Exposure to ambient air pollution and cognitive function: an analysis of the English Longitudinal Study of Ageing cohort.

BACKGROUND: An increasing number of studies suggest adverse effects of exposure to ambient air pollution on cognitive function, but the evidence is still limited. We investigated the associations between long-term exposure to air pollutants and cognitive function in the English Longitudinal Study of Ageing (ELSA) cohort of older adults. METHODS: Our sample included 8,883 individuals from ELSA, based on a nationally representative study of people aged ≥ 50 years, followed-up from 2002 until 2017. Exposure to air pollutants was modelled by the CMAQ-urban dispersion model and assigned to the participants' residential postcodes. Cognitive test scores of memory and executive function were collected biennially. The associations between these cognitive measures and exposure to ambient concentrations of NO2, PM10, PM2.5 and ozone were investigated using mixed-effects models adjusted for time-varying age, physical activity and smoking status, as well as baseline gender and level of education. RESULTS: Increasing long-term exposure per interquartile range (IQR) of NO2 (IQR: 13.05 µg/m3), PM10 (IQR: 3.35 µg/m3) and PM2.5 (IQR: 2.7 µg/m3) were associated with decreases in test scores of composite memory by -0.10 (95% confidence interval [CI]: -0.14, -0.07), -0.02 [-0.04, -0.01] and -0.08 [-0.11, -0.05], respectively. The same increases in NO2, PM10 and PM2.5 were associated with decreases in executive function score of -0.31 [-0.38, -0.23], -0.05 [-0.08, -0.02] and -0.16 [-0.22, -0.10], respectively. The association with ozone was inverse across both tests. Similar results were reported for the London-dwelling sub-sample of participants. CONCLUSIONS: The present study was based on a long follow-up with several repeated measurements per cohort participant and long-term air pollution exposure assessment at a fine spatial scale. Increasing long-term exposure to NO2, PM10 and PM2.5 was associated with a decrease in cognitive function in older adults in England. This evidence can inform policies related to modifiable environmental exposures linked to cognitive decline.

Characterising sources of PM2·5 exposure for school children with asthma: a personal exposure study across six cities in sub-Saharan Africa.

BACKGROUND: Air pollution is the second largest risk to health in Africa, and children with asthma are particularly susceptible to its effects. Yet, there is a scarcity of air pollution exposure data from cities in sub-Saharan Africa. We aimed to identify potential exposure reduction strategies for school children with asthma living in urban areas in sub-Saharan Africa. METHODS: This personal exposure study was part of the Achieving Control of Asthma in Children in Africa (ACACIA) project. Personal exposure to particulate matter (PM) was monitored in school children in six cities in sub-Saharan Africa (Blantyre, Malawi; Durban, South Africa; Harare, Zimbabwe; Kumasi, Ghana; Lagos, Nigeria; and Moshi, Tanzania). Participants were selected if they were aged 12-16 years and had symptoms of asthma. Monitoring was conducted between June 21, and Nov 26, 2021, from Monday morning (approximately 1000 h) to Friday morning (approximately 1000 h), by use of a bespoke backpack with a small air pollution monitoring unit with an inbuilt Global Positioning System (GPS) data logger. Children filled in a questionnaire detailing potential sources of air pollution during monitoring and exposures were tagged into three different microenvironments (school, commute, and home) with GPS coordinates. Mixed-effects models were used to identify the most important determinants of children's PM2·5 (PM <2·5 µm in diameter) exposure. FINDINGS: 330 children were recruited across 43 schools; of these, 297 had valid monitoring data, and 1109 days of valid data were analysed. Only 227 (20%) of 1109 days monitored were lower than the current WHO 24 h PM2·5 exposure health guideline of 15 µg/m3. Children in Blantyre had the highest PM2·5 exposure (median 41·8 µg/m3), whereas children in Durban (16·0 µg/m3) and Kumasi (17·9 µg/m3) recorded the lowest exposures. Children had significantly higher PM2·5 exposures at school than at home in Kumasi (median 19·6 µg/m3vs 14·2 µg/m3), Lagos (32·0 µg/m3vs 18·0 µg/m3), and Moshi (33·1 µg/m3vs 23·6 µg/m3), while children in the other three cities monitored had significantly higher PM2·5 exposures at home and while commuting than at school (median 48·0 µg/m3 and 43·2 µg/m3vs 32·3 µg/m3 in Blantyre, 20·9 µg/m3 and 16·3 µg/m3vs 11·9 µg/m3 in Durban, and 22·7 µg/m3 and 25·4 µg/m3vs 16·4 µg/m3 in Harare). The mixed-effects model highlighted the following determinants for higher PM2·5 exposure: presence of smokers at home (23·0% higher exposure, 95% CI 10·8-36·4), use of coal or wood for cooking (27·1%, 3·9-56·3), and kerosene lamps for lighting (30·2%, 9·1-55·2). By contrast, 37·2% (95% CI 22·9-48·2) lower PM2·5 exposures were found for children who went to schools with paved grounds compared with those whose school grounds were covered with loose dirt. INTERPRETATION: Our study suggests that the most effective changes to reduce PM2·5 exposures in these cities would be to provide paving in school grounds, increase the use of clean fuel for cooking and light in homes, and discourage smoking within homes. The most efficient way to improve air quality in these cities would require tailored interventions to prioritise different exposure-reduction policies in different cities. FUNDING: UK National Institute for Health and Care Research.

Health impact assessment for air pollution in the presence of regional variation in effect sizes: The implications of using different meta-analytic approaches.

The estimated health effects of air pollution vary between studies, and this variation is caused by factors associated with the study location, hereafter termed regional heterogeneity. This heterogeneity raises a methodological question as to which studies should be used to estimate risks in a specific region in a health impact assessment. Should one use all studies across the world, or only those in the region of interest? The current study provides novel insight into this question in two ways. Firstly, it presents an up-to-date analysis examining the magnitude of continent-level regional heterogeneity in the short-term health effects of air pollution, using a database of studies collected by Orellano et al. (2020). Secondly, it provides in-depth simulation analyses examining whether existing meta-analyses are likely to be underpowered to identify statistically significant regional heterogeneity, as well as evaluating which meta-analytic technique is best for estimating region-specific estimates. The techniques considered include global and continent-specific (sub-group) random effects meta-analysis and meta-regression, with omnibus statistical tests used to quantify regional heterogeneity. We find statistically significant regional heterogeneity for 4 of the 8 pollutant-outcome pairs considered, comprising NO2, O3 and PM2.5 with all-cause mortality, and PM2.5 with cardiovascular mortality. From the simulation analysis statistically significant regional heterogeneity is more likely to be identified as the number of studies increases (between 3 and 30 in each region were considered), between region heterogeneity increases and within region heterogeneity decreases. Finally, while a sub-group analysis using Cochran's Q test has a higher median power (0.71) than a test based on the moderators' coefficients from meta-regression (0.59) to identify regional heterogeneity, it also has an inflated type-1 error leading to more false positives (median errors of 0.15 compared to 0.09).

Corrigendum re "Impact of Body Mass Index on Survival Outcomes for Patients with Metastatic Renal Cell Carcinoma in the Immuno-oncology Era: A Systematic Review and Meta-analysis" [Eur Urol Open Sci 2022;39:62-71].

[This corrects the article DOI: 10.1016/j.euros.2022.03.002.].

Exposure to Ambient Air Pollution and the Incidence of Dementia in the Elderly of England: The ELSA Cohort.

Increasing evidence suggests an adverse association between ambient air pollution and the incidence of dementia in adult populations, although results at present are mixed and further work is required. The present study investigated the relationships between NO2, PM10, PM2.5 and ozone on dementia incidence in a cohort of English residents, aged 50 years and older, followed up between 2004 and 2017 (English Longitudinal Study of Ageing; n = 8525). Cox proportional hazards models were applied to investigate the association between time to incident dementia and exposure to pollutants at baseline. Hazard ratios (HRs) were calculated per 10 µg/m3. Models were adjusted for age, gender, physical activity, smoking status and level of education (the latter as a sensitivity analysis). A total of 389 dementia cases were identified during follow-up. An increased risk of developing dementia was suggested with increasing exposure to PM2.5 (HR: 1.10; 95% confidence interval (CI): 0.88, 1.37), whilst NO2, PM10 and ozone exhibited no discernible relationships. Hazard ratios were 0.97 (CI: 0.89, 1.05) for NO2; 0.98 (CI: 0.89, 1.08) for PM10; 1.01 (CI: 0.94, 1.09) for ozone. In the London sub-sample (39 dementia cases), a 10 µg/m3 increase in PM10 was found to be associated with increased risk of dementia by 16%, although not statistically significant (HR: 1.16; CI: 0.90, 1.48), and the magnitude of effect for PM2.5 increased, whilst NO2 and ozone exhibited similar associations as observed in the England-wide study. Further work is required to fully elucidate the potentially adverse associations between air pollution exposure and dementia incidence.

The establishment of Air Quality Health Index in China: A comparative analysis of methodological approaches.

BACKGROUND: The Air Quality Index (AQI) has been criticized because it does not adequately account for the health effect of multi-pollutants. Although the developed Air Quality Health Index (AQHI) is a more effective communication tool, little is known about the best method to construct AQHI on long time and large spatial scales. OBJECTIVES: To further evaluate the validity of existing approaches to the establishment of AQHI on both long time and larger spatial scales. METHODS: By introducing 3 approaches addressing multi-pollutant exposures: cumulative risk index (CRI), supervised principal component analysis (SPCA), and Bayesian multi-pollutants weighted model (BMP), we constructed CRI-AQHI, SPCA-AQHI, BMP-AQHI and standard-AQHI on cardiovascular mortality in China from 2015 to 2019 at both the national and geographic regional levels. We further assessed the performance of the four methods in estimating the joint effect of multi-pollutants by simulations under various scenarios of pollution effect. RESULTS: The results of national China showed that the BMP-AQHI improved the goodness of fit of the standard-AQHI by 108.24%, followed by CRI-AQHI (5.02%), and all AQHIs performed better than AQI, consistent with 6 geographic regional results. In addition, the simulation result showed that the BMP method provided stable and relatively accurate estimations of the short-term combined effect of exposure to multi-pollutants. CONCLUSIONS: AQHI based on BMP could communicate the air pollution risk to the public more effectively than the current AQHI and AQI.

Impact of Body Mass Index on Survival Outcomes of Patients with Metastatic Renal Cell Carcinoma in the Immuno-oncology Era: A Systematic Review and Meta-analysis.

Context: Body mass index (BMI) is a useful tool for measuring body composition. It is unclear whether high BMI is a favourable indicator in patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint inhibitors (ICIs). Objective: To investigate the prognostic significance of BMI in patients with mRCC treated with ICIs in a systematic review and meta-analysis. Evidence acquisition: Ovid MEDLINE, Embase, and Web of Science were systematically searched in July 2021, and meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Evidence synthesis: A total of 517 nonduplicate citations were screened by title and abstract, followed by full-text screening of 57 candidate articles to determine whether each study met the eligibility criteria. Overall, a total of 2281 patients from eight studies were included in the systematic review and meta-analysis. BMI levels were compared with overall survival (OS) and progression-free survival (PFS) in seven and three studies, respectively. Overweight/obese BMI was significantly associated with better OS compared to normal BMI (adjusted hazard ratio [aHR] 0.77, 95% confidence intervals [CI] 0.65-0.91; p = 0.002). A similar trend was observed for PFS (aHR 0.66, 95% CI 0.44-1.00; p = 0.050). There was no statistical heterogeneity or obvious publication bias among these studies. Conclusions: This is the first systematic review and meta-analysis to evaluate the impact of BMI on survival outcomes of patients with mRCC treated with ICIs. To confirm the existence of the obesity paradox for patients with mRCC in the immuno-oncology era, high-quality clinical trials and basic research are warranted. Patient summary: We reviewed published data on survival outcomes of 2281 patients with metastatic kidney cancer treated with immunotherapy drugs in relation to their body mass index (BMI). We found that higher BMI was associated with better survival when compared to normal BMI for this disease setting and treatment strategy.

Quantifying the short-term effects of air pollution on health in the presence of exposure measurement error: a simulation study of multi-pollutant model results.

BACKGROUND: Most epidemiological studies estimate associations without considering exposure measurement error. While some studies have estimated the impact of error in single-exposure models we aimed to quantify the effect of measurement error in multi-exposure models, specifically in time-series analysis of PM2.5, NO2, and mortality using simulations, under various plausible scenarios for exposure errors. Measurement error in multi-exposure models can lead to effect transfer where the effect estimate is overestimated for the pollutant estimated with more error to the one estimated with less error. This complicates interpretation of the independent effects of different pollutants and thus the relative importance of reducing their concentrations in air pollution policy. METHODS: Measurement error was defined as the difference between ambient concentrations and personal exposure from outdoor sources. Simulation inputs for error magnitude and variability were informed by the literature. Error-free exposures with their consequent health outcome and error-prone exposures of various error types (classical/Berkson) were generated. Bias was quantified as the relative difference in effect estimates of the error-free and error-prone exposures. RESULTS: Mortality effect estimates were generally underestimated with greater bias observed when low ratios of the true exposure variance over the error variance were assumed (27.4% underestimation for NO2). Higher ratios resulted in smaller, but still substantial bias (up to 19% for both pollutants). Effect transfer was observed indicating that less precise measurements for one pollutant (NO2) yield more bias, while the co-pollutant (PM2.5) associations were found closer to the true. Interestingly, the sum of single-pollutant model effect estimates was found closer to the summed true associations than those from multi-pollutant models, due to cancelling out of confounding and measurement error bias. CONCLUSIONS: Our simulation study indicated an underestimation of true independent health effects of multiple exposures due to measurement error. Using error parameter information in future epidemiological studies should provide more accurate concentration-response functions.

Personal exposure to air pollution and respiratory health of COPD patients in London.

Previous studies have investigated the effects of air pollution on chronic obstructive pulmonary disease (COPD) patients using either fixed-site measurements or a limited number of personal measurements, usually for one pollutant and a short time period. These limitations may introduce bias and distort the epidemiological associations as they do not account for all the potential sources or the temporal variability of pollution.We used detailed information on individuals' exposure to various pollutants measured at fine spatiotemporal scale to obtain more reliable effect estimates. A panel of 115 patients was followed up for an average continuous period of 128 days carrying a personal monitor specifically designed for this project that measured temperature, nitrogen dioxide (NO2), ozone (O3), nitric oxide (NO), carbon monoxide (CO), and particulate matter with aerodynamic diameter <2.5 and <10 µm at 1-min time resolution. Each patient recorded daily information on respiratory symptoms and measured peak expiratory flow (PEF). A pulmonologist combined related data to define a binary variable denoting an "exacerbation". The exposure-response associations were assessed with mixed effects models.We found that gaseous pollutants were associated with a deterioration in patients' health. We observed an increase of 16.4% (95% CI 8.6-24.6%), 9.4% (95% CI 5.4-13.6%) and 7.6% (95% CI 3.0-12.4%) in the odds of exacerbation for an interquartile range increase in NO2, NO and CO, respectively. Similar results were obtained for cough and sputum. O3 was found to have adverse associations with PEF and breathlessness. No association was observed between particulate matter and any outcome.Our findings suggest that, when considering total personal exposure to air pollutants, mainly the gaseous pollutants affect COPD patients' health.

Does climatic zone of birth modify the temperature-mortality association of London inhabitants during the warm season? A time-series analysis for 2004-2013.

BACKGROUND: It is known that on days with high temperatures higher mortality is observed and there is a minimum mortality temperature (MMT) point which is higher in places with warmer climate. This indicates some population adaptation to local climate but information on how quickly this adaptation will occur under climate change is lacking. METHODS: To investigate this, we associated daily mortality data with temperature during the warm period in 2004-2013 for London inhabitants born in five climatic zones (UK, Tropical, Sub-tropical, Boreal and Mixed). We fitted Poisson regression with distributed-lag non-linear models for each climatic zone group separately to estimate group-specific exposure-response associations and MMTs. We report relative risks of death comparing the 95th percentile (21 °C) and maximum (25 °C) of the temperature distribution in London with the zone-specific minimum mortality temperature. RESULTS: No heat-related mortality was observed for people born in countries with Sub-tropical and Mixed climates. We observed an increase of 26%, 35% and 39% in the risk of death at 25 °C compared to the MMT in people born in the UK (marine climate), Tropical and Boreal climate respectively. The temperatures with the lowest mortality in these groups ranged from 15.9 to 17.7 °C. DISCUSSION: Our findings imply that people born in different climatic zones do not adapt fully to their new environment within their lifetime. This implies that populations may not adapt readily to climate change and will suffer increased effects from heat. In the presence of climate change, policy makers should be aware of a delayed process of adaptation.

The role of burden of disease assessment in tracking progress towards achieving WHO global air quality guidelines.

OBJECTIVES: More than 90% of the global population live in areas exceeding the PM2.5 air quality guidelines (AQGs). We provide an overview of the ambient PM2.5-related burden of disease (BoD) studies along with scenario analysis in the framework of the WHO AQG update on the estimated reduction in the BoD if AQGs were achieved globally. METHODS: We reviewed the literature for large-scale studies for the BoD attributed to ambient PM2.5. Moreover, we used the latest WHO statistics to calculate the BoD at current levels and the scenarios of aligning with interim targets and AQG levels. RESULTS: The most recent BoD studies (2010 onwards) share a similar methodology, but there are differences in the input data which affect the estimates for attributable deaths (2.9-8.9 million deaths annually). Moreover, we found that if AQGs were achieved, the estimated BoD would be reduced by up to 50% in total deaths worldwide. CONCLUSIONS: Understanding the BoD across countries, especially in those that do not align with the AQGs, is essential in order to inform actions to reduce air pollution globally.

PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis.

BACKGROUND: The use of proxy exposure estimates for PM2.5 and NO2 in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest. OBJECTIVES: We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants. DATA SOURCES AND ELIGIBILITY CRITERIA: We reviewed the literature (ISI Web of Science, Medline, 2000-2016) for English language studies (in any age group in any location (NO2) or Europe and North America (PM2.5)) that reported repeated measurements over time both for personal and ambient PM2.5 or NO2 concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study. STUDY APPRAISAL AND SYNTHESIS METHODS: Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures. RESULTS: Thirty-two papers for PM2.5 and 24 for NO2 were identified. Outdoor sources were found to contribute 44% (range: 33-55%) of total personal exposure to PM2.5 and 74% (range: 57-88%) to NO2. Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 µg/m3 and 12.0 ppb for PM2.5 and NO2 respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 µg/m3 and 7.17 ppb. Our findings indicated also higher error variability for NO2 than PM2.5. Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample. LIMITATIONS, CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO2 had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO2 compared with PM2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models.

Is daily exposure to ozone associated with respiratory morbidity and lung function in a representative sample of schoolchildren? Results from a panel study in Greece.

Previous time series or panel studies of asthmatics have reported respiratory health effects following short-term exposure to ozone (O3). We followed 186 children aged 10 years old in Athens and Thessaloniki, Greece for 5 weeks during the academic year 2013-2014 and recorded daily their respiratory symptoms, absenteeism and peak expiratory flow (PEF). We applied mixed models controlling for various possible confounders to investigate the daily associations between O3 exposure - derived from weekly personal and fixed school site measurements calibrated using daily values of the fixed monitoring site nearest to the child's school location - and PEF, presence of any symptom, cough and stuffy nose, as well as absenteeism. We tested the robustness of our findings to varying modeling assumptions and confounders and investigated effect modification patterns by medication use, time spent outdoors and prevalence of asthma. A 10 µg/m3 increase in O3 personal exposure was associated with increased odds of any symptom (odds ratio (OR): 1.19, 95% confidence interval (CI): 0.98, 1.44), largely attributed to the increase in the odds of stuffy nose (OR: 1.23, 95% CI: 1.00, 1.51). PEF and absenteeism were not related to O3 exposure. Our results were robust to several sensitivity analyses. Effects were modified by medication use as presence of symptoms but also decreases in PEF were mainly reported among non-users, while our effect estimates were not driven by the asthmatic subgroup of children. Our findings indicate that short-term O3 exposure may be associated with respiratory symptoms extending previously reported results for asthmatics to the general population.