Long-term exposure to ambient fine particulate matter and carotid intima media thickness at bilateral, left and right in adults from Mexico City: Results from GEA study

BACKGROUND

PM2.5 exposure has been associated with intima-media thickness (cIMT) increase. However, very few studies distinguished between left and right cIMT in relation to PM2.5 exposure.

AIM

To evaluate associations between chronic exposure to PM2.5 and cIMT at bilateral, left, and right in adults from Mexico City.

METHODS

This study comprised 913 participants from the control group, participants without personal or family history of cardiovascular disease, of the Genetics of Atherosclerosis Disease Mexican study (GEA acronym in Spanish), recruited at the Instituto Nacional de Cardiología Ignacio Chávez from June 2008 to January 2013. To assess the associations between chronic exposure to PM2.5 (per 5 μg/m3 increase) at different lag years (1-4 years) and cIMT (bilateral, left, and right) we applied distributed lag non-linear models (DLNMs).

RESULTS

The median and interquartile range for cIMT at bilateral, left, and right, were 630 (555, 735), 640 (550, 750), and 620 (530, 720) μm, respectively. Annual average PM2.5 exposure was 26.64 μg/m3, with median and IQR, of 24.46 (23.5-25.46) μg/m3. Results from DLNMs adjusted for age, sex, body mass index, low-density lipoproteins, and glucose, showed that PM2.5 exposure for year 1 and 2, were positively and significantly associated with right-cIMT [6.99% (95% CI: 3.67; 10.42) and 2.98% (0.03; 6.01), respectively]. Negative associations were observed for PM2.5 at year 3 and 4 and right-cIMT; however only year 3 was statistically significant [-2.83% (95% CI: 5.12; -0.50)]. Left-cIMT was not associated with PM2.5 exposure at any lag year. The increase in bilateral cIMT followed a similar pattern as that observed for right-cIMT, but with lower estimates.

CONCLUSIONS

Our results suggest different susceptibility between left and right cIMT associated with PM2.5 exposure highlighting the need of measuring both, left and right cIMT, regarding ambient air pollution in epidemiological studies.

Exposure to outdoor artificial light at night increases risk and burden of metabolic disease in Ningxia, China

Nearly a quarter of the world's land has already been polluted by artificial light. And numerous human and animal studies have corroborated that light at night can disrupt metabolism. Therefore, we aimed to estimate the association between outdoor artificial light at night (ALAN) and the presence of metabolic disease. Daily hospital admission cases from Ningxia, China, between 2014 and 2020 were included. Cumulative associations between outdoor ALAN and metabolic disease were estimated using logistic regression and distributed lagged non-linear models (DLNM) with lags of 0-30 days and stratified analysis by age groups and gender. The results suggest that 26.80% of metabolic disease cases in Ningxia can be attributed to outdoor ALAN and that men, especially in men aged 46-59 years, are more susceptible to lighting. Policymakers need to develop measures and facilities in corresponding areas, such as universal access to indoor blackout curtains. In particular, men should be urged to minimize going outside at night and to develop protective measures specifically for men.

The short-term effects of air pollution exposure on preterm births in Chongqing, China: 2015-2020

Accumulating evidence suggested that the risk of preterm births (PTBs) following prenatal exposure to air pollution was inconclusive. The aim of this study is to investigate the relationship between air pollution exposure in the days before delivery and PTB and assess the threshold effect of short-term prenatal exposure to air pollution on PTB. This study collected data including meteorological factors, air pollutants, and information in Birth Certificate System from 9 districts during 2015-2020 in Chongqing, China. Generalized additive models (GAMs) with the distributed lag non-linear models were conducted to assess the acute impact of air pollutants on the daily counts of PTB, after controlling for potential confounding factors. We observed that PM2.5 was related to increased occurrence of PTB on lag 0-3 and lag 10-21 days, with the strongest on the first day (RR = 1.017, 95%CI: 1.000-1.034) and then decreasing. The thresholds of PM2.5 for lag 1-7 and 1-30 days were 100 μg/m3 and 50 μg/m3, respectively. The lag effect of PM10 on PTB was very similar to that of PM2.5. In addition, the lagged and cumulative exposure of SO2 and NO2 was also associated with the increased risk of PTB. The lag relative risk and cumulative relative risk of CO exposure were the strongest, with a maximum RR at lag 0 (RR = 1.044, 95%CI: 1.018, 1.069). Importantly, the exposure-response curve of CO showed that RR increased rapidly when the concentration exceeded 1000 μg/m3. This study indicated significant associations between air pollution and PTB. The relative risk decreases with day lag, while the cumulative effect increases. Thus, pregnant women should understand the risk of air pollution and try to avoid high concentration exposure.

Temporal variation of the temperature-mortality association in Spain: a nationwide analysis

BACKGROUND

Although adaptation to continuously rising ambient temperatures is an emerging topic and has been widely studied at a global scale, detailed analysis of the joint indicators for long-term adaptation in Spain are scarce. This study aims to explore temporal variations of the minimum mortality temperature and mortality burden from heat and cold between 1979 and 2018.

METHODS

We collected individual all-cause mortality and climate reanalysis data for 4 decades at a daily time step. To estimate the temperature-mortality association for each decade, we fitted a quasi-Poisson time-series regression model using a distributed lag non-linear model with 21 days of lag, controlling for trends and day of the week. We also calculated attributable mortality fractions by age and sex for heat and cold, defined as temperatures above and below the optimum temperature, which corresponds to the minimum mortality in each period.

RESULTS

We analysed over 14 million deaths registered in Spain between 1979 and 2018. The optimum temperature estimated at a nationwide scale declined from 21 °C in 1979-1988 to 16 °C in 1999-2008, and raised to 18 °C in 2009-2018. The mortality burden from moderate cold showed a 3-fold reduction down to 2.4% in 2009-2018. Since 1988-1999, the mortality risk attributable to moderate (extreme) heat reduced from 0.9% (0.8%) to 0.6% (0.5%). The mortality risk due to heat in women was almost 2 times larger than in men, and did not decrease over time.

CONCLUSION

Despite the progressively warmer temperatures in Spain, we observed a persistent flattening of the exposure-response curves, which marked an expansion of the uncertainty range of the optimal temperatures. Adaptation has been produced to some extent in a non-uniform manner with a substantial decrease in cold-related mortality, while for heat it became more apparent in the most recent decade only.

Climate change and air pollution: Translating their interplay into present and future mortality risk for Rome and Milan municipalities

Heat and cold temperatures associated with exposure to poor air quality lead to increased mortality. Using a generalized linear model with Poisson regression for overdispersion, this study quantifies the natural-caused mortality burden attributable to heat/cold temperatures and PM₁₀ and O₃ air pollutants in Rome and Milan, the two most populated Italian cities. We calculate local-specific mortality relative risks (RRs) for the period 2004-2015 considering the overall population and the most vulnerable age category (≥85 years). Combining a regional climate model with a chemistry-transport model under future climate and air pollution scenarios (RCP2.6 and RCP8.5), we then project mortality to 2050. Results show that for historical mortality the burden is much larger for cold than for warm temperatures. RR peaks during wintertime in Milan and summertime in Rome, highlighting the relevance of accounting for the effects of air pollution besides that of climate, in particular PM₁₀ for Milan and O₃ for Rome. Overall, Milan reports higher RRs while, in both cities, the elderly appear more susceptible to heat/cold and air pollution events than the average population. Two counterbalancing effects shape mortality in the future: an increase associated with higher and more frequent warmer daily temperatures - especially in the case of climate inaction - and a decrease due to declining cold-mortality burden. The outcomes highlight the urgent need to adopt more stringent and integrated climate and air quality policies to reduce the temperature and air pollution combined effects on health.

Outdoor ambient temperatures and occupational injuries and illnesses: Are there risk differences in various regions within a city?

Increased risk of occupational injuries and illnesses (OI) is associated with hot ambient temperatures. However, the existing evidence of risk estimation is limited to large regions at the city or provincial scales. For effective and localized occupational health risk management, spatio-temporal analysis should be carried out at the intra-city level to identify high-risk areas within cities. This study examined the exposure-response relationship between ambient temperatures and OI at the intra-city scale in Greater Adelaide, Australia. Vulnerable groups of workers, in terms of workers' characteristics, the nature of their work, and workplace characteristics were identified. Further, the projected risk of OI was quantified in various climate change scenarios. The temperature-OI association was estimated using a time-series study design combined with Distributed Lag Non-linear Models. Daily workers' compensation claims (2005-2018) were merged with 5 km gridded meteorological data of maximum temperature (°C) at Statistical Area Level 3 in Greater Adelaide. Region-wise subgroup analyses were conducted to identify vulnerable groups of workers. Future projections (2006-2100) were conducted using downscaled climate projections and the risk was quantified using log-linear extrapolation. The analyses were performed in R 4.1.0. The overall OI risk was 16.7% (95%CI: 10.8-23.0) at moderate heat (90th percentile) and increased to 25.0% (95%CI: 16.4-34.2) at extreme heat (99th percentile). Northern Adelaide had a higher risk of OI for all types of workers at moderate heat, while western regions had a high risk for indoor industries. Southern and eastern regions had a higher OI risk for males, older workers, and outdoor industries at extreme heat. The projected risk of OI is estimated to increase from 20.8% (95%CI: -0.2-46.3) in 2010s to 22.9% (95%CI: -8.0-64.1) by 2050s. Spatio-temporal risk assessment at the intra-city scale can help us identify high-risk areas, where targeted interventions can be efficiently employed to reduce the socio-economic burden of OI.

A time series analysis of the short-term association between climatic variables and acute respiratory infections in Singapore

BACKGROUND

Acute respiratory infections (ARIs) are among the most common human illnesses globally. Previous studies that examined the associations between climate variability and ARIs or ARI pathogens have reported inconsistent findings. Few studies have been conducted in Southeast Asia to date, and the impact of climatic factors are not well-understood. This study aimed to investigate the short-term associations between climate variability and ARIs in Singapore.

METHODS

We obtained reports of ARIs from all government primary healthcare services from 2005 to 2019 and analysed their dependence on mean ambient temperature, minimum temperature and maximum temperature using the distributed lag non-linear framework. Separate negative binomial regression models were used to estimate the association between each temperature (mean, minimum, maximum temperature) and ARIs, adjusted for seasonality and long-term trend, rainfall, relative humidity, public holidays and autocorrelations. For temperature variables and relative humidity we reported cumulative relative risks (RRs) at 10th and 90th percentiles compared to the reference value (centered at their medians) with corresponding 95% confidence intervals (CIs). For rainfall we reported RRs at 50th and 90th percentiles compared to 0 mm with corresponding 95% CIs.

RESULTS

Statistically significant inverse S-curve shaped associations were observed between all three temperature variables (mean, minimum, maximum) and ARIs. A decrease of 1.1 °C from the median value of 27.8 °C to 26.7 °C (10th percentile) in the mean temperature was associated with a 6% increase (RR: 1.06, 95% CI: 1.03 to 1.09) in ARIs. ARIs also increased at 23.9 °C (10th percentile) compared to 24.9 °C of minimum temperature (RR: 1.11, 95% CI: 1.07 to 1.16). The effect of maximum temperature for the same comparison (30.5 °C vs 31.7 °C) was non-significant (RR: 1.02, 95% CI: 0.99 to 1.05). An increase in ambient temperature to 28.9 °C (90th percentile) was associated with an 18% decrease (RR: 0.82, 95% CI: 0.80 to 0.83) in ARIs. Similarly, ARIs decreased with the same increase to 90th percentile in minimum (RR: 0.84, 95% CI: 0.80 to 0.87) and maximum (RR: 0.89, 95% CI: 0.86 to 0.93) temperatures. Rainfall was inversely associated with ARIs and displayed similar shape in all three temperature models. Relative humidity, on the other hand, exhibited a U-shaped relationship with ARIs.

CONCLUSION

Our findings suggest that lower temperatures increase the risk of ARIs. Anticipated extreme weather events that reduce ambient temperature can be used to inform increased healthcare resource allocation for ARIs.

Contrasting patterns of temperature related mortality and hospitalization by cardiovascular and respiratory diseases in 52 Spanish cities

BACKGROUND

Climate change is a severe public health challenge. Understanding to what extent fatal and non-fatal consequences of specific diseases are associated with temperature may help to improve the effectiveness of preventive public health efforts. This study examines the effects of temperature on deaths and hospital admissions by cardiovascular and respiratory diseases, empathizing the difference between mortality and morbidity.

METHODS

Daily counts for mortality and hospital admissions by cardiovascular and respiratory diseases were collected for the 52 provincial capital cities in Spain, between 1990 and 2014. The association with temperature in each city was investigated by means of distributed lag non-linear models using quasi-Poisson regression. City-specific exposure-response curves were pooled by multivariate random-effects meta-analysis to obtain countrywide risk estimates of mortality and hospitalizations due to heat and cold, and attributable fractions were computed.

RESULTS

Heat and cold exposure were identified to be associated with increased risk of cardiovascular and respiratory mortality. Heat was not found to have an impact on hospital admissions. The estimated fraction of mortality attributable to cold was of greater magnitude in hospitalizations (17.5% for cardiovascular and 12.5% for respiratory diseases) compared to deaths (9% and 2.7%, respectively).

CONCLUSIONS

There were noteworthy differences between temperature-related mortality and hospital admissions regarding cardiovascular and respiratory diseases, hence reinforcing the convenience of cause-specific measures to prevent temperature-related deaths.

Effect of ambient air pollution and temperature on the risk of stillbirth: a distributed lag nonlinear time series analysis

OBJECTIVES

This study aimed to determine the effect of ambient air pollution and temperature on stillbirth in Tehran.

METHODS

In this time-series study, the effect of O3 (ppb), CO (ppm), NO2 (ppb), SO2 (ppb), PM2.5 (μg/m3), and minimum, maximum, and mean daily temperature (°C) on stillbirth was evaluated in Tehran, Iran between March 2015 and March 2018. Using a quasi-Poisson regression model in combination with a Distributed Lag Non-linear Models (DLNM), the Relative Risk (RR) was estimated through comparing the high temperature (99th, 95th, and 75th percentiles) and low temperature (1st, 5th, and 25th percentiles) with the median. The effect of air pollution was estimated for each 1-, 5-, or 10-unit increase in the concentration during lags (days) 0-21.

RESULTS

Among air pollutants, only a 5-ppm increase in the SO2 concentration in lag 0 increased the risk of stillbirth significantly (RR = 1.062; 1.002-1.125). The largest effect of heat was observed while comparing the 99th percentile of minimum daily temperature (26.9 °C) with the median temperature (13.2 °C), which was not statistically significant (RR = 1.25; 0.95-1.65). As for cold, a non-significant protective effect was observed while comparing the 1st percentile of maximum daily temperature (3.1 °C) with the median temperature (23.2 °C) (RR = 0.92; 0.72-1.19).

CONCLUSION

Each 5-ppm increase in the mean daily SO2 in lag 0 increased the risk of stillbirth by 6% while other air pollutants had no significant effects on stillbirth. In lags 0 and 1, the heat increased the risk of stillbirth while the cold had protective effects, which were not statistically significant.

Effect of climatic factors on the seasonal fluctuation of human brucellosis in Yulin, northern China

Background

Brucellosis is a serious public health problem primarily affecting livestock workers. The strong seasonality of the disease indicates that climatic factors may play important roles in the transmission of the disease. However, the associations between climatic variability and human brucellosis are still poorly understood.

Methods

Data for a 14-year series of human brucellosis cases and seven climatic factors were collected in Yulin City from 2005 to 2018, one of the most endemic areas in northern China. Using cross-correlation analysis, the Granger causality test, and a distributed lag non-linear model (DLNM), we assessed the quantitative relationships and exposure-lag-response effects between monthly climatic factors and human brucellosis.

Results

A total of 7103 cases of human brucellosis were reported from 2005 to 2018 in Yulin City with a distinct peak between April and July each year. Seasonal fluctuations in the transmission of human brucellosis were significantly affected by temperature, sunshine duration, and evaporation. The effects of climatic factors were non-linear over the 6-month period, and higher values of these factors usually increased disease incidence. The maximum separate relative risk (RR) was 1.36 (95% confidence interval [CI], 1.03–1.81) at a temperature of 17.4 °C, 1.12 (95% CI, 1.03–1.22) with 311 h of sunshine, and 1.18 (95% CI, 0.94–1.48) with 314 mm of evaporation. In addition, the effects of these three climatic factors were cumulative, with the highest RRs of 2.27 (95% CI, 1.09–4.57), 1.54 (95% CI, 1.10–2.18), and 1.27 (95% CI, 0.73–2.14), respectively.

Conclusions

In Yulin, northern China, variations in climatic factors, especially temperature, sunshine duration, and evaporation, contributed significantly to seasonal fluctuations of human brucellosis within 6 months. The key determinants of brucellosis transmission and the identified complex associations are useful references for developing strategies to reduce the disease burden.

Comparison of temperature-mortality associations using observed weather station and reanalysis data in 52 Spanish cities

BACKGROUND

Most studies use temperature observation data from weather stations near the analyzed region or city as the reference point for the exposure-response association. Climatic reanalysis data sets have already been used for climate studies, but are not yet used routinely in environmental epidemiology.

METHODS

We compared the mortality-temperature association using weather station temperature and ERA-5 reanalysis data for the 52 provincial capital cities in Spain, using time-series regression with distributed lag non-linear models.

RESULTS

The shape of temperature distribution is very close between the weather station and ERA-5 reanalysis data (correlation from 0.90 to 0.99). The overall cumulative exposure-response curves are very similar in their shape and risks estimates for cold and heat effects, although risk estimates for ERA-5 were slightly lower than for weather station temperature.

CONCLUSIONS

Reanalysis data allow the estimation of the health effects of temperature, even in areas located far from weather stations or without any available.

Climate factors driven typhus group rickettsiosis incidence dynamics in Xishuangbanna Dai autonomous prefecture of Yunnan province in China, 2005-2017

BACKGROUND

Typhus group rickettsiosis (TGR), which is a neglected vector-borne infectious disease, including epidemic typhus and endemic typhus. We explored the lag effects and nonlinear association between meteorological factors and TGR incidence in Xishuangbanna Dai autonomous prefecture from 2005 to 2017, China.

METHODS

A Poisson regression with a distributed lag nonlinear model (DLNM) was utilized to analyze TGR cases data and the contemporaneous meteorological data.

RESULTS

A J-shaped nonlinear association between weekly mean temperature and TGR incidence was found. The cumulative exposure to weekly mean temperature indicated that the RR increased with the increment of temperature. Taking the median value as the reference, lower temperatures could decrease the risk of TGR incidence, while higher temperatures could increase the risk of TGR incidence and last for 21 weeks. We also found a reversed U-shaped nonlinear association between weekly mean precipitation and TGR incidence. Precipitation between 5 mm and 13 mm could increase the risk of TGR incidence. Taking the median value as the reference, no precipitation and lower precipitation could decrease the risk of TGR incidence, while higher precipitation could increase the risk of TGR incidence and last for 18 weeks.

CONCLUSIONS

The prevention and control measures of TGR should be implemented according to climatic conditions by the local government and health departments in order to improve the efficiency.

Exposure-lag-response associations between lung cancer mortality and radon exposure in German uranium miners

Exposure-lag-response associations shed light on the duration of pathogenesis for radiation-induced diseases. To investigate such relations for lung cancer mortality in the German uranium miners of the Wismut company, we apply distributed lag non-linear models (DLNMs) which offer a flexible description of the lagged risk response to protracted radon exposure. Exposure-lag functions are implemented with B-Splines in Cox models of proportional hazards. The DLNM approach yielded good agreement of exposure-lag-response surfaces for the German cohort and for the previously studied cohort of American Colorado miners. For both cohorts, a minimum lag of about 2 year for the onset of risk after first exposure explained the data well, but possibly with large uncertainty. Risk estimates from DLNMs were directly compared with estimates from both standard radio-epidemiological models and biologically based mechanistic models. For age > 45 year, all models predict decreasing estimates of the Excess Relative Risk (ERR). However, at younger age, marked differences appear as DLNMs exhibit ERR peaks, which are not detected by the other models. After comparing exposure-responses for biological processes in mechanistic risk models with exposure-responses for hazard ratios in DLNMs, we propose a typical period of 15 year for radon-related lung carcinogenesis. The period covers the onset of radiation-induced inflammation of lung tissue until cancer death. The DLNM framework provides a view on age-risk patterns supplemental to the standard radio-epidemiological approach and to biologically based modeling.

Increases in external cause mortality due to high and low temperatures: evidence from northeastern Europe

The relationship between temperature and mortality is well established but has seldom been investigated in terms of external causes. In some Eastern European countries, external cause mortality is substantial. Deaths owing to external causes are the third largest cause of mortality in Estonia, after cardiovascular disease and cancer. Death rates owing to external causes may reflect behavioural changes among a population. The aim for the current study was to investigate if there is any association between temperature and external cause mortality, in Estonia. We collected daily information on deaths from external causes (ICD-10 diagnosis codes V00-Y99) and maximum temperatures over the period 1997-2013. The relationship between daily maximum temperature and mortality was investigated using Poisson regression, combined with a distributed lag non-linear model considering lag times of up to 10 days. We found significantly higher mortality owing to external causes on hot (the same and previous day) and cold days (with a lag of 1-3 days). The cumulative relative risks for heat (an increase in temperature from the 75th to 99th percentile) were 1.24 (95% confidence interval, 1.14-1.34) and for cold (a decrease from the 25th to 1st percentile) 1.19 (1.03-1.38). Deaths due to external causes might reflect changes in behaviour among a population during periods of extreme hot and cold temperatures and should therefore be investigated further, because such deaths have a severe impact on public health, especially in Eastern Europe where external mortality rates are high.

The effect of extreme cold temperatures on the risk of death in the two major Portuguese cities

It is well known that meteorological conditions influence the comfort and human health. Southern European countries, including Portugal, show the highest mortality rates during winter, but the effects of extreme cold temperatures in Portugal have never been estimated. The objective of this study was the estimation of the effect of extreme cold temperatures on the risk of death in Lisbon and Oporto, aiming the production of scientific evidence for the development of a real-time health warning system. Poisson regression models combined with distributed lag non-linear models were applied to assess the exposure-response relation and lag patterns of the association between minimum temperature and all-causes mortality and between minimum temperature and circulatory and respiratory system diseases mortality from 1992 to 2012, stratified by age, for the period from November to March. The analysis was adjusted for over dispersion and population size, for the confounding effect of influenza epidemics and controlled for long-term trend, seasonality and day of the week. Results showed that the effect of cold temperatures in mortality was not immediate, presenting a 1-2-day delay, reaching maximum increased risk of death after 6-7 days and lasting up to 20-28 days. The overall effect was generally higher and more persistent in Lisbon than in Oporto, particularly for circulatory and respiratory mortality and for the elderly. Exposure to cold temperatures is an important public health problem for a relevant part of the Portuguese population, in particular in Lisbon.

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter

OBJECTIVE

We used log-linear and log-log exposure-response (E-R) functions to model the association between PM2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions.

METHODS

We used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM2.5 exposure from the mean (21.4μg/m(3)) to the WHO guideline for annual mean PM2.5 (10μg/m(3)) were estimated and extrapolated for Belgium.

RESULTS

Non-elective hospitalizations for pneumonia were significantly associated with PM2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM2.5 exposure to 10μg/m(3) was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively.

DISCUSSION

Although further research is required to assess the shape of the association between PM2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced.