US Nutrition Research Articles

Associations Between Diabetic Retinopathy and Frailty: Insights From the National Health and Nutrition Examination Survey and Mendelian Randomization.

To elucidate the relationship between diabetic retinopathy (DR) and frailty and investigate genetic correlations and causality. We analyzed data from the US National Health and Nutrition Examination Survey, which included 1003 individuals with diabetes. DR was evaluated via nonmydriatic retinal imaging, and frailty was measured using a 49-item frailty index. The association between DR and frailty was assessed using survey-weighted logistics regression adjusted for multiple covariates, including age, sex, race, education level, family income-to-poverty ratio, marital status, and Healthy Eating Index. Genetic correlations and causal relationships were investigated through linkage disequilibrium score regression and bidirectional Mendelian randomization. DR was significantly associated with higher odds of frailty after full adjustment (odd ratio [OR] = 4.25; 95% confidence interval [CI], 1.08-16.67; P = 0.040). The association was robust and did not significantly differ across age (P interaction = 0.080), sex (P interaction = 0.216), or race (P interaction = 0.749) groups. DR exhibited a moderate but significant genetic correlation with frailty (rg = 0.27, standard error = 0.04; P = 2.43 × 10-10). Genetically inferred DR was significantly associated with a greater frailty index (β = 0.03; 95% CI, 0.01-0.05; P < 0.001), whereas frailty was not associated with DR risk (OR = 1.20; 95% CI, 0.80-1.81; P = 0.376). Our findings suggest that DR is associated with an increased risk of frailty, indicating that DR not only impairs vision but also accelerates physical decline. This study highlights the critical need for integrated care approaches that incorporate frailty screening and proactive management in individuals with DR to prevent further health deterioration and improve both quality of life and long-term outcomes.

Association between Helicobacter pylori infection, serum thyroid-stimulating hormone, and thyroxine in the National Health and Nutrition Examination Survey 1999–2000

BackgroundHelicobacter pylori has been increasingly implicated in extra-gastric diseases. Current evidence regarding the association between serum thyroid-stimulating hormone (TSH), thyroxine (T4), and H. pylori infection remains inconclusive. Consequently, this study aimed to explore the correlation between TSH and T4 levels and H. pylori infection in a US-based population sample.MethodsData from the US National Health and Nutrition Examination Survey (NHANES), comprising 971 participants aged 30–85 years from 1999 to 2000, were analyzed. Binary logistic regression was employed to analyze the correlation between H. pylori and TSH and T4 levels. The impact of TSH and T4 on H. pylori infection was further assessed using restricted cubic spline (RCS) analysis. In addition, subgroup analyses stratified by sex and age were conducted.ResultsSubjects with H. pylori seropositivity demonstrated lower serum TSH levels and higher serum T4 levels compared to those with H. pylori seronegativity. A significant positive correlation was identified between H. pylori seropositivity and T4 levels with increasing quartiles of hormonal levels in both univariate regression models (Q4 vs. Q1: OR = 1.483; 95% CI, 1.033–2.129) and multivariate regression models (Q4 vs. Q1: OR = 1.004; 95% CI, 0.981–1.026). Conversely, a negative correlation was observed between H. pylori seropositivity and TSH levels with increasing quartiles of hormonal levels in univariate regression models (Q4 vs. Q1: OR = 0.579; 95% CI, 0.403–0.831) and in multivariate regression models (Q4 vs. Q1: OR = 0.580; 95% CI, 0.389–0.866). In stratified analyses, the adjusted association of serum T4 levels with H. pylori seropositivity was statistically significant among men (T4: Q4 vs. Q1: OR = 2.253; 95% CI, 1.311–3.873), age over 68 years in TSH levels (Q4 vs. Q1: OR = 0.434; 95% CI, 0.206–0.911), and age 41–54 years in T4 levels (Q4 vs. Q1: OR = 4.965; 95% CI, 2.071–11.903). RCS analysis revealed a non-linear relationship between TSH levels and H. pylori infection. Notably, when TSH &amp;lt; 0.98 IU/ml, the likelihood of H. pylori infection significantly increased.ConclusionsLower TSH and higher T4 levels were associated with H. pylori infection, particularly among men and elderly individuals.

Associations between co-exposure to multiple heavy metals and age-related macular degeneration: a cross-sectional study

Background & aimsAccumulating evidence suggests that exposure to single heavy metal can facilitate the progression of age-related macular degeneration (AMD). However, the effects of exposure to mixtures of heavy metals on AMD remain largely unexplored. This study aims to investigate both the joint and individual impacts of arsenic (As), mercury (Hg), cadmium (Cd), and lead (Pb) on AMD within a co-exposure framework. MethodsData from subjects participating the US National Health and Nutrition Examination Survey (NHANES, 2005-2008) were analyzed. Concentrations of As, Hg, Cd, and Pb were determined in urine by inductively coupled plasma dynamic reaction cell mass spectrometry (ICP-DRC-MS) for As and Hg, and inductively coupled plasma mass spectrometry (ICP-MS) for Cd and Pb. The weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models were employed to assess the effects of heavy metal mixtures on AMD risk. ResultsBoth WQS and BKMR analyses consistently revealed a significant overall association between heavy metal mixtures and the risk of all types of AMD. The combined effect was more evident among patients with early AMD compared to those with late AMD. Cd and Hg were the main contributors driving these combined effects within the context of metal mixtures. Elevated urinary levels of Cd were positively correlated with an increased risk for all types as well as early AMD. Higher exposure to Hg corresponded with an elevated risk for early AMD. Furthermore, BKMR analysis indicated that the influence of Cd on early AMD exhibited a non-linear pattern. ConclusionsOur findings suggest that co-exposure to As, Hg, Cd, and Pb is associated with an elevated risk for developing AMD, particularly in its early stages. Furthermore, excessive exposure to Cd and Hg has been identified as key contributing factors in this process.

Associations between neutrophil-percentage-to-albumin ratio level and all-cause mortality and cardiovascular disease-cause mortality in diabetes population

BackgroundThe prevalence of type 2 diabetes mellitus (T2DM) remains high and biomarkers related to T2DM are needed to be investigated. This study aimed to investigate the association between neutrophil percentage-to-albumin ratio (NPAR) with all-cause mortality and the risk of cardiovascular disease (CVD) mortality in community-dwelling individuals with T2DM.MethodsThis prospective cohort study included 3602 adults aged 20 or above who were diagnosed with diabetes by the American Diabetes Association criteria in the US National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2016, and followed up until 2019. Multivariable Cox proportional hazards regression models were utilized to determine the relationship between NPAR with all-cause mortality and cardiovascular disease (CVD) mortality. Restricted cubic spline regression analyses were employed to explore the nonlinear relationship between NPAR and cardiovascular disease (CVD) mortality. The assessment of nonlinearity was conducted using the likelihood ratio test.ResultsAfter adjustment, the risk ratio for all-cause mortality in the highest NPAR group (≥ 15.40) compared to the lowest serum NPAR reference group (< 13.30) was 1.62 (95% CI, 1.36, 1.94) with P values < 0.001. Nevertheless, the risk ratio for cardiovascular disease (CVD) mortality in the highest NPAR group (≥ 15.40) versus the lowest serum NPAR reference group (< 13.30) was 1.41 (95% CI, 0.99, 2.00) with a P value of 0.06. Among patients with T2DM, serum NPAR levels exhibited a nonlinear correlation with both CVD mortality risk and all-cause mortality risk, with P values < 0.001 for both.ConclusionsThis study identified a significant association between elevated levels of the neutrophil percentage-to-albumin ratio (NPAR) and an increased risk of all-cause mortality among individuals with type 2 diabetes mellitus (T2DM). Conversely, no correlation was found between NPAR levels and CVD mortality.

Exposome-wide association study of cognition among older adults in the national health and nutrition examination survey

Abstract Cognitive impairment among older adults is a growing public health challenge and environmental chemicals may be modifiable risk factors. A wide array of chemicals has not yet been tested for association with cognition in an environment-wide association framework. In the US National Health and Nutrition Examination Survey (NHANES) 1999 - 2000 and 2011 - 2014 cross-sectional cycles, cognition was assessed using the Digit Symbol Substitution Test (DSST, scores 0 - 117) among participants aged 60 years and older. Concentrations of environmental chemicals measured in blood or urine were log2 transformed and standardized. Chemicals with at least 50% of measures above the lower limit of detection were included (nchemicals=147, nclasses=14). We tested for associations between chemical concentrations and cognition using parallel survey-weighted multivariable linear regression models adjusted for age, sex, race/ethnicity, education, smoking status, fish consumption, cycle year, urinary creatinine, and cotinine. Participants with at least one chemical measurement (n = 4,982) were mean age 69.8 years, 55.0% female, 78.2% non-Hispanic White, and 77.0% at least high school educated. The mean DSST score was 50.4 (standard deviation (SD)=17.4). In adjusted analyses, 5 of 147 exposures were associated with DSST at P-value &amp;lt; 0.01. Notably, a SD increase in log2-scaled cotinine concentration was associated with 2.71 points lower DSST score (95% CI -3.69, -1.73). A SD increase in log2-scaled urinary tungsten concentration was associated with 1.34 points lower DSST score (95% CI -2.11, -0.56). Exposure to environmental chemicals, particularly metals and tobacco smoke, may be modifiable factors for cognition among older adults.

Associations of the Gap Between 2-Hour Post-Load Plasma Glucose and Fasting Blood Glucose With All-Cause or Cardiovascular Mortality in US Normoglycemic Adults.

The gap between 2-hour post-load plasma glucose (2h PG) and fasting blood glucose (FBG) has been shown to be informative of the risk of developing prediabetes and diabetes. We aimed to examine the significance of the gap between 2h PG and FBG in relation to all-cause or cardiovascular disease (CVD) mortality in normoglycemic adults. 3611 normoglycemic participants from the 2005-2016 US National Health and Nutrition Examination Survey were included and dichotomized into the low (2h PG ≤ FBG) and high post-load (2h PG > FBG) groups. Associations of the gap between 2h PG and FBG with all-cause or CVD mortality were evaluated with Kaplan-Meier curves, Cox proportional hazard ratio, and subgroup analysis. The mean age was 38.80years, with a male prevalence of 43.59%. Finally, 1746 (50.22%) and 1865 (49.78%) participants were categorized into the low and high post-load groups, respectively. During a median follow-up of 107months, 130 deaths (36 CVD-related) occurred. Kaplan-Meier curves showed significantly higher all-cause and CVD mortality rates in the high post-load group compared with the low post-load group. The hazard ratio and 95% confidence interval for all-cause and CVD mortality in the high post-load group were 1.816 (1.149-2.870) and 2.302 (1.052-5.038), respectively, with the low post-load group as the reference. The results were robust and consistent in the sensitivity and subgroup analyses. The gap between 2h PG and FBG may be potentially useful for predicting the risk of all-cause and CVD mortality in US normoglycemic adults.

Construction of the cancer patients’ database based on the US National Health and Nutrition Examination Survey (NHANES) datasets for cancer epidemiology research

BackgroundThe US National Health and Nutrition Examination Survey (NHANES) dataset does not include a specific question or laboratory test to confirm a history of cancer diagnosis. However, if straightforward variables for cancer history are introduced, US NHANES could be effectively utilized in future cancer epidemiology studies. To address this gap, the authors developed a cancer patient database from the US NHANES datasets by employing multiple R programming codes.MethodsTo illustrate the practical application of this methodology to a real-world problem, the authors extracted the R codes applied in an academic paper published in another journal on January 30th, 2024 (https://doi.org/10.1016/j.heliyon.2024.e24337). This paper will focus on the construction of the database and analysis using R codes. Entire.ResultsIn the first example, the urine concentration of monocarboxynonyl phthalate, monocarboxyoctyl phthalate, mono-2-ethyl-5-carboxypentyl phthalate, and mono-2-hydroxy-iso-butyl phthalate (all ng/mL) were used as the independent variable, instead of the serum concentration of perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA), respectively. In the second example, the serum concentration of 2,3,3’,4,4’-Pentachlorobiphenyl (PCB105), 2,3,4,4´,5-Pentachlorobiphenyl (PCB114), 2,3’,4,4’,5-Pentachlorobiphenyl (PCB118), and 2,2’,3,4,4’,5’- and 2,3,3’,4,4’,6-Hexachlorobiphenyl (PCB138) were used as the independent variable, instead of the serum concentration of PFOA, PFOS, PFHxS, and PFNA, respectively.DiscussionThis research offers a comprehensive set of R codes aimed at creating a single, user-friendly variable that encapsulates the history of each type of cancer while also considering the age at which the diagnosis was made. The US NHANES provides a wealth of critical data on environmental toxicant exposures. By employing these R codes, researchers can potentially discover numerous new associations between environmental toxicant exposures and cancer diagnoses. Ultimately, these codes could significantly advance the field of cancer epidemiology in relation to environmental toxicant exposure.

The association of lifestyle with cardiovascular and all-cause mortality based on machine learning: a prospective study from the NHANES

BackgroundLifestyle and cardiovascular mortality and all-cause mortality have been exhaustively explored by traditional methods, but the advantages of machine learning (ML) over traditional methods may lead to different or more precise conclusions. The aim of this study was to evaluate the effectiveness of machine learning-based lifestyle factors in predicting cardiovascular and all-cause mortality and compare the results obtained by traditional methods.MethodA prospective cohort study was conducted using a nationally representative sample of adults aged 40 years or older, drawn from the US National Health and Nutrition Examination Survey from 2007 to 2010. The participants underwent a comprehensive in-person interview and medical laboratory examinations, and subsequently, their records were linked with the National Death Index for further analysis. Extreme gradient enhancement, random forest, support vector machine and other machine learning methods are used to build the prediction model.ResultWithin a cohort comprising 7921 participants, spanning an average follow-up duration of 9.75 years, a total of 1911 deaths, including 585 cardiovascular-related deaths, were recorded. The model predicted mortality with an area under the receiver operating characteristic curve (AUC) of 0.862 and 0.836. Stratifying participants into distinct risk groups based on ML scores proved effective. All lifestyle behaviors were associated with a reduced risk of all-cause and cardiovascular mortality. As age increases, the effects of dietary scores and sedentary time on mortality risk become more pronounced, while the influence of physical activity tends to diminish.ConclusionWe develop a ML model based on lifestyle behaviors to predict all-cause and cardiovascular mortality. The developed model offers valuable insights for the assessment of individual lifestyle-related risks. It applies to individuals, healthcare professionals, and policymakers to make informed decisions.

Association of arm circumference with the prevalence of gallstones in United States adults: a retrospective analysis on US National Health and Nutrition Examination Survey

BackgroundArm circumference (AC) is a measure of nutritional status and an indicator of the risk of developing diseases, such as metabolic disorders. However, its relationship with the prevalence of gallstone disease (GS), a metabolic disorder, is unknown. Consequently, this research sought to investigate the relationship between AC and the prevalence of GS among the general adult population in America.MethodsParticipant data were extracted from the National Health and Nutrition Examination Survey (NHANES) 2017–2020 cycle. GS was defined based on self-reported medical history. AC was measured following standardized protocols as the primary exposure variable. Multivariable logistic regression models were employed to assess the association between AC and GS. Dose–response relationships were evaluated using generalized additive models with smoothed curve fitting, and subgroup analyses were conducted to explore effect modification by key covariates such as age, sex, race, hypertension, diabetes, and body mass index.ResultsOverall, a total of 8,081 participants were included in this study, with 849 reporting a history of GS. After accounting for potential confounders, we discovered that each centimeter increase in AC was linked to an 8% rise in the prevalence of GS (Odd ratio = 1.08, 95% confidence interval: 1.07–1.10). Dose–response curves demonstrated a positive linear relationship between AC and the prevalence of GS, which, according to the results of the subgroup analyses, was consistent in the vast majority of subgroups, although there were subtle differences.ConclusionAC exhibited a linear and positive association with the prevalence of GS. Although a causal relationship between AC and the prevalence of GS could not be established, our study provides strong new support for the potential role of AC in the health assessments of adult populations.

A Population-Based Study of the Association Among Dry Mouth, Vitamin B2, and Mortality.

Previous studies have indicated that older adults with the symptom of dry mouth have an increased risk of death. B vitamins are strongly linked to oral and systemic health. However, the relationship among dry mouth, vitamin B2 and mortality remains unclear. This study aimed to investigate the potential relationship among dry mouth, vitamin B2 and mortality. A total of 6183 participants from the US National Health and Nutrition Examination Survey (NHANES) 2011-2014 with information on dry mouth were included at baseline. 4324 normal individuals and 684 individuals with dry mouth were followed up until 31 December 2019. The Cox proportional hazard model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations among dry mouth, vitamin B2 and all-cause mortality. Compared to the population without dry mouth, the risk of all-cause mortality was significantly higher in the population with dry mouth. The multivariable-adjusted HR and 95% CI was 1.41 (1.05, 1.90). The intake of vitamin B2 can significantly reduce the risk of death in participants with dry mouth, but not in participants without dry mouth. The HR and 95% CI of all-cause mortality in the highest vitamin B2 intake group was 0.37 (0.19, 0.73) compared to the lowest intake group. Individuals with dry mouth suffered a significantly higher risk of all-cause mortality compared to those without dry mouth. Higher intake of vitamin B2 was apparently associated with a lower risk of all-cause mortality in the population with dry mouth.

Tiered intake assessment for propylene glycol in beverages

A tiered intake assessment approach is presented and applied to derive estimates of maximum potential global propylene glycol (PG) intake from beverage sources. The US and UK markets served as surrogates for the world and the EU region, respectively, to determine the maximum potential exposure for PG in various subpopulations, including brand-loyal consumers. Conservative intake estimates for PG used in non-alcoholic beverages were calculated for toddlers less than 2 years (y), young children 3-9 y, adolescents 10-17 y, adults 18-64 y, elderly 65-74 y, very elderly 75+ y, based on assumed uses in high beverage consumption markets, leveraging either the 2-day food consumption data from the 2013–2016 US National Health and Nutrition Examination Survey or the 4-day food consumption data from the 2008-2017 UK National Diet and Nutrition Survey Rolling Programme. This study shows that safety of PG in beverages at proposed use levels up to 3,000 mg kg−1 can be supported for any geography, based not only on a refined budget method approach but also on a refined deterministic approach when applying the proposed safe intake (pADI) of 62.5 mg kg bw−1 day−1. In all refined assessments, intake estimates across all age groups fell close to or well below the pADI even among high consumers at the 95th percentile.

The relationship between C-reactive protein to lymphocyte ratio and the prevalence of chronic kidney disease in US adults: a cross-sectional study.

The C-reactive protein/Lymphocyte Ratio (CLR) is a novel biomarker whose role in the development of chronic kidney disease (CKD) is not well understood. This study aimed to investigate the correlation between CLR and the prevalence of CKD. This cross-sectional study included participants from the US National Health and Nutrition Examination Survey conducted between 1999 and 2010. Multivariate regression analyses and subgroup analyses were performed, controlling for socio-demographic variables, lifestyle behaviors, chronic diseases associated with kidney disease, and biochemical markers of bone metabolism. The associations between CLR and CKD prevalence, as well as indicators of renal damage, were explored. Non-linear relationships were analyzed using weighted restricted cubic splines. The predictive ability of CLR for CKD was assessed by the receiver operating characteristic curve and the area under the curve was calculated. Subgroup and sensitivity analyses were conducted to validate the robustness of the model. A total of 13,862 respondents were included, comprising 2,449 CKD patients and 11,413 non-CKD patients. Weighted logistic regression modeling revealed a positive correlation between CLR levels and CKD prevalence (Odds ratio [OR] = 1.54, 95% Confidence interval [CI] = 1.30 to 1.83, P < 0.001). Additionally, CLR levels were negatively correlated with the glomerular filtration rate, a marker of renal injury, and positively correlated with the urinary albumin/creatinine ratio. The receiver operating characteristic curve demonstrated that the area under the curve for CLR in predicting CKD was 0.653 (95% CI, 0.641-0.665). The optimal cutoff value was 0.856, with a sensitivity of 0.703, specificity of 0.526, positive predictive value of 0.874, and negative predictive value of 0.275. The robustness of the model was confirmed through subgroup and sensitivity analyses. Analysis of a large cross-sectional dataset demonstrated a positive correlation between CLR levels and CKD prevalence, suggesting that CLR may serve as a novel marker for the development and treatment of CKD.

Association between domain-specific physical activity and triglyceride‑glucose (TyG) index among US adults: Evidence from NHANES 2007–2018

ObjectivesThe triglyceride-glucose (TyG) index is not only a reliable marker for insulin resistance, but also has broad applications in assessing the risk of various diseases, including cardiovascular disease, stroke, depression, and Alzheimer’s disease. The study aims to investigate the relationship between domain-specific moderate- or vigorous-intensity physical activity (MVPA) and TyG index among US adults.MethodsThe participants from the US National Health and Nutrition Examination Survey (NHANES) (2007–2018) were included. Different PA domains, including occupation-related MVPA (O-MVPA), transportation-related MVPA (T-MVPA), and leisure-time MVPA (LT-MVPA), were assessed by the Global Physical Activity Questionnaire. Weighted multivariable linear regression and the propensity score matching (PSM) method were used to determine the relationship between domain-specific MVPA and TyG index. Furthermore, stratified and mediation analyses were employed to assess the potential effect modifications and mediators on the association.ResultsA total of 12,069 participants were included. The participants had a weighted mean age of 47.43 ± 16.91 years and a weighted mean TyG index of 8.58 ± 0.67. Weighted multivariable linear regression showed that leisure-time MVPA (LT-MVPA), whether at any amount or achieving physical activity guidelines, was negatively associated with TyG index (β = -0.10, 95%CI: -0.13- -0.07, P < 0.001, and β = -0.13, 95%CI: -0.17- -0.10, P < 0.001, respectively). O-MVPA and T-MVPA were not correlated with the TyG index, even at the recommended amount (β = 0.01, 95%CI: -0.02–0.03, P = 0.59 for O-MVPA, and β = -0.02, 95%CI: -0.07–0.02, P = 0.32 for T-MVPA). After PSM, the results were still robust. Furthermore, the stratified analysis found that the correlation between LT-MVPA and TyG index was stronger in females, those with higher family incomes, and non-smokers. Finally, mediation analyses indicated a significant joint mediation effect of BMI on the relationships between LT-MVPA (≥ 150 min/week) and the TyG index, accounting for 31.48% of the total effect.ConclusionsLT-MVPA was associated with a decreased TyG index in US adults, while no such association was observed with O-MVPA or T-MVPA. Specific recommendations for PA categories should be provided, especially for populations at risk of diseases linked to a high TyG index or insulin resistance.

Machine learning in public health informatics: Evidence that complex sampling structures may not be needed for prediction models with imbalanced outcomes.

The objective of this study is to investigate the predictive ability of machine learning models for imbalanced outcomes from national survey data without the use of sampling weights. We evaluated the predictive performance of machine learning models on imbalanced outcomes from the US National Health and Nutrition Examination Survey (USNHANES) without using sampling weights. Four machine learning models (support vector machine, random forest, least absolute shrinkage and selection operator regression, and deep neural network) were compared with a logistic model that incorporates the survey's complex sampling design. Three resampling methods (oversampling, undersampling, and combined) were used to address class imbalance during the model training process. For all models, the balanced accuracy was similar (ranging from 0.72 to 0.76) and the specificity was smaller than sensitivity except for random forest. The support vector machine and neural networks performed best with sensitivity (ranging from 0.79 to 0.83), while the random forest had the largest specificity (ranging from 0.86 to 0.96), with one exception. PR-AUC scores and Brier scores were low ranging from 0.2529 to 0.3313 (lower scores worse) and 0.1005-0.3245 (lower scores better), respectively CONCLUSIONS: The machine learning models had overall similar predictive capacity to the recommended methods which integrate the complex sampling design for the prediction of osteoarthritis occurrence with USNHANES.

Exposome-wide association study of cognitive function in US older adults using the NHANES data

Abstract Neurodegenerative diseases pose increasing challenges to global aging populations. Cognitive decline in older adults is an initial indicator of neurodegenerative diseases, yet comprehensive research on environmental chemical exposures related to cognitive decline is limited. This study uses Exposome-Wide Association Study (ExWAS) framework to investigate associations of environmental chemicals with cognitive function in individuals aged ≥60 years. We used the Digit Symbol Substitution Test (DSST) scores and chemical biomarker data of the US National Health and Nutrition Examination Survey (NHANES) spanning four cycles (1999-2000, 2001-2002, 2011-2012, 2013-2014). We conducted multiple survey-weighted regression to identify biomarkers associated with DSST scores, Bayesian weighted quantile sum regression to estimate odds ratio (OR) of cognitive decline from multiple exposures to the identified biomarkers, and correlation network analyses to examine relationships among possible important biomarkers and cognitive decline. After correction for multiple comparisons, among 229 biomarkers having a ≥10% detection rate, 40 were associated with DSST scores (q-value &amp;lt;0.05). When assessing the effects of chemical mixtures on cognitive decline, no association between mixtures of chemicals and DSST scores was observed. Correlation network showed that cognitive decline is directly related with age and education level and identified that thiocyanate, m-/p-xylene, triclosan, benzophenone-3 and diphenyl phosphate were weakly related to cognitive function. In conclusion, leveraging the ExWAS framework enables us to identify chemical biomarkers that were not previously discovered from traditional approaches of examining a small number of chemicals at a time. While our findings provide foundation for further research, longitudinal studies are warranted to elucidate causal relationships.

Long-term weight change, incident cardiovascular disease and all-cause mortality among diabetic adults

We aimed to explore the impact of weight change from young to middle adulthood on incident cardiovascular disease (CVD) and all-cause mortality in US diabetic adults. All study subjects aged 40–79 years were from the US National Health and Nutrition Examination Survey (NHANES) 1988–2018, and they were non-pregnant and had complete data on self-reported weight at age 25 and 10 years before baseline enrollment over average 29.4 years. CVD events occurring from 10 years ago to baseline enrollment were recorded. Relative to stable non-obesity group, the strongest association was noted for the weight-losing group, followed by the stable-obesity group and weight-gaining group over following 10 years. Referring to the stable-obesity group identified significance for the stable non-obesity group. If total population had maintained non-obese from young to middle adulthood, 12 % of CVD cases could have been averted. Relative to the stable non-obesity group, subjects who maintained obese between young and middle adulthood had an increased risk of all-cause mortality. Our findings indicated that the risk for incident CVD and all-cause mortality was potentially reinforced in diabetic adults who were obese at age 25 but non-obese at midlife and who remained stable obese vis-à-vis those with stable non-obesity.

Type and physical intensity of occupations at pulmonary TB diagnosis.

Pulmonary TB (PTB) predominantly affects individuals of working age. We sought to characterise the occupations of people newly diagnosed with PTB in Karachi, Pakistan, by type and physical intensity. We did a secondary analysis of data from a study evaluating the diagnostic accuracy of artificial intelligence-based chest X-ray (CXR) analysis software, where individuals had been evaluated for active PTB using sputum cultures and had provided information on occupation. We used an accelerometer-validated US National Health and Nutrition Examination Survey-based job categorisation to assign physical activity levels to participant-reported occupations as High, Intermediate, or Low. Among 272 participants with microbiologically confirmed PTB (women: 130/272, 48%; median age: 29 years, IQR 22-45), 78% (211/272) had smear-positive disease, and 96% (260/272) had data on occupation. Unemployment was common (women: 70/122, 57%; men: 23/138, 17%). Most women reporting an occupation were homemakers (21/52, 40%), and 54% (28/52) had an intermediate- or a high physical activity occupation. Among men reporting an occupation, 35% (40/115) were labourers, and 79% (91/115) had an intermediate- or high-physical activity occupation. The majority of individuals with PTB were in their working age, had extensive disease, and had intermediate or high physical activity occupations, suggesting economic vulnerability due to physical impairment.

Association of relative fat mass (RFM) index with diabetes-related mortality and heart disease mortality

Although studies have examined the association of the Relative Fat Mass (RFM, a novel anthropometric index used as a surrogate for whole-body fat percentage) with all-cause mortality, the association of RFM with diabetes-related mortality and heart disease mortality has not been thoroughly investigated. In addition, no study has compared the associations of RFM and waist circumference (a surrogate for intra-abdominal fat) with cause-specific mortality and all-cause mortality. In the present study, we addressed these knowledge gaps. We used data from the US National Health and Nutrition Examination Survey (NHANES) 1999–2018. NHANES III was used for validation. Analyses included 46,535 adults (mean age 46.5 years). During a median follow-up time of 9.7 years, 6,101 participants died (743 from diabetes; 1,514 from heart disease). Compared with BMI and WC, RFM was more strongly associated with diabetes-related mortality in both women and men, adjusting for age, ethnicity, education, and smoking status. All anthropometric measures were similarly strongly associated with heart disease mortality and all-cause mortality. RFM showed greater predictive discrimination of mortality. Similar results were found in NHANES III (n = 14,448). In conclusion, RFM is strongly associated with diabetes-related mortality, heart disease mortality, and all-cause mortality, and outperforms conventional adiposity measures for prediction of mortality.

Associations between the Dietary Inflammatory Index and fractional exhaled nitric oxide among United States adults: A cross-sectional study.

Fractional exhaled nitric oxide (FeNo) is a convenient and noninvasive test that measures the concentration of nitric oxide in exhalation as a surrogate biomarker of airway inflammation. This cross-sectional study aimed to determine the associations between Dietary Inflammatory Index (DII) and FeNo in US adults. Adults participating in the 2007-2012 cycles of the US National Health and Nutrition Examination Survey with complete information and available measurement data of DII and FeNo were included. Associations between DII and FeNo were assessed using univariable and multivariable logistic regression models, restricted cubic spline analysis, stratified analysis, and sensitivity analysis. A total of 7677 participants (mean age 45.68 years, 53.03% men) with a mean DII of 1.28 and FeNo of 17.33 ppb were included. The multivariable-adjusted linear regression analysis showed that a one-unit increase in DII was associated with a 0.283-ppb reduction in FeNo level. The beta and 95% CI for the second, third, and fourth DII quartile groups were -1.19 (-2.04 to -0.35), -1.07 (-2.26 to 0.12), and -1.60 (-2.85 to -0.36), respectively (P for trend = 0.04), with the lowest quartile group as the reference. The restricted cubic spline curve showed an inversely linear relationship between DII and FeNo. The study result is robust and did not appear to be affected by the participant's age, sex, race, body mass index, physical activity, diabetes status, or white blood cell or eosinophil counts. A proinflammatory diet, as indicated by a higher DII, is cross-sectionally associated with lower FeNo levels in US adults.

Use of consensus clustering to identify distinct subtypes of chronic kidney disease and associated mortality risk

BackgroundChronic kidney disease (CKD) is a complex condition with diverse etiology and outcomes. Utilizing a data-driven clustering approach holds promise in identifying distinct CKD subgroups associated with specific risk profiles for death.MethodsUnsupervised consensus clustering was utilized to classify chronic kidney disease (CKD) into subtypes based on 45 baseline characteristics in a cohort of 6,526 participants from the US National Health and Nutrition Examination Survey (NHANES) spanning the years 1999–2000 to 2017–2018.We examined the associations between CKD subgroups and clinical endpoints related to mortality, including all-cause mortality, cardiovascular disease mortality, cancer mortality, and mortality due to other causes.ResultsA total of 6,526 individuals with CKD were classified into four clusters at baseline. Cluster 1 (n = 508) comprised patients with relatively favorable levels of cardiac and kidney function markers, lower prevalence of cancer and higher prevalence of obesity, lower medication usage, and younger age. Cluster 4 (n = 2,029) comprised patients with the worst cardiac and kidney function markers. The characteristics of cluster 2 (n = 1,439) and 3 (n = 2,550) fell in between these two clusters. From cluster 1 to cluster 4, we observed a gradual increase in the hazard ratios of all-cause mortality, cardiovascular disease mortality, and mortality due to other causes. Additionally, further sensitivity analysis revealed patient heterogeneity among predefined subgroups with similar baseline kidney function and mortality risks.ConclusionsConsensus clustering integrated baseline clinical and laboratory measures, revealing distinct CKD subgroups with markedly different risks of death, suggesting that further examination of patient subgroups could advance precision medicine.