Table of Contents

Abstract

Background: The 10 key characteristics (KCs) of carcinogens form the basis of a framework to identify, organize, and evaluate mechanistic evidence relevant to carcinogenic hazard identification. The 10 KCs are related to mechanisms by which carcinogens cause cancer. The International Agency for Research on Cancer (IARC) Monographs programme has successfully applied the KCs framework for the mechanistic evaluation of different types of exposures, including chemicals, metals, and complex exposures, such as environmental, occupational, or dietary exposures. The use of this framework has significantly enhanced the identification and organization of relevant mechanistic data, minimized bias in evaluations, and enriched the knowledge base regarding the mechanisms of known and suspected carcinogens.

Objectives: We sought to report the main outcomes of an IARC Scientific Workshop convened by the IARC to establish appropriate, transparent, and uniform application of the KCs in future IARC Monographs evaluations.

Methods: A group of experts from different disciplines reviewed the IARC Monographs experience with the KCs of carcinogens, discussing three main themes: a) the interpretation of end points forming the evidence base for the KCs, b) the incorporation of data from novel assays on the KCs, and c) the integration of the mechanistic evidence as part of cancer hazard identification. The workshop participants assessed the relevance and the informativeness of multiple KCs-associated end points for the evaluation of mechanistic evidence in studies of exposed humans and experimental systems.

Discussion: Consensus was reached on how to enhance the use of in silico, molecular, and cellular high-output and high-throughput data. In addition, approaches to integrate evidence across the KCs and opportunities to improve methodologies of mechanistic evaluation of cancer hazards were explored. The findings described herein and in a forthcoming IARC technical report will support future working groups of experts in reporting and interpreting results under the KCs framework within the IARC Monographs or in other contexts. https://doi.org/10.1289/EHP15389

Abstract

Background: Studies evaluating how water, sanitation, and/or handwashing (WASH) interventions in low- and middle-income countries impact diarrheal diseases have shown inconsistent results. The prevalence of enteric pathogen infections and diarrhea are highly seasonal and climate-sensitive, which could explain heterogeneous findings. Understanding how season influences the effectiveness of WASH interventions is critical for informing intervention approaches that will be resistant under the varying weather conditions that climate change will bring.

Methods: We conducted a systematic review of the literature and meta-analysis to test whether and to what extent the impact of WASH interventions on diarrhea differs by season. We searched the literature for randomized and nonrandomized controlled WASH intervention trials and identified the season in which data were collected—rainy, dry, or both—for each study using proximate land station weather datasets. We compared the relative risk (RR) estimates for the impact of interventions on diarrhea for each study, stratified by season, and analyzed estimates using meta-analysis and meta-regression. This study is registered with PROSPERO, CRD42021231137.

Results: A total of 50 studies met the inclusion criteria, resulting in 34 drinking water intervention estimates, 8 sanitation intervention estimates, and 14 handwashing intervention estimates. Of the total studies, 60% ($n=30$) spanned more than one season, with most single-season studies (75%, $n=15$) occurring exclusively in the dry season. The effect of WASH interventions was stronger in dry seasons than in rainy seasons, with a 33% [95% confidence interval (CI): 24%, 41%] and 18% reduction (95% CI: 5%, 29%) in diarrhea risk, respectively. When stratified by type of intervention, the stronger effect size in dry seasons was consistent for water and handwashing interventions but not for sanitation interventions.

Conclusions: Estimates of the seasonal impact of WASH interventions revealed larger effects in the dry season than in the rainy season overall and for water and handwashing interventions in particular. These patterns likely affected previous estimates of intervention effectiveness, which included more dry season estimates. These findings suggest the need to collect data across seasons and report seasonally stratified results to allow for more accurate estimates of the burden of disease impacted by WASH investments and to improve projections of potential impacts of these interventions under future climate conditions. These findings also underscore the need for robust WASH interventions designed to be resistant to seasonal variations in temperature and rainfall now and under future climate change scenarios. https://doi.org/10.1289/EHP14502

Abstract

Background: People who live near airports are exposed to higher concentrations of ultrafine particles (UFPs) from aviation. Pregnant women and their fetuses, in particular, are considered to be highly susceptible to environmental exposures.

Objective: Using existing national databases, we investigated associations between adverse birth outcomes and exposure to UFPs from aviation (UFP-aviation) at the residential address during pregnancy.

Methods: We identified $\sim \mathrm{286,000}$ singleton birth records (from between 2006 and 2018) from mothers who, for at least 6 months during pregnancy, lived in a $50\times 56\mathrm{km}$ area around Schiphol Airport. This information was linked to modeled monthly averaged UFP-aviation concentrations at the residential address during pregnancy. We modeled the association between exposure to UFP-aviation during pregnancy and pregnancy outcomes through logistic regression, adjusting for individual and neighborhood level covariates. We performed a number of sensitivity analyses to investigate the robustness of the results, including adjustment for other air pollutants and noise.

Results: Effect estimates, expressed per 3,500 particles/cm³ (approximately the 5th–9th percentile difference) increase, were generally positive in the main model for preterm birth (PTB) and small for gestational age (SGA) [PTB $\text{OR}=$ 1.02 (95% CI: 0.96, 1.07) and SGA $\text{OR}=$ 1.02 (95% CI: 0.98, 1.07)] and congenital anomalies (CAs) at birth [any CA $\text{OR}=$ 1.05 (95% CI: 0.98, 1.07)]. Associations with UFP-aviation became stronger in some of the sensitivity analyses, such as when the four municipalities with the lowest exposure were excluded (for PTB, SGA, and CA), when the population was restricted to mothers with a Dutch background (PTB), after nonlinear adjustment for nitrogen dioxide (${\mathrm{NO}}_2$) and elemental carbon (EC) (PTB), after including municipality as a random effect (CA), and in some specific strata of the population. No associations were found with infant mortality, low Apgar score, and low birth weight.

Conclusions: We found suggestive evidence for associations between exposure to UFP-aviation during pregnancy and pregnancy outcomes. https://doi.org/10.1289/EHP14398

Abstract

Background: Telomere length (TL) and mitochondrial DNA copy number (mtDNAcn) variations are linked to age-related diseases and are associated with environmental exposure and nutritional status. Limited data, however, exist on the associations with mercury exposure, particularly early in life.

Objective: We examined the association between prenatal mercury (Hg) exposure and TL and mtDNAcn in 1,145 Seychelles children, characterized by a fish-rich diet.

Methods: Total mercury (THg) was determined in maternal hair at delivery and cord blood. TL and mtDNAcn were determined relative to a single-copy hemoglobin beta gene in the saliva of 7-y-old children. Linear regression models assessed associations between THg and relative TL (rTL) and relative mtDNAcn (rmtDNAcn) while controlling for maternal and cord serum polyunsaturated fatty acid (PUFA) status and sociodemographic factors. Interactions between THg and child sex, PUFA, and telomerase genotypes were evaluated for rTL and rmtDNAcn.

Results: Higher THg concentrations in maternal hair and cord blood were associated with longer rTL [$\mathrm{\beta }=0.009$; 95% confidence interval (CI): 0.002, 0.016 and $\mathrm{\beta }=0.002$; 95% CI: 0.001, 0.003, respectively], irrespective of sex, PUFA, or telomerase genotypes. Maternal serum n-6 PUFA and n-6/n-3 ratio were associated with shorter [$\mathrm{\beta }=-0.24$; 95% CI: $-0.33$, $-0.15$ and $\mathrm{\beta }=-0.032$; 95% CI: $-0.048$, $-0.016$, respectively] and $n-3$ PUFA with longer ($\mathrm{\beta }=0.34$; 95% CI: 0.032, 0.65) rTL. Cord blood n-6 PUFA was associated with longer ($\mathrm{\beta }=0.15$; 95% CI: 0.050, 0.26) rTL. Further analyses revealed linoleic acid in maternal blood and arachidonic acid in cord blood as the main drivers of the n-6 PUFA associations. No associations were observed for THg and PUFA with rmtDNAcn.

Discussion: Our results indicate that prenatal THg exposure and PUFA status are associated with rTL later in childhood, although not consistently aligned with our initial hypothesis. Subsequent research is needed to confirm this finding, further evaluate the potential confounding of fish intake, and investigate the underlying molecular mechanisms to verify the use of rTL as a true biomarker of THg exposure. https://doi.org/10.1289/EHP14776

Abstract

Background: Younger generations are projected to experience more severe climate exposure impacts during their lifetimes than older generations as global warming progresses. Despite the increasing evidence of the recent temporal changes in heat-related mortality risks, there remains a lack of research exploring this association from a cohort perspective.

Objective: Our objective was to quantify the variation in susceptibility to short-term effects of non-optimal temperature on mortality, across generations and over the life course of specific generations, using a novel age–period–cohort approach.

Methods: An extended two-stage analytical approach was applied to a nationwide mortality dataset covering individuals born from 1866 to 2019 in all 47 prefectures in Japan. Daily mortality counts observed between 1972 and 2019 were aggregated into 5-year birth cohorts and corresponding age groups of the decedents. For each prefecture and birth cohort, the age-dependent association between ambient temperature and daily mortality was modeled using conditional quasi-Poisson regression. Then, the prefecture-specific associations were pooled across cohorts, separately for each age group, using a repeated-measure meta-regression. To model the intergenerational changes in risks, a nonlinear, continuous term for cohort was applied in the meta-analysis.

Results: A total of 29 million all-cause deaths were analyzed. The relative risk (RR) of heat-related mortality (99th temperature percentile compared to minimum mortality temperature) decreased across generations for elder adults (65–89 years of age), from $\text{RR}=1.18$ [95% confidence interval (CI): 1.13, 1.23] for those born in 1901–1905 to $\text{RR}=1.04$ (95% CI: 1.01, 1.07) for those born in 1926–1930 ($p\text{-trend}=0.004$). Similar to heat-related risk, the cold-related mortality risk (at first percentile) also decreased across the same cohorts ($p\text{-trend}<0.001$). The predicted continuous trends in heat- and cold-related mortality risks exhibited a nonlinear decline across generations. An inconsistent pattern was observed for middle-aged people (40–64 years of age) born between 1930 and 1960, with a slight increase in risks for cold and heat over generations. For cohort-specific risk trajectories, heat- and cold-related mortality risks generally increased with age, after 60 years old.

Discussion: This nationwide, individual-level study adopted a novel cohort perspective to investigate how population susceptibility to short-term non-optimal temperature exposure varies across generations. Our findings revealed disparities in susceptibility between generations, highlighting the importance for researchers and policymakers to consider cohort differences in efforts to promote future health advancements and reduce inequalities. https://doi.org/10.1289/EHP15226