Using Parametric g-Computation to Estimate the Effect of Long-Term Exposure to Air Pollution on Mortality Risk and Simulate the Benefits of Hypothetical Policies: The Canadian Community Health Survey Cohort (2005 to 2015).

BACKGROUND: Numerous epidemiological studies have documented the adverse health impact of long-term exposure to fine particulate matter [particulate matter ≤2.5µm in aerodynamic diameter (PM2.5)] on mortality even at relatively low levels. However, methodological challenges remain to consider potential regulatory intervention's complexity and provide actionable evidence on the predicted benefits of interventions. We propose the parametric g-computation as an alternative analytical approach to such challenges. METHOD: We applied the parametric g-computation to estimate the cumulative risks of nonaccidental death under different hypothetical intervention strategies targeting long-term exposure to PM2.5 in the Canadian Community Health Survey cohort from 2005 to 2015. On both relative and absolute scales, we explored the benefits of hypothetical intervention strategies compared with the natural course that a) set the simulated exposure value at each follow-up year to a threshold value if exposure was above the threshold (8.8 µg/m3, 7.04 µg/m3, 5 µg/m3, and 4 µg/m3), and b) reduced the simulated exposure value by a percentage (5% and 10%) at each follow-up year. We used the 3-y average PM2.5 concentration with 1-y lag at the postal code of respondents' annual mailing addresses as their long-term exposure to PM2.5. We considered baseline and time-varying confounders, including demographics, behavior characteristics, income level, and neighborhood socioeconomic status. We also included the R syntax for reproducibility and replication. RESULTS: All hypothetical intervention strategies explored led to lower 11-y cumulative mortality risks than the estimated value under the natural course without intervention, with the smallest reduction of 0.20 per 1,000 participants (95% CI: 0.06, 0.34) under the threshold of 8.8 µg/m3, and the largest reduction of 3.40 per 1,000 participants (95% CI: -0.23, 7.03) under the relative reduction of 10% per interval. The reductions in cumulative risk, or numbers of deaths that would have been prevented if the intervention was employed instead of maintaining the status quo, increased over time but flattened toward the end of the follow-up period. Estimates among those ≥65 years of age were greater with a similar pattern. Our estimates were robust to different model specifications. DISCUSSION: We found evidence that any intervention further reducing the long-term exposure to PM2.5 would reduce the cumulative mortality risk, with greater benefits in the older population, even in a population already exposed to low levels of ambient PM2.5. The parametric g-computation used in this study provides flexibilities in simulating real-world interventions, accommodates time-varying exposure and confounders, and estimates adjusted survival curves with clearer interpretation and more information than a single hazard ratio, making it a valuable analytical alternative in air pollution epidemiological research. https://doi.org/10.1289/EHP11095.

Inequities in ambient fine particulate matter: A spatiotemporal analysis in Canadian communities.

BACKGROUND: Exposure to fine particulate matter (PM2.5) is associated with adverse health outcomes but communities are not randomly exposed to PM2.5. Previous cross-sectional environmental injustice analyses in Canada found disproportionately higher exposure to PM2.5 in low-income populations, visible minorities and immigrants. Beyond static surveillance, it is also important to evaluate how changes in PM2.5 exposure over time may differentially impact disadvantaged communities. We examine whether communities with different sociodemographic characteristics benefited equitably from the overall decreases in ambient concentrations of PM2.5 from 2001 to 2016 in Canada. METHODS: We derived census tract level estimates of average annual PM2.5 using validated satellite-based estimations of annual average PM2.5 concentration surfaces. We investigated how the spatial distribution of PM2.5 has evolved over 15 years (2001-2016) by comparing absolute values and rank percentiles of census tract level annual average PM2.5 concentrations in 2001 and 2016. Using decennial census data and multivariable linear regression, we determined if sociodemographic characteristics are associated with changes in exposure to PM2.5, accounting for geographic boundary changes between census periods. RESULTS: Overall, ambient PM2.5 concentrations decreased from 2001 (median of 9.1 µg/m3) to 2016 (median of 6.4 µg/m3), with varying provincial patterns. Across communities, ranked census tract specific PM2.5 in 2001 and in 2016 are highly correlated (Spearman's rho = 0.75). We found that, on average and accounting for provincial differences and baseline PM2.5, communities with greater density of aboriginal population, lower education, higher shelter-cost-to-income ratio, unemployment or lower income experienced smaller absolute decreases in PM2.5 from 2001 to 2016. CONCLUSIONS: Identifying sociodemographic groups that benefit least from decreasing exposure to PM2.5 highlights the need to consider environmental injustice when designing or revising air pollution policies.

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study.

BACKGROUND: The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. METHODS: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ground-level ozone (O3), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals' long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. RESULTS: Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM2.5 (1.70 µg/m3), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01-1.12), 1.09 (95% CI 0.98-1.21) and 1.00 (95% CI 0.90-1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO2. We also estimated odds ratios of 1.15 (95% CI 1.06-1.23), 1.30 (95% CI 1.12-1.50) and 1.18 (95% CI 1.02-1.36) per interquartile range increase of 5.14 ppb in O3 for hospital admission, ICU admission and death, respectively. INTERPRETATION: Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O3.

Changes in exposure to ambient fine particulate matter after relocating and long term survival in Canada: quasi-experimental study.

OBJECTIVE: To investigate the association between changes in long term residential exposure to ambient fine particulate matter (PM2.5) and premature mortality in Canada. DESIGN: Population based quasi-experimental study. SETTING: Canada. PARTICIPANTS: 663 100 respondents to the 1996, 2001, and 2006 Canadian censuses aged 25-89 years who had consistently lived in areas with either high or low PM2.5 levels over five years preceding census day and moved during the ensuing five years. INTERVENTIONS: Changes in long term exposure to PM2.5 arising from residential mobility. MAIN OUTCOME MEASURES: The primary outcome was deaths from natural causes. Secondary outcomes were deaths from any cardiometabolic cause, any respiratory cause, and any cancer cause. All outcomes were obtained from the national vital statistics database. RESULTS: Using a propensity score matching technique with numerous personal, socioeconomic, health, and environment related covariates, each participant who moved to a different PM2.5 area was matched with up to three participants who moved within the same PM2.5 area. In the matched groups that moved from high to intermediate or low PM2.5 areas, residential mobility was associated with a decline in annual PM2.5 exposure from 10.6 µg/m3 to 7.4 and 5.0 µg/m3, respectively. Conversely, in the matched groups that moved from low to intermediate or high PM2.5 areas, annual PM2.5 increased from 4.6 µg/m3 to 6.7 and 9.2 µg/m3. Five years after moving, individuals who experienced a reduction in exposure to PM2.5 from high to intermediate levels showed a 6.8% (95% confidence interval 1.7% to 11.7%) reduction in mortality (2510 deaths in 56 025 v 4925 deaths in 101 960). A greater decline in mortality occurred among those exposed to a larger reduction in PM2.5. Increased mortality was found with exposure to PM2.5 from low to high levels, and to a lesser degree from low to intermediate levels. Furthermore, the decreases in PM2.5 exposure were most strongly associated with reductions in cardiometabolic deaths, whereas the increases in PM2.5 exposure were mostly related to respiratory deaths. No strong evidence was found for the changes in PM2.5 exposure with cancer related deaths. CONCLUSIONS: In Canada, decreases in PM2.5 were associated with lower mortality, whereas increases in PM2.5 were associated with higher mortality. These results were observed at PM2.5 levels considerably lower than many other countries, providing support for continuously improving air quality.

Differences in suppression of regrowth and resistance despite similar initial bacterial killing for meropenem and piperacillin/tazobactam against Pseudomonas aeruginosa and Escherichia coli.

We described bacterial killing and resistance emergence at various fixed concentrations of meropenem and piperacillin/tazobactam against Pseudomonas aeruginosa and Escherichia coli. Time-kill studies were conducted utilizing nine isolates and a large range of concentrations. Within each strain and antibiotic, initial killing was similar, with concentrations ≥2×MIC. At many (strain-specific) concentrations causing substantial initial killing, regrowth occurred at 24-48h. For remaining concentrations, growth typically remained suppressed (<5-log10 cfu/mL). The concentrations of meropenem required to suppress regrowth ranged from 2-8×MIC for P. aeruginosa and 2-64×MIC for E. coli. For piperacillin/tazobactam, the equivalent concentrations ranged from 8-16×MIC for P. aeruginosa and 4-16×MIC for E. coli. The number of less-susceptible bacteria increased with rising concentrations before decreasing at even higher concentrations. Suppression of regrowth and resistance was substantially improved with higher concentrations (typically ≥8×MIC), suggesting a benefit of higher ß-lactam concentrations beyond those required for maximum initial killing.

Substantial Impact of Altered Pharmacokinetics in Critically Ill Patients on the Antibacterial Effects of Meropenem Evaluated via the Dynamic Hollow-Fiber Infection Model.

Critically ill patients frequently have substantially altered pharmacokinetics compared to non-critically ill patients. We investigated the impact of pharmacokinetic alterations on bacterial killing and resistance for commonly used meropenem dosing regimens. A Pseudomonas aeruginosa isolate (MICmeropenem 0.25 mg/liter) was studied in the hollow-fiber infection model (inoculum ∼107.5 CFU/ml; 10 days). Pharmacokinetic profiles representing critically ill patients with augmented renal clearance (ARC), normal, or impaired renal function (creatinine clearances of 285, 120, or ∼10 ml/min, respectively) were generated for three meropenem regimens (2, 1, and 0.5 g administered as 8-hourly 30-min infusions), plus 1 g given 12 hourly with impaired renal function. The time course of total and less-susceptible populations and MICs were determined. Mechanism-based modeling (MBM) was performed using S-ADAPT. All dosing regimens across all renal functions produced similar initial bacterial killing (≤∼2.5 log10). For all regimens subjected to ARC, regrowth occurred after 7 h. For normal and impaired renal function, bacterial killing continued until 23 to 47 h; regrowth then occurred with 0.5- and 1-g regimens with normal renal function (fT>5×MIC = 56 and 69%, fCmin/MIC < 2); the emergence of less-susceptible populations (≥32-fold increases in MIC) accompanied all regrowth. Bacterial counts remained suppressed across 10 days with normal (2-g 8-hourly regimen) and impaired (all regimens) renal function (fT>5×MIC ≥ 82%, fCmin/MIC ≥ 2). The MBM successfully described bacterial killing and regrowth for all renal functions and regimens simultaneously. Optimized dosing regimens, including extended infusions and/or combinations, supported by MBM and Monte Carlo simulations, should be evaluated in the context of ARC to maximize bacterial killing and suppress resistance emergence.

Effect of different renal function on antibacterial effects of piperacillin against Pseudomonas aeruginosa evaluated via the hollow-fibre infection model and mechanism-based modelling.

BACKGROUND: Pathophysiological changes in critically ill patients can cause severely altered pharmacokinetics and widely varying antibiotic exposures. The impact of altered pharmacokinetics on bacterial killing and resistance has not been characterized in the dynamic hollow-fibre in vitro infection model (HFIM). METHODS: A clinical Pseudomonas aeruginosa isolate (piperacillin MIC 4 mg/L) was studied in the HFIM (inoculum ∼10(7) cfu/mL). Pharmacokinetic profiles of three piperacillin dosing regimens (4 g 8-, 6- and 4-hourly, 30 min intravenous infusion) as observed in critically ill patients with augmented renal clearance (ARC), normal renal function or impaired renal function (creatinine clearances of 250, 110 or 30 mL/min, respectively) were simulated over 7 days. The time courses of total and less-susceptible populations and MICs were determined. Mechanism-based modelling was performed in S-ADAPT. RESULTS: For all regimens with ARC and regimens with 8- or 6-hourly dosing with normal renal function, initial killing of ≤∼2 log10 was followed by regrowth to 10(8)-10(9) cfu/mL at 48 h. For 8- and 6-hourly dosing at normal renal function, the proportion of less-susceptible colonies increased ∼10-100-fold above those in ARC and control arms. Regimens achieving an fCmin of ≥5× MIC resulted in bacterial killing of 3-4 log10 without regrowth and suppressed less-susceptible populations to ≤∼2 log10. The mechanism-based model successfully quantified the time course of bacterial growth, killing and regrowth. CONCLUSIONS: Only high piperacillin concentrations prevented regrowth of P. aeruginosa. Individualized dosing regimens that account for altered pharmacokinetics and aim for higher-than-standard antibiotic exposures to achieve an fCmin of ≥5× MIC were required to maximize bacterial killing and suppress emergence of resistance.

Aberrant P53 expression lacks prognostic or predictive significance in colorectal cancer: results from the VICTOR trial.

AIM: Biomarkers with prognostic and predictive value can help stratify patients with colorectal cancer (CRC) into appropriate treatment groups. We sought to evaluate the clinical utility of P53 protein expression as a biomarker in VICTOR, a large phase III trial of rofecoxib in stage II and III CRC. PATIENTS AND METHODS: Tissue micro arrays were constructed from 884 tumors and the expression of P53 was examined by immunohistochemistry. Tumors were dichotomised as either P53-positive (nuclear expression in >10% of cells or the 'absent' pattern, both representing TP53 mutation) or P53-negative (nuclear expression in <10% of cells). RESULTS: Aberrant P53 expression was found in 65% (482/740) of patients. It was associated with distal location (p<0.001) and stage III disease (p<0.001). No effect was observed on disease-free or overall survival, and there was no interaction with chemotherapy or radiotherapy. CONCLUSION: Analysis of P53 expression in the patients recruited to the VICTOR trial confirmed that P53 expression is associated with site and stage of CRC. However, independently, this biomarker has neither prognostic nor predictive utility in this cohort of patients.

Loss of expression of the double strand break repair protein ATM is associated with worse prognosis in colorectal cancer and loss of Ku70 expression is associated with CIN.

Repair of double strand DNA breaks (DSBs) is pivotal in maintaining normal cell division and disruption of this system has been shown to be a key factor in carcinogenesis. Loss of expression of the DSB repair proteins have previously been shown to be associated with poorer survival in colorectal cancer. We wished to ascertain the relationship of altered expression of the DSB repair proteins γ-H2AX (gamma-H2AX), ATM and Ku70 with biological and clinico-pathological features of colorectal cancer. 908 tumours from the VICTOR clinical trial of stage II/III colorectal cancer were analysed for expression of γ-H2AX, ATM and Ku70 using immunohistochemistry. Expression levels were correlated with CIN and with disease-free survival, correcting for microsatellite instability, BRAF/KRAS mutation status, Dukes stage, chemo/radiotherapy, age, gender and tumour location. Down-regulated Ku70 expression was associated with chromosomal instability (p=0.029) in colorectal cancer. Reduced ATM expression was an independent marker of poor disease-free survival (HR=1.67, 95% CI 1.11-2.50, p=0.015). For Ku70, further studies are required to investigate the potential relationship of non-homologous end joining with chromosomal instability. Loss of ATM expression might serve as a biomarker of poor prognosis in colorectal cancer.