Variational autoencoders for generative modeling of drug dosing determinants in renal, hepatic, metabolic, and cardiac disease states.

Physiological determinants of drug dosing (PDODD) are a promising approach for precision dosing. This study investigates the alterations of PDODD in diseases and evaluates a variational autoencoder (VAE) artificial intelligence model for PDODD. The PDODD panel contained 20 biomarkers, and 13 renal, hepatic, diabetes, and cardiac disease status variables. Demographic characteristics, anthropometric measurements (body weight, body surface area, waist circumference), blood (plasma volume, albumin), renal (creatinine, glomerular filtration rate, urine flow, and urine albumin to creatinine ratio), and hepatic (R-value, hepatic steatosis index, drug-induced liver injury index), blood cell (systemic inflammation index, red cell, lymphocyte, neutrophils, and platelet counts) biomarkers, and medical questionnaire responses from the National Health and Nutrition Examination Survey (NHANES) were included. The tabular VAE (TVAE) generative model was implemented with the Synthetic Data Vault Python library. The joint distributions of the generated data vs. test data were compared using graphical univariate, bivariate, and multidimensional projection methods and distribution proximity measures. The PDODD biomarkers related to disease progression were altered as expected in renal, hepatic, diabetes, and cardiac diseases. The continuous PDODD panel variables generated by the TVAE satisfactorily approximated the distribution in the test data. The TVAE-generated distributions of some discrete variables deviated from the test data distribution. The age distribution of TVAE-generated continuous variables was similar to the test data. The TVAE algorithm demonstrated potential as an AI model for continuous PDODD and could be useful for generating virtual populations for clinical trial simulations.

Association of urinary bisphenol A with hyperlipidemia and all-cause mortality: NHANES 2003-2016.

BACKGROUND: The connection between urinary bisphenol A (BPA) and hyperlipidemia is still unclear, and few studies have evaluated whether urinary BPA affects mortality among individuals with hyperlipidemia. Therefore, we aimed to investigate the link between urinary BPA and hyperlipidemia and assess the impact of urinary BPA on mortality risk in subjects with hyperlipidemia. METHODS: We analyzed data of the National Health and Nutrition Examination Survey from 2003 to 2016. Multivariable logistic analysis was performed to examine the relationship between urinary BPA and hyperlipidemia. Cox regression analysis was carried out to investigate the relationship between urinary BPA and all-cause mortality in subjects with hyperlipidemia. RESULTS: This study included 8,983 participants, of whom 6,317 (70.3%) were diagnosed with hyperlipidemia. The results showed that urinary BPA was higher in participants with hyperlipidemia group than those without hyperlipidemia (3.87 ± 0.32 vs. 2.98 ± 0.14, P = 0.01). Urinary BPA levels were analyzed in tertiles. Compared with tertile 1 of BPA (reference), the odds ratio (95% confidence interval) of hyperlipidemia related to tertile 3 of BPA was 1.28 (1.11-1.48). The hazard ratio for all-cause death associated with the highest versus lowest tertile of urinary BPA was 1.20 (95% confidence interval: 1.01-1.44; P = 0.04) among participants with hyperlipidemia. CONCLUSIONS: The study indicated a positive relationship between urinary BPA and the risk of hyperlipidemia. Urinary BPA was associated with a significantly higher risk of all-cause mortality in adults with hyperlipidemia.

Associations of accelerometer-measured physical activity and sedentary time with renal function and chronic kidney disease: a national population-based study.

Introduction: There is limited information about the relationship between physical activity (PA) and sedentary behaviors in chronic kidney disease (CKD). Therefore, this study aims to explore the associations of accelerometer-measured PA and sedentary behaviors with CKD. Methods: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey in the 2003-2004 and 2005-2006 survey cycles. A uniaxial accelerometer measured physical activity (PA) and sedentary time (ST). The associations of PA and ST with estimated glomerular filtration rate (eGFR) and odds of CKD adopted the generalized linear regression, multivariable logistic regression, and isotemporal substitution models. Results: A total of 5,990 adults with 605 CKD patients were included in this study. Compared with the individuals in the first quartile group, participants in the fourth quartile of low-intensity physical activity (LIPA), moderate to vigorous physical activity (MVPA), and ST were associated with 52% (35%, 65%) and 42% (14%, 62%) lower odds of CKD and 64% (17%, 131%) higher odds of CKD, respectively. Substituting 30 min/day of ST with equivalent LIPA/MVPA contributed to risk reduction in CKD. Discussion: The findings suggest that increased LIPA and MVPA and reduced ST were associated with a lower risk of CKD and that replacing ST with LIPA may decrease the risk of CKD.

Assessing causal associations of blood counts and biochemical indicators with pulmonary arterial hypertension: a Mendelian randomization study and results from national health and nutrition examination survey 2003-2018.

Background: Blood counts and biochemical markers are among the most common tests performed in hospitals and most readily accepted by patients, and are widely regarded as reliable biomarkers in the literature. The aim of this study was to assess the causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension (PAH). Methods: A two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between blood counts and biochemical indicators with PAH. The genome-wide association study (GWAS) for blood counts and biochemical indicators were obtained from the UK Biobank (UKBB), while the GWAS for PAH were sourced from the FinnGen Biobank. Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by three sensitivity analyses to assess the robustness of the results. And we conducted an observational study using data from National Health and Nutrition Examination Survey (NHANES) 2003-2018 to verify the relationship. Results: The MR analysis primarily using the IVW method revealed genetic variants of platelet count (OR=2.51, 95% CI 1.56-4.22, P<0.001), platelet crit(OR=1.87, 95% CI1.17-7.65, P=0.022), direct bilirubin (DBIL)(OR=1.71, 95%CI 1.18-2.47,P=0.004), insulin-like growth factor (IGF-1)(OR=0.51, 95% CI 0.27-0.96, P=0.038), Lipoprotein A (Lp(a))(OR=0.66, 95% CI 0.45-0.98, P=0.037) and total bilirubin (TBIL)(OR=0.51, 95% CI 0.27-0.96, P=0.038) were significantly associated with PAH. In NHANES, multivariate logistic regression analyses revealed a significant positive correlation between platelet count and volume and the risk of PAH, and a significant negative correlation between total bilirubin and PAH. Conclusion: Our study reveals a causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension. These findings offer novel insights into the etiology and pathological mechanisms of PAH, and emphasizes the important value of these markers as potential targets for the prevention and treatment of PAH.

Joint association of weight-adjusted-waist index and physical activity with insulin resistance in adolescents: a cross-sectional study.

BACKGROUND: The weight-adjusted waist index (WWI) is a recently developed obesity metric, and the aim of this study was to investigate the relationship between physical activity (PA) and WWI and the homeostasis model assessment of insulin resistance (HOMA-IR) in adolescents, as well as the joint association of HOMA-IR. METHODS: This study was based on the National Health and Nutrition Survey conducted between 2013 and 2016 and included 1024 adolescents whose median age was 15.4. Multivariate linear regression was used to examine the associations between HOMA-IR and PA and WWI. Using generalized additive models, a potential nonlinear link between WWI and HOMA-IR was evaluated. Subgroup analysis was also carried out. RESULTS: The fully adjusted model revealed a positive association (ß: 0.48, 95% CI: 0.43, 0.53) between the WWI and HOMA-IR. The HOMA-IR was lower in physically active (ß: -0.16, 95% CI: -0.26, -0.05) participants versus inactive participants. Participants who had higher WWI and were not physically active (ß: 0.69; 95% CI: 0.56, 0.82) had the highest levels of HOMA-IR compared to participants who had lower WWI and were physically active. Subgroup analysis revealed that these correlations were similar in males and females. CONCLUSION: Our results demonstrated that higher WWI and PA were associated with a lower HOMA-IR and that WWI and PA had a combined association with HOMA-IR. The findings of this study are informative for the preventing insulin resistance in adolescents.

Association Between Economic Activity and Depressive Symptoms Among Women With Parenting Children.

BACKGROUND: Balancing parenting and work life poses challenges for women with children, potentially making them vulnerable to depression owing to their dual responsibilities. Investigating working mothers' mental health status is important on both the individual and societal levels. This study aimed to explore the relationship between economic activity participation and depressive symptoms among working mothers. METHODS: This study was a cross-sectional study and used data from the Korea National Health and Nutrition Examination Survey collected in 2014, 2016, 2018, and 2020. The participants in the study were women aged 19 to 50 who were residing with their children. In the total, 3,151 participants were used in the analysis. The independent variable was economic activity, categorized into two groups: 1) economically active and 2) economically inactive. The dependent variable was the depressive symptoms, categorized as present for a Patient Health Questionnaire-9 score of ≥ 10 and absent for a score < 10. Multiple logistic regression analysis was performed to assess the association between economic activity and depressive symptoms, and sensitivity analyses were performed based on the severity of depressive symptoms. RESULTS: Among women with children, economically active women had reduced odds ratio of depressive symptoms compared with economically inactive women (odds ratio [OR], 0.54; 95% confidence interval [CI], 0.36-0.80). In additional analysis, women working as wage earners had the lowest odds of depressive symptoms (OR, 0.43; 95% CI, 0.28-0.66). Women working an average of 40 hours or less per week were least likely to have depressive symptoms (OR, 0.42; 95% CI, 0.25-0.69). CONCLUSION: Economic activity is significantly associated with depressive symptoms among women with children. Environmental support and policy approaches are needed to ensure that women remain economically active after childbirth.

Influence of lifestyle patterns on depression among adults with diabetes: a mediation effect of dietary inflammatory index.

BACKGROUND: Lifestyle has become a crucial modulator in the management of diabetes and is intimately linked with the development and exacerbation of comorbid depression. The study aimed to analyze lifestyle patterns and their impact on depression in individuals with diabetes and to explore the role of the Dietary Inflammatory Index (DII) in the relationship between lifestyle patterns and depression. METHODS: Data was attained from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2020. A latent class analysis (LCA) was performed on 3,009 diabetic adults based on lifestyle behaviors. A generalised linear model (GLM) was employed to analyse the effects of different lifestyle patterns on depression. The mediation effect model was utilised to examine the relationship between lifestyle patterns, DII and Patient Health Questionnaire-9 (PHQ-9) scores. RESULTS: The cohort was divided through LCA into unhealthy lifestyle (44.53%), unhealthy but non-alcohol use (48.06%) and healthy but smoking (7.41%) groups of lifestyle behaviors, the unhealthy but non-alcohol use group was identified as a risk factor for depression (OR = 1.379, 95%CI = 1.095 ~ 1.735, P = 0.006). The DII partially mediated the relationship between the unhealthy but non-alcohol use group and PHQ-9, and fully mediated the relationship between the healthy but smoking group and PHQ-9, with effect coefficients of - 0.018 (95%CI: -0.044 ~ - 0.001) and - 0.035 (95%CI: -0.083 ~ - 0.001). CONCLUSIONS: Lifestyle patterns significantly influence the occurrence of depression among diabetes patients. The dietary inflammation plays a varying mediating role between different lifestyle patterns and depression. Restricting pro-inflammatory diets or encouraging anti-inflammatory diets, combined with the promotion of healthy lifestyle practices, may be an effective method for preventing and alleviating symptoms of depression among patients with diabetes.

Reallocating just 10 min to moderate-to-vigorous physical activity from other components of 24-hour movement behaviors improves cardiovascular health in adults.

BACKGROUND: As components of a 24-hour day, sedentary behavior (SB), physical activity (PA), and sleep are all independently linked to cardiovascular health (CVH). However, insufficient understanding of components' mutual exclusion limits the exploration of the associations between all movement behaviors and health outcomes. The aim of this study was to employ compositional data analysis (CoDA) approach to investigate the associations between 24-hour movement behaviors and overall CVH. METHODS: Data from 581 participants, including 230 women, were collected from the 2005-2006 wave of the US National Health and Nutrition Examination Survey (NHANES). This dataset included information on the duration of SB and PA, derived from ActiGraph accelerometers, as well as self-reported sleep duration. The assessment of CVH was conducted in accordance with the criteria outlined in Life's Simple 7, encompassing the evaluation of both health behaviors and health factors. Compositional linear regression was utilized to examine the cross-sectional associations of 24-hour movement behaviors and each component with CVH score. Furthermore, the study predicted the potential differences in CVH score that would occur by reallocating 10 to 60 min among different movement behaviors. RESULTS: A significant association was observed between 24-hour movement behaviors and overall CVH (p < 0.001) after adjusting for potential confounders. Substituting moderate-to-vigorous physical activity (MVPA) for other components was strongly associated with favorable differences in CVH score (p < 0.05), whether in one-for-one reallocations or one-for-remaining reallocations. Allocating time away from MVPA consistently resulted in larger negative differences in CVH score (p < 0.05). For instance, replacing 10 min of light physical activity (LPA) with MVPA was related to an increase of 0.21 in CVH score (95% confidence interval (95% CI) 0.11 to 0.31). Conversely, when the same duration of MVPA was replaced with LPA, CVH score decreased by 0.67 (95% CI -0.99 to -0.35). No such significance was discovered for all duration reallocations involving only LPA, SB, and sleep (p > 0.05). CONCLUSIONS: MVPA seems to be as a pivotal determinant for enhancing CVH among general adult population, relative to other movement behaviors. Consequently, optimization of MVPA duration is an essential element in promoting overall health and well-being.

Association between bedtime and female infertility: a secondary analysis from a cross-sectional study.

Objective: To evaluate the association between bedtime and infertility and to identify the optimal bedtime for women of reproductive age. Methods: We conducted a cross-sectional study using data from 3,903 female participants in the National Health and Nutrition Examination Survey (NHANES) from 2015 to 2020. The effect of bedtime on female infertility was assessed using the binary logistic regression in different models, including crude model and adjusted models. To identify the non-linear correlation between bedtime and infertility, generalized additive models (GAM) were utilized. Subgroup analyses were conducted by age, body mass index (BMI), waist circumference, physical activity total time, marital status, smoking status, drinking status and sleep duration. Results: After adjusting for potential confounders (age, race, sleep duration, waist circumference, marital status, education, BMI, smoking status, drinking status and physical activity total time), a non-linear relationship was observed between bedtime and infertility, with the inflection point at 22:45. To the left side of the inflection point, no significant association was detected. However, to the right of it, bedtime was positively related to the infertility (OR: 1.22; 95% CI: 1.06 to 1.39; P = 0.0049). Subgroup analyses showed that late sleepers with higher BMI were more prone to infertility than those with a lower BMI (BMI: 25-30 kg/m2: OR: 1.26; 95% CI: 1.06 to 1.51; P = 0.0136; BMI ≥ 30 kg/m²: OR: 1.21, 95% CI: 1.09 to 1.34; P = 0.0014). Conclusion: Bedtime was non-linearly associated with infertility, which may provide guidance for sleep behavior in women of childbearing age.

Association between oxidative balance score and serum uric acid and hyperuricemia: a population-based study from the NHANES (2011-2018).

Background: Oxidative Balance Score (OBS) is a novel indicator of the overall antioxidant/oxidant balance, providing a comprehensive reflection of the body's overall oxidative stress status, with higher OBS suggesting more substantial antioxidant exposures. We aimed to investigate the possible relationship between OBS with serum uric acid (SUA) and hyperuricemia. Methods: Data utilized in this study were sourced from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Participants under 18 years old, those with ≤16 complete data out of 20 OBS components, incomplete serum uric acid data, and missing covariates were excluded from the analysis. OBS was computed by evaluating 16 nutrients and 4 lifestyle factors, encompassing 5 pro-oxidants and 15 antioxidants, guided by a priori knowledge of their relationship with oxidative stress. Results: A total of 1,5096 individuals were included in our analysis with 49.7% being male, and an average age of 49.05 ± 17.56 years. The mean OBS was 19.76 ± 7.17. Hyperuricemia was present in 19.28% of participants. Due to the right-skewed distribution of the OBS, a natural log transformation was applied to address this issue, and Quartiles of lnOBS 1, 2, 3, and 4 were 1.10-2.56 (N=3526), 2.64-2.94 (N=3748), 3.00-3.22 (N=4026), and 3.26-3.61 (N=3796), respectively. Multivariable logistic regression showed that higher lnOBS quantiles were correlated with lower serum uric acid levels. Compared with the lowest lnOBS quantile, participants in the highest lnOBS quantile had a significant serum uric acid decrease of 16.94 µmol/L for each unit increase in lnOBS (ß=-16.94, 95% CI: -20.44, -13.45). Similar negative associations were observed in the second-highest (ß=-8.07, 95% CI: -11.45, -4.69) and third-highest (ß=-11.69, 95% CI: -15.05, -8.34) lnOBS quantiles. The adjusted odds ratios (ORs) for hyperuricemia in Quartiles 1, 2, 3, and 4 were 1.00, 0.84 (95% CI: 0.75, 0.95), 0.78 (95% CI: 0.69, 0.88), and 0.62 (95% CI: 0.55, 0.71), respectively. Compared to Quartile 1, participants in Quartile 4 had a 38% lower prevalence of hyperuricemia. Subgroup analysis and interaction test showed that there was a significant dependence of sex between OBS and serum uric acid (p for interaction <0.05), but not hyperuricemia (p for interaction >0.05). Subgroup analysis stratified by age, BMI, hypertension, diabetes, and hyperlipidemia showed there is no significant dependence on these negative correlations (all p for interaction >0.05). Conclusions: The serum uric acid levels and prevalence of hyperuricemia in US adults exhibited a negative association with OBS. By exploring this connection, our research aims to gain a better understanding of how oxidative balance affects the prevalence of hyperuricemia. This could provide valuable insights for developing preventive strategies and interventions for hyperuricemia. Additional large-scale prospective studies are required to explore the role of OBS in hyperuricemia further.

Overall, sex-and race/ethnicity-specific prevalence of thyroid dysfunction in US adolescents aged 12-18 years.

Background: Thyroid dysfunction significantly affects the health and development of adolescents. However, comprehensive studies on its prevalence and characteristics in US adolescents are lacking. Methods: We investigated the prevalence of thyroid dysfunction in US adolescents aged 12-18 years using data from the National Health and Nutrition Examination Survey (NHANES) 2001-2002 and 2007-2012 cycles. Thyroid dysfunction was assessed using serum thyroid-stimulating hormone (TSH) and free thyroxine (fT4) measurements. We analyzed the prevalence across demographic subgroups and identified associated risk factors. Results: The study included 2,182 participants, representing an estimated 12.97 million adolescents. The group had a weighted mean age of 15.1 ± 0.06 years, with males constituting 51.4%. Subclinical hyperthyroidism emerged as the most prevalent thyroid dysfunction, affecting 4.4% of the population. From 2001-2002 to 2011-2012, subclinical hyperthyroidism remained consistent at 4.99% vs. 5.13% in the overall cohort. Subclinical and overt hypothyroidism was found in 0.41 and 1.03% of adolescents respectively, and overt hyperthyroidism was rare (0.04%). The prevalence of thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb) positivity in the overall population were 5.8 and 9.8%, respectively. Positivity for TgAb was risk factors for hypothyroidism, while older age, female and Black Americans were risk factors for hyperthyroidism. Female adolescents and adolescents with an older age were more likely to be positive for TPOAb and TgAb, while Black and Mexican Americans had a lower risk of TPOAb and TgAb positivity. Conclusion: Subclinical hyperthyroidism was the most common form of thyroid dysfunction, and its prevalence remained stable from 2001-2002 to 2011-2012. Notable disparities in the prevalence of hyperthyroidism and antibody positivity were observed among different age, sex and racial/ethnic groups.

Estimated effects of reductions in processed meat consumption and unprocessed red meat consumption on occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the USA: a microsimulation study.

BACKGROUND: High consumption of processed meat and unprocessed red meat is associated with increased risk of multiple chronic diseases, although there is substantial uncertainty regarding the relationship for unprocessed red meat. We developed a microsimulation model to estimate how reductions in processed meat and unprocessed red meat consumption could affect rates of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the US adult population. METHODS: We used data from two versions of the US National Health and Nutrition Examination Survey, one conducted during 2015-16 and one conducted during 2017-18, to create a simulated US population. The starting cohort was restricted to respondents aged 18 years or older who were not pregnant and had 2 days of dietary-recall data. First, we used previously developed risk models to estimate the baseline disease risk of an individual. For type 2 diabetes we used a logistic-regression model and for cardiovascular disease and colorectal cancer we used Cox proportional-hazard models. We then multiplied baseline risk by relative risk associated with individual processed meat and unprocessed red meat consumption. Prevented occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality were computed by taking the difference between the incidence in the baseline and intervention scenarios. All stages were repeated for ten iterations to correspond to a 10-year time span. Scenarios were reductions of 5%, 10%, 30%, 50%, 75%, and 100% in grams consumed of processed meat, unprocessed red meat, or both. Each scenario was repeated 50 times for uncertainty analysis. FINDINGS: The total number of individual respondents included in the simulated population was 8665, representing 242 021 876 US adults. 4493 (51·9%) of 8665 individuals were female and 4172 (48·1%) were male; mean age was 49·54 years (SD 18·38). At baseline, weighted mean daily consumption of processed meat was 29·1 g, with a 30% reduction being 8·7 g per day, and of unprocessed red meat was 46·7 g, with a 30% reduction being 14·0 g per day. We estimated that a 30% reduction in processed meat intake alone could lead to 352 900 (95% uncertainty interval 345 500-359 900) fewer occurrences of type 2 diabetes, 92 500 (85 600-99 900) fewer occurrences of cardiovascular disease, 53 300 (51 400-55 000) fewer occurrences of colorectal cancer, and 16 700 (15 300-17 700) fewer all-cause deaths during the 10-year period. A 30% reduction in unprocessed red meat intake alone could lead to 732 600 (725 700-740 400) fewer occurrences of type 2 diabetes, 291 500 (283 900-298 800) fewer occurrences of cardiovascular disease, 32 200 (31 500-32 700) fewer occurrences of colorectal cancer, and 46 100 (45 300-47 200) fewer all-cause deaths during the 10-year period. A 30% reduction in both processed meat and unprocessed red meat intake could lead to 1 073 400 (1 060 100-1 084 700) fewer occurrences of type 2 diabetes, 382 400 (372 100-391 000) fewer occurrences of cardiovascular disease, 84 400 (82 100-86 200) fewer occurrences of colorectal cancer, and 62 200 (60 600-64 400) fewer all-cause deaths during the 10-year period. INTERPRETATION: Reductions in processed meat consumption could reduce the burden of some chronic diseases in the USA. However, more research is needed to increase certainty in the estimated effects of reducing unprocessed red meat consumption. FUNDING: The Wellcome Trust.

Environmental Toxicant Exposure and Depressive Symptoms.

Importance: Recognizing associations between exposure to common environmental toxicants and mental disorders such as depression is crucial for guiding targeted mechanism research and the initiation of disease prevention efforts. Objectives: To comprehensively screen and assess the associations between potential environmental toxicants and depressive symptoms and to assess whether systemic inflammation serves as a mediator. Design, Setting, and Participants: A total of 3427 participants from the 2013-2014 and 2015-2016 waves of the National Health and Nutrition Examination and Survey who had information on blood or urine concentrations of environmental toxicants and depression scores assessed by the 9-item Patient Health Questionnaire (PHQ-9) were included. Statistical analysis was performed from July 1, 2023, to January 31, 2024. Exposures: Sixty-two toxicants in 10 categories included acrylamide, arsenic, ethylene oxide, formaldehyde, iodine, metals, nicotine metabolites, polycyclic aromatic hydrocarbons, volatile organic compound (VOC) metabolites; and perchlorate, nitrate, and thiocyanate. Main Outcomes and Measures: An exposome-wide association study and the deletion-substitution-addition algorithm were used to assess associations with depression scores (PHQ-9 ≥5) adjusted for other important covariates. A mediation analysis framework was used to evaluate the mediating role of systemic inflammation assessed by the peripheral white blood cell count. Results: Among the 3427 adults included, 1735 (50.6%) were women, 2683 (78.3%) were younger than 65 years, and 744 (21.7%) were 65 years or older, with 839 (24.5%) having depressive symptoms. In terms of race and ethnicity, 570 participants (16.6%) were Mexican American, 679 (19.8%) were non-Hispanic Black, and 1314 (38.3%) were non-Hispanic White. We identified associations between 27 chemical compounds or metals in 6 of 10 categories of environmental toxicants and the prevalence of depressive symptoms, including the VOC metabolites N-acetyl-S-(2-hydroxy-3-butenyl)-l-cysteine (odds ratio [OR], 1.74 [95% CI, 1.38, 2.18]) and total nicotine equivalent-2 (OR, 1.42 [95% CI, 1.26-1.59]). Men and younger individuals appear more vulnerable to environmental toxicants than women and older individuals. Peripheral white blood cell count mediated 5% to 19% of the associations. Conclusions and Relevance: In this representative cross-sectional study of adults with environmental toxicant exposures, 6 categories of environmental toxicants were associated with depressive symptoms with mediation by systemic inflammation. This research provides insight into selecting environmental targets for mechanistic research into the causes of depression and facilitating efforts to reduce environmental exposures.

Comparison of model feature importance statistics to identify covariates that contribute most to model accuracy in prediction of insomnia.

IMPORTANCE: Sleep is critical to a person's physical and mental health and there is a need to create high performing machine learning models and critically understand how models rank covariates. OBJECTIVE: The study aimed to compare how different model metrics rank the importance of various covariates. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional cohort study was conducted retrospectively using the National Health and Nutrition Examination Survey (NHANES), which is publicly available. METHODS: This study employed univariate logistic models to filter out strong, independent covariates associated with sleep disorder outcome, which were then used in machine-learning models, of which, the most optimal was chosen. The machine-learning model was used to rank model covariates based on gain, cover, and frequency to identify risk factors for sleep disorder and feature importance was evaluated using both univariable and multivariable t-statistics. A correlation matrix was created to determine the similarity of the importance of variables ranked by different model metrics. RESULTS: The XGBoost model had the highest mean AUROC of 0.865 (SD = 0.010) with Accuracy of 0.762 (SD = 0.019), F1 of 0.875 (SD = 0.766), Sensitivity of 0.768 (SD = 0.023), Specificity of 0.782 (SD = 0.025), Positive Predictive Value of 0.806 (SD = 0.025), and Negative Predictive Value of 0.737 (SD = 0.034). The model metrics from the machine learning of gain and cover were strongly positively correlated with one another (r > 0.70). Model metrics from the multivariable model and univariable model were weakly negatively correlated with machine learning model metrics (R between -0.3 and 0). CONCLUSION: The ranking of important variables associated with sleep disorder in this cohort from the machine learning models were not related to those from regression models.

Association of the systemic immune-inflammation index with all-cause and cardiovascular mortality in individuals with rheumatoid arthritis.

The systemic immune-inflammation index (SII), a metric reflecting systemic inflammatory response and immune activation, remains underexplored concerning its correlation with mortality among rheumatoid arthritis (RA) patients. This study aimed to delineate the association between SII and both all-cause and cardiovascular mortality within the cohort of American adults diagnosed with RA, utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. The investigation extracted data from NHANES cycles between 1999 and 2018, identifying RA patients through questionnaire responses. The SII was computed based on complete blood counts, employing the formula: (platelets × neutrophils) / lymphocytes. The optimal SII cutoff value for significant survival outcomes was determined using maximally selected rank statistics. Multivariable Cox proportional hazards models assessed the relationship between SII levels and mortality (all-cause and cardiovascular) among RA patients, with subgroup analyses examining potential modifications by clinical confounders. Additionally, restricted cubic spline (RCS) analyses were conducted to explore the linearity of the SII-mortality association. The study encompassed 2070 American adults with RA, among whom 287 exhibited a higher SII (≥ 919.75) and 1783 a lower SII (< 919.75). Over a median follow-up duration of 108 months, 602 participants died. After adjustments for demographic, socioeconomic, and lifestyle variables, a higher SII was associated with a 1.48-fold increased risk of all-cause mortality (hazard ratio [HR] = 1.48, 95% confidence interval [CI] 1.21-1.81, P < 0.001) and a 1.51-fold increased risk of cardiovascular mortality (HR = 1.51, 95% CI 1.04-2.18, P = 0.030) compared to a lower SII. Kaplan-Meier analyses corroborated significantly reduced survival rates within the higher SII cohort for both all-cause and cardiovascular mortality (Pall-cause mortality < 0.0001 and Pcardiovascular mortality = 0.0004). RCS analyses confirmed a positive nonlinear relationship between SII and mortality rates. In conclusion, the SII offers a straightforward indicator of the equilibrium between detrimental innate inflammation and beneficial adaptive immunity. Our investigation, utilizing a comprehensive and nationally representative sample, reveals that elevated SII levels independently forecast a greater risk of mortality from all causes, as well as cardiovascular-specific mortality, in individuals suffering from RA. These insights underscore the clinical relevance of the SII as an affordable and readily accessible biomarker. Its incorporation into regular clinical practice could significantly enhance the precision of risk assessment and forecasting for patients with RA, facilitating more tailored and effective management strategies. Specifically, patients with high SII levels could be identified for more stringent cardiovascular risk management, including closer monitoring, lifestyle interventions, and aggressive pharmacological treatments to mitigate their increased risk of mortality.

Interaction effects between sleep-related disorders and depression on hypertension among adults: a cross-sectional study.

BACKGROUND: Hypertension, sleep disorders, and depression represent notable public health issues, and their interconnected nature has long been acknowledged. The objective of this study is to explore the interplay between sleep disorders and depression in the context of hypertension. METHODS: This cross-sectional study involved 42,143 participants aged 18 and above from the NHANES database across seven survey cycles between 2005 and 2018. After excluding those with missing data on depression, sleep disorders, and hypertension, as well as incomplete main variables, 33,383 participants remained. We used weighted logistic regression to examine the relationship between sleep disorders, depression, and hypertension. Additionally, we assessed the interaction between sleep disorders and depression on hypertension using both multiplicative and additive approaches to quantify their combined effect. RESULTS: Compared to individuals without sleep disorders, those with sleep disorders have an increased risk of hypertension (OR = 1.51, 95% CI: 1.37-1.67). Furthermore, individuals with depression experience a significantly higher risk of hypertension compared to those with sleep disorders alone (OR = 2.34, 95% CI: 1.95-2.80). Our study reveals a positive interaction between sleep disorders and depression in relation to hypertension risk (OR = 1.07, 95% CI: 1.02-1.13). In addition, we observed the quantitative additive interaction indicators (RERI = 0.73, 95% CI: 0.56 ~ 0.92; API = 0.31, 95% CI: 0.11 ~ 0.46; SI = 2.19, 95% CI: 1.08-3.46) influencing hypertension risk. Furthermore, our research also identified that individuals with less than 7 h of sleep, a sleep latency period between 5 and 30 min, or a latency period exceeding 30 min experience a significantly increased risk of hypertension. CONCLUSIONS: Our research uncovered separate links between sleep disorders, depression, and hypertension prevalence. Moreover, we identified an interaction between depression and sleep disorders in hypertension prevalence. Enhancing mental well-being and tackling sleep disorders could help prevent and manage hypertension. Yet, more investigation is required to establish causation and clarify mechanisms.

Association between dietary patterns and the risk of all-cause mortality among old adults with obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) was associated with the increased cardiovascular events and all-cause mortality. And anti-inflammatory dietary has potential to improve the prognosis of OSA. This study aimed to investigate the association of anti-inflammatory dietary patterns with all-cause mortality among individuals with OSA. METHODS: This retrospective cohort study involved 1522 older adults with OSA from 2005 to 2008 in the National Health and Nutrition Examinations Survey (NHANES). Mortality status was determined by routine follow-up through December 31, 2019, using the National Death Index. Anti-inflammatory dietary patterns included Alternate Mediterranean Diet Score (aMED), Healthy Eating Index-2015 (HEI-2015), and Alternate Healthy Eating Index-2010 (AHEI-2010). Weighted Cox proportional hazard regression models were performed to investigate the association between anti-inflammatory dietary pattern and all-cause mortality. RESULTS: After a median follow-up of 131 months, 604 participants were recorded all-cause mortality. The mean age of OSA patients was 68.99 years old, of whom 859 were male (52.34%). Higher adherence of aMED (HR = 0.61, 95%CI: 0.48 to 0.78) and HEI-2015 (HR = 0.75, 95%CI: 0.60 to 0.95) were associated with lower all-cause mortality risk in the elderly with OSA. Conversely, no association was found between AHEI-2010 dietary pattern and all-cause mortality in individuals with OSA. In the component analysis of aMED, it was found that a higher intake of vegetables and olive oil potentially contributes to the reduction all-cause mortality risk in the elderly with OSA (HR = 0.60, 95%CI: 0.48 to 0.76; HR = 0.67, 95%CI: 0.63 to 0.71). CONCLUSION: Higher adherence to the aMED and the HEI-2015 was associated with a lower risk of all-cause mortality in OSA. Future interventions in the elderly with OSA should considering adopting anti-inflammatory dietary patterns.

Dietary calcium intake at breakfast is associated with a lower risk of cognitive impairment than at dinner in Chinese adults: the CHNS cohort study.

BACKGROUND AND OBJECTIVES: If the proportion of calcium intake over a whole day is related to the risk of cognitive impairment in adults is still largely unknown. This research aimed to examine the relation of dietary calcium intake at dinner versus breakfast with the risk of cognitive impairment by using data from the China Health and Nutrition Survey (CHNS). METHODS AND STUDY DESIGN: A total of 2,099 participants (including 668 cognitive impairment) in the CHNS (1997-2006) were included. The participants were categorized into 5 groups in accordance with the ratio of dietary calcium intake at dinner and breakfast (Δ = dinner/breakfast). After adjustment was conducted for a series of confounding factors, Cox hazard regression modelling was performed to discuss the relation of Δ with cognitive impairment. Dietary substitution models were used to explore the changes in cognitive impairment risk when a 5% dietary calcium intake at dinner was replaced with dietary calcium intake at breakfast. RESULTS: Participants in the highest distribution of Δ showed a greater susceptibility to cognitive impairment than those in the lowest quintile, with an adjusted hazard ratio of cognitive impairment of 1.38 (95% CI: 1.08-1.76). When maintaining total calcium intake, substituting 5% of dietary calcium intake at dinner with calcium intake at breakfast was related to an 8% decrease in the risk of cognitive impairment. CONCLUSIONS: Higher dietary calcium intake at dinner was associated with an increased risk of cognitive impairment, emphasizing the importance of appropriately distributing dietary calcium intake between breakfast and dinner.

Associations between dietary iron intake from different sources and non-alcoholic fatty liver disease in adults.

BACKGROUND AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) has become a worldwide public health problem. Current evidence on the association between dietary iron intake and the risk of NAFLD is limited. The present study aimed to investigate the associations of animal-derived dietary iron (ADDI) intake, plant-derived dietary iron (PDDI) intake, and the ratio of PDDI:ADDI with NAFLD risk among U.S. adult population. METHODS AND STUDY DESIGN: This was a repeated cross-sectional study. Data were collected from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. NAFLD was defined as a United States Fatty Lives Index ≥30, and dietary iron intake was assessed through two 24-h dietary recall in-terviews. Logistic regression and restricted cubic spline models were applied to examine the associations between dietary iron intake from different sources and NAFLD risk. RESULTS: A total of 9478 participants aged ≥20 years were enrolled in the present study. After adjustment for multiple confounding factors, relative to the lowest quartile, the odds ratio (OR) and 95% confidence interval (CI) of NAFLD for the highest quartile was 1.01(95% CI, 0.82-1.24) for ADDI intake, 0.82 (95% CI, 0.64-0.99) for PDDI intake, and 1.00 (95% CI, 0.81-1.24) for the PDDI: ADDI intake ratio. In stratified analysis by sex and age, the significantly negative associations of PDDI intake with NAFLD was observed in women and participants older than 45 years. Dose-response analyses indicated that NAFLD was negatively associated with PDDI intake in a non-linear manner. CONCLUSIONS: PDDI intake was negatively associated with NAFLD in U.S. adults.

Association of the dietary inflammation index DII with the prevalence of chronic kidney disease in patients with hypertension.

BACKGROUND AND OBJECTIVE: Chronic kidney disease (CKD) is a global health concern that is frequently associated with hypertension. Inflammation is an important factor in the development of both illnesses. The Dietary Inflammation Index (DII) has evolved as a way to measure how much a diet can cause inflammation, which may impact CKD, especially in hypertensive persons. The study's goal is to investigate the link between DII and the occurrence of CKD in hypertensive individuals. METHODS: This study examined data from 22940 hypertensive patients from 1999 to 2018 of the National Health and Nutrition Examination Survey (NHANES). The DII was computed using 28 dietary components. CKD was diagnosed based on the estimated glomerular filtration rate and urine albumin-to-creatinine ratio. The link between DII and CKD was explored using sampling-weighted logistic regression and restricted cubic splines. RESULTS: Higher DII scores were shown to be strongly related with an increased risk of CKD. In the fully adjusted model, this connection remained consistent across demographic and clinical categories. CONCLUSIONS: The study found a strong association between a pro-inflammatory diet and an elevated risk of CKD in hypertensive individuals, emphasizing the potential of dietary changes in CKD management.