Air pollution influence on serum inflammatory interleukins: A prospective study in childhood-onset systemic lupus erythematous patients

Objective To assess the effect of individual exposure, in real-time, to traffic-related pollutants on serum interleukin levels of childhood-onset lupus erythematous systemic (c-SLE) patients. Methods A longitudinal and observational design was conducted in 12 repeated measures of serum samples and clinical evaluations (totaling 108 measurements) of c-SLE patients over 30 consecutive months. Real-time, individual exposure to fine particles (PM2.5) and nitrogen dioxide (NO2) was measured with portable monitors. Generalized estimating equation was used to evaluate the association between exposure to PM2.5 and NO2 and the following serum cytokine levels on the 7 days preceding clinical assessment and serum collection: MCP1, IL-6, IL-8, IL-10, IL-17, IFN-alpha, and TNF-alpha. Disease activity and other risk factors were also controlled. Results An interquartile range (IQR) increase in PM2.5 daily concentration was significantly associated with increased levels of TNF-alpha on the third, fourth, and seventh day after exposure; IL-10 on the third and fourth day after exposure; IL-17 on the third and seventh day after exposure; and INF-alpha on the third day after exposure ( p < 0.05). An IQR increase in 7-day moving average of PM2.5 was associated with a 6.2 pg/mL (95% CI: 0.5; 11.8; p = 0.04) increase in serum IFN-alpha level. An unexpected significant association was observed between an IQR increase in NO27-day cumulative concentration and a decrease of 1.6 pg/mL (95% CI: −2.6; −0.7; p < 0.001) in serum IL-17. Conclusion Real-time exposure to PM2.5 prospectively associated with increased serum TNF-alpha, INF-alpha, IL-10, and IL-17 levels in c-SLE patients.

Individual vulnerability to industrial robot adoption increases support for the radical right

The increasing success of populist and radical-right parties is one of the most remarkable developments in the politics of advanced democracies. We investigate the impact of industrial robot adoption on individual voting behavior in 13 western European countries between 1999 and 2015. We argue for the importance of the distributional consequences triggered by automation, which generates winners and losers also within a given geographic area. Analysis that exploits only cross-regional variation in the incidence of robot adoption might miss important facets of this process. In fact, patterns in individual indicators of economic distress and political dissatisfaction are masked in regional-level analysis, but can be clearly detected by exploiting individual-level variation. We argue that traditional measures of individual exposure to automation based on the current occupation of respondents are potentially contaminated by the consequences of automation itself, due to direct and indirect occupational displacement. We introduce a measure of individual exposure to automation that combines three elements: 1) estimates of occupational probabilities based on employment patterns prevailing in the preautomation historical labor market, 2) occupation-specific automatability scores, and 3) the pace of robot adoption in a given country and year. We find that individuals more exposed to automation tend to display higher support for the radical right. This result is robust to controlling for several other drivers of radical-right support identified by earlier literature: nativism, status threat, cultural traditionalism, and globalization. We also find evidence of significant interplay between automation and these other drivers.

Individual exposure to ambient PM2.5 and hospital admissions for COPD in 110 hospitals: a case-crossover study in Guangzhou, China

Few studies have evaluated the short-term association between hospital admissions and individual exposure to ambient particulate matter (PM2.5). Particularly, no studies focused on hospital admissions for chronic obstructive pulmonary disease (COPD) at the individual level. We assessed the short-term effects of PM2.5 on hospitalization admissions for COPD in Guangzhou, China, during 2014–2015, based on satellite-derived estimates of ambient PM2.5 concentrations at a 1-km resolution near the residential address as individual-level exposure for each patient. Around 40,002 patients with COPD admitted to 110 hospitals were included in this study. A time-stratified case-crossover design with conditional logistic regression models was applied to assess the effects of PM2.5 based on a 1-km grid data of aerosol optical depth provided by the National Aeronautics and Space Administration on hospital admissions for COPD. Further, we performed stratified analyses by individual demographic characteristics and season of hospital admission. Around 10 μg/m3 increase in individual-level PM2.5 was associated with an increase of 1.6% (95% confidence interval [CI]: 0.6%, 2.7%) in hospitalization for COPD at a lag of 0–5 days. The impact of PM2.5 on hospitalization for COPD was greater significantly in males and patients admitted in summer. Our study strengthened the evidence for the adverse effect of PM2.5 based on satellite-based individual-level exposure data.

Individual Exposure to Ambient PM2.5 and Hospital Admissions for COPD in 110 Hospitals: A Case-Crossover Study in Guangzhou, China

Few studies have evaluated the short-term association between hospital admissions and individual exposure to ambient particulate matter (PM2.5). Particularly, no studies focused on hospital admissions for chronic obstructive pulmonary disease (COPD) at individual level. We assessed the short-term effects of PM2.5 on hospitalization admissions for COPD in Guangzhou, China, during 2014–2015, based on satellite-derived estimates of ambient PM2.5 concentrations at 1-km resolution near the residential address as individual-level exposure for each patient. 40,002 patients with COPD admitted to 110 hospitals were included in this study. A time-stratified case-crossover design with conditional logistic regression models was applied to assess the effects of PM2.5 based on 1-km grid data of aerosol optical depth provided by National Aeronautics and Space Administration on hospital admissions for COPD. Further, we performed stratified analyses by individual demographic characteristics and season of hospital admission. 10 µg/m3 increase in individual-level PM2.5 was associated with an increase of 1.6% (95% confidence interval [CI]: 0.6%, 2.7%) in hospitalization for COPD at lag of 0–5 days. The impact of PM2.5 on hospitalization for COPD was greater significantly in male and patients admitted in summer and accordingly the impacts may be exacerbated in the context of global warming. Our study strengthened the evidence for the adverse effect of PM2.5 based on satellite-based individual-level exposure data.

Do Individuals’ Activity Structures Influence Their PM2.5 Exposure Levels? Evidence from Human Trajectory Data in Wuhan City

Severe air pollution has become a major risk to human health from a global environmental perspective. It has been recognized that human mobility is an essential component in individual exposure assessment. Activity structure reflects the characteristics of human mobility. Thus, a better understanding of the relationship between human activity structure and individual exposure level is of crucial relevance. This study examines this relationship using a large cell-phone GPS dataset in Wuhan, China. The results indicate that there is a strong linear relationship between people’s activity structures and exposures to PM2.5. Inter-group comparisons based on the four activity structure groups obtained with K-means clustering found that groups with different activity structures do experience different levels of PM2.5 exposure. Furthermore, differences in detailed characteristics of activity structure were also found at different exposure levels at the intra-group level. These results show that people’s activity structures do influence their exposure levels. The paper provides a new perspective for understanding individual exposure through human activity structure, which helps move the perspective of research on individual exposure from the semantic of physical location to the semantic of human activity pattern.