Do we underestimate risk of cardiovascular mortality due to lead exposure?

BACKGROUND: Studies using data from the National Health and Nutrition Examination Survey-III (NHANES-III) have demonstrated significant prospective associations between blood lead levels and increased mortality. Bone lead represents cumulative lead burden and thus is a better biomarker for assessing chronic impacts, but its in vivo assessment requires special K-x-ray fluorescence (KXRF) instrumentation. Our team recently developed an algorithm predicting bone lead levels from a combination of blood lead levels, age and other socioeconomic and behavioral variables. We examined the associations of our algorithm-estimated bone lead levels and mortality in NHANES-III. METHODS: We included 11,628 adults followed up to December 31, 2019. Estimated tibia lead and patella lead levels were calculated using our prediction algorithms. We used survey-weighted Cox proportional hazards models to compute hazard ratios (HRs) and 95 % confidence intervals (CIs). RESULTS: During the median follow-up of 26.8 years, 4900 participants died (mortality rate = 1398 per 100,000 adults/year). Geometric means (95 % CIs) of blood lead, predicted tibia lead, and predicted patella lead were 2.69 µg/dL (2.54, 2.84), 6.73 µg/g (6.22, 7.25), and 16.3 µg/g (15.9, 16.8), respectively. The associations for all-cause mortality were similar between blood lead and bone lead. However, the associations for cardiovascular mortality were much greater with predicted bone lead markers compared to blood lead: for comparing participants at the 90th vs. 10th percentiles of exposure, HR = 3.32 (95 % CI: 1.93-5.73) for tibia lead, 2.42 (1.56-3.76) for patella lead, 1.63 (1.25-2.14) for blood lead. The population attributable fractions for cardiovascular disease mortality if everyone's lead concentrations were declined to the 10th percentiles were 45.8 % (95 % CI: 28.1-59.4) for tibia lead, 33.1 % (18.1-45.8) for patella lead, and 22.8 % (10.4-33.8) for blood lead. CONCLUSIONS: These findings suggest that risk assessment for cardiovascular mortality based on blood lead levels may underestimate the true mortality risk of lead exposure.

Predicting the Climate Impact of Healthcare Facilities Using Gradient Boosting Machines.

Health care accounts for 9-10% of greenhouse gas (GHG) emissions in the United States. Strategies for monitoring these emissions at the hospital level are needed to decarbonize the sector. However, data collection to estimate emissions is challenging, especially for smaller hospitals. We explored the potential of gradient boosting machines (GBM) to impute missing data on resource consumption in the 2020 survey of a consortium of 283 hospitals participating in Practice Greenhealth. GBM imputed missing values for selected variables in order to predict electricity use and beef consumption (R2=0.82) and anesthetic gas desflurane use (R2=0.51), using administrative data readily available for most hospitals. After imputing missing consumption data, estimated GHG emissions associated with these three examples totaled over 3 million metric tons of CO2 equivalent emissions (MTCO2e). Specifically, electricity consumption had the largest total carbon footprint (2.4 MTCO2e), followed by beef (0.6 million MTCO2e) and desflurane consumption (0.03 million MTCO2e) across the 283 hospitals. The approach should be applicable to other sources of hospital GHGs in order to estimate total emissions of individual hospitals and to refine survey questions to help develop better intervention strategies.

Dose dependence of prenatal fluoride exposure associations with cognitive performance at school age in three prospective studies.

BACKGROUND: Fluoride may be a developmental neurotoxicant at elevated exposures. We merged new data from a prospective Odense Child Cohort (OCC) with results from two previous birth cohort studies from Mexico and Canada to characterize the dose-effect relationship in greater detail. METHODS: The OCC contributed 837 mother-child pairs to the total of >1500. We measured creatinine-adjusted urine-fluoride concentrations in maternal urine samples obtained during late pregnancy. Child IQ was determined at age 7 years using an abbreviated version of the Wechsler Intelligence Scales for Children. Findings from the three cohorts were used to calculate the joint benchmark concentration (BMC) and the lower confidence limit (BMCL) after adjustment for covariables. RESULTS: In the OCC, urine-fluoride concentrations varied between 0.08 and 3.04 mg/l (median 0.52 mg/l) but were not significantly associated with full-scale IQ at age 7 years (ß = 0.08; 95% confidence interval -1.14 to 1.30 for a doubling in exposure). No difference was apparent between boys and girls. In the OCC, the BMC was 0.92 mg/l, with a BMCL of 0.30 mg/l. The joint analysis of all three cohorts showed a statistically significant association between urine-fluoride and IQ, with a BMC of 0.45 mg/l (BMCL, 0.28 mg/l), slightly higher than the BMC previously reported for the two North American cohorts alone. CONCLUSIONS: As the BMCL reflects an approximate threshold for developmental neurotoxicity, the results suggest that pregnant women and children may need protection against fluoride toxicity.

Association between levels of receptor binding domain antibodies of SARS-CoV-2, receipt of booster and risk of breakthrough infections: LA pandemic surveillance cohort study.

Prevention of COVID-19 with vaccine requires multiple doses and updated boosters to maintain protection; however currently there are no tests that can measure immunity and guide clinical decisions about timing of booster doses. This study examined the association between the risk of COVID-19 breakthrough infections and receptor binding domain (RBD) antibody levels and receipt of booster of COVID-19 vaccines. A community sample of Los Angeles County adults were surveyed between 2021 and 2022 to determine if they had a self-reported breakthrough infection. Predictors included RBD antibody levels, measured by binding antibody responses to the ancestral strain at baseline and self-reported booster shot during the study period. Of the 859 participants, 182 (21%) reported a breakthrough infection. Irrespective of the level of antibodies, the risk of breakthrough infection was similar, ranging from 19 to 23% (P = 0.78). The risk of breakthrough infections was lower among participants who had a booster shot (P = 0.004). The protective effect of a booster shot did not vary by antibody levels prior to receiving the booster. This study found no association between RBD antibody levels and risk of breakthrough infections, while the receipt of booster was associated with lower risk of breakthrough infections, which was independent of pre-booster antibody levels. Therefore, antibody levels might not be a useful guide for clinical decisions about timing of booster doses.

Urinary fluoride levels and metal co-exposures among pregnant women in Los Angeles, California.

BACKGROUND: Fluoride is ubiquitous in the United States (US); however, data on biomarkers and patterns of fluoride exposure among US pregnant women are scarce. We examined specific gravity adjusted maternal urinary fluoride (MUFsg) in relation to sociodemographic variables and metal co-exposures among pregnant women in Los Angeles, California. METHODS: Participants were from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) cohort. There were 293 and 490 women with MUFsg measured during first and third trimesters, respectively. An intra-class correlation coefficient examined consistency of MUFsg between trimesters. Kruskal-Wallis and Mann-Whitney U tests examined associations of MUFsg with sociodemographic variables. Covariate adjusted linear regression examined associations of MUFsg with blood metals and specific gravity adjusted urine metals among a subsample of participants within and between trimesters. A False Discovery Rate (FDR) correction accounted for multiple comparisons. RESULTS: Median (IQR) MUFsg was 0.65 (0.5) mg/L and 0.8 (0.59) mg/L, during trimesters one and three respectively. During both trimesters, MUFsg was higher among older participants, those with higher income, and White, non-Hispanic participants than Hispanic participants. MUFsg was also higher for White, non-Hispanic participants than for Black, non-Hispanic participants in trimester three, and for those with graduate training in trimester one. MUFsg was negatively associated with blood mercury in trimester one and positively associated with blood lead in trimester three. MUFsg was positively associated with various urinary metals, including antimony, barium, cadmium, cobalt, copper, lead, nickel, tin, and zinc in trimesters one and/or three. CONCLUSIONS: MUFsg levels observed were comparable to those found in pregnant women in Mexico and Canada that have been associated with poorer neurodevelopmental outcomes. Lower urinary fluoride levels among Hispanic and non-Hispanic Black participants in MADRES compared to non-Hispanic White participants may reflect lower tap water consumption or lower fluoride exposure from other sources. Additional research is needed to examine whether MUFsg levels observed among pregnant women in the US are associated with neurodevelopmental outcomes.

Characteristics associated with attitudes and behaviors towards mask wearing during the COVID-19 pandemic: The Trojan Pandemic Response Initiative.

BACKGROUND: Attitudes and behaviors towards mask wearing may influence the ability to reduce transmission of COVID-19 and other diseases. METHODS: University students, staff, and faculty (N = 9653) responded to an email invitation to complete electronic surveys (November 2021 and April 2022). Surveys included 19 items measuring attitudes and behaviors towards mask wearing from the Understanding America Study. Linear mixed models including variables for sex, age group, division, race and ethnicity, political affiliation, and history of COVID-19, were used to estimate the mean difference of the mean score for attitudes and behavior between Time 1 (November 2021) and Time 2 (April 2022). RESULTS: Participants were mostly female (62.1%), students (70.6%), White (39.5%) and Asian (34.7%). More than half identified their political affiliation as Democrat (65.5%). Characteristic variable-by-time interactions for difference in mean mask attitude scores difference were significant at Time 1 (T1) and Time 2 (T2) between Black and White participants (B = 0.18 (0.05), 95% CI: 0.07, 0.28, p = 0.001), Asian and White participants (B = 0.07 (0.02), 95% CI: 0.03-0.12, p = 0.001), participants with self-reported history of COVID-19 and no history of COVID-19 (B= -0.13 (0.02), 95% CI: -0.07, -0.18, p < 0.0001), females and males (B = 0.07 (0.02), 95% CI: 0.03, 0.11, p = 0.001), Republicans and Democrats (B= -0.18 (0.04), 95%CI: -0.26, -0.10, p < 0.0001) and Independents and Democrats (B= -0.10 (0.03), 95%CI: -0.15, -0.05, p < 0.0001). Mean difference in mean scores for mask behaviors at Time and Time 2 were significant between participants with COVID-19 and participants who did not have COVID-19 (B= -0.12 (0.04), 95% CI: -0.19, -0.04, p = 0.004), students compared to faculty and staff (B=-0.22 (0.05), -0.32, -0.12, p < 0.0001), between Republicans and Democrats (B-= -0.16 (0.07), 95% CI: -0.28, -0.03, p = 0.020, and between Independents and Democrats (B=-0.08 (0.04), 95% CI: -0.16, -0.002, p = 0.04). CONCLUSION: Race and ethnicity, political affiliation, and division may affect attitudes and behaviors in mask wearing. Further investigation into how characteristics influence public health measures such as mask wearing is needed to contain the spread of the COVID-19 virus, other infectious diseases, and future pandemics.

Early Lead Exposure Associated with Molar Hypomineralization.

Purpose: The purpose of this study was to determine the association between prenatal and early life exposure to lead and the presence of molar hypomineralization (MH) in a group of Mexican children. Methods: A subset of participants of the Early Life Exposure in Mexico to Environmental Toxicants (ELEMENTS) cohort study was examined for the presence of molar hypomineralization using European Academy of Pedi- atric Dentistry (EAPD) criteria. Prenatal lead exposure was assessed by K-ray fluorescence measurements of patella and tibia lead and by maternal blood lead levels by trimester and averaged over trimesters. Postnatal exposure was assessed by levels of maternal blood lead at delivery and child blood lead at 12 and 24 months. Results: A subset of 506 subjects from the ELEMENT cohorts (nine to 18 years old) were examined for MH; 87 subjects (17.2 percent) had MH. Maternal blood lead levels in the third trimester (odds ratio [OR] equals 1.08; 95 percent confidence interval [95% CI] equals 1.02 to 1.15) and averaged over three trimesters (OR equals 1.10; 95% CI equals 1.02 to 1.19) were significantly associated with MH status. None of the maternal bone lead or the child's blood lead parameters was significantly associated with the presence of MH (P>0.05). Conclusions: This study documents a significant association between prenatal lead exposure especially in late pregnancy and the odds of molar hypomineralization.

Altered Tumor Necrosis Factor Response in Neurologic Postacute SARS-CoV-2 Syndrome.

Neurologic manifestations of postacute sequelae after SARS-CoV-2 infection (neuro-PASC) are common; however, the underlying drivers of those symptoms remain poorly understood. Prior work has postulated that immune dysregulation leads to ongoing neuroinflammation. We aimed to identify the cytokines involved in that immune dysregulation by comparing 37 plasma cytokine profiles among 20 case patients with neuro-PASC to 20 age- and gender-matched controls. Neuro-PASC cases were defined as individuals with self-reported persistent headache, general malaise, and anosmia or ageusia at least 28 days post-SARS-CoV-2 infection. As a sensitivity analysis, we repeated the main analysis among only participants of Hispanic heritage. In total, 40 specimens were tested. Participants were an average of 43.5 years old (interquartile range 30-52), 20 (50.0%) of whom identified as women. Levels of tumor necrosis factor alpha (TNFα) were 0.76 times lower [95% confidence interval (CI) 0.62-0.94] among cases of neuro-PASC compared with controls, as were levels of C-C motif chemokine 19 (CCL19) (0.67; 95% CI 0.50-0.91), C-C motif chemokine 2 (CCL2) (0.72; 95% CI 0.55-0.95), chemokine interferon-gamma inducible protein 10 (CXCL10) (0.63; 95% CI 0.42-0.96), and chemokine interferon-gamma inducible protein 9 (CXCL9) (0.62; 95% CI 0.38-0.99). Restricting analysis of TNF and CCL19 to participants who identified as Hispanic did not alter results. We noted a reduction in TNFα and down-stream chemokines among patients with neuro-PASC, suggesting an overall immune attenuation.

SARS-CoV-2 viral variants can rapidly be identified for clinical decision making and population surveillance using a high-throughput digital droplet PCR assay.

Epidemiologic surveillance of circulating SARS-CoV-2 variants is essential to assess impact on clinical outcomes and vaccine efficacy. Whole genome sequencing (WGS), the gold-standard to identify variants, requires significant infrastructure and expertise. We developed a digital droplet polymerase chain reaction (ddPCR) assay that can rapidly identify circulating variants of concern/interest (VOC/VOI) using variant-specific mutation combinations in the Spike gene. To validate the assay, 800 saliva samples known to be SARS-CoV-2 positive by RT-PCR were used. During the study (July 2020-March 2022) the assay was easily adaptable to identify not only existing circulating VAC/VOI, but all new variants as they evolved. The assay can discriminate nine variants (Alpha, Beta, Gamma, Delta, Eta, Epsilon, Lambda, Mu, and Omicron) and sub-lineages (Delta 417N, Omicron BA.1, BA.2). Sequence analyses confirmed variant type for 124/124 samples tested. This ddPCR assay is an inexpensive, sensitive, high-throughput assay that can easily be adapted as new variants are identified.

Surveillance of Severe Acute Respiratory Syndrome Coronavirus 2 and Variants Using Digital Droplet Polymerase Chain Reaction at a Large University and Healthcare System in California.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with different infectivity, transmission potential, and morbidity change the characteristics of local epidemics and affect vaccine effectiveness. As part of the University of Southern California COVID-19 Pandemic Research Center's efforts to understand, control, and inform local community on coronavirus disease 2019 (COVID-19), we implemented a SARS-CoV-2 surveillance program among students, employees, and USC Keck Medical Center patients. We present the epidemiology and distribution of SARS-CoV-2 and its variants among the population. Methods: We used digital droplet reverse-transcriptase polymerase chain reaction (PCR) to analyze in real-time remnant SARS-CoV-2 PCR-positive saliva specimens stored at the USC Keck Medicine laboratory between September 2020 and April 2022. Samples were tested for the original strain (A20) and 9 SARS-CoV-2 variants: α(B.1.1.7, Q.1-Q.8), ß(B.1.351, B.1.351.2, B.1.351.3), γ(P.1, P.1.1, P.1.2), δ(B.1.617.2), δ+(or δ417N), ε(B.1.427 and B.1.429), η(B.1.525), λ(C.37) and ο(B.1.1.529, ΒΑ.1, BA.2). We reviewed deidentified health information from positive cases including demographics, history of COVID-19 (eg, symptoms, hospitalizations, and repeat infections), and COVID-19 vaccination status. Results: We reviewed 1169 cases and determined the variant type of 482 specimens: 77 specimens were original strain, 119 "Delta", 165 "Omicron". The original strain was detected during the third and fourth quarters of 2020. The Delta variant appeared during the second quarter of 2021, whereas Omicron appeared in the fourth quarter of 2021. Conclusions: Prospectively tracking SARS-CoV-2 variants in a university population and a hospital system, utilizing a low-cost, high-throughput PCR assay, was feasible. Local variant monitoring remains important to inform prevention and control efforts among university and clinical settings.

Trust in science and scientists among university students, staff, and faculty of a large, diverse university in Los Angeles during the COVID-19 pandemic, the Trojan Pandemic Response Initiative.

BACKGROUND: Mistrust in science and scientists may adversely influence the rate of COVID-19 vaccination and undermine public health initiatives to reduce virus transmission. METHODS: Students, staff and faculty responded to an email invitation to complete an electronic survey. Surveys included 21-items from the Trust in Science and Scientists Inventory questionnaire. Responses were coded so higher scores indicated a higher trust in science and scientists, A linear regression model including sex, age group, division, race and ethnicity, political affiliation, and history of COVID-19, was used to determine variables significantly associated with trust in science and scientists scores at the p < 0.05 level. RESULTS: Participants were mostly female (62.1%), Asian (34.7%) and White (39.5%) and students (70.6%). More than half identified their political affiliation as Democrat (65%). In the final regression model, all races and ethnicities had significantly lower mean trust in science and scientists scores than White participants [Black ([Formula: see text]= -0.42, 95% CI: -0.55, -0.43, p < 0.001); Asian ([Formula: see text]= -0.20, 95% CI: -0.24, -0.17, p < 0.001); Latinx ([Formula: see text]= -0.22, 95% CI: -0.27, -0.18, p < 0.001); Other ([Formula: see text]= -0.19, 95% CI: -0.26, -0.11, p < 0.001)]. Compared to those identifying as Democrat, all other political affiliations had significantly lower mean scores. [Republican ([Formula: see text] =-0.49, 95% CI: -0.55, -0.43, p < 0.0001); Independent ([Formula: see text] =-0.29, 95% CI: -0.33, -0.25, p < 0.0001); something else ([Formula: see text] =-0.19, 95% CI: -0.25, -0.12, p < 0.0001)]. Having had COVID-19 ([Formula: see text]= -0.10, 95% CI: -0.15, -0.06, p < 0.001) had significantly lower scores compared to those who did not have COVID-19. CONCLUSION: Despite the setting of a major research University, trust in science is highly variable. This study identifies characteristics that could be used to target and curate educational campaigns and university policies to address the COVID19 and future pandemics.

Correlates of COVID-19 vaccination status among college students.

Objectives: Despite the widespread availability of COVID-19 vaccines in the United States, vaccine hesitancy remains high among certain groups. This study examined the correlates of being unvaccinated among a sample of students attending a single university (N = 2900) during the spring and summer of 2021, when the campus had been closed for over a year and students were preparing to return to in-person learning. Methods: Students responded to an email invitation and completed electronic surveys. Results: In multivariable logistic regression analyses, students were more likely to be unvaccinated if they were African American, identified with any political affiliation other than Democrat, were undergraduates or international students, had not traveled outside the Los Angeles during the pandemic, and/or had previously been ill with COVID-19. Conclusion: Findings indicate that culturally resonant educational interventions, and possibly vaccine requirements, are needed to promote vaccination among university students.

Quantification of Severe Acute Respiratory Syndrome Coronavirus 2 Binding Antibody Levels To Assess Infection and Vaccine-Induced Immunity Using WHO Standards.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binding antibody (Ab) levels following vaccination or natural infection could be used as a surrogate for immune protection if results of serological assays were standardized to yield quantitative results using an international standard. Using a bead-based serological assay (Luminex xMAP), anti-receptor binding domain (anti-RBD) Ab levels were determined for 1,450 participants enrolled in the Los Angeles Pandemic Surveillance Cohort (LAPSC) study. For 123 participants, SARS-CoV-2 binding antibody unit (BAU) levels were also quantified using WHO standards and then compared to the semiquantitative results. Samples were chosen to represent the range of results and time from vaccination. Antibody levels and decay rates were then compared using unadjusted and adjusted linear regression models. The linear range of the assay used in this study was determined to be 300 to 5,000 mean fluorescence intensity units (MFI). Among the fully vaccinated groups (vaccinated only and vaccinated with past infection), 84.8% had anti-RBD MFI values above the linear range of >5,000 MFI, and 33.8% had values of >15,000 MFI. Among vaccinated participants with past infection (hybrid immunity), 97% had anti-RBD values of >5,000 MFI and 70% (120/171) had anti-RBD values of >15,000 MFI. In the subgroup quantified using the WHO control, BAU levels were significantly higher than the semiquantitative MFI results. In vaccinated participants, Ab decay levels were similar between infected and noninfected groups (P = 0.337). These results demonstrate that accurate quantitation is possible if standardized with an international standard. BAU can then be compared over time or between subjects and would be useful in clinical decision making. IMPORTANCE Accurate quantification of SARS-CoV-2-specific antibodies can be achieved using a universal standard with sample dilution within the linear range. With hybrid immunity being now common, it is critical to use protocols adapted to high Ab levels to standardize serological results. We validated this approach with the Los Angeles Pandemic Surveillance Cohort by comparing the antibody decay rates in vaccinated participants and vaccinated infected participants.

Predicting cumulative lead (Pb) exposure using the Super Learner algorithm.

Chronic lead (Pb) exposure causes long term health effects. While recent exposure can be assessed by measuring blood lead (half-life 30 days), chronic exposures can be assessed by measuring lead in bone (half-life of many years to decades). Bone lead measurements, in turn, have been measured non-invasively in large population-based studies using x-ray fluorescence techniques, but the method remains limited due to technical availability, expense, and the need for licensing radioactive materials used by the instruments. Thus, we developed prediction models for bone lead concentrations using a flexible machine learning approach--Super Learner, which combines the predictions from a set of machine learning algorithms for better prediction performance. The study population included 695 men in the Normative Aging Study, aged 48 years and older, whose bone (patella and tibia) lead concentrations were directly measured using K-shell-X-ray fluorescence. Ten predictors (blood lead, age, education, job type, weight, height, body mass index, waist circumference, cumulative cigarette smoking (pack-year), and smoking status) were selected for patella lead and 11 (the same 10 predictors plus serum phosphorus) for tibia lead using the Boruta algorithm. We implemented Super Learner to predict bone lead concentrations by calculating a weighted combination of predictions from 8 algorithms. In the nested cross-validation, the correlation coefficients between measured and predicted bone lead concentrations were 0.58 for patella lead and 0.52 for tibia lead, which has improved the correlations obtained in previously-published linear regression-based prediction models. We evaluated the applicability of these prediction models to the National Health and Nutrition Examination Survey for the associations between predicted bone lead concentrations and blood pressure, and positive associations were observed. These bone lead prediction models provide reasonable accuracy and can be used to evaluate health effects of cumulative lead exposure in studies where bone lead is not measured.

Factors associated with parents' willingness to vaccinate their children against COVID-19: The LA pandemic surveillance cohort study.

Background: Children age 5-11 became eligible for COVID-19 vaccination in November 2021 in the United States, but vaccine uptake in this age group remains low. Understanding reasons why parents are hesitant to vaccinate their children may provide critical insights to help protect children from COVID-19 infection. This study examines factors associated with parents' willingness to vaccinate their children. Methods: We conducted a cross-sectional survey focusing on the Los Angeles County adult residents between March and June 2021. Our analytic sample focused on a subgroup of participants who self-report having a child. Predictors included parents' vaccination status and beliefs about COVID-19. We used multivariable logistic regression analysis and calculated the predicted probabilities of parents' willingness to vaccinate their children. Results: Parents (n = 401) who worried about catching the virus, had trust in vaccine development and the COVID-19 vaccine approval process, and vaccinated against COVID-19 were more likely to be willing to vaccinate their children. Socio-economic, racial and ethnic differences were no longer statistically significant in the adjusted model. Predicted probabilities of parents who were willing to vaccine their children were 55% among the vaccinated and 36% among the unvaccinated. Conclusions: Parents' intent to vaccinate their children is influenced by their perceived severity of the pandemic, trust in the vaccine development process, and their vaccination status, which can be the potential drivers of hesitancy to vaccinate their children.