Structural equation modeling of the inflammatory response to traffic air pollution

A systematic review and meta-analysis of the stability of peripheral immune markers in healthy adults

Peripheral immune markers are widely used to predict risk for inflammatory disease. However, whether single assessments of inflammatory biomarkers represent stable individual differences remains unclear. We reviewed 50 studies (N = 48,674; 57 % male; mean age 54 (range 13-79) years) that assessed markers of inflammation on >1 occasion, with time between measures ranging from 24 h to 7+ years. Separate random effects meta-analyses were conducted for each inflammatory marker and time interval. Markers that had broad coverage across most time intervals included C-reactive protein (CRP; k = 37), interleukin (IL)-6 (k = 22), TNF-α (k = 10), and fibrinogen (Fg; k = 9). For CRP, IL-6, and TNF-α, stability estimates generally decreased with time, with strong to moderate stability over intervals <6 months (r's = 0.80-0.61), modest to moderate stability over 6 months - 3 years (r's = 0.60-0.51), and low stability for >3 years (r's = 0.39-0.30). Estimates were less reliable for Fg for time intervals ≤ 3 years although they generally followed the same pattern; more reliable findings suggested greater stability for Fg than other markers for intervals >3 years (r = 0.53). These findings suggest that single measures of inflammatory biomarkers may be an adequate index of stable individual differences in the short term (<6 months), with repeated measures of inflammatory biomarkers recommended over intervals ≥ 6 months to 3 years, and absolutely necessary over intervals >3 years to reliably identify stable individual differences in health risk. These findings are consistent with stability estimates and clinical recommendations for repeated measurement of other cardiovascular measures of risk (e.g., blood lipids, blood pressure).

Maternal air pollution exposure during the first trimester of pregnancy and markers of inflammation and endothelial dysfunction

BACKGROUND

Maternal exposure to air pollutants has been associated with pregnancy complications and adverse birth outcomes. Endothelial dysfunction, an imbalance in vascular function, during pregnancy is considered a key element in the development of pre-eclampsia. Environmental exposure to particulate matter (PM) during the first trimester of pregnancy might increase maternal inflammatory status thus affecting fetal growth, possibly leading to preterm delivery.

OBJECTIVES

The purpose of the study was to evaluate possible effects of PM₁₀ and PM_2.5 exposure on fetal growth in healthy pregnant women at the end of the first trimester of pregnancy by investigating the relationship between circulating biomarkers of inflammation (IL-6), early systemic prothrombotic effects (CRP, plasma fibrinogen, PAI-1) and endothelial dysfunction (sICAM-1 and sVCAM-1).

METHODS

295 pregnant women were recruited. Individual PM exposure was assigned to each subject by calculating the mean of PM₁₀ and PM_2.5 daily values observed during the 30, 60, and 90 days preceding enrolment (long-term) and single lag days back to fourteen days (short-term), and circulating plasma biomarkers were determined.

RESULTS

For long-term exposure, we observed an increase in sVCAM-1 and a decrease of PAI-1 levels for each 10 μg/m³ increase in PM₁₀ concentration. Decreases in IL-6 and CRP levels were associated with each 10 μg/m³ PM_2.5 increase. For short-term exposure, the levels of sVCAM-1 and PAI-1 were found to be associated with PM₁₀ exposure, whereas fibrinogen levels were associated with PM_2.5 exposure. Maternal plasmatic fibrinogen levels were negatively associated with the crown-rump length (p-value = 0.008).

DISCUSSION

The present study showed that both long- and short-term exposures to PM are associated with changes in circulating levels of biomarkers in pregnant women reflecting systemic inflammation and endothelial dysfunction/activation. Our findings support the hypothesis that inflammation and endothelial dysfunction might have a central role in modulating the detrimental effects of air pollution exposure during pregnancy.

Maternal exposure to black carbon and nitrogen dioxide during pregnancy and birth weight: Using machine-learning methods to achieve balance in inverse-probability weights

BACKGROUND

Low birth weight is associated with increased risks of health problems in infancy and later life. Among the epidemiological analyses suggesting an association between air pollution and birth weight, few have estimated the effects of black carbon (BC) or together with nitrogen dioxide (NO₂), and even fewer studies have used causal modelling.

METHODS

We examined 1,119,011 birth records between 2001/01/01 and 2015/12/31 from the Massachusetts Birth Registry to investigate causal associations between prenatal exposure to BC and NO₂ and birth weight. We calculated mean residential BC and NO₂ exposures 0-30, and 31-280 days prior to birth from validated spatial-temporal models. We fit generalized propensity score models with gradient boosting tuned by a new algorithm to achieve covariate balance, then fit marginal structural models with stabilized inverse-probability weights.

RESULTS

Throughout pregnancy, the average birth weight would drop by 17.0 g (95% CI: 15.4, 18.6) for an IQR increase of 0.14 μg/m³ in BC and would independently drop by 19.9 g (95% CI: 18.6, 21.3) for an IQR increase of 9.8 ppb in NO₂. Most of the negative effects of BC on birth weight are from 0 to 30 days before the delivery date. The estimated odds ratio of low birth weight for every IQR increase during the entire pregnancy was 1.131 (95% CI: 1.106, 1.156) for BC and 1.082 (95% CI: 1.062, 1.103) for NO₂.

CONCLUSIONS

We found that prenatal exposures to both BC and NO₂ were associated with lower birth weight.

The Role of Mobility and Sanitary Measures on the Delay of Community Transmission of COVID-19 in Costa Rica

The aim of this paper is to infer the effects that change on human mobility had on the transmission dynamics during the first four months of the SARS-CoV-2 pandemic in Costa Rica, which could have played a role in delaying community transmission in the country. First, by using parametric and non-parametric change-point detection techniques, we were able to identify two different periods when the trend of daily new cases significantly changed. Second, we explored the association of these changes with data on population mobility. This also allowed us to estimate the lag between changes in human mobility and rates of daily new cases. The information was then used to establish an association between changes in population mobility and the sanitary measures adopted during the study period. Results showed that during the initial two months of the pandemic in Costa Rica, the implementation of sanitary measures and their impact on reducing human mobility translated to a mean reduction of 54% in the number of daily cases from the projected number, delaying community transmission.

A cross-disciplinary evaluation of evidence for multipollutant effects on cardiovascular disease

BACKGROUND

The current single-pollutant approach to regulating ambient air pollutants is effective at protecting public health, but efficiencies may be gained by addressing issues in a multipollutant context since multiple pollutants often have common sources and individuals are exposed to more than one pollutant at a time.

OBJECTIVE

We performed a cross-disciplinary review of the effects of multipollutant exposures on cardiovascular effects.

METHODS

A broad literature search for references including at least two criteria air pollutants (particulate matter [PM], ozone [O₃], oxides of nitrogen, sulfur oxides, carbon monoxide) was conducted. References were culled based on scientific discipline then searched for terms related to cardiovascular disease. Most multipollutant epidemiologic and experimental (i.e., controlled human exposure, animal toxicology) studies examined PM and O₃ together.

DISCUSSION

Epidemiologic and experimental studies provide some evidence for O₃ concentration modifying the effect of PM, although PM did not modify O₃ risk estimates. Experimental studies of combined exposure to PM and O₃ provided evidence for additivity, synergism, and/or antagonism depending on the specific health endpoint. Evidence for other pollutant pairs was more limited.

CONCLUSIONS

Overall, the evidence for multipollutant effects was often heterogeneous, and the limited number of studies inhibited making a conclusion about the nature of the relationship between pollutant combinations and cardiovascular disease.

Using Structural Equation Modeling to Assess the Links between Tobacco Smoke Exposure, Volatile Organic Compounds, and Respiratory Function for Adolescents Aged 6 to 18 in the United States

Asthma is an inflammatory airway disease that affects 22 million Americans in the United States. Research has found associations between impaired respiratory function, including asthma and increased symptoms among asthmatics, and common indoor air pollutants, including tobacco smoke exposure and volatile organic compounds (VOCs). However, findings linking VOC exposure and asthma are inconsistent and studies are of mixed quality due to design limitations, challenges measuring VOC exposure, small sample sizes, and suboptimal statistical methodologies. Because of the correlation between tobacco smoke exposure and VOCs, and associations between both tobacco smoke and VOCs with respiratory function, it is crucial that statistical methodology employed to assess links between respiratory function and individual air pollutants control for these complex relationships. This research uses Structural Equation Modeling (SEM) to assess the relationships between respiratory function, tobacco smoke exposure, and VOC exposure among a nationally-representative sample of adolescents. SEM allows for multiple outcome variables, the inclusion of both observed and latent variables, and controls the effects of confounding and correlated variables, which is critically important and is lacking in earlier studies when estimating the effects of correlated air pollutants on respiratory function. We find evidence of associations between respiratory function and some types of VOCs, even when controlling for the effects of tobacco smoke exposure and additional covariates. Furthermore, we find that poverty has an indirect effect on respiratory function through its relationships with tobacco smoke exposure and some types of VOCs. This analysis demonstrates how SEM is a robust analytic tool for assessing associations between respiratory function and multiple exposures to pollutants.

Factors Associated with Asthma ED Visit Rates among Medicaid-enrolled Children: A Structural Equation Modeling Approach

BACKGROUND

Asthma is one of the leading causes of emergency department visits and school absenteeism among school-aged children in the United States, but there is significant local-area variation in emergency department visit rates, as well as significant differences across racial-ethnic groups.

ANALYSIS

We first calculated emergency department (ED) visit rates among Medicaid-enrolled children age 5-12 with asthma using a multi-state dataset. We then performed exploratory factor analysis using over 226 variables to assess whether they clustered around three county-level conceptual factors (socioeconomic status, healthcare capacity, and air quality) thought to be associated with variation in asthma ED visit rates. Measured variables (including ED visit rate as the outcome of interest) were then standardized and tested in a simple conceptual model through confirmatory factor analysis.

RESULTS

County-level (contextual) variables did cluster around factors declared a priori in the conceptual model. Structural equation models connecting the ED visit rates to socioeconomic status, air quality, and healthcare system professional capacity factors (consistent with our conceptual framework) converged on a solution and achieved a reasonable goodness of fit on confirmatory factor analysis.

CONCLUSION

Confirmatory factor analysis offers an approach for quantitatively testing conceptual models of local-area variation and racial disparities in asthma-related emergency department use.

The cardiopulmonary effects of ambient air pollution and mechanistic pathways: a comparative hierarchical pathway analysis

Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2-3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system.

Association between In Utero arsenic exposure, placental gene expression, and infant birth weight: a US birth cohort study

BACKGROUND

Epidemiologic studies and animal models suggest that in utero arsenic exposure affects fetal health, with a negative association between maternal arsenic ingestion and infant birth weight often observed. However, the molecular mechanisms for this association remain elusive. In the present study, we aimed to increase our understanding of the impact of low-dose arsenic exposure on fetal health by identifying possible arsenic-associated fetal tissue biomarkers in a cohort of pregnant women exposed to arsenic at low levels.

METHODS

Arsenic concentrations were determined from the urine samples of a cohort of 133 pregnant women from New Hampshire. Placental tissue samples collected from enrollees were homogenized and profiled for gene expression across a panel of candidate genes, including known arsenic regulated targets and genes involved in arsenic transport, metabolism, or disease susceptibility. Multivariable adjusted linear regression models were used to examine the relationship of candidate gene expression with arsenic exposure or with birth weight of the baby.

RESULTS

Placental expression of the arsenic transporter AQP9 was positively associated with maternal urinary arsenic levels during pregnancy (coefficient estimate: 0.25; 95% confidence interval: 0.05 - 0.45). Placental expression of AQP9 related to expression of the phospholipase ENPP2 which was positively associated with infant birth weight (coefficient estimate: 0.28; 95% CI: 0.09 - 0.47). A structural equation model indicated that these genes may mediate arsenic's effect on infant birth weight (coefficient estimate: -0.009; 95% confidence interval: -0.032 - -0.001; 10,000 replications for bootstrapping).

CONCLUSIONS

We identified the expression of AQP9 as a potential fetal biomarker for arsenic exposure. Further, we identified a positive association between the placental expression of phospholipase ENPP2 and infant birth weight. These findings suggest a path by which arsenic may affect birth outcomes.