UNASSIGNED: Fine needle aspiration (FNA) biopsy is a widely accepted method for diagnosing thyroid nodules. However, the influence of maximum diameter (MD) of ACR TIRADS 5 (TR5) thyroid nodules on the FNA outcomes remains debated. This study examined the influence of MD on the FNA outcomes and investigated the optimal MD threshold for FNA in TR5 nodules.
UNASSIGNED: We conducted a retrospective analysis of 280 TR5 thyroid nodules from 226 patients who underwent FNA from January to June 2022 in our department. Probably malignant (PM) group was defined as Bethesda V in cytopathology with confirmed BRAF V600E mutation or Bethesda VI, the other cytopathology outcomes were defined as probably benign (PB) group. We examined factors influencing malignant cytopathology outcomes and determined the optimal MD threshold for FNA in TR5 nodules using logistic regression and restricted cubic spline (RCS) analysis.
UNASSIGNED: Among these nodules, 58.2% (163/280) had PM outcomes. The PM group had a significantly larger MD than the PB group [6.5mm (range 5.0-8.4) vs. 5.3mm (range 4.0-7.0), p < 0.001]. In multivariate logistic regression fully adjusted for confounders, MD was significantly associated with PM outcomes [odds ratio 1.16, 95%CI 1.05-1.31; p = 0.042]. The highest quartile of MD had a greater likelihood of PM outcomes compared to the lowest quartile [odds ratio 4.71, 95% CI 1.97-11.69, p = 0.001]. The RCS analysis identified 6.2 mm as the optimal MD threshold for FNA in TR5 nodules.
UNASSIGNED: MD significantly affects the probability of malignant outcomes in FNA of TR5 thyroid nodules. A MD threshold of ≥6.2mm is suggested for FNA in these nodules.

UNASSIGNED: Atherogenic Index of plasma (AIP) is closely related to metabolic abnormalities. But as of now, there is no definitive conclusion on the dose-response relationship pattern between AIP and metabolic associated fatty liver disease (MAFLD).
UNASSIGNED: The objective of this study was to provide a fresh insight for understanding the intrinsic link between AIP and the prevalence of MAFLD by exploring the dose-response pattern between AIP and MAFLD.
UNASSIGNED: A total of 9254 participants received the survey and 1090 participants were finally included according to the screening criteria. To evaluate the association between AIP and the prevalence of MAFLD based on weighted multivariate logistic regression. Sensitivity analysis of the association between AIP and MAFLD was performed using propensity score matching (PSM). Restrictive cubic splines (RCS) were used to identify patterns of dose-response relationships between AIP and MAFLD, and receiver operator characteristic (ROC) curves were used to evaluate the predictive ability of AIP and traditional lipid parameters for MAFLD.
UNASSIGNED: In this study, a total of 563 participants were found to have MAFLD. The results of weighted multivariate logistic regression analysis demonstrated that, after adjusting for sex and age, participants in the highest quartile (Q4) of AIP had a significantly increased risk of developing MAFLD compared to those in the lowest quartile (Q1) (Model 2: OR = 9.03, 95% CI 4.75-17.17). A similar trend was observed in the fully adjusted model (Model 3: OR = 3.85, 95% CI 1.55-9.52). The RCS analysis revealed a linear dose-response association between AIP and MAFLD(P for crude non-linearity = 0.087). This association remained significant after accounting for potential confounding variables(P for adjusted non-linearity = 0.663). The ROC curve results suggest that AIP performs better than traditional lipid indicators in predicting MAFLD (AUC = 0.732, 95%CI 0.705-0.758).
UNASSIGNED: A linear dose-response relationship exists between AIP and MAFLD, suggesting that as AIP increases, so does the risk of developing MAFLD.

UNASSIGNED: People are constantly exposed to phthalates, but few reliable studies have focused on the connection between phthalate exposure and latent tuberculosis infection (LTBI).
UNASSIGNED: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) database (2011-2012). The LTBI was assessed by QuantiFERON®-TB Gold-In-Tube (QFT) or tuberculin skin testing (TST). The odds ratios (ORs) and 95% confidence intervals (CIs) per log10 unit change in the concentration of phthalate metabolites were calculated using crude and adjusted logistic regression models. The relationships between mixed phthalate concentrations and LTBI were assessed using Bayesian kernel machine regression (BKMR) models.
UNASSIGNED: According to the results of the multivariable logistic regression, in a fully adjusted model, only monobenzyl phthalate (MBZP) was negatively associated with LTBI in Q3 (OR (95% CI): 0.485 (0.286,0.823), P = 0.007). According to the restricted cubic spline (RCS) model, there was a linear dose‒response association between all 11 phthalate metabolites and LTBI (p for nonlinearity >0.05). We found a significant positive correlation between mixed phthalate metabolites and LTBI by using fully adjusted BKMR model.
UNASSIGNED: Our analysis demonstrated that LTBI in the general U.S. population is linearly linked with exposure to single or combined phthalates.

UNASSIGNED: Serum albumin levels and cancer mortality are closely related, yet large-sample studies encompassing a broad spectrum of cancer types are lacking.
UNASSIGNED: This study encompassed patients diagnosed with cancer across the continuous 10 cycles of NHANES surveys from 1999 to 2018. The study population was stratified into two groups based on median albumin levels (≤ 4.2g/dL and > 4.2 g/dL) or cancer aggressiveness (well-survived cancers and poorly-survived cancers). Survival rates were estimated using the Kaplan-Meier method. The Cox proportional hazards model was employed to evaluate the association between serum albumin levels and cancer mortality. Restricted cubic spline (RCS) analysis was conducted to assess the nonlinear relationship between serum albumin levels and the risk of cancer mortality.
UNASSIGNED: Kaplan-Meier curves demonstrated that patients with albumin levels ≤ 4.2 g/dL exhibited lower survival rates compared to those with levels > 4.2 g/dL, irrespective of cancer aggressiveness. Following adjustment for confounders, decreased albumin levels were associated with an elevated risk of cancer mortality across all groups [all cancers, HR (95%CI) = 2.03(1.73, 2.37); well survived cancers, HR (95%CI) = 1.78(1.38, 2.32); and poorly survived cancers, HR (95%CI) = 1.99(1.64, 2.42)]. RCS analyses revealed a stable nonlinear negative association between albumin levels and cancer mortality in all groups, regardless of confounder adjustment.
UNASSIGNED: Low serum albumin levels predict higher cancer mortality. Furthermore, a nonlinear negative association was observed between serum albumin levels and the risk of cancer mortality.

Earlier research has indicated that being exposed to polychlorinated dibenzo-p-dioxins (PCDDs) in the workplace can heighten the likelihood of cancer-related deaths. Nevertheless, there is limited information available regarding the connection between PCDD exposure and the risk of cancer mortality in the general population (i.e., individuals not exposed to these substances through their occupation).
The National Health and Nutrition Examination Survey (NHANES) detected PCDDs in the general population, and the death data were recently updated as of December 31, 2019. We conducted Cox regression analysis and controlled for covariates including age, gender, ethnicity, educational attainment, physical activity, alcohol intake, NHANES survey period, BMI category, cotinine concentration, and household earnings.
After accounting for confounding factors, the findings indicated that for each incremental rise of 1 log unit in 1,2,3,4,6,7,8,9-octachlorodibenzo-p-dioxin, there was a 76% rise in the likelihood of death from any cause, with a p value of 0.003. An increase of 1 log unit in the concentration of 1,2,3,4,6,7,8-heptachlorodibenzofuran could potentially lead to a 90% higher risk of cancer mortality, as indicated by a p value of 0.034 and a 95% confidence interval of 0.05-2.43. As the concentrations of 1,2,3,4,6,7,8-heptachlorodibenzofuran increased, the dose-response curve indicated a proportional rise in the risk of cancer mortality, accompanied by a linear p value of 0.044. The sensitivity analysis demonstrated that our findings were resilient.
In the general population, an elevated risk of cancer mortality was observed in PCDDs due to the presence of 1,2,3,4,6,7,8-heptachlorodibenzofuran. Mechanistic research is required to further confirm it.

BACKGROUND: Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) has become a global epidemic, and air pollution has been identified as a potential risk factor. This study aims to investigate the non-linear relationship between ambient air pollution and MASLD prevalence.
METHODS: In this cross-sectional study, participants undergoing health checkups were assessed for three-year average air pollution exposure. MASLD diagnosis required hepatic steatosis with at least 1 out of 5 cardiometabolic criteria. A stepwise approach combining data visualization and regression modeling was used to determine the most appropriate link function between each of the six air pollutants and MASLD. A covariate-adjusted six-pollutant model was constructed accordingly.
RESULTS: A total of 131,592 participants were included, with 40.6% met the criteria of MASLD. \"Threshold link function,\" \"interaction link function,\" and \"restricted cubic spline (RCS) link functions\" best-fitted associations between MASLD and PM2.5, PM10/CO, and O3 /SO2/NO2, respectively. In the six-pollutant model, significant positive associations were observed when pollutant concentrations were over: 34.64 µg/m3 for PM2.5, 57.93 µg/m3 for PM10, 56 µg/m3 for O3, below 643.6 µg/m3 for CO, and within 33 and 48 µg/m3 for NO2. The six-pollutant model using these best-fitted link functions demonstrated superior model fitting compared to exposure-categorized model or linear link function model assuming proportionality of odds.
CONCLUSIONS: Non-linear associations were found between air pollutants and MASLD prevalence. PM2.5, PM10, O3, CO, and NO2 exhibited positive associations with MASLD in specific concentration ranges, highlighting the need to consider non-linear relationships in assessing the impact of air pollution on MASLD.

Selenium is an essential trace element for human health, playing a key role in regulating cellular oxidative stress, immune response, and inflammation. In recent years, the association between selenium and Parkinson\'s disease (PD) has aroused people\'s attention. The objective of this study is to investigate the relationship between blood selenium concentrations and PD risk in a sample of U.S. adults. A cross-sectional study was conducted using the National Health and Nutrition Examination Survey (NHANES) data from 2011-2020 and included 15,660 adults aged over 40 years old. Univariate logistic regression and multivariate logistic regression models were utilized to analyze the association between blood selenium concentrations and PD prevalence. Additionally, the restricted cubic spline (RCS) model was applied to investigate the dose-response relationships between blood selenium and PD. The findings indicated a link between elevated blood selenium levels and a reduced occurrence of Parkinson\'s disease (PD). Notably, this association between blood selenium and PD exhibited a non-linear pattern, wherein the decline in PD risk was more pronounced at higher selenium concentrations than at lower levels. An inflection point emerged at approximately 2.4 μmol/L, beyond which the rate of decline in risk significantly diminished with increasing selenium levels. A potential association between blood selenium concentrations and PD has been observed, with PD patients having lower blood selenium levels compared to non-PD patients. Higher levels of blood selenium may have a protective effect against PD. However, further prospective studies are needed to investigate the effect of blood selenium in PD patients and to determine causality.

Multiple animals and in vitro studies have demonstrated that perfluoroalkyl and polyfluoroalkyl substances (PFASs) exposure causes liver damage associated with fat metabolism. However, it is lack of population evidence for the correlation between PFAS exposure and nonalcoholic fatty liver disease (NAFLD). A cross-sectional analysis was performed of 1150 participants aged over 20 from the US. Liver ultrasound transient elastography was to identify the participants with NAFLD and multiple biomarkers were the indicators for hepatic steatosis and hepatic fibrosis. Logistics regression and restricted cubic splines models were used to estimate the association between PFASs and NAFLD. PFASs had not a significant association with NAFLD after adjustment. The hepatic steatosis indicators including fatty liver index, NAFLD liver fat score, and Framingham steatosis index were almost not significantly correlated with PFASs exposure respectively. But fibrosis indicators including fibrosis-4 index (FIB-4), NAFLD fibrosis score, and Hepamet fibrosis score were positively correlated with each type of PFASs exposure. After adjustment by gender, age, race, education, and poverty income rate, there was also a significant correlation between PFOS and FIB-4 with 0.07 (0.01, 0.13). The mixed PFASs were associated with FIB-4, with PFOS contributing the most (PIP = 1.000) by the Bayesian kernel machine regression model. The results suggested PFASs exposure appeared to be more closely associated with hepatic fibrosis than steatosis, and PFOS might be the main cause of PFASs associated with hepatic fibrosis.Key messagesCurrent exposure doses of PFAS did not significantly change the risk of developing NAFLD.PFASs exposure appeared to be more closely associated with hepatic fibrosis than steatosis.PFOS might be the main cause of PFASs associated with hepatic fibrosis.

With advances in medical diagnosis, more people are diagnosed with more than one disease. The damage caused by different diseases varies, so relying solely on the number of diseases to represent multimorbidity is limited. The Charlson comorbidity index (CCI) is widely used to measure multimorbidity and has been validated in various studies. However, CCI\'s demographic and behavioral risk factors still need more exploration.
We conduct multivariate logistic regression analysis and restricted cubic splines to examine the influence factors of CCI and the relationship between covariates and risk of CCI, respectively. Our research employs the Multivariate Imputation by Chained Equations method to interpolate missing values. In addition, the CCI score for each participant is calculated based on the inpatient\'s condition using the International Classification of Diseases, edition 10 (ICD10). Considering the differences in the disease burden between males and females, the research was finally subgroup analyzed by sex.
This study includes 5,02,411 participants (2,29,086 female) with CCI scores ranging from 0 to 98. All covariates differed between CCI groups. High waist-hip ratio (WHR) increases the risk of CCI in both males [OR = 19.439, 95% CI = (16.261, 23.241)] and females [OR = 12.575, 95% CI = (11.005, 14.370)], and the effect of WHR on CCI is more significant in males. Associations between age, Body Mass Index (BMI) and WHR, and CCI risk are J-shaped for all participants, males, and females. Concerning the association between Townsend deprivation index (TDI) and CCI risk, the U-shape was found in all participants and males and varied to a greater extent in males, but it is a J-shape in females.
Increased WHR, BMI, and TDI are significant predictors of poor health, and WHR showed a greater role. The impact of deprivation indices on health showed differences by sex. Socio-economic factors, such as income and TDI, are associated with CCI. The association of social status differences caused by these socioeconomic factors with health conditions should be considered. Factors might interact with each other; therefore, a comprehensive, rational, and robust intervention will be necessary for health.

The extent of the relationship between age and the presence of breast cancer synchronous brain metastases (BCSBMs) and mortality has not yet been well-identified or sufficiently quantified. We aimed to examine the association of age with the presence of BCSBMs and all-cause and cancer-specific mortality outcomes using the SEER database.
Age-associated risk of the presence and survival of BCSBMs were evaluated on a continuous scale (restricted cubic spline, RCS) with logistic or Cox regression models. The main endpoints were the presence of BCSBMs and all-cause mortality or cancer-specific mortality. Cox proportional hazards regression and competing risk models were used in survival analysis.
Among 374,132 adult breast cancer patients, 1,441 (0.38%) had BMs. The presence of BCSBMs displayed a U-shaped relationship with age, with the highest point of the curve occurring at the age of 62. In both the younger (age ≤ 61) and older (age ≥ 62) groups, the observed curve showed a nearly linear relationship between age and the presence of BCSBMs. The relationship between age and all-cause mortality (ASM) and cancer-specific mortality (CSM) was linear. Older age at diagnosis was associated with a higher risk of ASM (HR 1.019, 95% CI: 1.013-1.024, p < 0.001) and CSM (HR 1.016, 95% CI: 1.010-1.023, p < 0.001) in multivariable Cox models. Age (sHR 1.007, 95% CI 1-1.013, p = 0.049) was substantially related to a significantly increased risk of CSM in competing risk models.
Age had a non-linear U-shaped relationship with the presence of BCSBMs and a linear relationship with BCSBMs mortality.