doherty. “Zero to Six: The Basis for School Readiness” (1997)) essential for school readiness and later academic success are fostered. In fact, variables that influence the early architecture of the brain and a child’s cognitive ability include the health and well being of the mother prior to conception. The highly dynamic nature of neurodevelopment from pregnancy through childhood, in addition to the vastly expanding scientific research in this area, suggests that a single determinant or a single time point of exposure does not ultimately determine a child’s cognitive ability as demonstrated in mice (Hensch et al. , Science (1998)). Rather, cognitive development culminates through continuous acquisition of knowledge provided the right environment; and cumulative exposure to a myriad of variables over time as a result of their environment can either impede or help to maximize a child’s ability to gain this knowledge. These variables include both chemical and nonchemical stressors that are present in a child’s home, their school and neighborhoods/communities. Unfortunately, many of these factors can be influenced beyond the control of the child or their mother as a result of decisions or policies trickled down from indirect environments (e. g. , individuals, businesses, local councils, government). Summary of Results to Date Table 2. Preliminary Analysis of Exposure Variables Associated with Cognitive Development Age at which outcome was assessed (study n) 1 mo to Positive Negative Null (P< 0. 05) (P< 0. 10) <3 yo 3 to <6 > 6 yo Results across studies (%) Factors (study n) Individual Demographics Race/ethnicity (minority) (6) Child's health/behavior Gestational age (7) Sleep Patterns (duration, efficiency, timing) (5) Child illness (5) Preterm Birth (14) Low birth weight/poor weight gain (10) Resuscitation (2) Prenatal conditions Multiple birth (2) Maternal health (pregnancy related or pre-existing) Hypothyroidism (13) Other maternal disease (3) Prenatal Chemical - Maternal lifestyle choices or medical Drugs (cocaine, MDMA, ecstasy, methamphetamine) (8) Medications (7) Diet/Prenatal Supplements Fish intake (5) Healthy diet pattern (3) Breastfeeding/LC-PUFA (16) Malnutrition (2) Iodine (2) Folate (2) Physical Environment Chemical Lead (<10 ug/d. L) (10) Brominated (PBDE, HBCDD) (7) Other natural elements (Cd, Mn, As, F) (18) Pesticides (15) PAHs (3) Phthalates (3) Traffic related pollutants (NO 2, black carbon) (3) PCBs (8) Mercury (9) ETS (10) Social Environment Demographics Parent education (24) Maternal intelligence (12) Maternal age (9) Siblings, birth order (9) Psychosocial (familial) Mother child interaction (positive) (7) Quality of home environment (13) Paternal alcohol consumption (2) Maternal stress/anxiety (7) Child trauma/violence (3) Psychosocial (non-familial) Child care (quality, attendance) (3) Institutionalization/Foster care/Adoption (2) Cultural Language (primary, bilingual) (3) Economic Demographics SES (occupational social class, income) (19) 0 67 33 0 3 3 80 60 0 0 20 80 71 70 0 14 20 20 29 20 100 3 3 3 1 3 0 0 3 4 0 1 5 2 8 3 1 0 100 0 2 0 0 54 33 39 67 6 0 5 0 2 3 0 0 63 0 38 71. 4 1 3 5 1 2 3 80 67 56 0 0 0 20 0 0 100 0 33 25 0 100 0 0 5 1 2 2 3 1 7 0 0 0 2 2 4 1 0 0 0 14 0 0 0 0 100 71 72 67 67 63 56 40 0 0 28 33 33 25 33 60 2 3 3 6 0 2 0 4 0 3 3 4 3 1 1 2 5 6 5 1 12 5 0 0 2 2 4 1 88 67 56 0 0 78 12 33 44 22 6 3 3 2 2 4 15 7 4 3 100 69 0 0 0 100 71 67 0 23 2 29 33 5 6 0 7 0 2 5 2 0 1 0 2 0 0 2 100 0 0 3 0 0 1 0 33 67 1 2 0 79 0 16 5 5 9 • Individual associations of 153 exposure variables with cognitive health were evaluated in the 262 publications reviewed Table 3. Exposure Interactions Evaluated in the Literature Review (Total studies that include interactions n = 49) Type of Interaction Study n Gene x Chemical 10 Chemical x Demographics 10 Health x Demographic 9 Chemical x Chemical 8 Health conditions x Chemical 6 Environmental chemicals (4) Prescribed drugs (2) Table 4. Top Ten Covariates or Confounders used in Selected Studies Rank Covariate/Confounder Frequency of use (%) 1 maternal education 64 2 gender 61 3 household economic status 40 4 maternal intelligence 38 5 age at assessment 33 6 maternal age at birth 29 7 birthweight 26 Psychosocial x Psychosocial 5 Breastfeeding x Chemical 4 8 quality of home environment 21 Health x Health 2 9 18 Gene x Gene 1 Chemical x Psychosocial 1 Chemical x Built Environment 1 Demographic x Demographic 1 child's blood Pb; prenatal maternal smoking or prenatal ETS; parity or siblings; premature birth or gestational age Psychosocial x Health 1 10 parent marital status; parent occupational/social class; race/ethnicity 17 Figure 2. Conceptual Model Depicting the Interplay between Economic, (orange), Social (blue), Environmental (purple) and Individual (red) variables across a child’s environment and the cumulative impact of exposure per lifestage on cognitive health– (variables included in the model were shown to be significant in over 50% of studies evaluating them); Adapted from Mc. Leroy et al. , Health Educ Q (1988). Future Direction • 100 exposure variables were evaluated in 2 or more studies – they were categorized into 57 variables • The summary of results for 41 of the 57 categorized variables showed > 50% consensus as either having a positive, negative or null association among the studies that evaluated them (Table 2) Meta-analysis will be used to estimate summary effects for each exposure variable evaluated in 2 or more studies. These analyses will be used to prioritize and rank these factors based on their strength of association with children’s cognitive development.