Nickel in ambient particulate matter and respiratory or cardiovascular outcomes: A critical review.

Exposure to ambient particulate matter (PM) has been associated with respiratory and cardiovascular outcomes, and nickel has been more frequently associated with these outcomes than other metal constituents of ambient PM. Because of this, we evaluated whether the evidence to date supports causal relationships between exposure to nickel in ambient PM and respiratory or cardiovascular outcomes. We critically reviewed 38 studies in human populations published between 2012 and 2022. Although a large variety of respiratory and cardiovascular outcomes were examined, data were sparse for many. As a result, we focused our evaluation on seven respiratory outcomes and three cardiovascular outcomes that were each examined in ≥3 studies. Of these health outcomes, exposure to nickel in ambient PM has been statistically significantly associated with respiratory mortality, respiratory emergency hospital visits, asthma, lung function (i.e., forced expiratory volume in 1 s, forced vital capacity), cardiovascular mortality, and ischemic heart disease mortality. Studies of the health outcomes of focus are subject to multiple methodological limitations, primarily ecological fallacy (short-term exposure studies), exposure measurement error, confounding, model misspecification, and multiple comparisons issue. While some statistically significant associations were reported, they were not strong, precise, or consistent. Statistically significant findings for long-term exposure to nickel in PM were largely reported in studies that could not establish temporality, despite their cohort study design. Statistically significant findings for short-term exposure to nickel in PM were largely reported in studies that could establish temporality, although this cannot inform causal inference at the individual level due to the aggregate level data used. The biological plausibility of the associations is only supported at high concentrations not relevant to ambient exposures. Overall, the literature to date does not provide adequate support for a causal relationship between nickel in ambient PM and respiratory or cardiovascular outcomes.

Perspectives on recent reviews of aspartame cancer epidemiology.

Aspartame is a dipeptide non-sugar sweetener that was first marketed in the US in carbonated beverages in 1983, before gaining prominence globally. The Joint Food and Agriculture Organization of the United Nations (FAO)/World Health Organization (WHO) Expert Committee on Food Additives (JECFA) and the WHO International Agency for Research on Cancer (IARC) completed evaluations of aspartame and cancer in July 2023. JECFA reaffirmed the safety of aspartame, stating that epidemiology evidence is "not convincing," and that there are no consistent associations between aspartame and cancer (JECFA/IARC, 2023; JECFA, 2023). JECFA also noted "reverse causality, chance, bias and confounding by socioeconomic or lifestyle factors, or consumption of other dietary components, could not be completely ruled out" in relevant epidemiology studies (JECFA/IARC, 2023). In contrast, IARC stated that there are three "high quality" studies on liver cancer (Riboli, 2023), but that the evidence is limited because "chance, bias or confounding could not be ruled out as an explanation for the positive findings" (JECFA/IARC, 2023). IARC does not provide an explanation as to how these studies can be both high quality and have these weaknesses, most notably potential exposure misclassification, or how inconsistent associations from studies with these weaknesses constitute limited evidence. Further, when IARC concludes an agent has limited or inadequate human evidence (and no sufficient animal or strong mechanistic evidence), it classifies that agent as either Group 2B, a possible human carcinogen, or Group 3, not classifiable as to its carcinogenicity. Ultimately, the interpretations of Group 2B and Group 3 classifications are intended to be similar. However, a Group 2B designation may make it appear to scientists and non-scientists alike that the evidence is pointing in the direction of causality. This can lead to unnecessary confusion with respect to the evidence, as well as a perception of a disagreement within WHO regarding aspartame. This apparent contradiction could have been avoided by assigning the IARC classification most consistent with the conclusion that the human evidence for cancer is inadequate: Group 3.

The role of study quality in aspartame and cancer epidemiology study reviews.

Toews et al. [1] and the World Health Organization (WHO) [2] reviewed observational epidemiology studies of non-sugar sweeteners (NSSs) and various health effects. The former used the Risk of Bias in Non-randomised Studies - of Interventions (ROBINS-I) tool and the latter used both the ROBINS-I tool and the Newcastle-Ottawa Scale to evaluate study quality. Both reviews concluded that there were no associations between NSS or aspartame consumption and cancer (except possibly between saccharin and bladder cancer) but indicated that the certainty of the evidence for all cancer types was "very low." While we agree with this conclusion, the support for the confidence in the evidence generally was not transparently documented, as the results of the study quality assessment were only provided in scores or ratings. An examination of illustrative case studies shows that some important aspects of study quality domains specific for NSSs generally or aspartame specifically (i.e., issues with the exposure and outcome assessments, the consideration of confounding/covariates, and selection bias) may have been overlooked or not given appropriate consideration, while other aspects that were less likely to have a large impact on overall study quality dominated the results in the two assessments. Our review of other studies published after the WHO [2] review further demonstrates this point. While this may not seem important given the overall lack of associations, it impacts the degree to which evidence supports a lack of effects as opposed to not being adequate to evaluate associations. In the future, aspartame and cancer outcome reviews should focus on those study quality domains that are most likely to impact the interpretation of results and discuss them in a transparent, systematic manner. If there is very low certainty in the evidence as a result of low study quality, reviewers should conclude the evidence is inadequate for making a causal determination.

Trends in heroin use and injection drug use among high school students in five urban school districts in the US (2005-2017).

Background. We describe the prevalence of and changes in heroin use and injection drug use (IDU) among high school students in five large, urban school districts in the US (2005-2017); nearly three-fourths of the students were Black and/or Hispanic/Latino.Methods. Data are from the Centers for Disease Control and Prevention's "Youth Risk Behavior Survey" program, which includes biennial surveys in urban school districts. We pooled data across districts and survey years, and then generated weighted prevalence estimates (and 95% CIs) for any lifetime heroin use and IDU. Joinpoint regression modeling was used to estimate changes in prevalence over the study period.Results. Biennial prevalence estimates (2005-2017) for heroin use and IDU were above 1.8% for all seven timepoints. In 2017, prevalence of heroin use and IDU were 2.9% and 2.5%, respectively. Both heroin use and IDU were higher among boys than girls. There were statistically significant increases in heroin use and IDU among girls from 2005-2009, whereas changes over time were stable among boys.Conclusions. High school students in large, urban school districts may have higher rates of heroin use and IDU than US high school students in general, and there is little evidence of increases since 2009. This study suggests that adolescence may be a critical period for initiation of heroin use among adolescents in large urban school districts, the majority of whom are Black and/or Latino.Supplemental data for this article is available online at https://doi.org/10.1080/15332640.2021.1992327 .

Research on COVID-19 and air pollution: A path towards advancing exposure science.

The COVID-19 pandemic has resulted in an extraordinary incidence of morbidity and mortality, with almost 6 million deaths worldwide at the time of this writing (https://covid19.who.int/). There has been a pressing need for research that would shed light on factors - especially modifiable factors - that could reduce risks to human health. At least several hundred studies addressing the complex relationships among transmission of SARS-CoV-2, air pollution, and human health have been published. However, these investigations are limited by available and consistent data. The project goal was to seek input into opportunities to improve and fund exposure research on the confluence of air pollution and infectious agents such as SARS-CoV-2. Thirty-two scientists with expertise in exposure science, epidemiology, risk assessment, infectious diseases, and/or air pollution responded to the outreach for information. Most of the respondents expressed value in developing a set of common definitions regarding the extent and type of public health lockdown. Traffic and smoking ranked high as important sources of air pollution warranting source-specific research (in contrast with assessing overall ambient level exposures). Numerous important socioeconomic factors were also identified. Participants offered a wide array of inputs on what they considered to be essential studies to improve our understanding of exposures. These ranged from detailed mechanistic studies to improved air quality monitoring studies and prospective cohort studies. Overall, many respondents indicated that these issues require more research and better study design. As an exercise to solicit opinions, important concepts were brought forth that provide opportunities for scientific collaboration and for consideration for funding prioritization. Further conversations on these concepts are needed to advance our thinking on how to design research that moves us past the documented limitations in the current body of research and prepares us for the next pandemic.

Considerations towards the better integration of epidemiology into quantitative risk assessment.

Environmental epidemiology has proven critical to study various associations between environmental exposures and adverse human health effects. However, there is a perception that it often does not sufficiently inform quantitative risk assessment. To help address this concern, in 2017, the Health and Environmental Sciences Institute initiated a project engaging the epidemiology, exposure science, and risk assessment communities with tripartite representation from government agencies, industry, and academia, in a dialogue on the use of environmental epidemiology for quantitative risk assessment and public health decision making. As part of this project, four meetings attended by experts in epidemiology, exposure science, toxicology, statistics, and risk assessment, as well as one additional meeting engaging funding agencies, were organized to explore incentives and barriers to realizing the full potential of epidemiological data in quantitative risk assessment. A set of questions was shared with workshop participants prior to the meetings, and two case studies were used to support the discussion. Five key ideas emerged from these meetings as areas of desired improvement to ensure that human data can more consistently become an integral part of quantitative risk assessment: 1) reducing confirmation and publication bias, 2) increasing communication with funding agencies to raise awareness of research needs, 3) developing alternative funding channels targeted to support quantitative risk assessment, 4) making data available for reuse and analysis, and 5) developing cross-disciplinary and cross-sectoral interactions, collaborations, and training. We explored and integrated these themes into a roadmap illustrating the need for a multi-stakeholder effort to ensure that epidemiological data can fully contribute to the quantitative evaluation of human health risks, and to build confidence in a reliable decision-making process that leverages the totality of scientific evidence.

Curating the Evidence About COVID-19 for Frontline Public Health and Clinical Care: The Novel Coronavirus Research Compendium.

The public health crisis created by the COVID-19 pandemic has spurred a deluge of scientific research aimed at informing the public health and medical response to the pandemic. However, early in the pandemic, those working in frontline public health and clinical care had insufficient time to parse the rapidly evolving evidence and use it for decision-making. Academics in public health and medicine were well-placed to translate the evidence for use by frontline clinicians and public health practitioners. The Novel Coronavirus Research Compendium (NCRC), a group of >60 faculty and trainees across the United States, formed in March 2020 with the goal to quickly triage and review the large volume of preprints and peer-reviewed publications on SARS-CoV-2 and COVID-19 and summarize the most important, novel evidence to inform pandemic response. From April 6 through December 31, 2020, NCRC teams screened 54 192 peer-reviewed articles and preprints, of which 527 were selected for review and uploaded to the NCRC website for public consumption. Most articles were peer-reviewed publications (n = 395, 75.0%), published in 102 journals; 25.1% (n = 132) of articles reviewed were preprints. The NCRC is a successful model of how academics translate scientific knowledge for practitioners and help build capacity for this work among students. This approach could be used for health problems beyond COVID-19, but the effort is resource intensive and may not be sustainable in the long term.

Curating and translating the evidence about SARS-CoV-2 and COVID-19 for frontline public health and clinical care: The Novel Coronavirus Research Compendium (NCRC).

The public health crisis created by the SARS-CoV-2 pandemic has spurred a deluge of scientific research aimed at informing public health and medical response to the COVID-19 pandemic. However, those working in frontline public health and clinical care had insufficient time to parse the rapidly evolving evidence and use it for decision making. Academics in public health and medicine were well-placed to translate the evidence for use by frontline clinicians and public health practitioners. The Novel Coronavirus Research Compendium (NCRC), a group of >50 faculty and trainees, began in March 2020 with the goal to quickly triage and review the large volume of preprints and peer-reviewed publications on SARS-CoV-2 and COVID-19, and to summarize the most important, novel evidence to inform pandemic response. From April 6, 2020 through January 1, 2021, 54,192 papers and preprints were screened by NCRC teams and 527 were selected for review and uploaded to the NCRC website for public consumption. The majority of papers reviewed were peer-reviewed publications (n=395, 75%), published in 102 journals; 25% (n=132) of papers reviewed were of preprints. The NCRC is a successful model of how academics can support practitioners by translating scientific knowledge into action and help to build capacity among students for this work. This approach could be used for health problems beyond COVID-19, but the effort is resource intensive and may not be sustainable over the long term.

Comparative Performance of Five Commercially Available Serologic Assays To Detect Antibodies to SARS-CoV-2 and Identify Individuals with High Neutralizing Titers.

Accurate serological assays to detect antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to characterize the epidemiology of SARS-CoV-2 infection and identify potential candidates for coronavirus disease 2019 (COVID-19) convalescent plasma (CCP) donation. This study compared the performances of commercial enzyme immunoassays (EIAs) with respect to detection of IgG or total antibodies to SARS-CoV-2 and neutralizing antibodies (nAbs). The diagnostic accuracy of five commercially available EIAs (Abbott, Euroimmun, EDI, ImmunoDiagnostics, and Roche) for detection of IgG or total antibodies to SARS-CoV-2 was evaluated using cross-sectional samples from potential CCP donors who had prior molecular confirmation of SARS-CoV-2 infection (n = 214) and samples from prepandemic emergency department patients without SARS-CoV-2 infection (n = 1,099). Of the 214 potential CCP donors, all were sampled >14 days since symptom onset and only a minority (n = 16 [7.5%]) had been hospitalized due to COVID-19; 140 potential CCP donors were tested by all five EIAs and a microneutralization assay. Performed according to the protocols of the manufacturers to detect IgG or total antibodies to SARS-CoV-2, the sensitivity of each EIA ranged from 76.4% to 93.9%, and the specificity of each EIA ranged from 87.0% to 99.6%. Using a nAb titer cutoff value of ≥160 as the reference representing a positive test result (n = 140 CCP donors), the empirical area under the receiver operating curve for each EIA ranged from 0.66 (Roche) to 0.90 (Euroimmun). Commercial EIAs with high diagnostic accuracy to detect SARS-CoV-2 antibodies did not necessarily have high diagnostic accuracy to detect high nAb titers. Some but not all commercial EIAs may be useful in the identification of individuals with high nAb titers among convalescent individuals.

Comparative performance of five commercially available serologic assays to detect antibodies to SARS-CoV-2 and identify individuals with high neutralizing titers.

Accurate serological assays to detect antibodies to SARS-CoV-2 are needed to characterize the epidemiology of SARS-CoV-2 infection and identify potential candidates for COVID-19 convalescent plasma (CCP) donation. This study compared the performance of commercial enzyme immunoassays (EIAs) to detect IgG or total antibodies to SARS-CoV-2 and neutralizing antibodies (nAb). The diagnostic accuracy of five commercially available EIAs (Abbott, Euroimmun, EDI, ImmunoDiagnostics, and Roche) to detect IgG or total antibodies to SARS-CoV-2 was evaluated from cross-sectional samples of potential CCP donors that had prior molecular confirmation of SARS-CoV-2 infection for sensitivity (n=214) and pre-pandemic emergency department patients for specificity (n=1,102). Of the 214 potential CCP donors, all were sampled >14 days since symptom onset and only a minority had been hospitalized due to COVID-19 (n=16 [7.5%]); 140 potential CCP donors were tested by all five EIAs and a microneutralization assay. When performed according to the manufacturers' protocol to detect IgG or total antibodies to SARS-CoV-2, the sensitivity of each EIA ranged from 76.4% to 93.9%, and the specificity of each EIA ranged from 87.0% to 99.6%. Using a nAb titer cutoff of ≥160 as the reference positive test (n=140 CCP donors), the empirical area under receiver operating curve of each EIA ranged from 0.66 (Roche) to 0.90 (Euroimmun). Commercial EIAs with high diagnostic accuracy to detect SARS-CoV-2 antibodies did not necessarily have high diagnostic accuracy to detect high nAbs. Some but not all commercial EIAs may be useful in the identification of individuals with high nAbs in convalescent individuals.

Variation in False-Negative Rate of Reverse Transcriptase Polymerase Chain Reaction-Based SARS-CoV-2 Tests by Time Since Exposure.

BACKGROUND: Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on reverse transcriptase polymerase chain reaction (RT-PCR) are being used to rule out infection among high-risk persons, such as exposed inpatients and health care workers. It is critical to understand how the predictive value of the test varies with time from exposure and symptom onset to avoid being falsely reassured by negative test results. OBJECTIVE: To estimate the false-negative rate by day since infection. DESIGN: Literature review and pooled analysis. SETTING: 7 previously published studies providing data on RT-PCR performance by time since symptom onset or SARS-CoV-2 exposure using samples from the upper respiratory tract (n = 1330). PATIENTS: A mix of inpatients and outpatients with SARS-CoV-2 infection. MEASUREMENTS: A Bayesian hierarchical model was fitted to estimate the false-negative rate by day since exposure and symptom onset. RESULTS: Over the 4 days of infection before the typical time of symptom onset (day 5), the probability of a false-negative result in an infected person decreases from 100% (95% CI, 100% to 100%) on day 1 to 67% (CI, 27% to 94%) on day 4. On the day of symptom onset, the median false-negative rate was 38% (CI, 18% to 65%). This decreased to 20% (CI, 12% to 30%) on day 8 (3 days after symptom onset) then began to increase again, from 21% (CI, 13% to 31%) on day 9 to 66% (CI, 54% to 77%) on day 21. LIMITATION: Imprecise estimates due to heterogeneity in the design of studies on which results were based. CONCLUSION: Care must be taken in interpreting RT-PCR tests for SARS-CoV-2 infection-particularly early in the course of infection-when using these results as a basis for removing precautions intended to prevent onward transmission. If clinical suspicion is high, infection should not be ruled out on the basis of RT-PCR alone, and the clinical and epidemiologic situation should be carefully considered. PRIMARY FUNDING SOURCE: National Institute of Allergy and Infectious Diseases, Johns Hopkins Health System, and U.S. Centers for Disease Control and Prevention.

Antibody avidity-based approach to estimate population-level incidence of hepatitis C.

BACKGROUND & AIMS: Accurate HCV incidence estimates are critical for monitoring progress towards HCV elimination goals, including an 80% reduction in HCV incidence by 2030. Moreover, incidence estimates can help guide prevention and treatment programming, particularly in the context of the US opioid epidemic. METHODS: An inexpensive, Genedia-based HCV IgG antibody avidity assay was evaluated as a platform to estimate cross-sectional, population-level primary HCV incidence using 1,840 HCV antibody and RNA-positive samples from 875 individuals enrolled in 5 cohort studies in the US and India. Using samples collected <2 years following HCV seroconversion, the mean duration of recent infection (MDRI) was calculated by fitting a maximum likelihood binomial regression model to the probability of appearing recent. Among samples collected ≥2 years post-HCV seroconversion, an individual-level false recent ratio (FRR) was calculated by estimating the probability of appearing recent using an exact binomial test. Factors associated with falsely appearing recent among samples collected ≥2 years post seroconversion were determined by Poisson regression with generalized estimating equations and robust variance estimators. RESULTS: An avidity index cut-off of <40% resulted in an MDRI of 113 days (95% CI 84-146), and FRRs of 0.4% (95% CI 0.0-1.2), 4.6% (95% CI 2.2-8.3), and 9.5% (95% CI 3.6-19.6) among individuals who were HIV-uninfected, HIV-infected, and HIV-infected with a CD4 count <200/µl, respectively. No variation was seen between HCV genotypes 1 and 3. In hypothetical scenarios of high-risk settings, a sample size of <1,000 individuals could reliably estimate primary HCV incidence. CONCLUSIONS: This cross-sectional approach can estimate primary HCV incidence for the most common genotypes. This tool can serve as a valuable resource for program and policy planners seeking to monitor and reduce HCV burden. LAY SUMMARY: Determining the rate of new hepatitis C virus (HCV) infections in a population is critical to monitoring progress toward HCV elimination and to appropriately guide control efforts. However, since HCV infections are most often initially asymptomatic, it is difficult to estimate the rate of new HCV infections without following HCV-uninfected people over time and repeatedly testing them for HCV infection. Here, we present a novel, resource-efficient method to estimate the rate of new HCV infections in a population using data from a single timepoint.

Adolescent Anabolic-Androgenic Steroid Use in Association with Other Drug Use, Injection Drug Use, and Team Sport Participation.

Introduction: The majority of epidemiologic research on adolescent non-medical anabolic-androgenic steroid (AAS) use was conducted in the 1990s and early 2000s, indicating a need to update evidence for the modern era. We aim to understand the prevalence of AAS use among US adolescents and assess associations between AAS use, sports participation, other drug use, and injection drug use (IDU). Methods: Using data from the 2017 National Youth Risk Behavior Survey, we estimated the prevalence of AAS use and tested for associations between AAS use, sports participation, and drug use, overall and by sex. Results: The prevalence of AAS use was 2.98%. The prevalence among boys (3.46%) was higher than among girls (2.41%). AAS use was high among youth with lifetime heroin use (64.41%) and IDU (64.42%). There was no association between AAS and team sport participation (p=0.61). Conclusions: Our results indicate that adolescent AAS use is an aspect of polysubstance use rather than a substance used solely for performance enhancement in sports. Research with adolescents should be mindful of the overlap of heroin and AAS use among youth with IDU.

Prevalence of Hepatitis B and Hepatitis D Virus Infections in the United States, 2011-2016.

Among adults in the 2011-2016 National Health and Nutrition Examination Survey (NHANES), the estimated prevalence of hepatitis B surface antigen (HBsAg) was 0.36% overall and 3.4% in non-Hispanic Asians. Among adult HBsAg carriers, 42% had antibodies to hepatitis delta virus (anti-HDV). Routine anti-HDV testing should be considered for HBsAg carriers.

Limited Coverage of Hepatitis C Virus Testing in the United States, 2013-2017.

In the US household population, hepatitis C virus testing coverage marginally increased between 2013 and 2017 among persons born between 1966 and 1994 (13.2% to 16.8%) and persons born between 1945 and 1965 (12.3% to 17.3%). Testing coverage remains limited and sociodemographic disparities were observed in both populations.

Hepatitis E Virus Seroprevalence and Correlates of Anti-HEV IgG Antibodies in the Rakai District, Uganda.

A cross-sectional study was conducted of 500 human immunodeficiency virus (HIV)-infected adults frequency matched on age, sex, and community to 500 HIV-uninfected individuals in the Rakai District, Uganda to evaluate seroprevalence of anti-hepatitis E virus (HEV) IgG antibodies. HEV seroprevalence was 47%, and 1 HIV-infected individual was actively infected with a genotype 3 virus. Using modified Poisson regression, male sex (prevalence ratios [PR] = 1.247; 95% confidence interval [CI], 1.071-1.450) and chronic hepatitis B virus infection (PR = 1.377; 95% CI, 1.090-1.738) were associated with HEV seroprevalence. HIV infection status (PR = 0.973; 95% CI, 0.852-1.111) was not associated with HEV seroprevalence. These data suggest there is a large burden of prior exposure to HEV in rural Uganda.

Use of Hepatitis C Virus (HCV) Immunoglobulin G Antibody Avidity as a Biomarker to Estimate the Population-Level Incidence of HCV Infection.

BACKGROUND: Sensitive methods are needed to estimate the population-level incidence of hepatitis C virus (HCV) infection. METHODS: We developed an HCV immunoglobulin G (IgG) antibody avidity assay by modifying the Ortho 3.0 HCV enzyme-linked immunoassay and tested 997 serum or plasma samples from 568 people who inject drugs enrolled in prospective cohort studies. Avidity-based testing algorithms were evaluated by their (1) mean duration of recent infection (MDRI), defined as the average time an individual is identified as having been recently infected, according to a given algorithm; (2) false-recent rate, defined as the proportion of samples collected >2 years after HCV seroconversion that were misclassified as recent; (3) sample sizes needed to estimate incidence; and (4) power to detect a reduction in incidence between serial cross-sectional surveys. RESULTS: A multiassay algorithm (defined as an avidity index of <30%, followed by HCV viremia detection) had an MDRI of 147 days (95% confidence interval [CI], 125-195 days), and the false-recent rates were 0.7% (95% CI, .2%-1.8%) and 7.6% (95% CI, 4.2%-12.3%) among human immunodeficiency virus (HIV)-negative and HIV-positive persons, respectively. In various simulated high-risk populations, this algorithm required <1000 individuals to estimate incidence (relative standard error, 30%) and had >80% power to detect a 50% reduction in incidence. CONCLUSIONS: Avidity-based algorithms have the capacity to accurately estimate HCV infection incidence and rapidly assess the impact of public health efforts among high-risk populations. Efforts to optimize this method should be prioritized.