Neighborhood disadvantage and pediatric inpatient opioid prescription patterns.

BACKGROUND: To explore the role of children's residential environment on opioid prescribing patterns in a predominantly Latinx sample. METHODS: We connected geocoded data from electronic medical records in a diverse sample of pediatric patients to neighborhood environments constructed using latent profile modeling techniques. We then estimated a series of multilevel models to determine whether opioid prescribing patterns vary by residential context. RESULTS: A stepwise pattern exists between neighborhood disadvantage and pediatric opioid prescription patterns, such that higher levels of disadvantage associate with a greater likelihood of opioid prescription, independent of the patient's individual profile. CONCLUSION: In a largely Latinx sample of children, the neighborhood in which a child lives influences whether or not they will receive opioids. Considering the differences in patient residential environment may reduce variation in opioid dispensing rates among pediatric patients.

Deconstructing sex differences in C-reactive protein trends over time.

OBJECTIVES: Heightened inflammatory state, as measured by circulating C-reactive protein (CRP) levels, can promote inflammation-mediated disease risk. It is important to account for population fluctuation and sex variation in serum CRP concentrations on overall time trends. METHODS: Using the National Health and Nutrition Examination Survey data, we specify linear and algebraic decomposition models separately by sex to identify the drivers of the changing trends in the distribution of CRP values in the population. RESULTS: We found a nonsignificant overall increase in CRP, but a significant decrease among women and increase among men, over a 10-year period. We then used linear and algebraic decomposition techniques to identify the sources of change in CRP over time, separately for women and men. CRP increased among men mainly because lifestyle/health characteristics worsened over time, and because the size of socioeconomic/demographic groups with higher CRP increased and the size of groups with lower CRP decreased. The downward shift in CRP among women occurred because the typical woman across all cohorts had lower CRP levels. CONCLUSIONS: We identified two fundamentally different processes of change driving the decline and rise in CRP values among women and men, respectively.

Neighborhood and Social Environmental Influences on Child Chronic Disease Prevalence.

We investigate how distinct residential environments uniquely influence chronic child disease. Aggregating over 200,000 pediatric geocoded medical records to the census tract of residence and linking them to neighborhood-level measures, we use multiple data analysis techniques to assess how heterogeneous exposures of social and environmental neighborhood conditions influence an index of child chronic disease (CCD) prevalence for the neighborhood. We find there is a graded relationship between degree of overall neighborhood disadvantage and children's chronic disease such that the highest neighborhood CCD scores reside in communities with the highest concentrated disadvantage. Finally, results show that higher levels of neighborhood concentrated disadvantage and air pollution exposure associate with higher risks of having at least one chronic condition for children after also considering their individual- and family-level characteristics. Overall, our analysis serves as a comprehensive start for future researchers interested in assessing which neighborhood factors matter most for child chronic health conditions.

Comprehensive Neighborhood Portraits and Child Asthma Disparities.

Objectives Previous research has established links between child, family, and neighborhood disadvantages and child asthma. We add to this literature by first characterizing neighborhoods in Houston, TX by demographic, economic, and air quality characteristics to establish differences in pediatric asthma diagnoses across neighborhoods. Second, we identify the relative risk of social, economic, and environmental risk factors for child asthma diagnoses. Methods We geocoded and linked electronic pediatric medical records to neighborhood-level social and economic indicators. Using latent profile modeling techniques, we identified Advantaged, Middle-class, and Disadvantaged neighborhoods. We then used a modified version of the Blinder-Oaxaca regression decomposition method to examine differences in asthma diagnoses across children in these different neighborhoods. Results Both compositional (the characteristics of the children and the ambient air quality in the neighborhood) and associational (the relationship between child and air quality characteristics and asthma) differences within the distinctive neighborhood contexts influence asthma outcomes. For example, unequal exposure to PM2.5 and O3 among children in Disadvantaged and Middle-class neighborhoods contribute to asthma diagnosis disparities within these contexts. For children in Disadvantaged and Advantaged neighborhoods, associational differences between racial/ethnic and socioeconomic characteristics and asthma diagnoses explain a significant proportion of the gap. Conclusions for Practice Our results provide evidence that differential exposure to pollution and protective factors associated with non-Hispanic White children and children from affluent families contribute to asthma disparities between neighborhoods. Future researchers should consider social and racial inequalities as more proximate drivers, not merely as associated, with asthma disparities in children.

Pediatric obesity in the United States: Age-period-cohort analysis.

The rates of obesity among American children aged 2-5 years has reached a historic high. It is crucial to identify the putative sources of population-level increases in obesity prevalence among preschool-aged children because early childhood is a critical window for obesity prevention and thus reduction of future incidence. We used the National Health and Nutrition Examination Survey data and hierarchical age-period-cohort analysis to examine lifecycle (i.e., age), historical (i.e., period), and generational (i.e., cohort) distribution of age- and sex-specific body mass index z-scores (zBMI) among 2-5-year-olds in the U.S. from 1999 to 2018. Our current findings indicate that period effects, rather than differences in groups born at a specific time (i.e., cohort effects), account for almost all of the observed changes in zBMI. We need a broad socioeconomic, cultural, and environmental strategy to counteract the current obesogenic environment that influences children of all ages and generations in order to reach large segments of preschoolers and achieve population-wide improvement.

Obesity Heterogeneity by Neighborhood Context in a Largely Latinx Sample.

Neighborhood socioeconomic context where Latinx children live may influence body weight status. Los Angeles County and Orange County of Southern California both are on the list of the top ten counties with the largest Latinx population in the USA. This heterogeneity allowed us to estimate differential impacts of neighborhood environment on children's body mass index z-scores by race/ethnicity using novel methods and a rich data source. We geocoded pediatric electronic medical record data from a predominantly Latinx sample and characterized neighborhoods into unique residential contexts using latent profile modeling techniques. We estimated multilevel linear regression models that adjust for comorbid conditions and found that a child's place of residence independently associates with higher body mass index z-scores. Interactions further reveal that Latinx children living in Middle-Class neighborhoods have higher BMI z-scores than Asian and Other Race children residing in the most disadvantaged communities. Our findings underscore the complex relationship between community racial/ethnic composition and neighborhood socioeconomic context on body weight status during childhood.

Neighborhood Socioeconomic Context Predicts Pediatric Asthma Exacerbation.

Causes of asthma exacerbation in children have been studied extensively at the individual level, but contributions of neighborhood-level factors are less explored. We test which distinctive residential characteristics produce variation in uncontrolled asthma among pediatric patients. We extracted electronic medical record data from pediatric patients living in Southern California and used multilevel modeling techniques to isolate which neighborhood characteristics drive inequitable asthma control. Above and beyond the individual-level factors known to predict inadequate disease control, neighborhoods with greater concentration of non-Hispanic black residents (odds ratios [OR] = 1.02; 95% confidence interval [CI]: 0.99-1.03; P < .05), higher proportions of female-headed households (OR = 1.01; 95% CI: 0.99-1.01; P < .05), and higher levels of ambient air pollution (OR = 1.05; 95% CI: 1.01-1.10; P < .001) associate with greater odds of asthma exacerbation. The interplay between community characteristics and asthma management during childhood is complex, and place-based initiatives are needed to narrow the gap in asthma exacerbation.

Explaining adult obesity, severe obesity, and BMI: Five decades of change.

Obesity rates have increased across all segments of society since the late 1970s, but the reason behind population-level increases in body weight remains unclear. We used the 1971-2020 NHANES data to examine whether the observed trend in obesity prevalence is attributable to changing public health behaviors (i.e., intracohort change) or changing publics (i.e., cohort replacement). We partitioned total change in mean BMI, and rates of obesity and severe obesity, into its IC and CR components using linear and algebraic decomposition methods. We found that the IC mechanism (i.e., broad sectors of individuals changing) plays a dominant role in the overall increase in mean BMI, and obesity and severe obesity prevalence. Birth cohort membership (i.e., the CR mechanism) is also influencing mean BMI, and rates of obesity and severe obesity, but in differing ways. Specifically, the large positive IC and the small positive CR effects are amplifying one another, thus creating a steep increase in the observed rates of severe obesity. Conversely, the large positive IC effect is offset by a small negative CR effect, which created a more gradual rise in mean BMI and rates of obesity. Furthermore, we computed total change for models that entered separately sociodemographic, lifestyle, nutritional, and physical activity measures to estimate differences in mean BMI, and rates of obesity and severe obesity, among cohorts and time periods. Adjustment for all the compositional differences among the cohorts during the study period indicate that a combination of a more pronounced IC and a less pronounced CR drove the observed increase in mean BMI, and rates of obesity and severe obesity. Thus, "universal prevention" (i.e., entire community) strategies for healthy weight promotion may need to be combined with "selective prevention" (i.e., at-risk groups) and/or "targeted prevention" (i.e., at-risk individuals) approaches in order to reverse the obesity epidemic.

Neighborhoods matter; but for whom? Heterogeneity of neighborhood disadvantage on child obesity by sex.

Although evidence suggests that neighborhood context, particularly socioeconomic context, influences child obesity, little is known about how these neighborhood factors may be heterogeneous rather than monolithic. Using a novel dataset comprised of the electronic medical records for over 250,000 children aged 2-17 nested within 992 neighborhoods in the greater Houston area, we assessed whether neighborhoods influenced the obesity of children differently based on sex. Results indicated that neighborhood disadvantage, assessed using a comprehensive, multidimensional, latent profile analysis-generated measure, had a strong, positive association with the odds of obesity for both boys and girls. Interactions revealed that the relationship between disadvantage and obesity was stronger for girls, relative to boys. Our findings demonstrated the complex dynamics underlying the influence of residential neighborhood context on obesity for specific subgroups of children.

School-Level Body Mass Index Shapes Children's Weight Trajectories.

BACKGROUND: Embedded within children's weight trajectories are complex environmental contexts that influence obesity risk. As such, the normative environment of body mass index (BMI) within schools may influence children's weight trajectories as they age from kindergarten to fifth grade. METHODS: I use 5 waves of the ECLS-K-Kindergarten Class 1998-1999 data and a series of multilevel growth models to examine whether attending schools with higher overall BMI influences children's weight status over time. RESULTS: Results show that, net of child, family, and school sociodemographic characteristics, children who attend schools with higher rates of obesity have increased weight compared to children who attend schools with lower rates of obesity, and this effect increases annually. CONCLUSIONS: Findings indicate that the overall weight status of schools influence child obesity, and further speak to the importance of school-based intervention programs.