Progress in the impact of polluted meteorological conditions on the incidence of asthma

Lagging effects and prediction of pollutants and their interaction modifiers on influenza in northeastern China

BACKGROUND

Previous studies have typically explored the daily lagged relations between influenza and meteorology, but few have explored seasonally the monthly lagged relationship, interaction and multiple prediction between influenza and pollution. Our specific objectives are to evaluate the lagged and interaction effects of pollution factors and construct models for estimating influenza incidence in a hierarchical manner.

METHODS

Our researchers collect influenza case data from 2005 to 2018 with meteorological and contaminative factors in Northeast China. We develop a generalized additive model with up to 6 months of maximum lag to analyze the impact of pollution factors on influenza cases and their interaction effects. We employ LASSO regression to identify the most significant environmental factors and conduct multiple complex regression analysis. In addition, quantile regression is taken to model the relation between influenza morbidity and specific percentiles (or quantiles) of meteorological factors.

RESULTS

The influenza epidemic in Northeast China has shown an upward trend year by year. The excessive incidence of influenza in Northeast China may be attributed to the suspected primary air pollutant, NO2, which has been observed to have overall low levels during January, March, and June. The Age 15-24 group shows an increase in the relative risk of influenza with an increase in PM2.5 concentration, with a lag of 0-6 months (ERR 1.08, 95% CI 0.10-2.07). In the quantitative analysis of the interaction model, PM10 at the level of 100-120 μg/m3, PM2.5 at the level of 60-80 μg/m3, and NO2 at the level of 60 μg/m3 or more have the greatest effect on the onset of influenza. The GPR model behaves better among prediction models.

CONCLUSIONS

Exposure to the air pollutant NO2 is associated with an increased risk of influenza with a cumulative lag effect. Prioritizing winter and spring pollution monitoring and influenza prediction modeling should be our focus.

Maternal apparent temperature during pregnancy on the risk of offspring asthma and wheezing: effect, critical window, and modifiers

The objective of this study was to explore the impact of maternal AT during pregnancy on childhood asthma and wheezing, as well as the potential effect modifiers in this association. A cross-sectional study was implemented from December 2018 to March 2019 in Jinan to investigate the prevalence of childhood asthma and wheezing among aged 18 months to 3 years. Then, we conducted a case-control study based on population to explore the association between prenatal different AT exposure levels and childhood asthma and wheezing. The association was assessed by generalized additive models and logistic regression models, and stratified analyses were performed to explore potential effect modifiers. A total of 12,384 vaccinated children participated in screening for asthma and wheezing, 236 cases were screened, as well as 1445 controls were randomized. After adjusting for the covariates, childhood asthma and wheezing were significantly associated with cold exposure in the first trimester, with OR 1.731 (95% CI: 1.117-2.628), and cold exposure and heat exposure in the third trimester, with ORs 1.610 (95% CI: 1.030-2.473) and 2.039 (95% CI: 1.343-3.048). In the third trimester, enhanced impacts were found among girls, children whose distance of residence was close to the nearest main traffic road, and children whose parents have asthma. The study indicates that exposure to extreme AT during the first and third trimesters could increase the risk of childhood asthma and wheezing.

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia

Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter 10 (PM10,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran's I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO2 (lag 2), SO2 (lag 1), PM10 (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R2 value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.

Relationship between biometeorological factors and the number of hospitalizations due to asthma

The incidence of asthma exacerbation depends on atmospheric conditions, including such meteorological factors as the ambient temperature, relative air humidity or concentration of atmospheric aerosols. An assessment of relations between the frequency of asthma exacerbation and environmental conditions was made according to the meteorological components, the biometeorological index UTCI (Universal Thermal Climate Index), as well as selected air quality parameters, including concentrations of PM₁₀ and PM_2.5. The study was conducted on the basis of a retrospective analysis of medical data collected at the Independent Public Hospital of Tuberculosis and Pulmonary Diseases in Olsztyn (Poland). Our analysis of patient data (from 1 January 2013 until 31 December 2017) showed a significant correlation between the number of asthma exacerbation and the UTCI value. More frequent asthma exacerbations are observed in patients aged over 65 years when air humidity increases. The UTCI values contained within class 5, describing thermoneutral conditions, correspond to an average frequency of asthma exacerbation. A decline in the UTCI value leads to a reduced number of asthma exacerbation, while a rise makes the cases of asthma exacerbations increase.

Conurbation, Urban, and Rural Living as Determinants of Allergies and Infectious Diseases: Royal College of General Practitioners Research and Surveillance Centre Annual Report 2016-2017

BACKGROUND

Living in a conurbation, urban, or rural environment is an important determinant of health. For example, conurbation and rural living is associated with increased respiratory and allergic conditions, whereas a farm or rural upbringing has been shown to be a protective factor against this.

OBJECTIVE

The objective of the study was to assess differences in general practice presentations of allergic and infectious disease in those exposed to conurbation or urban living compared with rural environments.

METHODS

The population was a nationally representative sample of 175 English general practices covering a population of over 1.6 million patients registered with sentinel network general practices. General practice presentation rates per 100,000 population were reported for allergic rhinitis, asthma, and infectious conditions grouped into upper and lower respiratory tract infections, urinary tract infection, and acute gastroenteritis by the UK Office for National Statistics urban-rural category. We used multivariate logistic regression adjusting for age, sex, ethnicity, deprivation, comorbidities, and smoking status, reporting odds ratios (ORs) with 95% CIs.

RESULTS

For allergic rhinitis, the OR was 1.13 (95% CI 1.04-1.23; P=.003) for urban and 1.29 (95% CI 1.19-1.41; P<.001) for conurbation compared with rural dwellers. Conurbation living was associated with a lower OR for both asthma (OR 0.70, 95% CI 0.67-0.73; P<.001) and lower respiratory tract infections (OR 0.94, 95% CI 0.90-0.98; P=.005). Compared with rural dwellers, the OR for upper respiratory tract infection was greater in urban (OR 1.06, 95% CI 1.03-1.08; P<.001) but no different in conurbation dwellers (OR 1.00, 95% CI 0.97-1.03; P=.93). Acute gastroenteritis followed the same pattern: the OR was 1.13 (95% CI 1.01-1.25; P=.03) for urban dwellers and 1.04 (95% CI 0.93-1.17; P=.46) for conurbation dwellers. The OR for urinary tract infection was lower for urban dwellers (OR 0.94, 95% CI 0.89-0.99; P=.02) but higher in conurbation dwellers (OR 1.06, 95% CI 1.00-1.13; P=.04).

CONCLUSIONS

Those living in conurbations or urban areas were more likely to consult a general practice for allergic rhinitis and upper respiratory tract infection. Both conurbation and rural living were associated with an increased risk of urinary tract infection. Living in rural areas was associated with an increased risk of asthma and lower respiratory tract infections. The data suggest that living environment may affect rates of consultations for certain conditions. Longitudinal analyses of these data would be useful in providing insights into important determinants.

Relationships between aeroallergen levels and hospital admissions for asthma in the Brussels-Capital Region: a daily time series analysis

BACKGROUND

Outdoor pollen grain and fungal spore concentrations have been associated with severe asthma exacerbations at the population level. The specific impact of each taxon and the concomitant effect of air pollution on these symptoms have, however, still to be better characterized. This study aimed to investigate the short-term associations between ambient concentrations of various aeroallergens and hospitalizations related to asthma in the Brussels-Capital Region (Belgium), an area recording especially high rates of admissions.

METHODS

Based on administrative records of asthma hospitalizations and regular monitoring of 11 tree/herbaceous pollen taxa and 2 fungal spore taxa, daily time series analyses covering the 2008-2013 period were performed. Effects up to 6 days after exposure were captured by combining quasi-Poisson regression with distributed lag models, adjusting for seasonal and long-term trends, day of the week, public holidays, mean temperature and relative humidity. Effect modification by age and air pollution (PM, NO₂, O₃) was tested.

RESULTS

A significant increase in asthma hospitalizations was observed for an interquartile range increase in grass (5.9%, 95% CI: 0.0, 12.0), birch (3.2%, 95% CI: 1.1, 5.3) and hornbeam (0.7%, 95% CI: 0.2, 1.3) pollen concentrations. For several taxa including grasses, an age modification effect was notable, the hospitalization risk tending to be higher in individuals younger than 60 years. Air pollutants impacted the relationships too: the risk appeared to be stronger for grass and birch pollen concentrations in case of high PM₁₀ and O₃ concentrations respectively.

CONCLUSIONS

These findings suggest that airborne grass, birch and hornbeam pollen are associated with severe asthma exacerbations in the Brussels region. These compounds appear to act in synergy with air pollution and to more specifically affect young and intermediate age groups. Most of these life-threatening events could theoretically be prevented with improved disease diagnosis/management and targeted communication actions.

Temperature drop and the risk of asthma: a systematic review and meta-analysis

The relationship between asthma and temperature changes remains controversial. The aim of this study was to investigate the association between temperature changes and the risk of asthma. A total of 26 studies (combined total number of subjects N > 26 million), covering 13 countries and Costa Rica, were identified by using a series of keywords in different combinations and searching the papers in PubMed, EMBSEA, Web of Science, MEDLINE, AIM, LILACS, and WPRIM before February 2016. Most of the papers were published in English. Random-effects meta-analyses were performed to evaluate the effect of temperature drop on risk of asthma. Several secondary analyses were also calculated based on stratification for different age, season, latitude, and region on risk of asthma. The odds ratio (OR) estimate between temperature drop and asthma was 1.05 (95% CI 1.02, 1.08) in the meta-analysis. For children, the overall OR was 1.09 (95% CI 1.03, 1.15). Dose-effect analyses showed stronger associations in asthma risk for each 1°1 °C decrement in short-term temperature (OR 1.055, 95% CI 1.00, 1.11). Further stratifications showed that winter (OR 1.03, 95% CI 1.01, 105) and low latitude (OR 1.72, 95% CI 1.23, 2.41) have a statistically significant association with the increased risk of asthma. Exposure of people to short-term temperature drop (per 1 °C decrement) was significantly associated with the risk of lower respiratory tract infections (LRTI) with asthma (OR 1.02, 95% CI 1.00, 1.04). Results suggest an adverse effect of temperature drop on asthma risk, especially in children and low-latitude areas. It may be opportune to consider the preventive actions against temperature drop, including simple face masks, to decrease the risk of asthma.