Relationship between phthalates exposures and hyperuricemia in U.S. general population, a multi-cycle study of NHANES 2007-2016

Cross-sectional and longitudinal associations of PAHs exposure with serum uric acid and hyperuricemia among Chinese urban residents: The potential role of oxidative damage

A few studies found polycyclic aromatic hydrocarbons (PAHs) were associated with serum uric acid (SUA) or hyperuricemia (HUA). However, the longitudinal study is vacant, and the underlying mechanisms remain unclear. We aimed to assess the cross-sectional and longitudinal associations of urinary PAHs metabolites with SUA levels and HUA risk, and explore the mediating effects of oxidative stress and inflammation. 10 urinary mono-hydroxylated PAHs metabolites and SUA levels were measured among 4047 Chinese urban residents at baseline and 1496 individuals at 6-year follow-up. Biomarkers of oxidative damage and inflammation in urine/plasma were determined at baseline. We adopted generalized linear mixed models and logistic regression to assess the associations of PAHs metabolites with SUA and HUA, weighted quantile sum regression and adaptive elastic net regression to evaluate the overall effects of multi-PAHs mixture, and mediation analysis to estimate the mediating roles of the biomarkers. In the cross-sectional study, each 1-unit increase in the ln-transformed values of 2-OHNa, 2-OHFlu, 4-OHPh, 9-OHPh, 3-OHPh, 2-OHPh, ΣOHNa, ΣOHPh, and ΣOHPAHs was associated with a 4.10-, 3.90-, 6.42-, 7.33-, 4.85-, 5.43-, 4.47-, 7.67-, and 5.22-μmol/L increase in SUA, respectively. Meanwhile, each 1-unit increase in the ln-transformed values of 1-OHNa, 2-OHNa, 4-OHPh, 9-OHPh, 3-OHPh, 2-OHPh, ΣOHNa, ΣOHPh, and ΣOHPAHs was associated with a 17, 14, 15, 22, 14, 19, 18, 27, and 21% increment in HUA risk, respectively. After 6 years, individuals with persistent high level of 9-OHPh had a 12.5 μmol/L increase in SUA compared with those with persistent low level. The overall effects of multi-PAHs mixture on SUA and HUA remain positive. 8-hydroxy-deoxyguanosine mediated the associations of PAHs metabolites with SUA and HUA, and the mediated proportion ranged from 5.39% to 15.34%. PAHs exposure was associated with the elevated SUA levels and increased HUA risk, and oxidative DNA damage may be one of the underlying mechanisms.

Relationship between phthalate exposure and kidney function in Taiwanese adults as determined through covariate-adjusted standardization and cumulative risk assessment

Few studies have investigated the associations between phthalate exposure and kidney function indicators in adults by simultaneously performing covariate-adjusted creatinine standardization, cumulative risk assessment, and mixture analysis. Thus, we applied these methods simultaneously to investigate the aforementioned associations in an adult population. This cross-sectional study analyzed data (N = 839) from a community-based arm of the Taiwan Biobank. The levels of 10 urinary phthalate metabolites were measured and calculated as the sum of the molar concentrations of the dibutyl phthalate metabolite (ΣDBPm) and di(2-ethylhexyl) phthalate (DEHP) metabolite (ΣDEHPm). The hazard index (HI) and daily intake (DI) were estimated by measuring the urinary levels of the phthalate metabolite. Kidney function biomarkers were assessed by measuring the following: blood urea nitrogen (BUN), uric acid, the albumin-to-creatinine ratio (ACR), and the estimated glomerular filtration rate (eGFR). Generalized linear models were implemented to examine the associations between exposure to individual phthalates, HI scores, and kidney function biomarkers. We also employed Bayesian kernel machine regression (BKMR) to analyze the relationships between exposure to various combinations of phthalates and kidney function. ΣDEHPm levels were significantly and positively associated with BUN and ACR levels, and ΣDBPm levels were positively associated with ACR levels. In addition, eGFR was negatively associated with ΣDBPm and ΣDEHPm levels. In the BKMR model, a mixture of 10 phthalate metabolites was significantly associated with BUN, uric acid, ACR, and eGFR results. Higher DIDEHP and higher DIDnBP values were significantly associated with lower eGFRs and higher ACRs, respectively. Higher DIDiBP and DIDEP values were significantly associated with higher uric acid levels. A higher HI was significantly associated with lower eGFRs and higher ACRs. Our results suggest that exposure to environmental phthalates is associated with impaired kidney function in Taiwanese adults.

The effect of low-level phthalate mixture on the prevalence of type 2 diabetes mellitus among adults in the US

Type 2 diabetes mellitus (T2DM) is an important public health issue owing to its rising global prevalence. Phthalates cause various health problems and are currently regulated in developed countries. However, studies on the impacts of low-level phthalate exposure under these regulations on T2DM are limited. This study investigated the impacts of combined and single exposures to phthalates and their alternatives on the prevalence of T2DM in 3,005 adults in the United States. The results indicated a positive joint effect of phthalate mixtures on the prevalence of T2DM. The joint effect was primarily attributed to Di-2-ethylhexyl phthalate (DEHP) metabolites, whereas the contributions of others were limited. This study suggests that, despite the stringent regulations on phthalates, low levels of phthalates, including DEHP, still have joint effects on T2DM. The findings highlight the importance of regulating hazardous phthalates and the need for safer alternatives to reduce public health risks.

Association between phthalates exposure and non-alcoholic fatty liver disease under different diagnostic criteria: a cross-sectional study based on NHANES 2017 to 2018

Purpose

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease. Phthalates have been suggested to influence the development of NAFLD due to their endocrine-disrupting properties, but studies based on nationally representative populations are insufficient, and existing studies seem to have reached conflicting conclusions. Due to changes in legislation, the use of traditional phthalates has gradually decreased, and the phthalates substitutes is getting more attention. This study aims to delve deeper into how the choice of diagnostic approach influences observed correlations and concern about more alternatives of phthalates, thereby offering more precise references for the prevention and treatment of NAFLD.

Methods

A cohort of 641 participants, sourced from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 database, was evaluated for NAFLD using three diagnostic methods: the Hepatic Steatosis Index (HSI), the US Fatty Liver Indicator (US.FLI), and Vibration Controlled Transient Elastography (VCTE). The urinary metabolite concentrations of Di-2-ethylhexyl phthalate (DEHP), Di-isodecyl phthalate (DIDP), Di-isononyl phthalate (DINP), Di-n-butyl phthalate (DnBP), Di-isobutyl phthalate (DIBP), Di-ethyl phthalate (DEP) and Di-n-octyl phthalate (DnOP) were detected. The association between NAFLD and urinary phthalate metabolites was evaluated through univariate and multivariate logistic regression analyses, considering different concentration gradients of urinary phthalates.

Results

Univariate logistic regression analysis found significant correlations between NAFLD and specific urinary phthalate metabolites, such as Mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), Mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), Mono-2-ethyl-5-carboxypentyl phthalate (MECPP), and Mono-(carboxyisoctyl) phthalate (MCiOP), across different diagnostic criteria. In a multivariate logistic regression analysis adjusting only for demographic data, MEOHP (OR = 3.26, 95% CI = 1.19-8.94, p = 0.029), MEHHP (OR = 3.98, 95% CI = 1.43-11.1, p = 0.016), MECPP (OR = 3.52, 95% CI = 1.01-12.2, p = 0.049), and MCiOP (OR = 4.55, 95% CI = 1.93-10.7, p = 0.005) were positively related to NAFLD defined by HSI and VCTE. The correlation strength varied with the concentration of phthalates, indicating a potential dose-response relationship. Adjusting for all covariates in multivariate logistic regression, only MCiOP (OR = 4.22, 95% CI = 1.10-16.2, p = 0.044), as an oxidative metabolite of DINP, remained significantly associated with NAFLD under the VCTE criterion, suggesting its potential role as a risk factor for NAFLD.

Conclusion

This research highlights a significant association between DINP and NAFLD. These findings underscore the need for further investigation into the role of the phthalates substitutes in the pathogenesis of NAFLD and the importance of considering different diagnostic criteria in research.

The association between dietary antioxidant quality score and uric acid related mortality in patients with chronic kidney disease

Aim

Antioxidants diet is beneficial for the prognosis of chronic kidney disease (CKD). However, the relationship between the Dietary Antioxidant Quality Score (DAQS), a measure of overall quality on antioxidant diet, and hyperuricemia related mortality is unclear. This study aimed to investigate the relationship between the DAQS and hyperuricemia mortality in CKD patients.

Methods

In this cohort study, data were collected in the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2018. The DAQS was calculated based on the six dietary antioxidants. Mortality status were determined by NHANES-linked National Death Index public access files through December 31, 2019. Weighted Cox proportional hazard models were used to investigate the association between the DAQS and hyperuricemia related mortality.

Results

A total of 3,684 participants were included. During the median follow-up of 63.83 months, 820 deaths were recorded. The results showed that higher dietary antioxidants intake associated with lower hyperuricemia related mortality risk among CKD patients (HR = 1.28, 95%CI: 1.07 to 1.54). In subgroup analyses, the association of antioxidants intake and hyperuricemia related mortality risk remained exist in groups of aged ≥65 years (HR = 1.23, 95%CI: 1.01 to 1.52), with hypertension (HR = 1.26, 95%CI: 1.02 to 1.55), with dyslipidemia (HR = 1.30, 95%CI: 1.07 to 1.58), with CVD (HR = 1.31, 95%CI: 1.03 to 1.67), and diabetes (HR = 1.62, 95%CI: 1.24 to 2.12).

Conclusion

Higher antioxidants intake associated with lower odds of hyperuricemia related mortality in CKD patients. Future interventional studies are needed to elucidate the beneficial effect of antioxidants diets.

Associations of phthalates with accelerated aging and the mitigating role of physical activity

Phthalates are positioned as potential risk factors for health-related diseases. However, the effects of exposure to phthalates on accelerated aging and the potential modifications of physical activity remain unclear. A total of 2317 participants containing complete study-related information from the National Health and Nutrition Examination Survey 2007-2010 were included in the current study. We used two indicators, the Klemera-Doubal method biological age acceleration (BioAgeAccel) and phenotypic age acceleration (PhenoAgeAccel), to assess the accelerated aging status of the subjects. Multiple linear regression (single pollutant models), weighted quantile sum (WQS) regression, Quantile g-computation, and Bayesian kernel machine regression (BKMR) models were utilized to explore the associations between urinary phthalate metabolites and accelerated aging. Three groups of physical activity with different intensities were used to evaluate the modifying effects on the above associations. Results indicated that most phthalate metabolites were significantly associated with BioAgeAccel and PhenoAgeAccel, with effect values (β) ranging from 0.16 to 0.21 and 0.16-0.37, respectively. The WQS indices were positively associated with BioAgeAccel (0.33, 95% CI: 0.11, 0.54) and PhenoAgeAccel (0.50, 95% CI: 0.19, 0.82). Quantile g-computation indicated that phthalate mixtures were associated with accelerated aging, with effect values of 0.15 (95% CI: 0.02, 0.28) for BioAgeAccel and 0.39 (95% CI: 0.12, 0.67) for PhenoAgeAccel respectively. The BKMR models indicated a significant positive association between the concentrations of urinary phthalate mixtures with the two indicators. In addition, we found that most phthalate metabolites showed the strongest effects on accelerated aging in the no physical activity group and that the effects decreased gradually with increasing levels of physical activity (P < 0.05 for trend). Similar results were also observed in the mixed exposure models (WQS and Quantile g-computation). This study indicates that phthalates exposure is associated with accelerated aging, while physical activity may be a crucial barrier against phthalates exposure-related aging.

Kidney function decline mediates the adverse effects of per- and poly-fluoroalkyl substances (PFAS) on uric acid levels and hyperuricemia risk

Previous studies indicated per- and poly-fluoroalkyl substances (PFAS) were related to uric acid and hyperuricemia risk, but evidence for the exposure-response (E-R) curves and combined effect of PFAS mixture is limited. Moreover, the potential mediation effect of kidney function was not assessed. Hence, we conducted a national cross-sectional study involving 13,979 US adults in NHANES 2003-2018 to examine the associations of serum PFAS with uric acid and hyperuricemia risk, and the mediation effects of kidney function. Generalized linear models and E-R curves showed positive associations of individual PFAS with uric acid and hyperuricemia risk, and nearly linear E-R curves indicated no safe threshold for PFAS. Weighted quantile sum regression found positive associations of PFAS mixture with uric acid and hyperuricemia risk, and PFOA was the dominant contributor to the adverse effect of PFAS on uric acid and hyperuricemia risk. Causal mediation analysis indicated significant mediation effects of kidney function decline in the associations of PFAS with uric acid and hyperuricemia risk, with the mediated proportion ranging from 19 % to 57 %. Our findings suggested that PFAS, especially PFOA, may cause increased uric acid and hyperuricemia risk increase even at low levels, and kidney function decline plays a crucial mediation effect.

Association between exposure to a mixture of organochlorine pesticides and hyperuricemia in U.S. adults: A comparison of four statistical models

The association between the exposure of organochlorine pesticides (OCPs) and serum uric acid (UA) levels remained uncertain. In this study, to investigate the combined effects of OCP mixtures on hyperuricemia, we analyzed serum OCPs and UA levels in adults from the National Health and Nutrition Examination Survey (2005-2016). Four statistical models including weighted logistic regression, weighted quantile sum (WQS), quantile g-computation (QGC), and bayesian kernel machine regression (BKMR) were used to assess the relationship between mixed chemical exposures and hyperuricemia. Subgroup analyses were conducted to explore potential modifiers. Among 6,529 participants, the prevalence of hyperuricemia was 21.15%. Logistic regression revealed a significant association between both hexachlorobenzene (HCB) and trans-nonachlor and hyperuricemia in the fifth quintile (OR: 1.54, 95% CI: 1.08-2.19; OR: 1.58, 95% CI: 1.05-2.39, respectively), utilizing the first quintile as a reference. WQS and QGC analyses showed significant overall effects of OCPs on hyperuricemia, with an OR of 1.25 (95% CI: 1.09-1.44) and 1.20 (95% CI: 1.06-1.37), respectively. BKMR indicated a positive trend between mixed OCPs and hyperuricemia, with HCB having the largest weight in all three mixture analyses. Subgroup analyses revealed that females, individuals aged 50 years and above, and those with a low income were more vulnerable to mixed OCP exposure. These results highlight the urgent need to protect vulnerable populations from OCPs and to properly evaluate the health effects of multiple exposures on hyperuricemia using mutual validation approaches.

A review of common statistical methods for dealing with multiple pollutant mixtures and multiple exposures

Traditional environmental epidemiology has consistently focused on studying the impact of single exposures on specific health outcomes, considering concurrent exposures as variables to be controlled. However, with the continuous changes in environment, humans are increasingly facing more complex exposures to multi-pollutant mixtures. In this context, accurately assessing the impact of multi-pollutant mixtures on health has become a central concern in current environmental research. Simultaneously, the continuous development and optimization of statistical methods offer robust support for handling large datasets, strengthening the capability to conduct in-depth research on the effects of multiple exposures on health. In order to examine complicated exposure mixtures, we introduce commonly used statistical methods and their developments, such as weighted quantile sum, bayesian kernel machine regression, toxic equivalency analysis, and others. Delineating their applications, advantages, weaknesses, and interpretability of results. It also provides guidance for researchers involved in studying multi-pollutant mixtures, aiding them in selecting appropriate statistical methods and utilizing R software for more accurate and comprehensive assessments of the impact of multi-pollutant mixtures on human health.

The relationship of organophosphate flame retardants with hyperuricemia and gout via the inflammatory response: An integrated approach

BACKGROUND

Evidence regarding the relationships between organophosphate flame retardants (OPFRs) and hyperuricemia and gout as well as the underlying mechanisms remains scarce, but some evidence indicates that inflammation might play a key role.

OBJECTIVES

Using an integrated approach, we aim to elucidate the associations of urinary metabolite OPFRs (m-OPFRs) with hyperuricemia and gout.

METHODS

Cross-sectional analyses using data from the National Health and Nutrition Examination Survey were performed to reveal the associations. Adults with complete data on five m-OPFRs with high detection frequencies and outcomes were enrolled. We used multivariate logistic regression, restricted cubic spline (RCS), and Bayesian kernel machine regression (BKMR) methods to account for single, nonlinear, and joint effects. The mediating effect of the inflammatory response was also estimated. Moreover, adverse outcome pathways (AOPs) based on network analysis were further constructed to reveal the underlying mechanism.

RESULTS

Multivariate logistic models revealed that bis(2-chloroethyl) phosphate (BCEP) significantly increased risk of hyperuricemia (OR [95 % CI]: 1.165 [1.047, 1.296]) in the fully adjusted model. Elevated levels of bis(1-chloro-2-propyl) phosphate were associated with gout (OR [95 % CI]: 1.293 [1.015, 1.647]). No nonlinear relationship was observed in RCS. There was a positive association between mixed m-OPFRs and hyperuricemia risk in BMKR, with bis(1,3-dichloro-2-propyl) phosphate and BCEP being the main contributors (PIP > 0.5). We found that the inflammatory response significantly mediated the association between BCEP and hyperuricemia (P < 0.05). Network topology analysis identified seven genes and six phenotypes related to OPFR exposure and hyperuricemia. The AOP framework suggested that the inflammatory response, especially the activation of the TNF pathway, played a core role in the above relationships.

CONCLUSION

Our results first revealed that individual and mixed OPFRs were associated with hyperuricemia, in which the inflammatory response plays an important role. Further longitudinal studies are warranted to consolidate or refute our main findings.

Stochastic modeling of obesity status in United States adults using Markov Chains: A nationally representative analysis of population health data from 2017-2020

Importance

The prevalence of obesity among United States adults has increased from 34.9% in 2013-2014 to 42.8% in 2017-2018. Developing methods to model the increase of obesity over-time is a necessity to know how to accurately quantify its cost and to develop solutions to combat this national public health emergency.

Methods

A cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES 2017-2020) was conducted in individuals who completed the weight questionnaire and had accurate data for both weight at the time of survey and weight 10 years ago. To model the dynamics of obesity, a Markov transition state matrix was created, which allowed for the analysis of weight transitions over time. Bootstrap simulation was incorporated to account for uncertainty and generate multiple simulated datasets, providing a more robust estimation of the prevalence and trends in obesity within the cohort.

Results

Of the 6146 individuals who met the inclusion criteria, 3024 (49%) individuals were male and 3122 (51%) were female. There were 2252 (37%) White individuals, 1257 (20%) Hispanic individuals, 1636 (37%) Black individuals, and 739 (12%) Asian individuals. The average BMI was 30.16 (SD = 7.15), the average weight was 83.67 kilos (SD = 22.04), and the average weight change was a 3.27 kg (SD = 14.97) increase in body weight. A total of 2411 (39%) individuals lost weight, and 3735 (61%) individuals gained weight. 87 (1%) individuals were underweight (BMI <18.5), 2058 (33%) were normal weight (18.5 ≤ BMI <25), 1376 (22%) were overweight (25 ≤ BMI <30) and 2625 (43%) were in the obese category (BMI >30).

Conclusion

United States adults are at risk of transitioning from normal weight to the overweight or obese category. Markov modeling combined with bootstrap simulations can accurately model long-term weight status.