Early family socioeconomic status and asthma-related outcomes in school-aged children: Results from seven birth cohort studies.

OBJECTIVE: To examine the associations between maternal education and household income during early childhood with asthma-related outcomes in children aged 9-12 years in the UK, the Netherlands, Sweden, Australia, the USA and Canada. METHODS: Data on 31 210 children were obtained from 7 prospective birth cohort studies across six countries. Asthma-related outcomes included ever asthma, wheezing/asthma attacks and medication control for asthma. Relative social inequalities were estimated using pooled risk ratios (RRs) adjusted for potential confounders (child age, sex, mother ethnic background and maternal age) for maternal education and household income. The Slope Index of Inequality (SII) was calculated for each cohort to evaluate absolute social inequalities. RESULTS: Ever asthma prevalence ranged from 8.3% (Netherlands) to 29.1% (Australia). Wheezing/asthma attacks prevalence ranged from 3.9% (Quebec) to 16.8% (USA). Pooled RRs for low (vs high) maternal education and low (vs high) household income were: ever asthma (education 1.24, 95% CI 1.13 to 1.37; income 1.28, 95% CI 1.15 to 1.43), wheezing/asthma attacks (education 1.14, 95% CI 0.97 to 1.35; income 1.22, 95% CI 1.03 to 1.44) and asthma with medication control (education 1.16, 95% CI 0.97 to 1.40; income 1.25, 95% CI 1.01 to 1.55). SIIs supported the lower risk for children with more highly educated mothers and those from higher-income households in most cohorts, with few exceptions. CONCLUSIONS: Social inequalities by household income on the risk of ever asthma, wheezing/asthma attacks, and medication control for asthma were evident; the associations were attenuated for maternal education. These findings support the need for prevention policies to address the relatively high risks of respiratory morbidity in children in families with low socioeconomic status.

Household income and maternal education in early childhood and risk of overweight and obesity in late childhood: Findings from seven birth cohort studies in six high-income countries.

BACKGROUND/OBJECTIVES: This study analysed the relationship between early childhood socioeconomic status (SES) measured by maternal education and household income and the subsequent development of childhood overweight and obesity. SUBJECTS/METHODS: Data from seven population-representative prospective child cohorts in six high-income countries: United Kingdom, Australia, the Netherlands, Canada (one national cohort and one from the province of Quebec), USA, Sweden. Children were included at birth or within the first 2 years of life. Pooled estimates relate to a total of N = 26,565 included children. Overweight and obesity were defined using International Obesity Task Force (IOTF) cut-offs and measured in late childhood (8-11 years). Risk ratios (RRs) and pooled risk estimates were adjusted for potential confounders (maternal age, ethnicity, child sex). Slope Indexes of Inequality (SII) were estimated to quantify absolute inequality for maternal education and household income. RESULTS: Prevalence ranged from 15.0% overweight and 2.4% obese in the Swedish cohort to 37.6% overweight and 15.8% obese in the US cohort. Overall, across cohorts, social gradients were observed for risk of obesity for both low maternal education (pooled RR: 2.99, 95% CI: 2.07, 4.31) and low household income (pooled RR: 2.69, 95% CI: 1.68, 4.30); between-cohort heterogeneity ranged from negligible to moderate (p: 0.300 to < 0.001). The association between RRs of obesity by income was lowest in Sweden than in other cohorts. CONCLUSIONS: There was a social gradient by maternal education on the risk of childhood obesity in all included cohorts. The SES associations measured by income were more heterogeneous and differed between Sweden versus the other national cohorts; these findings may be attributable to policy differences, including preschool policies, maternity leave, a ban on advertising to children, and universal free school meals.

Inverse probability weighted distributed lag effects of short-term exposure to PM2.5 and ozone on CVD hospitalizations in New England Medicare participants - Exploring the causal effects.

BACKGROUND: Although many studies have established significant associations between short-term air pollution and the risk of getting cardiovascular diseases, there is a lack of evidence based on causal distributed lag modeling. METHODS: Inverse probability weighting (ipw) propensity score models along with conditional logistic outcome regression models based on a case-crossover study design were applied to get the causal unconstrained distributed (lag0-lag5) as well as cumulative lag effect of short-term exposure to PM2.5/Ozone on hospital admissions of acute myocardial infarction (AMI), congestive heart failure (CHF) and ischemic stroke (IS) among New England Medicare participants during 2000-2012. Effect modification by gender, race, secondary diagnosis of Chronic Obstructive Pulmonary Diseases (COPD) and Diabetes (DM) was explored. RESULTS: Each 10 µg/m3 increase in lag0-lag5 cumulative PM2.5 exposure was associated with an increase of 4.3% (95% confidence interval: 2.2%, 6.4%, percentage change) in AMI hospital admission rate, an increase of 3.9% (2.4%, 5.5%) in CHF rate and an increase of 2.6% (0.4%, 4.7%) in IS rate. A weakened lagging effect of PM2.5 from lag0 to lag5 could be observed. No cumulative short-term effect of ozone on CVD was found. People with secondary diagnosis of COPD, diabetes, female gender and black race are sensitive population. CONCLUSIONS: Based on our causal distributed lag modeling, we found that short-term exposure to an increased ambient PM2.5 level had the potential to induce higher risk of CVD hospitalization in a causal way. More attention should be paid to population of COPD, diabetes, female gender and black race.

Change in PM2.5 exposure and mortality among Medicare recipients: Combining a semi-randomized approach and inverse probability weights in a low exposure population.

The association between PM2.5 and mortality is well established; however, confounding by unmeasured factors is always an issue. In addition, prior studies do not tell us what the effect of a sudden change in exposure on mortality is. We consider the sub-population of Medicare enrollees who moved residence from one ZIP Code to another from 2000 to 2012. Because the choice of new ZIP Code is unlikely to be related with any confounders, restricting to the population of movers allows us to have a study design that incorporates randomization of exposure. Over 10 million Medicare participants moved. We calculated change in exposure by subtracting the annual exposure at original ZIP Code from exposure at the new ZIP Code using a validated model. We used Cox proportional hazards models stratified on original ZIP Code with inverse probability weights (IPW) to control for individual and ecological confounders at the new ZIP Code. The distribution of covariates appeared to be randomized by change in exposure at the new locations as standardized differences were mostly near zero. Randomization of measured covariates suggests unmeasured covariates may be randomized also. Using IPW, per 10 µg/m3 increase in PM2.5, the hazard ratio was 1.21 (95% confidence interval [CI] = 1.20, 1.22] among whites and 1.12 (95% CI = 1.08, 1.15) among blacks. Hazard ratios increased for whites and decreased for blacks when restricting to exposure levels below the current standard of 12 µg/m3. This study provides evidence of likely causal effects at concentrations below current limits of PM2.5.

The concentration-response between long-term PM2.5 exposure and mortality; A meta-regression approach.

BACKGROUND: Long-term exposure to ambient fine particulate matter (≤ 2.5 µg/m3 in aerodynamic diameter; PM2.5) is significantly associated with increased risk of premature mortality. Our goal was to provide an updated meta-analysis of all-cause and cause-specific mortality associated with exposure to PM2.5 and to better estimate the risk of death as a function of air pollution levels. METHODS: We systematically searched all published cohort studies examining the association between long term exposure to PM2.5 and mortality. We applied multivariate linear random effects meta-analysis with random effects for cohort, and study within cohort. Meta-regression techniques were used to test whether study population or analytic characteristics modify the PM2.5 -mortality association and to estimate the shape of the concentration-response curve. RESULTS: A total of 53 studies that provided 135 estimates of the quantitative association between the risk of mortality and exposure to PM2.5 were included in the meta-analysis. There were 39 studies from North America, 8 from Europe, and 6 from Asia. Since 2015, 17 studies of long-term air pollution exposure have been published, covering, wider geographic areas with a wider range of mean exposures (e.g. <12 or > 20 µg/m3). A penalized spline showed the slope decreased at higher concentrations but appeared to level off. We found that the inverse transform of average PM2.5 well approximated that spline and provided a parametric estimate that fit better than a linear or logarithmic term for average PM2.5. In addition, we found that studies using space time exposure models or fixed monitors at Zip-code scale (as compared to land use regression method), or additionally controlling for area level socio-economic status, or with mean exposure less than 10 µg/m3 were associated with higher mortality effect estimates. CONCLUSIONS: This meta-analysis provides strong evidence for the adverse effect of PM2.5 on mortality, that studies with poorer exposure have lower effect size estimates, that more control for SES increases effect size estimates, and that significant effects are seen below 10 µg/m3. The concentration -response function produced here can be further applied in the global health risk assessment of air particulate matter.

Maternal residential air pollution and placental imprinted gene expression.

BACKGROUND: Maternal exposure to air pollution is associated with reduced fetal growth, but its relationship with expression of placental imprinted genes (important regulators of fetal growth) has not yet been studied. OBJECTIVES: To examine relationships between maternal residential air pollution and expression of placental imprinted genes in the Rhode Island Child Health Study (RICHS). METHODS: Women-infant pairs were enrolled following delivery between 2009 and 2013. We geocoded maternal residential addresses at delivery, estimated daily levels of fine particulate matter (PM2.5; n=355) and black carbon (BC; n=336) using spatial-temporal models, and estimated residential distance to nearest major roadway (n=355). Using linear regression models we investigated the associations between each exposure metric and expression of nine candidate genes previously associated with infant birthweight in RICHS, with secondary analyses of a panel of 108 imprinted genes expressed in the placenta. We also explored effect measure modification by infant sex. RESULTS: PM2.5 and BC were associated with altered expression for seven and one candidate genes, respectively, previously linked with birthweight in this cohort. Adjusting for multiple comparisons, we found that PM2.5 and BC were associated with changes in expression of 41 and 12 of 108 placental imprinted genes, respectively. Infant sex modified the association between PM2.5 and expression of CHD7 and between proximity to major roadways and expression of ZDBF2. CONCLUSIONS: We found that maternal exposure to residential PM2.5 and BC was associated with changes in placental imprinted gene expression, which suggests a plausible line of investigation of how air pollution affects fetal growth and development.

Maternal ambient air pollution, preterm birth and markers of fetal growth in Rhode Island: results of a hospital-based linkage study.

BACKGROUND: Maternal exposure to ambient air pollution has been associated with higher risk of preterm birth and reduced fetal growth, but heterogeneity among prior studies suggests that additional studies are needed in diverse populations and settings. We examined the associations between maternal ambient air pollution levels, risk of preterm birth and markers of fetal growth in an urban population with relatively low exposure to air pollution. METHODS: We linked 61 640 mother-infant pairs who delivered at a single hospital in Providence, Rhode Island, from 2002 to 2012 to birth certificate and hospital discharge data. We used spatial-temporal models and stationary monitors to estimate exposure to fine particulate matter (PM2.5) and black carbon (BC) during pregnancy. Using generalised linear models, we evaluated the association between pollutant levels, risk of preterm birth and markers of fetal growth. RESULTS: In adjusted models, an IQR (2.5 µg/m3) increase in pregnancy-average PM2.5 was associated with ORs of preterm birth of 1.04 (95% CI 0.94 to 1.15) and 0.86 (0.76 to 0.98) when considering modelled and monitored PM2.5, respectively. An IQR increase in modelled and monitored PM2.5 was associated with a 12.1 g (95% CI -24.2 to -0.1) and 15.9 g (95% CI -31.6 to -0.3) lower birth weight. Results for BC were highly sensitive to choice of exposure metric. CONCLUSION: In a population with relatively low exposures to ambient air pollutants, PM2.5 was associated with reduced birth weight but not with risk of preterm birth.