Single Exposure Models Research Articles

The association between traffic noise and self-rated health within the German National Cohort (NAKO)

Abstract Objectives Traffic noise can cause stress and disturb sleep, impacting health in many ways. However, few large studies on this topic exist. We investigated the association between traffic noise and self-rated health (SRH) within the German National Cohort (NAKO). Methods NAKO enrolled >200,000 adults ages 20-74 at 18 sites in Germany. We used logistic regression to test whether 1) annual mean 24-hour ambient traffic noise levels at or above 55 dB(A) within a 10-meter residential buffer and 2) subjectively reported nighttime traffic noise annoyance were associated with higher odds of reporting fair/poor SRH. We calculated these associations within the full sample, stratified by sex, and stratified by age group (≤39 years, 40-59 years, ≥60 years). We adjusted for study site, age, sex, marital status, education level, and migration background. Results Among participants without missing data (n = 121,232), moderate annoyance was associated with 1.27 higher odds (95% CI 1.21-1.32) and strong annoyance with 1.75 higher odds (95% CI 1.65-1.84) of fair/poor SRH, while annual mean noise ≥55 dB(A) was associated with 1.07 higher odds (95% CI 1.03-1.12). Females who reported strong annoyance had especially high odds of fair/poor SRH (OR 1.81, 95% CI 1.69-1.95), as did those aged 40-59 years who reported high annoyance (OR 1.78, 95% CI 1.66-1.92). Those 39 and under had no significant increase in odds of fair/poor SRH if they reported moderate annoyance or if they were exposed to ≥ 55 dB(A) annual mean noise. In single exposure models, noise annoyance and objectively measured noise were both significantly associated with higher odds of reporting fair/poor SRH, but in combined models, the effect of objectively measured noise became insignificant while the effect of annoyance remained strongly significant. Conclusions These findings confirm that traffic noise is an important public health issue. Further analyses on most affected populations should inform noise protection policies. Key messages • Higher levels of traffic noise are associated with worse self-rated health. • Ambient noise is an important public health issue for which more research is needed.

Association between urinary phthalate metabolites and Anemia in US adults

Initial research indicates a possible connection between exposure to phthalates and the development of anemia. To fill the gap in epidemiological data, our study utilized data from across the United States, representative on a national scale, to evaluate the association between the concentration of phthalate metabolites in urine and both anemia and iron levels. We gathered data on 11,406 individuals from the National Health and Nutrition Examination Survey (NHANES) database, spanning 2003–2018. We conducted logistic and linear regression analyses, adjusted for potential confounding factors, to evaluate the correlations between different phthalate metabolites and anemia, as well as serum iron levels, including gender-stratified analysis. Most urinary phthalate metabolites were positively correlated with an increased risk of anemia, and the majority were negatively correlated with serum iron levels. The study revealed that for every unit increase in ln-transformed metabolite concentrations, the odds ratios (ORs) for anemia increased to varying degrees, depending on the phthalate: Monobutyl phthalate (MBP) at 1.08 (95% CI 1.01–1.17, P = 0.0314), mono(3-carboxypropyl) phthalate (MCPP) at 1.17 (95% CI 1.10–1.24, P < 0.0001), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) at 1.08 (95% CI 1.02–1.15, P = 0.0153), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) at 1.14 (95% CI 1.07–1.21, P < 0.0001), mono(2-ethyl-5-carboxypentyl) phthalate (MECPP) at 1.11 (95% CI 1.03–1.18, P = 0.0030), monocarboxynonyl phthalate (MCNP) at 1.11 (95% CI 1.03–1.19, p = 0.0050), and monocarboxyoctyl phthalate (MCOP) at 1.13 (95% CI 1.07–1.19, P < 0.0001). Increased levels of MBP, MEHP, MBzP, MCPP, MEHHP, MEOHP, MIBP, MECPP, MCNP, and MCOP were linked with changes in serum iron levels, ranging from − 0.99 µg/dL (95% CI − 1.69 to − 0.29) to − 3.72 µg/dL (95% CI − 4.32 to − 3.11). Mixed-exposure analysis shows consistency with single-exposure model. Further mediation analysis showed that the association between single urinary phthalates and the risk of anemia was mediated by serum iron with a mediation ratio of 24.34–95.48% (P < 0.05). The presence of phthalate metabolites in urine shows a positive correlation with the prevalence of anemia, which was possibly and partly mediated by iron metabolism. Nonetheless, to confirm a definitive causal link and comprehend the underlying mechanisms of how phthalate exposure influences anemia, additional longitudinal and experimental research is required.

The association of mixed multi-metal exposure with sleep duration and self-reported sleep disorder: A subgroup analysis from the National Health and Nutrition Examination Survey (NHANES)

Sleep disorders significantly affect sleep duration and constitute a major public health issue. However, the relationship between metal exposure and sleep is not fully elucidated. This study utilized publicly available data from the National Health and Nutrition Examination Survey (NHANES) to measure blood concentrations of seven metals—copper (Cu), zinc (Zn), selenium (Se), manganese (Mn), mercury (Hg), cadmium (Cd), and lead (Pb)—in a cohort of 4263 American adults. The relationship between metal exposure and self-reported sleep duration and sleep disorder risk was analyzed using single exposure models like logistic and linear regression and mixedexposure models such as weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR). The results indicated an absence of statistically significant findings in the single exposure model. In contrast, the mixed exposure model revealed a positive correlation between selenium levels and the risk of sleep disorders across the entire population. A “U-shaped” association was identified between copper levels and the risk of sleep disorders in males, females, and individuals aged 60 and above. Moreover, a positive trend was observed between manganese levels and the risk of sleep disorders in individuals aged 60 and above. Additionally, elevated concentrations of metal mixtures were significantly associated with reduced sleep duration among females. Sensitivity analyses corroborated these findings. In conclusion, within the context of metal mixtures, selenium may be a risk factor for sleep disorders in the general population. Manganese may be a unique risk factor in older adults. Copper levels have a “U" shaped link to sleep disorder risk in specific population subgroups. Finally, the accumulation of blood metal mixtures in females, mainly due to lead and mercury, may reduce sleep duration. Further research is necessary to validate these findings.

Moderate BMI accumulation modified associations between blood benzene, toluene, ethylbenzene and xylene (BTEX) and phenotypic aging: mediating roles of inflammation and oxidative stress

The associations between blood benzene, toluene, ethylbenzene, and xylenes (BTEX) and biological aging among general adults remain elusive. The present study comprised 5780 participants from the National Health and Nutrition Examination Survey 1999–2010. A novel measure of biological aging, phenotypic age acceleration (PhenoAge.Accel), derived from biochemical markers was calculated. Weighted generalized linear regression and weighted quantile sum regression (WQS) were utilized to assess the associations between BTEX components and mixed exposure, and PhenoAge.Accel. The mediating roles of systemic immune-inflammation index (SII) and oxidative stress indicators (serum bilirubin and gamma-glutamyl transferase), along with the modifying effects of body mass index (BMI) were also examined. In the single-exposure model, the highest quantile of blood benzene (b = 0.89, 95%CI: 0.58 to 1.20), toluene (b = 0.87, 95%CI: 0.52 to 1.20), and ethylbenzene (b = 0.80, 95%CI: 0.46 to 1.10) was positively associated with PhenoAge.Accel compared to quantile 1. Mixed-exposure analyses revealed a consistent positive association between BTEX mixed exposure and PhenoAge.Accel (b = 0.88, 95%CI: 0.56 to 1.20), primarily driven by benzene (92.78%). The association between BTEX and PhenoAge.Accel was found to be partially mediated by inflammation and oxidative stress indicators (ranging from 3.2% to 13.7%). Additionally, BMI negatively modified the association between BTEX mixed exposure and PhenoAge.Accel, with a threshold identified at 36.2 kg/m^2. Furthermore, BMI negatively moderated the direct effect of BTEX mixed exposure on PhenoAge.Accel in moderated mediation models, while positively modified the link between SII and PhenoAge.Accel in the indirect path (binteraction = 0.04, 95%CI: 0.01 to 0.06). Overall, BTEX mixed exposure was associated with PhenoAge.Accel among US adults, with benzene may have reported most contribution, and inflammation and oxidative damage processes may partially explain this underlying mechanism. The study also highlighted the potential benefits of appropriate BMI increased. Additional large-scale cohort studies and experiments were necessary to substantiate these findings.

Associations between individual and mixed urinary metal exposure and dyslipidemia among Chinese adults: Data from the China Multi-Ethnic Cohort Study

The prevalence of dyslipidemia is increasing, and it has become a significant global public health concern. Some studies have demonstrated contradictory relationships between urinary metals and dyslipidemia, and the combined effects of mixed urinary metal exposure on dyslipidemia remain ambiguous. In this study, we examined how individual and combined urinary metal exposure are associated with the occurrence of dyslipidemia. According to the data from the 2018–2019 baseline survey database of the China Multi-Ethnic Cohort (CMEC) Study, a population of 9348 individuals was studied. Inductively coupled plasmamass spectrometry (ICP-MS) was used to measure 21 urinary metal concentrations in the collected adult urinary samples. The associations between urinary metals and dyslipidemia were analyzed by logistic regression, weighted quantile sum regression (WQS), and quantile-based g-computation (qgcomp), controlled for potential confounders to examine single and combined effects. Dyslipidemia was detected in 3231 individuals, which represented approximately 34.6 % of the total population. According to the single-exposure model, Al and Na were inversely associated with the risk of dyslipidemia (OR = 0.95, 95 % CI: 0.93, 0.98; OR = 0.89, 95 % CI: 0.83, 0.95, respectively), whereas Zn, Ca, and P were positively associated (OR = 1.69, 95 % CI: 1.42, 2.01; OR = 1.12, 95 % CI: 1.06, 1.18; OR = 1.21, 95 % CI: 1.09, 1.34, respectively). Moreover, Zn and P were significantly positively associated even after adjusting for these metals, whereas Al and Cr were negatively associated with the risk of dyslipidemia. The results of the WQS and qgcomp analyses showed that urinary metal mixtures were positively associated with the risk of dyslipidemia (OR = 1.26, 95 % CI: 1.15, 1.38; OR = 1.09, 95 % CI: 1.01, 1.19). This positive association was primarily driven by Zn, P, and Ca. In the sensitivity analyses with collinearity diagnosis, interaction, and stratified analysis, the results remained, confirming the reliability of the study findings. In this study, the individual and combined effects of urinary Zn, P, and Ca on dyslipidemia were determined, which provided novel insights into the link between exposure to metals and dyslipidemia.

Associations of Blood and Urinary Heavy Metals with Stress Urinary Incontinence Risk Among Adults in NHANES, 2003-2018.

People come into contact with heavy metals in various ways in their daily lives. Accumulating evidence shows that toxic metal exposure is hazardous to human health. However, limited information is available regarding the impact of metal mixtures on stress urinary incontinence (SUI). Therefore, we used data from 10,622 adults from the 2003-2018 National Health and Nutrition Examination Survey (NHANES) to investigate the independent and comprehensive association between heavy metal co-exposure and SUI. Among them, 2455 (23.1%) had been diagnosed with SUI, while the rest had no SUI. We evaluated the independent and combined associations of 3 blood metals and 10 urinary metals with SUI risk, along with subgroup analyses according to age and gender. In the single-exposure model, blood cadmium (Cd), lead (Pb), mercury (Hg), urinary Cd, Pb, and cesium (Cs) were found to be positively connected with SUI risk. Moreover, weighted quantile sum (WQS) regression, quantile-based g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) consistently demonstrated blood and urinary metal-mixed exposure were positively associated with the risk of SUI, and emphasized that blood Pb and Cd and urinary Cd and Cs were the main positive drivers, respectively. This association was more pronounced in the young and middle-aged group (20-59years old) and the female group. Nevertheless, further research is necessary to validate these significant findings.

Joint B Vitamin Intake and Type 2 Diabetes Risk: The Mediating Role of Inflammation in a Prospective Shanghai Cohort.

Type 2 diabetes (T2D) is a global and complex public health challenge, and dietary management is acknowledged as critical in its prevention. Recent studies have highlighted the involvement of micronutrients in T2D pathophysiology; our study aims to assess the association between B vitamin intake and T2D risks and the mediating role of inflammation. In a prospective cohort design, data on B vitamins intake, including thiamine (B1), riboflavin (B2), niacin (B3), pyridoxine (B6), folate (B9), and cobalamin (B12), was obtained using a validated food frequency questionnaire (FFQ), and blood inflammatory biomarkers were analyzed according to standard protocol in the local hospitals at baseline from 44,960 adults in the Shanghai Suburban Adult Cohort and Biobank (SSACB). Incident T2D cases were identified according to a physician's diagnosis or medication records from the electronic medical information system. We employed logistic and weighted quantile sum regression models to explore the associations of single and combined levels of B vitamins with T2D and mediation analyses to investigate the effects of inflammation. Negative correlations between B vitamins and T2D were observed in the single-exposure models, except for B3. The analyses of joint exposure (B1, B2, B6, B9, and B12) also showed an inverse association (OR 0.80, 95% CI 0.71 to 0.88), with vitamin B6 accounting for 45.58% of the effects. Further mediation analysis indicated a mediating inflammatory impact, accounting for 6.72% of the relationship. Dietary intake of B vitamins (B1, B2, B6, B9, B12) was associated with a reduced T2D risk partially mediated by inflammation in Shanghai residents.

Long-term exposure to air pollution, greenness and temperature and survival after a nonfatal myocardial infarction

BackgroundLittle is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI). ObjectiveThe goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI. MethodsWe used data from the US-based Nurses’ Health Study to construct an open cohort of survivors of a nonfatal MI 1990–2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM2.5) and nitrogen dioxide (NO2), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification. ResultsAmong 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO2 increase and suggestive positive associations were observed for PM2.5, lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO2, PM2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature. ConclusionWe observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

New findings on the risk of hypertension from organophosphorus exposure under different glycemic statuses: The key role of lipids?

Background and objectiveConsidering the widespread use of organophosphorus pesticides (OPs) and the global prevalence of hypertension (HTN), as well as studies indicating that different glycemic statuses may respond differently to the biological effects of OPs. Therefore, this study, based on the Henan rural cohort, aims to investigate the association between OPs exposure and HTN, and further explores whether lipids mediate these associations. MethodsWe measured the plasma levels of OPs in 2730 participants under different glycemic statuses using gas chromatography-triple quadrupole mass spectrometry (GC–MS/MS). A generalized linear model, Quantile g-computation (QGC), adaptive elastic net (AENET), and Bayesian kernel machine regression (BKMR) models were used to assess the impact of OPs exposure on HTN, with least absolute shrinkage and selection operator (LASSO) penalty regression identifying main OPs. Mediation models were used to evaluate the intermediary role of blood lipids in the OPs-HTN relationship. ResultsThe detection rates for all OPs were high, ranging from 76.35 % to 99.17 %. In the normal glucose tolerance (NGT) population, single exposure models indicated that malathion and phenthoate were associated with an increased incidence of HTN (P-FDR < 0.05), with corresponding odds ratios (ORs) and 95 % confidence intervals (CIs) of 1.624 (1.167,2.260) and 1.290 (1.072,1.553), respectively. QGC demonstrated a positive association between OP mixtures and HTN, with malathion and phenthoate being the primary contributors. Additionally, the AENET model's Exposure Response Score (ERS) suggested that the risk of HTN increases with higher ERS (P < 0.001). Furthermore, BKMR revealed that co-exposure to OPs increases HTN risk, with phenthoate having a significant impact. Furthermore, triglycerides (TG) mediated 6.55 % of the association between phenthoate and HTN. However, no association was observed in the impaired fasting glucose (IFG) and type 2 diabetes mellitus (T2DM) populations. ConclusionsOur findings suggest that in the NGT population, OPs may significantly contribute to the development of HTN, proposing TG as a potential novel target for HTN prevention.

The impact of co-exposure to air and noise pollution on the incidence of metabolic syndrome from a health checkup cohort

Previous studies have found associations between the incidence of metabolic syndrome (MetS) and exposure to air pollution or road traffic noise. However, investigations on environmental co-exposures are limited. This study aimed to investigate the association between co-exposure to air pollution and road traffic noise and MetS and its subcomponents. Participants living in Taipei City who underwent at least two health checkups between 2010 and 2016 were included in the study. Data were sourced from the MJ Health database, a longitudinal, large-scale cohort in Taiwan. The monthly traffic noise exposure (Lden and Lnight) was computed using a dynamic noise map. Monthly fine particulate data at one kilometer resolution were computed from satellite imagery data. Cox proportional hazards regression models with month as the underlying time scale were used to estimate hazard ratios (HRs) for the impact of PM2.5 and road traffic noise exposure on the risk of developing MetS or its subcomponents. Data from 10,773 participants were included. We found significant positive associations between incident MetS and PM2.5 (HR: 1.88; 95% CI 1.67, 2.12), Lden (HR: 1.10; 95% CI 1.06, 1.15), and Lnight (HR: 1.07; 95% CI 1.02, 1.13) in single exposure models. Results further showed significant associations with an elevated risk of incident MetS in co-exposure models, with HRs of 1.91 (95% CI 1.69, 2.16) and 1.11 (95% CI 1.06, 1.16) for co-exposure to PM2.5 and Lden, and 1.90 (95% CI 1.68, 2.14) and 1.08 (95% CI 1.02, 1.13) for co-exposure to PM2.5 and Lnight. The HRs for the co-exposure models were higher than those for models with only a single exposure. This study provides evidence that PM2.5 and noise exposure may elevate the risk of incident MetS and its components in both single and co-exposure models. Therefore, preventive approaches to mitigate the risk of MetS and its subcomponents should consider reducing exposure to PM2.5 and noise pollution.

Association and mediation analyses among multiple metal exposure, mineralocorticoid levels, and serum ion balance in residents of northwest China

Toxic metals are vital risk factors affecting serum ion balance; however, the effect of their co-exposure on serum ions and the underlying mechanism remain unclear. We assessed the correlations of single metal and mixed metals with serum ion levels, and the mediating effects of mineralocorticoids by investigating toxic metal concentrations in the blood, as well as the levels of representative mineralocorticoids, such as deoxycorticosterone (DOC), and serum ions in 471 participants from the Dongdagou–Xinglong cohort. In the single-exposure model, sodium and chloride levels were positively correlated with arsenic, selenium, cadmium, and lead levels and negatively correlated with zinc levels, whereas potassium and iron levels and the anion gap were positively correlated with zinc levels and negatively correlated with selenium, cadmium and lead levels (all P < 0.05). Similar results were obtained in the mixed exposure models considering all metals, and the major contributions of cadmium, lead, arsenic, and selenium were highlighted. Significant dose–response relationships were detected between levels of serum DOC and toxic metals and serum ions. Mediation analysis showed that serum DOC partially mediated the relationship of metals (especially mixed metals) with serum iron and anion gap by 8.3% and 8.6%, respectively. These findings suggest that single and mixed metal exposure interferes with the homeostasis of serum mineralocorticoids, which is also related to altered serum ion levels. Furthermore, serum DOC may remarkably affect toxic metal-related serum ion disturbances, providing clues for further study of health risks associated with these toxic metals.

Outdoor Light at Night, Air Pollution, and Risk of Cerebrovascular Disease: A Cohort Study in China.

We sought to explore the associations of outdoor light at night (LAN) and air pollution with the risk of cerebrovascular disease (CeVD). We included a total of 28 302 participants enrolled in Ningbo, China from 2015 to 2018. Outdoor LAN and air pollution were assessed by Satellite-derived images and land-use regression models. CeVD cases were confirmed by medical records and death certificates and further subdivided into ischemic and hemorrhagic stroke. Cox proportional hazard models were used to estimate hazard ratios and 95% CIs. A total of 1278 CeVD cases (including 777 ischemic and 133 hemorrhagic stroke cases) were identified during 127 877 person-years of follow-up. In the single-exposure models, the hazard ratios for CeVD were 1.17 (95% CI, 1.06-1.29) for outdoor LAN, 1.25 (1.12-1.39) for particulate matter with an aerodynamic diameter ≤2.5 µm, 1.14 (1.06-1.22) for particulate matter with aerodynamic diameter ≤10 μm, and 1.21 (1.06-1.38) for NO2 in every interquartile range increase. The results were similar for ischemic stroke, whereas no association was observed for hemorrhagic stroke. In the multiple-exposure models, the associations of outdoor LAN and PM with CeVD persisted but not for ischemic stroke. Furthermore, no interaction was observed between outdoor LAN and air pollution. Levels of exposure to outdoor LAN and air pollution were positively associated with the risk of CeVD. Furthermore, the detrimental effects of outdoor LAN and air pollution might be mutually independent.

Lead exposure across the life course and age at death

BackgroundLead (Pb) exposure has been associated with an increased risk of all-cause mortality, even at low levels. Little is known about how the timing of Pb exposure throughout life may influence these relationships. Quantifying the amount of Pb present in various tissues of the body provides measurements of exposure from different periods of life. These include bone, tooth enamel, which is the hard outer layer of the crown, and tooth cementum, which is the calcified connective tissue covering the tooth root. The purpose of the study was to examine Pb exposure at multiple periods throughout life, including childhood (enamel), adulthood (cementum), and later life (bone), and to estimate their associations with age at death. Methods208 skeleton donors (born 1910–1960) from an ongoing case-control study were included in this study. Pb was measured in tibia (shin), bone using X-Ray Florescence and in teeth using Laser-Ablation Inductively Coupled Plasma Mass Spectroscopy. After excluding unusually high measurements (>2sd), this resulted in a final sample of 111 with all exposure measures. Correlations across measures were determined using partial Spearman correlations. Associations between Pb exposure and age at death were estimated using Multivariable Linear Regression. ResultsPb measures across exposure periods were all significantly correlated, with the highest correlation between cementum and tibia measures (r = 0.61). Donors were largely female (63.0 %), White (97.3 %), and attended some college (49.5 %). Single exposure models found that higher tooth cementum Pb (−1.27; 95 % CI: −2.48, −0.06) and tibia bone Pb (−0.91; 95 % CI: −1.67, −0.15) were significantly associated with an earlier age at death. When considered simultaneously, only cementum Pb remained significant (−1.51; 95 % CI: −2.92, −0.11). Secondary analyses suggest that the outer cementum Pb may be especially associated with an earlier age at death. ConclusionResults suggest that higher Pb exposure is associated with an earlier age at death, with adulthood as the life period of most relevance. Additional studies using Pb exposure measures from different life stages should be conducted.

Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study.

The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases.

Serum albumin mediates the associations between heavy metals and two novel systemic inflammation indexes among U.S. adults

BackgroundThe effects of heavy metal exposure on immunological function have sparked widespread concern, but unequivocal evidence on the association between mixed metal exposure and novel systemic inflammatory indexes remains scarce. ObjectivesThis study aimed to analyze the associations of heavy metals with two novel systemic inflammation indexes and the mediated effects of serum albumin. MethodsNineteen metals were detected among 4082 U.S. adults based on the NHANES. A linear regression, restricted cubic splines (RCS) regression, weighted quantile sum (WQS), Quantile-based Gcomputation (qgcomp), and Bayesian kernel machine regression (BKMR) were conducted to evaluate the associations of single metal and mixed metals with systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) levels, respectively. A series of subgroup analyses were used to identify potentially vulnerable populations. Furthermore, we conducted mediation analyses to investigate the mediated effects of serum albumin on the associations of metals with SII and SIRI. ResultsIn the single-exposure model, exposure to various metals such as urinary Co, As, and serum Zn, Cu was associated with SII and SIRI (PFDR<0.05). Simultaneously, the above metals were linear positively correlated with SII and SIRI. Mixed-exposure analyses consistently showed that overall mixed urinary metal levels were positively pertinent for SII and SIRI levels, and the metal Co played a significant role in the urinary metal mixtures. Subgroup analyses showed that exposure to urinary Cd in men and elderly people increased SII and SIRI levels. The results of mediation analyses suggested the association of urinary metal mixture with SII and SIRI was mediated by albumin, and the proportion of mediation was 14.45% and 9.49%, respectively. ConclusionsOur findings suggested that metal exposure is strongly associated with the levels of system inflammation indexes and that serum albumin is, in part, a mediator of this association.

Association of environmental polycyclic aromatic hydrocarbons exposure with periodontitis in NHANES 2009-2014: A mixtures approach.

Polycyclic aromatic hydrocarbons (PAHs) can invade and cause harm to the human body through various pathways, but there is currently little research on the relationship between mixed-PAHs exposure and periodontitis. The purpose of this study was to examine the effects of mixed-urinary PAHs exposure on periodontitis in adults in the United States. The cross-sectional study included 2749 subjects selected from the National Health and Nutrition Examination Survey (NHANES) 2009-2014 cycles. A professional examination of the periodontal status was conducted to distinguish between periodontitis and non-periodontitis based on the Centers for Disease Control and Prevention/American Academy of Periodontology (CDC/AAP) case definition. Laboratory testing of urine samples was performed to obtain the levels of urinary PAHs. Pearson correlation coefficients were utilized to determine the degree of correlation between urinary PAHs, while weighted binary logistic regression and Bayesian kernel machine regression (BKMR) were employed to evaluate the relationship between urinary PAHs and periodontitis. In a single-exposure model, 3-hydroxyfluorene (OH-3F), 2-hydroxyfluorene (OH-2F), 1-hydroxyphenanthrene (OH-1Ph), and 2-hydroxyphenanthrene and 3-hydroxyphenanthrene (OH-2,3Ph) were positively associated with periodontitis risk. In the mixed-exposure model, BKMR analysis demonstrated that mixed exposure to urinary PAHs was positively associated with periodontitis, with OH-2F being the most critical factor for the overall mixed effects (posterior inclusion probability [PIP]=0.98). Univariate exposure-response function and univariate effects analysis revealed a positive correlation between urinary OH-2F levels and periodontitis. The study reveals a significant positive correlation between exposure to mixed PAHs and periodontitis, with a particular emphasis on the pivotal role of OH-2F. Mitigating PAHs in the environment may serve as a preventive measure against periodontitis and alleviate its global public health burden.

Prenatal Exposure to Multiple Endocrine-Disrupting Chemicals and Childhood BMI Trajectories in the INMA Cohort Study.

Prenatal exposure to endocrine-disrupting chemicals (EDCs) may disrupt normal fetal and postnatal growth. Studies have mainly focused on individual aspects of growth at specific time points using single chemical exposure models. However, humans are exposed to multiple EDCs simultaneously, and growth is a dynamic process. The objective of this study was to evaluate the associations between prenatal exposure to EDCs and children's body mass index (BMI) growth trajectories using single exposure and mixture modeling approaches. Using data from the INfancia y Medio Ambiente (INMA) Spanish birth cohort (), prenatal exposure to persistent chemicals [hexachlorobenzene (HCB), 4-4'-dichlorodiphenyldichloroethylene (DDE), polychlorinated biphenyls (PCB-138, -150, and -180), 4 perfluoroalkyl substances (PFAS)] and nonpersistent chemicals (8 phthalate metabolites, 7 phenols) was assessed using blood and spot urine concentrations. BMI growth trajectories were calculated from birth to 9 years of age using latent class growth analysis. Multinomial regression was used to assess associations for single exposures, and Bayesian weighted quantile sum (BWQS) regression was used to evaluate the EDC mixture's association with child growth trajectories. In single exposure models exposure to HCB, DDE, PCBs, and perfluorononanoic acid (PFNA) were associated with increased risk of belonging to a trajectory of lower birth size followed by accelerated BMI gain by 19%-32%, compared with a trajectory of average birth size and subsequent slower BMI gain [e.g., relative risk ratio (RRR) per doubling in DDE (95% CI: 1.05, 1.35); RRR for (95% CI: 1.05, 1.66)]. HCB and DDE exposure were also associated with higher probability of belonging to a trajectory of higher birth size and accelerated BMI gain. Results from the BWQS regression showed the mixture was positively associated with increased odds of belonging to a BMI trajectory of lower birth size and accelerated BMI gain (odds ratio per 1-quantile increase of the ; credible interval: 1.03, 2.61), with HCB, DDE, and PCBs contributing the most. This study provides evidence that prenatal EDC exposure, particularly persistent EDCs, may lead to BMI trajectories in childhood characterized by accelerated BMI gain. Given that accelerated growth is linked to a higher disease risk in later life, continued research is important. https://doi.org/10.1289/EHP11103.

Concomitant exposure to air pollution, green space and noise, and risk of myocardial infarction: a cohort study from Denmark.

The three correlated environmental exposures (air pollution, road traffic noise, and green space) have all been associated with the risk of myocardial infarction (MI). The present study aimed to analyse their independent and cumulative association with MI. In a cohort of all Danes aged 50 or older in the period 2005-17, 5-year time-weighted average exposure to fine particles (PM2.5), ultrafine particles, elemental carbon, nitrogen dioxide (NO2), and road traffic noise at the most and least exposed façades of residence was estimated. Green space around residences was estimated from land use maps. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence interval (CI), and cumulative risk indices (CRIs) were calculated. All expressed per interquartile range. Models were adjusted for both individual and neighbourhood-level socio-demographic covariates. The cohort included 1 964 702 persons. During follow-up, 71 285 developed MI. In single-exposure models, all exposures were associated with an increased risk of MI. In multi-pollutant analyses, an independent association with risk of MI was observed for PM2.5 (HR: 1.026; 95% CI: 1.002-1.050), noise at most exposed façade (HR: 1.024; 95% CI: 1.012-1.035), and lack of green space within 150 m of residence (HR: 1.018; 95% CI: 1.010-1.027). All three factors contributed significantly to the CRI (1.089; 95% CI: 1.076-1.101). In a nationwide cohort study, air pollution, noise, and lack of green space were all independently associated with an increased risk of MI. The air pollutant PM2.5 was closest associated with MI risk.

Changes in neighborhood physical and social environments matter for change in mental health: Longitudinal evidence from Dutch panel data

Numerous neighborhood environments have been recognized to affect mental health, but only a few longitudinal studies investigated these associations jointly and whether different population groups are affected differently. We used three-wave panel data of 2699 adults between 2010 and 2016 in the Netherlands to assess the associations between changes in neighborhood physical and social environments and mental health changes. Further, we assessed possible effect modification of gender and income. Mental health was measured using the Mental Health Inventory. Time-varying exposure to green space, blue space, population density, air pollution, socioeconomic deprivation, and social fragmentation were assigned based on individuals' neighborhood histories. Fixed-effect regressions were conducted to assess within-person associations between single and multiple exposures on mental health for the entire sample and stratified by gender and income. Our single-exposure models showed that increases in blue space were significantly associated with mental health improvements, while increases in fine particulate matter (PM2.5) resulted in declines in mental health. These associations were not attenuated in the multi-exposure model. We observed no significant associations for the remaining environments. Stratification analyses showed that females’ mental health further declined as PM2.5 concentrations increased compared to males. Increasing levels of socioeconomic deprivation were associated with further declines in mental health among the less well-off compared with higher-income earners. Our longitudinal findings suggested that neighborhood physical and social environment changes were associated with mental health changes. Future research is required to establish the underlying pathways.