National Health And Nutrition Examination Survey Dataset Research Articles

Dietary inflammatory index and all-cause mortality in adults with COPD: a prospective cohort study from the NHANES 1999-2018.

Chronic inflammation is closely linked to Chronic Obstructive Pulmonary Disease (COPD); however, the impact of the Dietaryq Inflammatory Index (DII) on mortality among COPD patients remains uncertain. To assess the correlation between the DII and all-cause mortality in COPD patients using data from the National Health and Nutrition Examination Survey (NHANES). We conducted a retrospective cohort study on 1,820 COPD patients from the NHANES dataset (1999-2018). The influence of DII on mortality was evaluated using multivariate Cox regression, smoothing spline fitting, and threshold effect analysis. Additionally, Kaplan-Meier survival analysis was performed to compare survival curves among different DII groups. Subgroup analyses and E-values identified sensitive cohorts and assessed unmeasured confounding. Over an average follow-up of 91 months, multivariate Cox regression models revealed a significant positive correlation between DII scores and mortality risk, with each unit increase in DII associated with a 10% higher risk of death (HR: 1.10, 95% CI: 1.03-1.16; P = 0.002). Among the DII tertiles, individuals in the second tertile (T2: 1.23-2.94) experienced a 67% increase in mortality risk compared to those in the lowest tertile (T1: -5.28-1.23) (HR: 1.67, 95% CI: 1.26-2.21; p < 0.001). The third tertile (T3) did not show a statistically significant increase in mortality risk (HR: 1.30, 95% CI: 0.98-1.72; p=0.074). A restricted cubic spline analysis indicated a significant nonlinear association between DII and all-cause mortality (p = 0.021). Threshold effect analysis further revealed that below a DII of 2.19, there was a significant increase in all-cause mortality risk (HR = 1.19, 95% CI: 1.07-1.33; p = 0.002), while at or above this threshold, the risk increase was not statistically significant (HR=0.89, 95% CI: 0.68-1.15; p = 0.380). Kaplan-Meier analysis revealed significant differences in survival curves among DII tertiles (p < 0.001), with the lowest DII tertile showing the highest survival probability. Both subgroup and sensitivity analyses confirmed the robustness of these findings. DII is positively correlated with mortality risk in COPD patients, showing nonlinear characteristics and threshold effects, underscoring its prognostic value.

Neutrophil-to-lymphocyte ratio as a predictor of cardiovascular mortality in cancer survivors

This study aims to evaluate the neutrophil-to-lymphocyte ratio (NLR) as a predictive biomarker for cardiovascular mortality among cancer patients, utilizing data from the National Health and Nutrition Examination Survey (NHANES). From the NHANES dataset (2007–2018), we analyzed 4974 cancer survivors, investigating the prognostic significance of NLR for all-cause, cardiovascular, and cancer-specific mortality. Survival outcomes were analyzed using Cox regression and Kaplan–Meier methods. Optimal NLR cutoffs were identified as 2.61 for differentiating the higher NLR group from lower NLR group. Elevated NLR levels significantly correlated with increased all-cause mortality (HR 1.11, 95% CI 1.07–1.14, P < 0.001) and cardiovascular mortality (HR 1.14, 95% CI 1.08–1.21, P < 0.001) in adjusted models. Subgroup analyses revealed that age, sex, smoking status, and hypertension significantly influence NLR’s association with cardiovascular mortality. Specific cancers including breast, prostate, non-melanoma skin, colon and melanoma experience increased all-cause and cardiovascular mortality in the higher NLR group compared to lower NLR group. Elevated NLR is a significant predictor of increased mortality in cancer patients, particularly for cardiovascular outcomes. These findings support that NLR acts as a pivotal prognostic tool with significant implications for clinical practice in the realm of cardio-oncology.

Association between triglyceride glucose index and hyperuricemia: a new evidence from China and the United States.

Hyperuricemia (HUA) is a glo\bal public health problem. The etiology of HUA is complex and efficient and accurate assessment metrics are still lacking when conducting large-scale epidemiologic screening. The aim of this study was to evaluate the association of the triglyceride glucose (TyG) index, TyG-body mass index (BMI), TyG-waist-to-height ratio (WHtR) with the risk of HUA. Based on data collected from the National Health and Nutrition Examination Survey (NHANES) in the United States and the China Health and Aging Longitudinal Study (CHARLS) in China, a total of 14,286 U.S. adults and 4,620 Chinese adults were included in the analysis. The study examined the levels of TyG, TyG-BMI, TyG-WHtR, and TyG-WC. Multivariate logistic regression was utilized to investigate the relationships between these variables and hyperuricemia (HUA), separately. Additionally, the study used restricted cubic splines (RCS) to explore the linear associations of TyG, TyG-BMI, TyG-WHtR, TyG-WC, and HUA, separately. The NHANES results showed that TyG [Q2, 1.58(1.26, 1.98); Q3, 2.36 (1.94, 2.88); Q4, 3.21 (2.61, 3.94)], TyG-BMI [Q2, 2.14 (1.74, 2.65); Q3, 3.38 (2.74, 4.17); Q4, 6.70 (5.55, 8.02)], TyG-WHtR [Q2, 1.92 (1.56, 2.36); Q3, 3.14 (2.56, 3.85); Q4, 6.28 (5.12, 7.69)], TyG-WC [Q2, 2.32 (1.85, 2.90); Q3, 3.51 (2.84, 4.34); Q4, 7.32 (5.95, 9.02)] were identified as risk factors for hyperuricemia (HUA). Similarly, the CHARLS results, when fully adjusted for covariates, indicated that TyG [Q4, 2.36 (1.08, 5.15)], TyG-BMI [Q3, 2.60 (1.05, 6.41); Q4, 3.70 (1.64, 8.32)], TyG-WHtR (Q4, 2.84 (1.23, 6.55), TyG-WC [Q4, 2.85 (1.23, 6.5)] were also risk factors for HUA. The predictive ability of each indicator for the risk of developing HUA was stronger in women than in men. Furthermore, there was an observed nonlinear relationship between TyG, TyG-BMI, TyG-WHtR, TyG-WC, and HUA in both the NHANES and CHARLS datasets (P-nonlinearity < 0.05). These findings suggest that TyG, TyG-BMI, TyG-WHtR and TyG-WC are associated with an increased risk of HUA. They are potential indicators for screening HUA status in the general population in China and the United States.

The mediation effect of Systemic Immunity Inflammation Index between urinary metals and TOFAT among adults in the NHANES dataset

Systemic Immune Inflammatory Index (SII) is a novel indicator of inflammation. However, no studies have reported the effect of SII on the association between metals and total fat (TOFAT). We aim to investigate the mediated effect of SII on the relationship between urinary metals and TOFAT in a US adult population. This cross-sectional study was conducted among adults with complete information on SII, urine metal concentrations, and TOFAT from the 2011–2018 National Health and Nutrition Examination Survey (NHANES). Multifactorial logistic regression and restricted cubic splines were used to explore the association between urine metal levels and TOFAT. Furthermore, serial mediation analyses were used to investigate the mediating effect of SII on metals and TOFAT. A total of 3324 subjects were included in this study. After adjusting for confounders, arsenic (As), cadmium (Cd), cobalt (Co), cesium (Cs), inorganic mercury (Hg), molybdenum (Mo), manganese (Mn), lead (Pb), antimony (Sb), and thallium(Tl) had negative decreased trends of odds ratios for TOFAT (all P for trend < 0.05). In the total population, we found that Cd, Co, and Tu were positively associated with SII (β = 29.70, 79.37, and 31.08), whereas As and Hg had a negative association with SII. The mediation analysis showed that SII mediated the association of Co with TOFAT, with the β of the mediating effect being 0.9% (95%CI: 0.3%, 1.6%). Our findings suggested that exposure to As, Cd, and Hg would directly decrease the level of TOFAT. However, Co would increase TOFAT, completely mediated by SII, mainly exerted in females rather than males.

How Much Physical Activity Is Needed for 75 Year and Older Adults: Using NHANES Datasets

&amp;lt;i&amp;gt;Targets&amp;lt;/i&amp;gt;: To examine the amount/level of Physical Activity (PA) needed to generate the most health benefits in noninstitutionalized 75 year and older U.S. resident adults. Intervention description: A total of 598 sample participants aged 75 year and above from National Health And Nutrition Examination Survey (NHANES) 2005-2006 datasets were included. Actigraph-monitored daily step counts, self-reported PA duration (time spent in weekly PA) and weekly energy expenditure were used to describe PA level/amount. Functional ability was expressed using the total levels of difficulties in doing twenty-one types of daily activities. PRISM Dose-response Curves Stimulation Variable slope model was applied to examine the needed PA level/amount in the population. &amp;lt;i&amp;gt;Mechanisms of action&amp;lt;/i&amp;gt;: PA benefits functional health in 75 year and older adults. Older females aged 75- 84 year need at least 150 mins/ 800 kcal energy expenditure per week or 5,800 daily steps to reach the most functional benefits. Older men aged 75-84 year need walk about 5,800 steps/day to achieve higher level of functionality. Older adults aged 85 years and above need to spend about 240 minutes/week on PA to gain health benefits. &amp;lt;i&amp;gt;Outcomes&amp;lt;/i&amp;gt;: Older males generally need/engage in more amount of PA compared to their female counterparts. Between 75-84 year old male and female adults, PA intensity is more important/reflective in male for expressing PA amount, while time spent in PA is more meaningful to older females. There is no difference in needed PA amount between different genders in 85 year and older adults.

Association between blood methylmalonic acid and chronic kidney disease in the general US population: insights from multi-cycle National Health and Nutrition Examination Survey (NHANES).

Chronic kidney disease (CKD) is significantly influenced by mitochondrial dysfunction (MD). Previous research suggests that methylmalonic acid (MMA) is involved in MD. Consequently, we aimed to investigate associations between blood MMA level and the prevalence of CKD as well as mortality in patients with CKD. The study included 23,587 individuals from National Health and Nutrition Examination Survey (NHANES). The NHANES datasets from 1999-2004 and 2011-2014 were utilized as separate primary and validation subsets. There were 3,554 patients with CKD. The association of blood MMA level with the prevalence of CKD was investigated using weighted logistic regression. Meanwhile, we employed weighted Cox regression models to evaluate the association between blood MMA level and all-cause mortality in patients with CKD. Blood MMA levels had a significant positive association with urinary albumin-to-creatinine ratio (β=45.29, P=0.01) and negative association with estimated glomerular filtration rate (β=-15.27, P<0.001) in CKD patients. Blood MMA level exhibited a significant increase in participants with CKD compared with those without CKD (7.60±0.86 vs. 7.03±0.62, P<0.001). The level of blood MMA was significantly associated with the prevalence of CKD [odds ratio (OR): 1.32, 95% confidence interval (CI): 1.05-1.64, P=0.01]. In addition, blood MMA level was significantly associated with all-cause mortality in CKD participants [hazard ratio (HR): 1.26, 95% CI: 1.11-1.43, P<0.001] after adjusting for other potential predictors. Increased blood MMA levels were associated with more severe kidney impairment and increased risk of both the prevalence of CKD and mortality in participants with CKD.

Attention-Oriented CNN Method for Type 2 Diabetes Prediction

Diabetes is caused by insulin deficiency or impaired biological action, and long-term hyperglycemia leads to a variety of tissue damage and dysfunction. Therefore, the early prediction of diabetes and timely intervention and treatment are crucial. This paper proposes a robust framework for the prediction and diagnosis of type 2 diabetes (T2DM) to aid in diabetes applications in clinical diagnosis. The data-preprocessing stage includes steps such as outlier removal, missing value filling, data standardization, and assigning class weights to ensure the quality and consistency of the data, thereby improving the performance and stability of the model. This experiment used the National Health and Nutrition Examination Survey (NHANES) dataset and the publicly available PIMA Indian dataset (PID). For T2DM classification, we designed a convolutional neural network (CNN) and proposed a novel attention-oriented convolutional neural network (SECNN) through the channel attention mechanism. To optimize the hyperparameters of the model, we used grid search and K-fold cross-validation methods. In addition, we also comparatively analyzed various machine learning (ML) models such as support vector machine (SVM), logistic regression (LR), decision tree (DT), random forest (RF), and artificial neural network (ANN). Finally, we evaluated the performance of the model using performance evaluation metrics such as precision, recall, F1-Score, accuracy, and AUC. Experimental results show that the SECNN model has an accuracy of 94.12% on the NHANES dataset and an accuracy of 89.47% on the PIMA Indian dataset. SECNN models and CNN models show significant improvements in diabetes prediction performance compared to traditional ML models. The comparative analysis of the SECNN model and the CNN model has significantly improved performance, further verifying the advantages of introducing the channel attention mechanism. The robust diabetes prediction framework proposed in this article establishes an effective foundation for diabetes diagnosis and prediction, and has a positive impact on the development of health management and medical industries.

Abstract P390: Cardiometabolic Disease Prevalence Are Inconsistent by Racial Group Across Three National United States Datasets From 2015 to 2021

Introduction: The United States uses the National Health Interview Survey (NHIS), Behavioral Risk Factor Surveillance System (BRFSS), and National Health and Nutrition Examination Survey (NHANES) to inform disease trends and preventative research. However, the consistency in prevalence of cardiometabolic disorders in these datasets by race is understudied. We examined differences in the crude and age/sex adjusted prevalence of self-reported doctor diagnosis of myocardial infarction (MI), stroke (CVA), coronary heart disease (CHD), any cardiovascular disease (CVD), and diabetes (DM) by racial group across the datasets. Methods: We harmonized available NHIS (N = 179,593), BRFSS (N = 2,592,050), and NHANES (N = 12,506) datasets of adults aged ≥ 30 from 2015-2021. We first calculated crude prevalence by race and survey. We then used multivariable logistic regression to calculate age and sex adjusted prevalence by race and survey, accounting for survey weights. Results: The majority of participants were female (52.3%) and 53.6 years old (SD=14.4). Crude prevalence was most similar within a given race group for CVA (Table). Prevalence across surveys varied up to 4.6% by race and was most variable on average for DM. For each race group, prevalence estimates were generally higher in BRFSS than NHIS. Prevalence estimates varied most in people of Other/Multiple race. Racial differences in DM were significant in all datasets (p&lt;0.001). Results were similar after adjustment for age and sex. Conclusion: While prevalence estimates for our national datasets are consistent for the NH-White population, estimates are less consistent for other racial groups. Additional work is needed to ensure consistency of cardiometabolic surveillance both nationally and among minoritized groups.

Blood Test-Based Age Acceleration Is Inversely Associated with High-Volume Sports Activity.

We develop blood test-based aging clocks and examine how these clocks reflect high-volume sports activity. We use blood tests and body metrics data of 421 Hungarian athletes and 283 age-matched controls (mean age, 24.1 and 23.9 yr, respectively), the latter selected from a group of healthy Caucasians of the National Health and Nutrition Examination Survey (NHANES) to represent the general population ( n = 11,412). We train two age prediction models (i.e., aging clocks) using the NHANES dataset: the first model relies on blood test parameters only, whereas the second one additionally incorporates body measurements and sex. We find lower age acceleration among athletes compared with the age-matched controls with a median value of -1.7 and 1.4 yr, P < 0.0001. BMI is positively associated with age acceleration among the age-matched controls ( r = 0.17, P < 0.01) and the unrestricted NHANES population ( r = 0.11, P < 0.001). We find no association between BMI and age acceleration within the athlete dataset. Instead, age acceleration is positively associated with body fat percentage ( r = 0.21, P < 0.05) and negatively associated with skeletal muscle mass (Pearson r = -0.18, P < 0.05) among athletes. The most important blood test features in age predictions were serum ferritin, mean cell volume, blood urea nitrogen, and albumin levels. We develop and apply blood test-based aging clocks to adult athletes and healthy controls. The data suggest that high-volume sports activity is associated with slowed biological aging. Here, we propose an alternative, promising application of routine blood tests.

Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies.

Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory. Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD. After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect. No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.

The association between statin use and depression in diabetes

BackgroundDepression is a common mental disorder. Some studies have demonstrated that people with diabetes are more likely to suffer from depression. Statins are an everyday use for diabetes. Trials of statin therapy have had conflicting findings on the potential risk of depression. MethodsThe National Health and Nutrition Examination Survey (NHANES) 2005–2018 was used to collect a representative sample. Weighted multivariate logistic regression models were used to evaluate odds ratios (ORs) and 95 % CIs for having depression symptoms. We performed stratified analyses to compare the effects of statins in subsamples with and without diabetes on depression symptoms. ResultsStatin use showed a significant and strong decreasing effect on having depression symptoms in participants with diabetes (aOR (adjusted OR) 0.59, p = 0.014) compared with that in non-diabetics (aOR 0.78, p = 0.128). Diabetic individuals with statin use for >5 years had a lower risk of having depression symptoms (aOR 0.42, p = 0.002) than those with shorter-term statin use (1–5 years, aOR 0.69, p = 0.111; <1 year: aOR 0.83, p = 0.646). Atorvastatin was more effective in decreasing depression symptoms either in diabetes (aOR 0.49, p = 0.018) or in non-diabetes (aOR 0.58, p = 0.033). LimitationsFirst, the dosage of statins cannot be obtained from NHANES datasets. Second, after being stratified, the number of participants for several statins was insufficient. Third, recall bias may exist in the survey. ConclusionsDiabetics with depression symptoms may benefit from long-term statin therapy. Atorvastatin and pravastatin should be recommended for diabetic patients with depression.

Is weight-adjusted waist index more strongly associated with diabetes than body mass index and waist circumference?: Results from the database large community sample study.

The uncertainty regarding the correlation between the weight-adjusted waist index (WWI) and diabetes within the National Health and Nutrition Examination Survey (NHANES) necessitates further exploration. As indicators of obesity, the differences in the intensity of association between WWI, body mass index (BMI), and waist circumference (WC) with diabetes are worth exploring. This investigation is undertaken to elucidate the association between WWI and diabetes in the NHANES dataset and to compare the extent to which BMI, WC, and WWI were closely associated with diabetes. Then, choose an obesity index that is more strongly associated with diabetes. A comprehensive cross-sectional stratified survey of 7,973 participants from the 2017-2020 NHANES was conducted. WWI is an anthropometric measure based on WC and weight. The formula is WWI (cm/√kg) = WC/√weight. The association between WWI and diabetes was investigated using weighted multiple logistic regression, smooth curve fitting, stratified analysis, and interaction testing. The participants' average age was 50.84±17.34 years, and 50.68% of them were female. The detection rate of diabetes was 15.11%. This positive association was particularly notable among non-diabetic patients. For each unit increase in BMI and WC as continuous variables, the likelihood of developing diabetes in the fully adjusted model increased by 5% (OR = 1.05; 95%CI, 1.03-1.07) and 3% (OR = 1.03; 95%CI, 1.02-1.04), respectively, but for each one-unit increase in WWI, the likelihood of developing diabetes increased by 111% (OR = 2.11; 95% CI, 1.68-2.65). Tests of interactions revealed that in various subgroups, the association between diabetes and WWI remained steady. We analyzed 2017-2020 NHANES data to explore the link between WWI and diabetes, finding a consistent positive correlation. The correlation between WWI and diabetes was stronger than that between WC and BMI. WWI seems to offer better potential aid in disease prevention and diagnosis.

The association between body roundness index and osteoporosis in American adults: analysis from NHANES dataset.

An innovative way to quantify obesity that appropriately captures levels of visceral and body fat is the Body Roundness Index (BRI). The purpose of this study is to look at the relationship between BRI and osteoporosis (OP) in adult Americans. This study utilized data from the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2018. NHANES is a research program designed to assess the health and nutritional status of adults and children in the United States. It conducts surveys focusing on various populations and health-related topics. Logistic regression analysis was employed to investigate the relationship between BRI and OP, adjusting for various covariates. BRI was categorized into four levels to further explore the association trends between different BRI levels and OP, enhancing the robustness of the results. Using restricted cubic spline (RCS) analysis, the dose-response relationship between BRI and OP was illustrated. Subgroup analyses were also carried out to evaluate the consistency and robustness of the findings. This study included 8,899 participants aged 50 years and older, among whom 763 had OP. BRI and the prevalence of OP were inversely correlated in the fully adjusted model (OR = 0.79, 95% CI: 0.69-0.86). The prevalence of OP considerably reduced with higher BRI levels when BRI was converted from a continuous to a categorical variable in comparison to the lowest BRI quartile. RCS analysis revealed an L-shaped negative correlation between BRI and OP prevalence, with a threshold effect analysis identifying a breakpoint at BRI = 5.29. Each unit increase in BRI to the left of this breakpoint was linked to a 36% decrease in the probability of OP (OR = 0.64, 95% CI: 0.57-0.72). Based on stratified factor subgroup analyses, it was shown that the negative correlation between BRI and OP persisted. In a large, representative sample of American adults, this study identified a significant negative correlation between BRI and the prevalence of OP. Specifically, as BRI increases, the prevalence of osteoporosis decreases. Maintaining an appropriate and healthy BRI level may play a critical role in the prevention of osteoporosis. Therefore, regular monitoring of BRI and the adoption of appropriate health measures are essential for reducing the risk of osteoporosis.

Clinical Evidence of the Relationship Between Alanine Aminotransferase and Diabetic Kidney Disease.

Multiple studies have investigated the association between alanine aminotransferase (ALT) and diabetes mellitus (DM); however, only a few studies have specifically examined the relationship between ALT and diabetic kidney disease (DKD). This study aimed to investigate the relationship between ALT and DKD using clinical data. A cross-sectional study was conducted on 668 individuals that included non-DM (N=281), DM without DKD (N=160), and DKD (N=227) patients. A generalized additive model (GAM) was used to examine the dose-response relationship between ALT and DKD risk. We also analyzed the data from the US National Health and Nutrition Examination Survey (NHANES) 2015-2018 using the same statistical methods; 4481, 1110, and 671 individuals were included in the non-DM, DM without DKD, and DKD groups, respectively. The changes in ALT activity among the non-DM, DM without DKD, and DKD groups showed a similar pattern in both our clinical data and the NHANES dataset. ALT activity increases with the onset of DM, whereas ALT activity decreases when DM progresses to DKD. The GAM revealed a nonlinear U-shaped relationship between ALT and DKD risk in the two datasets, and the lowest range of ALT was 40-50 IU/L. Both lower (<40 IU/L) and higher (>50 IU/L) ALT activity were found to be positively associated with DKD risk. A U-shaped nonlinear association between ALT and DKD was found in our clinical data and NHANES data. DKD risk was increased by both lower or higher ALT activity. To confirm the causality of nonlinear relationship, larger prospective studies or Mendelian randomization analysis are required.

ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age

Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We introduce ExplaiNAble BioLogical Age (ENABL Age), a computational framework that combines machine-learning models with explainable artificial intelligence (XAI) methods to accurately estimate biological age with individualised explanations. To construct the ENABL Age clock, we first predicted an age-related outcome (eg, all-cause or cause-specific mortality), and then rescaled these predictions to estimate biological age, using UK Biobank and National Health and Nutrition Examination Survey (NHANES) datasets. We adapted existing XAI methods to decompose individual ENABL Ages into contributing risk factors. For broad accessibility, we developed two versions: ENABL Age-L, based on blood tests, and ENABL Age-Q, based on questionnaire characteristics. Finally, we validated diverse ageing mechanisms captured by each ENABL Age clock through genome-wide association studies (GWAS) association analyses. Our ENABL Age clock was significantly correlated with chronological age (r=0·7867, p<0·0001 for UK Biobank; r=0·7126, p<0·0001 for NHANES). These clocks distinguish individuals who are healthy (ie, their ENABL Age is lower than their chronological age) from those who are unhealthy (ie, their ENABL Age is higher than their chronological age), predicting mortality more effectively than existing clocks. Groups of individuals who were unhealthy showed approximately three to 12 times higher log hazard ratio than healthy groups, as per ENABL Age. The clocks achieved high mortality prediction power with an area under the receiver operating characteristic curve of 0·8179 for 5-year mortality and 0·8115 for 10-year mortality on the UK Biobank dataset, and 0·8935 for 5-year mortality and 0·9107 for 10-year mortality on the NHANES dataset. The individualised explanations that revealed the contribution of specific characteristics to ENABL Age provided insights into the important characteristics for ageing. An association analysis with risk factors and ageing-related morbidities and GWAS results on ENABL Age clocks trained on different mortality causes showed that each clock captures distinct ageing mechanisms. ENABL Age brings an important leap forward in the application of XAI for interpreting biological age clocks. ENABL Age also carries substantial potential in practical settings, assisting medical professionals in untangling the complexity of ageing mechanisms, and potentially becoming a valuable tool in informed clinical decision-making processes. National Science Foundation and National Institutes of Health.

Dietary flavonoids intake contributes to delay biological aging process: analysis from NHANES dataset

BackgroundDiet may influence biological aging and the discrepancy (∆age) between a subject’s biological age (BA) and chronological age (CA). We aimed to investigate the correlation of dietary flavonoids with the ∆age of organs (heart, kidney, liver) and the whole body.MethodA total of 3193 United States adults were extracted from the National Health and Nutrition Examination Survey (NHANES) in 2007–2008 and 2017–2018. Dietary flavonoids intake was assessed using 24-h dietary recall method. Multiple linear regression analysis was performed to evaluate the association of dietary flavonoids intake with the ∆age of organs (heart, kidney, liver) and the whole body. BA was computed based on circulating biomarkers, and the resulting ∆age was tested as an outcome in linear regression analysis.ResultsThe ∆age of the whole body, heart, and liver was inversely associated with higher flavonoids intake (the whole body ∆age β = − 0.58, cardiovascular ∆age β = − 0.96, liver ∆age β = − 3.19) after adjustment for variables. However, higher flavonoids intake positively related to renal ∆age (β = 0.40) in participants with chronic kidney disease (CKD). Associations were influenced by population characteristics, such as age, health behavior, or chronic diseases. Anthocyanidins, isoflavones and flavones had the strongest inverse associations between the whole body ∆age and cardiovascular ∆age among all the flavonoids subclasses.ConclusionFlavonoids intake positively contributes to delaying the biological aging process, especially in the heart, and liver organ, which may be beneficial for reducing the long-term risk of cardiovascular or liver disease.

The triglyceride-waist circumference index is a valid biomarker of metabolic syndrome in African Americans

BackgroundThe hypertriglyceridemia waist (HTGW) phenotype is associated with visceral adiposity, metabolic syndrome, type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD). Since the cut points for abdominal obesity and hypertriglyceridemia, differ for different race groups, investigators have developed the product of triglycerides (TG) and waist circumference (WC) as the TG.WC index. We compared this TG.WC index to the TG:HDL-C ratio in the National Health and Nutrition Examination Survey (NHANES) study to predict metabolic syndrome (MetS) in African Americans (AAs). MethodsParticipants included 950 AAs and 2651 non-Hispanic Whites (NHWs) for comparison from the NHANES data set. Persons with diabetes, ASCVD and macro-inflammation were excluded. Fasting blood was obtained for lipids, insulin and CRP. ResultsIn AAs and NHWs, both the TG.WC index and TG:HDL-C ratio were significantly increased in MetS patients. Also, both increased with increasing severity of MetS and correlated with all features of MetS, insulin resistance and inflammation. Receiver operating characteristic (ROC) curve analysis showed that discrimination with TG.WC for MetS was superior to the TG:HDL-C ratio especially in AAs. ConclusionsTG.WC index is a superior biomarker to TG:HDL-C for predicting MetS in AAs despite their lower TG levels.

Daily physical activity is negatively associated with thyroid hormone levels, inflammation, and immune system markers among men and women in the NHANES dataset.

The acute effects of exercise on metabolic energy expenditure and inflammation are well studied, but the long-term effects of regular daily physical activity on metabolic and endocrine effects are less clear. Further, prior studies investigating the impact of daily physical activity in large cohorts have generally relied on self-reported activity. Here, we used the U.S. National Health and Nutrition Examination Survey (NHANES) to investigate the relationship between daily physical activity and both thyroid and immune activity. Daily physical activity was assessed through accelerometry or accelerometry-validated survey responses. Thyroid activity was assessed from circulating levels of thyroid stimulating hormone (TSH) and thyroxine (T4). Immune function was assessed from circulating cytokines (C-reactive protein [CRP], immunoglobulin E [IgE], fibrinogen) and blood cell counts. In general linear models including body mass index, age, gender, activity and TSH as factors, active adults had a lower levels of T4 and reduced slope of the TSH:T4 relationship. Similarly, greater physical activity was associated with lower CRP and fibrinogen levels (but not IgE) and lower white blood cell, basophil, monocyte, neutrophil, and eosinophil (but not lymphocyte) counts. Daily physical activity was also associated with lower prevalence of clinically elevated CRP, WBC, and lymphocytes in a dose-response manner. These results underscore the long-term impact of daily physical activity on both systemic metabolic activity (thyroid) and on specific physiological tasks (immune). The regulatory effects of physical activity on other bodily systems are clinically relevant and should be incorporated into public health strategies promoting exercise.

Urinary metals, arsenic, and polycyclic aromatic hydrocarbon exposure and risk of chronic bronchitis in the US adult population.

Metals, arsenic, and polycyclic aromatic hydrocarbons (PAHs) have all been linked to respiratory diseases. Chronic bronchitis, which is a form ofchronic obstructive pulmonary disease (COPD), is a major public health concern and source of morbidity and mortality in the US. The purpose of this study was to analyze the correlation of 14 urinary metals (antimony, barium, cadmium, cesium, cobalt, lead, manganese, mercury, molybdenum, strontium, thallium, tin, tungsten, uranium), seven species of arsenic, and seven forms of polycyclic aromatic hydrocarbon (PAH) concentrations and chronic bronchitis in the US population. A cross-sectional analysis using three datasets from the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2016 in adults, aged 20years and older. Chronic bronchitis was determined using a self-questionnaire from the NHANES dataset. A specialized weighted complex survey design analysis package was used to analyze NHANES data. Multivariate logistic regression models were used to determine the correlation between urinary metals, arsenic, PAHs, and chronic bronchitis. Models were adjusted for lifestyle and demographic factors. A total of 4186 participants were analyzed; 49.8% were female and 40.5% were non-Hispanic White. All seven types of PAHs showed a positive association with chronic bronchitis (1-hydroxynaphthalene odds ratio (OR): 1.559, 95% confidence interval (CI): 1.271-1.912; 2-hydroxynaphthalene OR: 2.498, 95% CI: 1.524-4.095; 3-hydroxyfluorene OR: 2.752, 95% CI: 2.100-3.608; 2-hydroxyfluorene OR: 3.461, 95% CI: 2.438-4.914; 1-hydroxyphenanthrene OR: 2.442, 95% CI: 1.515-3.937; 1-hydroxypyrene OR: 2.828, 95% CI: 1.728-4.629; 2 & 3-hydroxyphenanthrene OR: 3.690, 95% CI: 2.309-5.896). Of the metals, only urinary cadmium showed a statistically significant positive association (OR: 2.435, 95% CI: 1.401-4.235) with chronic bronchitis. No other metals or arsenic were correlated with chronic bronchitis. Seven forms of urinary PAHs, cadmium, and several demographic factors were associated with chronic bronchitis.

Surveillance of Hypertension Among Women of Reproductive Age: A Review of Existing Data Sources and Opportunities for Surveillance Before, During, and After Pregnancy.

Hypertension is one of the largest modifiable risk factors for cardiovascular disease in the United States, and when it occurs during pregnancy, it can lead to serious risks for both the mother and child. There is currently no nationwide or state surveillance system that specifically monitors hypertension among women of reproductive age (WRA). We reviewed hypertension information available in the Behavioral Risk Factor Surveillance System (BRFSS), National Health and Nutrition Examination Survey (NHANES), National Health Interview Survey (NHIS), and Pregnancy Risk Assessment and Monitoring System (PRAMS) health surveys, the Health care Cost and Utilization Project administrative data sets (National Inpatient Sample, State Inpatient Databases, Nationwide Emergency Department Sample, and State Emergency Department Database and the Nationwide Readmissions Database), and the National Vital Statistics System. BRFSS, NHIS, and NHANES and administrative data sets have the capacity to segment nonpregnant WRA from pregnant women. PRAMS collects information on hypertension before and during pregnancy only among women with a live birth. Detailed information on hypertension in the postpartum period is lacking in the data sources that we reviewed. Enhanced data collection may improve opportunities to conduct surveillance of hypertension among WRA.