Search

Objective: The objective of this study was to estimate the effects of trimester-specific gestational weight gain (GWG) on small and large (compared with appropriate) for gestational age (i.e., SGA, LGA, and AGA) by prepregnancy BMI classifications., Methods: We conducted a cohort study of pregnancies in a national network of community health care organizations, stratifying by prepregnancy BMI (n = 20,676 with normal weight; 19,156 with overweight; 11,647 with obesity class I; 5124 with obesity class II; and 3197 with obesity class III). SGA and LGA (vs. AGA) were modeled as a function of trimester 1, 2, or 3 GWG rate, previous trimester(s) GWG rate, and maternal characteristics using modified Poisson regression., Results: GWG rates ranged from weight loss to substantial gains. GWG-LGA associations were strongest in trimester 1 (risk ratio [RR] range for 10th vs. 50th percentile GWG, across BMI categories: 0.60-0.73). GWG-SGA associations were strongest in lower BMI categories and in trimester 2; RRs were 1.62, 1.40, and 1.17 for prepregnancy normal weight, obesity class I, and obesity class III, respectively, with curvilinear associations for class II and III., Conclusions: Among people with prepregnancy obesity class II or III, GWG rate is associated with higher LGA risk in a dose-dependent manner, including understudied ranges of weight loss, but with weak associations with SGA., (© 2024 The Obesity Society.)

Background: Growing evidence for the effect of maternal obesity on childhood asthma motivates investigation of mediating pathways., Objective: To investigate if childhood body mass index (BMI), gestational weight gain (GWG) and preterm birth mediate the association of maternal obesity on childhood asthma risk., Methods: We used electronic medical records from mother-child pairs enrolled in Kaiser Permanente Northern California integrated healthcare system. Children were followed from their birth (2005-2014) until at least age 4 (n = 95,723), age 6 (n = 59,230) or age 8 (n = 25,261). Childhood asthma diagnosis at each age was determined using ICD-9/10 codes and medication dispensings. Prepregnancy BMI (underweight [<18.5], normal [18.5-24.9], overweight [25-29.9], obese [≥30] kg/m 2 ) were defined using height and weight measurements close to the last menstrual period date. Child's BMI (Centers for Disease Control and Prevention BMI-for-age percentiles: underweight [<5th], normal [5th-85th], overweight [85th-95th], obese [>95th]) were obtained using anthropometric measurements taken the year preceding each follow-up age. GWG (delivery weight-prepregnancy weight) was categorised based on Institutes of Medicine recommendations (inadequate, adequate, excessive). Implementing first causal inference test (CIT) then causal mediator models (to decompose the natural direct and indirect effects), we examined the potential mediating effect of childhood BMI, GWG, and preterm birth on the association between prepregnancy BMI (continuous and categorical) and childhood asthma., Results: Overall, risk of childhood asthma increased as prepregnancy BMI increased (age 4 risk ratio: 1.07, 95% confidence interval: 1.04, 1.09, per 5 kg/m 2 increase in BMI; similar for age 6 and 8). CIT identified childhood BMI and preterm birth, but not GWG as potential mediators. Causal mediation models confirmed childhood BMI, but not preterm birth, as having a partial mediating effect. Results were similar for age 6 and 8, and when continuous mediators (instead of binary) were assessed., Conclusions: Childhood overweight/obesity has a modest mediating effect on the association between prepregnancy BMI and childhood asthma., (© 2023 John Wiley & Sons Ltd.)

Background: Growing evidence suggests that maternal obesity may affect the intrauterine environment and increase a child's risk of developing asthma. We aim to investigate the relationship between prepregnancy obesity and childhood asthma risk., Methods: Cohorts of children enrolled in Kaiser Permanente Northern California integrated healthcare system were followed from birth (2005-2014) to age 4 (n = 104,467), 6 (n = 63,084), or 8 (n = 31,006) using electronic medical records. Child's asthma was defined using ICD codes and asthma-related prescription medication dispensing. Risk ratios (RR) and 95% confidence intervals (95% CIs) for child's asthma were estimated using Poisson regression with robust error variance for (1) prepregnancy BMI categories (underweight [<18.5], normal [18.5-24.9], overweight [25-29.9], obese 1 [30-34.9], and obese 2/3 [≥35]) and (2) continuous prepregnancy BMI modeled using cubic splines with knots at BMI category boundaries. Models were adjusted for maternal age, education, race, asthma, allergies, smoking, gestational weight gain, child's birth year, parity, infant sex, gestational age, and child's BMI., Results: Relative to normal BMI, RRs (95%CIs) for asthma at ages 4, 6, and 8 were 0.91 (0.75, 1.11), 0.95 (0.78, 1.16), and 0.97 (0.75, 1.27) for underweight, 1.06 (0.99, 1.14), 1.08 (1.01, 1.16), and 1.03 (0.94, 1.14) for overweight, 1.09 (1.00, 1.19), 1.12 (1.03, 1.23), 1.03 (0.91, 1.17) for obese 1, and 1.10 (0.99, 1.21), 1.13 (1.02, 1.25), 1.14 (0.99, 1.31) for obese 2/3. When continuous prepregnancy BMI was modeled with splines, child's asthma risk generally increased linearly with increasing prepregnancy BMI., Conclusions: Higher prepregnancy BMI is associated with modestly increased childhood asthma risk., (© 2022 European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Acute effects of outdoor air pollution on asthma exacerbations may vary by asthma phenotype (allergic vs nonallergic). Associations of ambient PM 2.5 and ozone concentrations with acute asthma visits (office, urgent, emergency, and hospitalization) were investigated using electronic medical records. International Classification of Disease codes were used to identify asthmatics, and classify them based on the presence or absence of an allergic comorbidity in their medical records. Daily 24-h average PM 2.5 , 8-h maximum ozone, and mean temperature were obtained from a centralized monitor. Using a time-stratified case-crossover approach, pollutant concentrations were modeled using moving averages and distributed lag nonlinear models (lag 0-6) to examine lag associations and nonlinear concentration-response. The adjusted odds ratios for a 10 µg/m 3 increase in 3-day moving average (lag 0-2) PM 2.5 in the two-pollutant models among patients with and without allergic comorbidities were 1.10 (95% confidence interval [CI]: 1.07, 1.13) and 1.05 (95% CI: 1.02, 1.09), respectively; and for a 20 ppb increase in 3-day moving average (lag 0-2) ozone were 1.08 (95% CI: 1.02, 1.14) and 1.00 (95% CI: 0.95, 1.05), respectively. Estimated odds ratios among patients with allergic comorbidities were consistently higher across age, sex, and temperature categories. Asthmatics with an allergic comorbidity may be more susceptible to ambient PM 2.5 and ozone.

Objectives: We examined the relationship between income inequality and the risk for infant/neonatal mortality at the state and county level and tested possible mediators of this relationship., Methods: We first linked state and county Gini coefficients to US Vital Statistics 2010 Cohort Linked Birth and Infant Death records (n = 3,954,325). We then fit multilevel models to test whether income inequality was associated with infant/neonatal mortality. County-level factors were tested as potential mediators., Results: Adjusted analyses indicated that income inequality at the county level-but not at the state level-was associated with increased odds of infant mortality (OR 1.14, 95% CI 1.10, 1.18) and neonatal death (OR 1.17, 95% CI 1.12, 1.23). Our mediators explained most of this variation. Bivariate analyses revealed associations between 3 county-level measures-patient-to-physician ratio, the violent crime rate, and sexually transmitted infection rate-and infant and neonatal mortality. Proportion of college-educated adults was associated with decreased odds for neonatal mortality., Conclusions: Local variations in access to care, the rate of sexually transmitted disease, and crime are associated with infant mortality, while variations in college education in addition to these mediators explain neonatal mortality. To reduce infant and neonatal mortality, experiments are needed to examine the effectiveness of policies targeted at reducing income inequality and improving healthcare access, policing, and educational opportunities.

Background: Compared to other Organisation for Economic Co-operation and Development (OECD) nations, US infant mortality rates (IMRs) are particularly high. These differences are partially driven by racial disparities, with non-Hispanic black having IMRs that are twice those of non-Hispanic white. Income inequality (the gap between rich and poor) is associated with infant mortality. One proposed way to decrease income inequality (and possibly to improve birth outcomes) is to increase the minimum wage. We aimed to elucidate the relationship between state-level minimum wage and infant mortality risk using individual-level and state-level data. We also determined whether observed associations were heterogeneous across racial groups., Methods: Data were from US Vital Statistics 2010 Cohort Linked Birth and Infant Death records and the 2010 US Bureau of Labor Statistics. We fit multilevel logistic models to test whether state minimum wage was associated with infant mortality. Minimum wage was standardised using the z-transformation and was dichotomised (high vs low) at the 75th percentile. Analyses were stratified by mother's race (non-Hispanic black vs non-Hispanic white)., Results: High minimum wage (adjusted OR (AOR)=0.93, 95% CI 0.83 to 1.03) was associated with decreased odds of infant mortality but was not statistically significant. High minimum wage was significantly associated with reduced infant mortality among non-Hispanic black infants (AOR=0.80, 95% CI 0.68 to 0.94) but not among non-Hispanic white infants (AOR=1.04, 95% CI 0.92 to 1.17)., Conclusions: Increasing the minimum wage might be beneficial to infant health, especially among non-Hispanic black infants, and thus might decrease the racial disparity in infant mortality., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: United States state-level income inequality is positively associated with infant mortality in ecological studies. We exploit spatiotemporal variations in a large dataset containing individual-level data to conduct a cohort study and to investigate whether current income inequality and increases in income inequality are associated with infant and neonatal mortality risk over the period of the 2007-2010 Great Recession in the United States., Methods: We used data on 16,145,716 infants and their mothers from the 2007-2010 United States Statistics Linked Infant Birth and Death Records. Multilevel logistic regression was used to determine whether 1) US state-level income inequality, as measured by Z-transformed Gini coefficients in the year of birth and 2) change in Gini coefficient between 1990 and year of birth (2007-2010), predicted infant or neonatal mortality. Our analyses adjusted for both individual and state-level covariates., Results: From 2007 to 2010 there were 98,002 infant deaths: an infant mortality rate of 6.07 infant deaths per 1000 live births. When controlling for state and individual level characteristics, there was no significant relationship between Gini Z-score and infant mortality risk. However, the observed increase in the Gini Z-score was associated with a small but significant increase likelihood of infant mortality (AOR = 1.03 to 1.06 from 2007 to 2010). Similar findings were observed when the neonatal mortality was the outcome (AOR = 1.05 to 1.13 from 2007 to 2010)., Conclusions: Infants born in states with greater changes in income inequality between 1990 and 2007 to 2010 experienced a greater likelihood of infant and neonatal mortality.