The Associations between Neighborhood Characteristics and Childhood Overweight and Obesity in a National Dataset.

BACKGROUND: National child obesity rates continue to climb. While neighborhood factors are known to influence childhood weight, more work is needed to further our understanding of these relationships and inform intervention and policy approaches reflective of complex real-world contexts. METHODS: To evaluate the associations between neighborhood components and childhood overweight/obesity, we analyzed sequential, cross-sectional data from the National Survey of Children's Health collected annually between 2016 and 2021. To characterize the complexity of children's neighborhood environments, several interrelated neighborhood factors were examined: amenities, detractions, support, and safety. We used ordinal logistic regression models to evaluate the associations between these exposures of interest and childhood weight status, adjusting for potential confounders. RESULTS: Our analytic sample contained 96,858 children representing a weighted population of 28,228,799 children ages 10-17 years. Child weight status was healthy in 66.5%, overweight in 16.8%, and obese in 17.2%. All four neighborhood factors were associated with child weight status. The odds of overweight or obesity generally increased with a decreasing number of amenities and increasing number of detractions, with the highest adjusted odds ratio seen with no amenities and all three possible detractions (1.71; 95% confidence interval [1.31, 2.11]). CONCLUSIONS: Multiple factors within a child's neighborhood environment were associated with child weight status in this sample representative of the US population aged 10-17 years. This suggests the need for future research into how policies and programs can support multiple components of a healthy neighborhood environment simultaneously to reduce rates of childhood overweight/obesity.

Positive Outliers: A Mixed Methods Study of Resiliency to Childhood Obesity in High-Risk Neighborhoods.

OBJECTIVE: Despite the high prevalence of obesity and the clustering of risk by neighborhood, few studies have examined characteristics which promote healthy child weight in neighborhoods with high obesity risk. We aimed to identify protective factors for children living in neighborhoods with high obesity risk. METHODS: We identified neighborhoods with high obesity risk using geolocated electronic health record data with measured body mass index (BMI) from well-child visits (2012-2017). We then recruited caregivers with children aged 5 to 13 years who lived in census tracts with mean child BMI percentile ≥72 (February 2020-August 2021). We used sequential mixed methods (quantitative surveys, qualitative interviews) to compare individual, interpersonal, and perceived neighborhood factors among families with children at a healthy weight (positive outliers [PO]) versus families with ≥1 child with overweight or obesity (controls). Regression models and comparative qualitative analysis were used to identify protective characteristics. RESULTS: Seventy-three caregivers participated in the quantitative phase (41% PO; 34% preferred Spanish) and twenty in the qualitative phase (50% PO; 50% preferred Spanish). The frequency of healthy caregiver behaviors was associated with being a PO (Family Health Behavior Scale Parent Score adjusted ß 3.67; 95% CI 0.52-6.81 and qualitative data). Protective factors also included caregivers' ability to minimize the negative health influences of family members and adhere to family routines. CONCLUSIONS: There were few differences between PO and control families. Support for caregiver healthy habits and adherence to healthy family routines emerged as opportunities for childhood obesity prevention in neighborhoods with high obesity risk.

Interfacility Transfer Outcomes Among Children With Complex Chronic Conditions: Associations Between Patient-Level and Hospital-Level Factors and Transfer Outcomes.

OBJECTIVES: Determine patient- and referring hospital-level predictors of transfer outcomes among children with 1 or more complex chronic conditions (CCCs) transferred to a large academic medical center. METHODS: We conducted a retrospective chart review of 2063 pediatric inpatient admissions from 2017 to 2019 with at least 1 CCC defined by International Classification of Diseases, Tenth Revision codes. Charts were excluded if patients were admitted via any route other than transfer from a referring hospital's emergency department or inpatient ward. Patient-level factors were race/ethnicity, payer, and area median income. Hospital-level factors included the clinician type initiating transfer and whether the referring-hospital had an inpatient pediatric ward. Transfer outcomes were rapid response within 24 hours of admission, Pediatric Early Warning Score at admission, and hours to arrival. Regression analyses adjusted for age were used to determine association between patient- and hospital-level predictors with transfer outcomes. RESULTS: There were no significant associations between patient-level predictors and transfer outcomes. Hospital-level adjusted analyses indicated that transfers from hospitals without inpatient pediatrics wards had lower odds of ICU admission during hospitalization (odds ratio, 0.46; 95% confidence interval, 0.22-0.97) and shorter transfer times (ß-coefficient, -2.54; 95% CI, -3.60 to -1.49) versus transfers from hospitals with inpatient pediatrics wards. There were no significant associations between clinician type and transfer outcomes. CONCLUSIONS: For pediatric patients with CCCs, patient-level predictors were not associated with clinical outcomes. Transfers from hospitals without inpatient pediatric wards were less likely to require ICU admission and had shorter interfacility transfer times compared with those from hospitals with inpatient pediatrics wards.

The Built Environment and Pediatric Health.

Buildings, parks, and roads are all elements of the "built environment," which can be described as the human-made structures that comprise the neighborhoods and communities where people live, work, learn, and recreate (https://www.epa.gov/smm/basic-information-about-built-environment). The design of communities where children and adolescents live, learn, and play has a profound impact on their health. Moreover, the policies and practices that determine community design and the built environment are a root cause of disparities in the social determinants of health that contribute to health inequity. An understanding of the links between the built environment and pediatric health will help to inform pediatricians' and other pediatric health care professionals' care for patients and advocacy on their behalf. This policy statement outlines community design solutions that can improve pediatric physical and mental health, and improve health equity. It describes opportunities for pediatricians and the health care sector to incorporate this knowledge in patient care, as well as to play a role in advancing a health-promoting built environment for all children and families. The accompanying technical report reviews the range of pediatric physical and mental health conditions influenced by the built environment, as well as historical and persistent effects of the built environment on health disparities.

The Built Environment and Pediatric Health.

Buildings, parks, and roads are all elements of the "built environment," which can be described as the human-made structures that comprise the neighborhoods and communities where people live, work, learn, and recreate (https://www.epa.gov/smm/basic-information-about-built-environment). The design of communities where children and adolescents live, learn, and play has a profound impact on their health. Moreover, the policies and practices that determine community design and the built environment are a root cause of disparities in the social determinants of health that contribute to health inequity. An understanding of the links between the built environment and pediatric health will help to inform pediatricians' and other pediatric health professionals' care for patients and advocacy on their behalf. This technical report describes the range of pediatric physical and mental health conditions influenced by the built environment, as well as historical and persistent effects of the built environment on health disparities. The accompanying policy statement outlines community design solutions that can improve pediatric health and health equity, including opportunities for pediatricians and the health care sector to incorporate this knowledge in patient care, as well as to play a role in advancing a health-promoting built environment for all children and families.

Feeding, television, and sleep behaviors at one year of age in a diverse sample.

Background: Healthy lifestyle behaviors that can prevent adverse health outcomes, including obesity, are formed in early childhood. This study describes feeding, television, and sleep behaviors among one-year-old infants and examines differences by sociodemographic factors. Methods: Caregivers of one-year-olds presenting for well care at two clinics, control sites for the Greenlight Study, were queried about feeding, television time, and sleep. Adjusted associations between sociodemographic factors and behaviors were performed by modified Poisson (binary), multinomial logistic (multi-category), or linear (continuous) regression models. Results: Of 235 one-year-olds enrolled, 81% had Medicaid, and 45% were Hispanic, 36% non-Hispanic Black, 19% non-Hispanic White. Common behaviors included 20% exclusive bottle use, 32% put to bed with bottle, mean daily juice intake of 4.1 ± 4.6 ounces, and active television time 45 ± 73 min. In adjusted analyses compared to Hispanic caregivers, non-Hispanic Black caregivers were less likely to report exclusive bottle use (odds ratio: 0.11, 95% confidence interval [CI] 0.03-0.39), reported 2.4 ounces more juice (95% CI 1.0-3.9), 124 min more passive television time (95% CI 60-188), and 37 min more active television time (95% CI 10-64). Increased caregiver education and higher income were associated with 0.4 (95% CI 0.13-0.66) and 0.3 (95% CI 0.06-0.55) more servings of fruits and vegetables per day, respectively. Conclusion: In a diverse sample of one-year-olds, caregivers reported few protective behaviors that reduce the risk for adverse health outcomes including obesity. Differences in behavior by race/ethnicity, income, and education can inform future interventions and policies. Future interventions should strive to create culturally effective messaging to address common adverse health behaviors.

Organizational trust, usability, and inclusivity are key implementation facilitators for a proposed assets-based mobile health intervention.

Assets-based interventions can address child health disparities by connecting families to existing community resources. Community collaboration when designing interventions may identify barriers and facilitators to implementation. The objective of this study was to identify crucial implementation considerations during the design phase of an asset-based intervention to address disparities in childhood obesity, Assets for Health. We conducted focus groups and semi-structured interviews with caregivers of children (<18 years) (N = 17) and representatives of community-based organizations (CBOs) which serve children and families (N = 20). Focus group and interview guides were developed based on constructs from the Consolidated Framework for Implementation Research. Data were analyzed using rapid qualitative analysis and matrices were used to identify common themes within and across groups of community members. Desired intervention characteristics included an easy-to-use list of community programs that could be filtered based on caregiver preferences and local community health workers to promote trust and engagement among Black and Hispanic/Latino families. Most community members felt an intervention with these characteristics could be advantageous versus existing alternatives. Key outer setting characteristics which were barriers to family engagement included families' financial insecurity and lack of access to transportation. The CBO implementation climate was supportive but there was concern that the intervention could increase staff workload beyond current capacity. Assessment of implementation determinants during the intervention design phase revealed important considerations for intervention development. Effective implementation of Assets for Health may depend on app design and usability, fostering organizational trust and minimizing the costs and staff workload of caregivers and CBOs, respectively.

The purpose of our work was to design a program to connect families with children to existing health-promoting resources in their communities (i.e., group exercise, food pantries, community gardens). We specifically wanted to capture the needs and preferences of parents with children and community-based organizations and determine the possible barriers to creating this program. Based on prior community listening sessions, the program, called Assets for Health, would consist of a mobile app which lists community resources and a community health worker to help connect families to these resources. We presented the idea for Assets for Health to a diverse group of parents and community-based organizations using focus groups and interviews to carefully capture their thoughts. We then analyzed what was said. This work showed that parents were struggling to find community programs that fit their needs and thought a program like Assets for Health could be helpful. Also organizations were struggling to show families that they could be trusted and that all families were welcome.

Racial Inequities in Sepsis Mortality Among Children in the United States.

BACKGROUND: Racial inequities influence health outcomes in the United States, but their impact on sepsis outcomes among children is understudied. We aimed to evaluate for racial inequities in sepsis mortality using a nationally representative sample of pediatric hospitalizations. METHODS: This population-based, retrospective cohort study used the 2006, 2009, 2012 and 2016 Kids' Inpatient Database. Eligible children 1 month to 17 years old were identified using sepsis-related International Classification of Diseases, Ninth Revision or International Classification of Diseases, Tenth Revision codes. We used modified Poisson regression to evaluate the association between patient race and in-hospital mortality, clustering by hospital and adjusting for age, sex and year. We used Wald tests to assess for modification of associations between race and mortality by sociodemographic factors, geographic region and insurance status. RESULTS: Among 38,234 children with sepsis, 2555 (6.7%) died in-hospital. Compared with White children, mortality was higher among Hispanic (adjusted relative risk: 1.09; 95% confidence interval: 1.05-1.14), Asian/Pacific Islander (1.17, 1.08-1.27) and children from other racial minority groups (1.27, 1.19-1.35). Black children had similar mortality to White children overall (1.02, 0.96-1.07), but higher mortality in the South (7.3% vs. 6.4%; P < 0.0001). Hispanic children had higher mortality than White children in the Midwest (6.9% vs. 5.4%; P < 0.0001), while Asian/Pacific Islander children had higher mortality than all other racial categories in the Midwest (12.6%) and South (12.0%). Mortality was higher among uninsured children than among privately insured children (1.24, 1.17-1.31). CONCLUSIONS: Risk of in-hospital mortality among children with sepsis in the United States differs by patient race, geographic region and insurance status.

Protective and Unequal? Caregiver Presence During Pediatric Hospitalizations.

OBJECTIVES: Describe the association between caregiver presence on hospital day 1 and outcomes related to readmissions, pain, and adverse events (AE). METHODS: Caregiver presence during general pediatrics rounds on hospital day 1 was recorded, along with demographic data and clinical outcomes via chart review. AE data were obtained from the safety reporting system. χ2 tests compared demographic characteristics between present and absent caregivers. Background elimination determined significant predictors of caregiver presence and their association with outcomes. RESULTS: A total of 324 families were assessed (34.9% non-Hispanic white, 41.4% Black, 17% Hispanic or Latinx, 6.8% other race or ethnicity). Adolescents (aged ≥14 years) had increased odds of not having a caregiver present compared with 6- to 13-year-olds (36.2% vs 10%; adjusted odds ratio [aOR] 5.11 [95% confidence interval (CI) 1.88-13.87]). Publicly insured children were more likely to not have a caregiver present versus privately insured children (25.1% vs 12.4%; aOR 2.38 [95% CI 1.19-4.73]). Compared with having a caregiver present, children without caregivers were more likely to be readmitted at 7 days (aOR 3.6 [95% CI 1.0-12.2]), receive opiates for moderate/severe pain control (aOR 11.5 [95% CI 1.7-75.7]), and have an AE reported (aOR 4.0 [95% CI 1.0-15.1]). CONCLUSIONS: Adolescents and children with public insurance were less likely to have a caregiver present. Not having a caregiver present was associated with increased readmission, opiate prescription, and AE reporting. Further research is needed to delineate whether associations with clinical outcomes reflect differences in quality of care and decrease barriers to caregiver presence.

Healthcare Utilization for Medicaid-Insured Children with Medical Complexity: Differences by Sociodemographic Characteristics.

OBJECTIVE: To compare differences in healthcare utilization and costs for Medicaid-insured children with medical complexity (CMC) by race/ethnicity and rurality. METHODS: Retrospective cohort of North Carolina (NC) Medicaid claims for children 3-20 years old with 3 years continuous Medicaid coverage (10/1/2015-9/30/2018). Exposures were medical complexity, race/ethnicity, and rurality. Three medical complexity levels were: without chronic disease, non-complex chronic disease, and complex chronic disease; the latter were defined as CMC. Race/ethnicity was self-reported in claims; we defined rurality by home residence ZIP codes. Utilization and costs were summarized for 1 year (10/1/2018-9/30/2019) by complexity level classification and categorized as acute care (hospitalization, emergency [ED]), outpatient care (primary, specialty, allied health), and pharmacy. Per-complexity group utilization rates (per 1000 person-years) by race/ethnicity and rurality were compared using adjusted rate ratios (ARR). RESULTS: Among 859,166 Medicaid-insured children, 118,210 (13.8%) were CMC. Among CMC, 36% were categorized as Black non-Hispanic, 42.7% White non-Hispanic, 14.3% Hispanic, and 35% rural. Compared to White non-Hispanic CMC, Black non-Hispanic CMC had higher hospitalization (ARR = 1.12; confidence interval, CI 1.08-1.17) and ED visit (ARR = 1.17; CI 1.16-1.19) rates; Hispanic CMC had lower ED visit (ARR = 0.77; CI 0.75-0.78) and hospitalization rates (ARR = 0.79; CI 0.73-0.84). Black non-Hispanic and Hispanic CMC had lower outpatient visit rates than White non-Hispanic CMC. Rural CMC had higher ED (ARR = 1.13; CI 1.11-1.15) and lower primary care utilization rates (ARR = 0.87; CI 0.86-0.88) than urban CMC. DISCUSSION: Healthcare utilization varied by race/ethnicity and rurality for Medicaid-insured CMC. Further studies should investigate mechanisms for these variations and expand higher value, equitable care delivery for CMC.

Association of Sociodemographic Factors With Reported Penicillin Allergy in Pediatric Inpatients.

OBJECTIVES: Characterize the association of sociodemographic factors with reported penicillin allergy in pediatric inpatients. METHODS: We conducted a retrospective cohort study of pediatric inpatients admitted to general pediatric units at an academic medical center with reported penicillin allergy and reaction history. Sociodemographic factors evaluated were gender, age, race, ethnicity, language, and insurance payer. We conducted univariable and multivariable logistic regression models to evaluate associations between demographic variables and penicillin allergy. RESULTS: Of 3890 pediatric inpatients, 299 (7.7%) had a reported penicillin allergy. The majority of documented reaction histories were hives, rash, or unknown. In univariable analysis, odds of penicillin allergy were lower in patients who identify as Black and who prefer a language other than English, and higher in patients of non-Hispanic/Latino ethnicity, those with private insurance, and with increasing age. In multivariable logistic regression, only Black race (adjusted odds ratio 0.42, 95% confidence interval CI 0.30-0.59) and young age were significantly associated with lower odds of penicillin allergy. CONCLUSIONS: After adjustment for covariates, Black race was associated with lower odds of reported penicillin allergy in hospitalized children. Penicillin allergy reporting may be an indicator of racial differences in the prescribing of antimicrobial agents, patient-clinician communication, and access to health care.

The Prenatal Neighborhood Environment and Geographic Hotspots of Infants with At-risk Birthweights in New York City.

Infants born with low or high ("at-risk") birthweights are at greater risk of adverse health outcomes across the life course. Our objective was to examine whether geographic hotspots of low and high birthweight prevalence in New York City had different patterns of neighborhood risk factors. We performed census tract-level geospatial clustering analyses using (1) birthweight prevalence and maternal residential address from an all-payer claims database and (2) domains of neighborhood risk factors (socioeconomic and food environment) from national and local datasets. We then used logistic regression analysis to identify specific neighborhood risk factors associated with low and high birthweight hotspots. This study examined 2088 census tracts representing 419,025 infants. We found almost no overlap (1.5%) between low and high birthweight hotspots. The majority of low birthweight hotspots (87.2%) overlapped with a socioeconomic risk factor and 95.7% overlapped with a food environment risk factor. Half of high birthweight hotspots (50.0%) overlapped with a socioeconomic risk factor and 48.8% overlapped with a food environment risk factor. Low birthweight hotspots were associated with high prevalence of excessive housing cost, unemployment, and poor food environment. High birthweight hotspots were associated with high prevalence of uninsured persons and convenience stores. Programs and policies that aim to prevent disparities in infant birthweight should examine the broader context by which hotspots of at-risk birthweight overlap with neighborhood risk factors. Multi-level strategies that include the neighborhood context are needed to address prenatal pathways leading to low and high birthweight outcomes.

Racial and Ethnic Differences in Maternal Social Support and Relationship to Mother-Infant Health Behaviors.

OBJECTIVE: To examine racial and ethnic differences in maternal social support in infancy and the relationship between social support and mother-infant health behaviors. METHODS: Secondary analysis of baseline data from a multisite obesity prevention trial that enrolled mothers and their 2-month-old infants. Behavioral and social support data were collected via questionnaire. We used modified Poisson regression to determine association between health behaviors and financial and emotional social support, adjusted for sociodemographic characteristics. RESULTS: Eight hundred and twenty-six mother-infant dyads (27.3% non-Hispanic Black, 18.0% Non-Hispanic White, 50.1% Hispanic and 4.6% Non-Hispanic Other). Half of mothers were born in the United States; 87% were Medicaid-insured. There were no racial/ethnic differences in social support controlling for maternal nativity. US-born mothers were more likely to have emotional and financial support (rate ratio [RR] 1.14 95% confidence interval [CI]: 1.07, 1.21 and RR 1.23 95% CI: 1.11, 1.37, respectively) versus mothers born outside the United States. Mothers with financial support were less likely to exclusively feed with breast milk (RR 0.62; 95% CI: 0.45, 0.87) yet more likely to have tummy time ≥12min (RR 1.28; 95% CI: 1.02, 1.59) versus mothers without financial support. Mothers with emotional support were less likely to report feeding with breast milk (RR 0.82; 95% CI: 0.69, 0.97) versus mothers without emotional support. CONCLUSIONS: Nativity, not race or ethnicity, is a significant determinant of maternal social support. Greater social support was not universally associated with healthy behaviors. Interventions may wish to consider the complex nature of social support and population-specific social support needs.

Local-Level Immigration Enforcement and Risk of Pediatric Hospitalization for Ambulatory Care Sensitive Conditions.

Immigration enforcement may disrupt access to health care, potentially increasing hospitalizations for Ambulatory Care Sensitive Conditions (ACSC). We aimed to assess the effect of local-level 287(g) immigration enforcement on North Carolina pediatric ACSC hospitalizations. Pediatric (< 19 year) ACSC hospitalizations were identified based on ICD-9 codes. We compared ACSC hospitalizations pre and post 287(g) implementation using a difference-in-difference analysis of Fiscal Year (FY)2006-2009 data. We used multi-level models to assess the effects of 287(g) programs on ACSC hospitalizations during FY2011-2015. Difference-in-difference analyses showed that ACSC hospitalizations increased by more than 2.48% in the year following 287(g) implementation (95% CI: 0.99%, 3.97%). Among the counties that had ever implemented a 287(g) program, the ACSC-increasing effect of an active 287(g) program was greatest in counties with a shorter tenure of their 287(g) program and for Hispanic/Latino children/adolescents. Our findings underscore the importance of describing the effects of local-level immigration enforcement on pediatric access to care and potentially avoidable hospitalizations.

Parenting Stress, Child Weight-Related Behaviors, and Child Weight Status.

Background: There has been limited examination of the association between parenting stress and child weight-related behaviors. We aimed to determine whether parenting stress is associated with child weight-related behaviors, including physical activity, screen time, diet, sedentary time, and eating in the absence of hunger (EAH). Secondarily, we assessed association between parenting stress and child weight status. Methods: Mother-child dyads (N = 291) enrolled in the Newborn Epigenetic STudy (NEST), a longitudinal cohort study, completed surveys to describe parenting stress, and child diet. Children participated in the EAH task and wore accelerometers to assess sedentary time and physical activity. Child weight status was assessed using measured height and weight. Outcomes and exposures were examined using generalized linear models and restricted cubic splines as appropriate based on linear lack-of-fit test. Results: Child sedentary time and vegetable consumption were inversely associated with parenting stress (Total Stress B = -0.78; 95% confidence interval [CI]: -1.35 to -0.20; p = 0.017; and Total Stress adjusted odds ratio [aOR] = 0.98; 95% CI: 0.99 to 1.00; p = 0.022, respectively). Child screen time was directly associated with parenting stress (Total Stress = aOR 1.01; 95% CI: 1.00-1.02; p = 0.032). Fast-food intake was nonlinearly associated with parenting stress. There was no evidence of association between parenting stress and child EAH, physical activity, or weight status. Associations between parenting stress and child weight-related behaviors were not moderated by race or family structure. Conclusions: Parenting stress was associated with important child weight-related behaviors but not weight status. Management of parenting stress may represent a reasonable adjunct to family-based behavioral interventions.

The significant places of African American adults and their perceived influence on cardiovascular disease risk behaviors.

BACKGROUND: AA living in rural areas of the southeastern U.S. experience a disproportionate burden of cardiovascular disease (CVD) morbidity and mortality. Neighborhood environmental factors contribute to this disparity and may decrease the effectiveness of lifestyle interventions aimed at preventing CVD. Furthermore, the influence of neighborhood factors on AA CVD risk behaviors (i.e. physical activity) may be obscured by the use of researcher-defined neighborhoods and researcher-defined healthy and unhealthy places. The objective of this study was to elucidate the effects of neighborhood environments on AA CVD risk behaviors among AA adults who recently completed a lifestyle intervention. We specifically sought to identify AA adults' self-perceived places of significance and their perceptions of how these places impact CVD risk behaviors including diet, physical activity and smoking. METHODS: We conducted semi-structured interviews with AA adults (N = 26) living in two rural North Carolina counties (Edgecombe and Nash, North Carolina, USA). Participants were recruited from a community-based behavioral CVD risk reduction intervention. All had at least one risk factor for CVD. Participants identified significant places including where they spent the most time, meaningful places, and healthy and unhealthy places on local maps. Using these maps as a reference, participants described the impact of each location on their CVD risk behaviors. Data were transcribed verbatim and coded using NVivo 12. RESULTS: The average age of participants was 63 (SD = 10) and 92% were female. Places participants defined as meaningful and places where they spent the most time included churches and relatives' homes. Healthy places included gyms and parks. Unhealthy places included fast food restaurants and relatives' homes where unhealthy food was served. Place influenced CVD risk behaviors in multiple ways including through degree of perceived control over the environment, emotional attachment and loneliness, caretaking responsibilities, social pressures and social support. CONCLUSIONS: As we seek to improve cardiovascular interventions for rural AA in the American South, it will be important to further assess the effect of significant places beyond place of residence. Strategies which leverage or modify behavioral influences within person-defined significant places may improve the reach and effectiveness of behavioral lifestyle interventions.

Sociocultural Factors Affecting Vocabulary Development in Young South African Children.

Sociocultural influences on the development of child language skills have been widely studied, but the majority of the research findings were generated in Northern contexts. The current crosslinguistic, multisite study is the first of its kind in South Africa, considering the influence of a range of individual and sociocultural factors on expressive vocabulary size of young children. Caregivers of toddlers aged 16 to 32 months acquiring Afrikaans (n = 110), isiXhosa (n = 115), South African English (n = 105), or Xitsonga (n = 98) as home language completed a family background questionnaire and the MacArthur-Bates Communicative Development Inventory (CDI) about their children. Based on a revised version of Bronfenbrenner's (1977) ecological systems theory, information was obtained from the family background questionnaire on individual factors (the child's age and sex), microsystem-related factors (the number of other children and number of adults in the child's household, maternal level of education, and SES), and exosystem-related factors (home language and geographic area, namely rural or urban). All sociocultural and individual factors combined explained 25% of the variance in expressive vocabulary size. Partial correlations between these sociocultural factors and the toddlers' expressive vocabulary scores on 10 semantic domains yielded important insights into the impact of geographic area on the nature and size of children's expressive vocabulary. Unlike in previous studies, maternal level of education and SES did not play a significant role in predicting children's expressive vocabulary scores. These results indicate that there exists an interplay of sociocultural and individual influences on vocabulary development that requires a more complex ecological model of language development to understand the interaction between various sociocultural factors in diverse contexts.