National Health And Nutrition Examination Survey Data Research Articles

Association of herpes simplex virus infection with hearing loss: a cross-sectional study using NHANES data from 2011 to 2012 and 2015 to 2016

ObjectivesTo investigate the relationship between herpes simplex virus (HSV) and hearing loss using comprehensive population-based research.DesignThis cross-sectional study utilised data from the National Health and Nutrition Examination Survey (NHANES) to...

Association between depression severity and trouble sleeping: A population-based study.

This study investigates the association between insomnia and depression severity, exploring sleep disturbances in individuals with depression. The aim is to establish a new foundation for managing patients with co-occurring depression and insomnia, using 2015 to 2016 National Health and Nutrition Examination Survey (NHANES) data. We employed a cross-sectional design, using NHANES data from 2015 to 2018. The study included 11,261 participants after excluding incomplete data. Depression severity, assessed using Patient Health Questionnaire-9 (PHQ-9) scores, served as the exposure variable. We considered various demographic and lifestyle factors as covariates in the multivariate adjustment model. Statistical analyses adhered to CDC recommendations, with sample weights incorporated to account for NHANES' complex sample design. Our study, encompassing 19,225 participants, revealed that higher PHQ-9 scores correlated with an increased likelihood of sleep disorders. In the fully adjusted model, a positive association emerged between PHQ-9 scores and trouble sleeping (OR = 3.95, 95% CI: 3.35-4.66, P < .0001). This relationship displayed an inverted U-shaped curve, with an inflection point at 28. Subgroup analysis and interaction tests indicated no reliance on factors such as gender, age, marital status, or BMI for the connection between depression severity and trouble sleeping (all P for interaction > .05). We identified a significant inverted U-shaped correlation between sleep disturbances and depression severity. This underscores the crucial importance of assessing sleep disorder risks in individuals with varying degrees of depression severity, facilitating personalized therapeutic interventions.

Association between neutrophil-to-high-density lipoprotein cholesterol ratio and metabolic dysfunction-associated steatotic liver disease and liver fibrosis in the US population: a nationally representative cross-sectional study using NHANES data from 2017 to 2020

BackgroundThe neutrophil-to-high-density lipoprotein cholesterol ratio (NHR) has emerged as a promising biomarker for assessing inflammation and lipid dysregulation. Increasing evidence indicates that these metabolic disturbances play a crucial role in the development of metabolic dysfunction-associated steatotic liver disease(MASLD). This study aims to investigate the association between NHR, MASLD, and liver fibrosis.MethodsThis cross-sectional study analyzed data from the 2017–2020 National Health and Nutrition Examination Survey (NHANES). Weighted multivariate logistic regression models were used to investigate the association between NHR and both MASLD and liver fibrosis. Smoothed curve fitting and threshold effect analysis were performed to detect potential nonlinear relationships. Subgroup analyses were conducted to assess the consistency of these associations across different groups.ResultsThe study involved 4,761 participants. We observed a significant positive association between NHR and MASLD (OR = 1.20, 95% CI: 1.09–1.31). However, there was no significant association between NHR and liver fibrosis (OR = 1.01; 95% CI: 0.94–1.09). The analysis of smoothed curve fitting and threshold effect revealed an inverted U-shaped relationship between NHR and MASLD, with a turning point at 5.63.ConclusionOur findings indicate a positive correlation between elevated NHR levels and MASLD prevalence. However, we did not observe a significant association between NHR and liver fibrosis prevalence. Further prospective research is needed to validate these findings in a longitudinal setting.

Skin Cancer and Other Dermatologic Conditions Among US Veterans.

US veterans may be at an increased risk of developing various dermatologic conditions compared with nonveterans. To compare the prevalence and the odds of dermatologic conditions (eg, skin cancers, dermatitis/eczema/rash, psoriasis) between veterans and nonveterans. This population-based cross-sectional study leveraged nationally representative data from the National Health and Nutrition Examination Survey (NHANES). Three questionnaires (demographics, medical conditions, and dermatology) were merged from 1999-2018 for analysis. Participants were nonveterans and veterans from NHANES data. Data were analyzed from August 2023 to April 2024. The prevalence and odds ratios (ORs) comparing veterans and nonveterans were examined for various dermatologic conditions, including self-reported skin cancer history (any skin cancer, melanoma, nonmelanoma and unknown subtypes), dermatitis/eczema/inflamed rash, and psoriasis. In a total of 61 307 participants (54 554 nonveterans and 6753 veterans), there was a higher prevalence of any skin cancer history among US veterans compared with nonveterans (9.0% vs 2.9%; P < .001) as well as a higher prevalence of melanoma history (2.2% vs 0.6%; P < .001). Adjusted for demographic factors, veterans had higher odds of any skin cancer history (OR, 1.72; 95% CI, 1.23-2.40) and higher odds of a melanoma history (OR, 2.27; 95% CI, 1.17-4.39) compared with nonveterans. Veterans had a higher prevalence of a psoriasis diagnosis compared with nonveterans (4.5% vs 2.9%; P = .002) and a 61% higher odds of a psoriasis diagnosis (OR, 1.61; 95% CI, 1.05-2.46) compared with nonveterans. This cross-sectional study found that veterans have higher prevalence and odds of various dermatologic conditions compared with nonveterans. Efforts aimed at improving health care quality among veterans must investigate the underlying causes of worsened skin health in this population.

The triangular relationship of physical activity, depression, and inflammatory markers: A large cross-sectional analysis with NHANES data

Depression is a major public health problem worldwide and is closely related with systemic inflammatory responses. Additionly, physical activity (PA) is thought to be associated with lower levels of depression and inflammatory markers. This study aimed to elucidate the complex interactions between PA, depression, and inflammatory markers. Based on the National Health and Nutrition Examination Survey (NHANES), various logistic regression were applied to analyze the pairwise correlations among the three. Restrictive cubic splines were constructed to explore the nonlinear relationship between PA and depression. Mediation models were used to identify the mediating role of inflammatory markers. The findings revealed a positive link between depression and inflammatory marker, whereas PA was inversely correlated with both inflammatory marker and depression. Particularly, we noticed the greatest reduction in the risk of depression when the level of PA was between 1200 and 1722 MET-min/week. Besides, we demonstrated that inflammatory markers mediate the potential effects of physical inactivity on depression, ranging from 1.72 % to 6.25 %. In conclusion, PA appear to protect against depression, in which inflammatory markers may play a mediating role. Moreover, we determined the optimal dosage of PA to minimize the likelihood of depression, thereby offering valuable guidance for managing depression.

Japanese Diet Indices and Nutrient Density in US Adults: A Cross-Sectional Analysis with NHANES Data.

Previous studies have shown that Japanese dietary patterns are associated with high nutrient density. However, these studies were limited to the Japanese population. We examined this association in the US population. A cross-sectional analysis was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018. We included 3138 people aged 20-79 years. Food and nutrient intake data were based on the 24 h recall method. Three Japanese diet indices were used: (1) Japanese Diet Index (JDI, based on 9 food items), (2) modified JDI (mJDI, based on 12 food items), and (3) weighted JDI (wJDI, selected and weighted from mJDI food items). The nutrient density (ND) score was calculated based on the Nutrient-Rich Food Index 9.3. Spearman's rank correlation coefficients were calculated. The correlation coefficients with the ND score were 0.24 (p < 0.001) for the JDI and 0.38 (p < 0.001) for the mJDI. The correlation coefficient between the wJDI and ND score was 0.48 (p < 0.001). The three Japanese diet indices were correlated with the ND score in all racial groups (p < 0.001). Even among the US population, higher degrees of Japanese diet defined by the JDI or mJDI were associated with higher nutrient density.

Associations between body mass index and all-cause and CVD mortality in agriculture, forestry, and fishing occupations: A prospective cohort study using NHANES data (1999-2014).

Obesity, as indicated by elevated Body Mass Index (BMI), is a well-established global health concern associated with increased morbidity and mortality across diverse populations. However, the influence of BMI on individuals in Agriculture, Forestry, and Fishing (AFF) occupations, characterized by unique challenges and environmental factors, has received limited research attention. Our study, a prospective cohort analysis, utilized National Health and Nutrition Examination Survey (NHANES) data from 1999-2014, targeting adults above 18 in AFF occupations with comprehensive BMI data, omitting individuals with a history of cancer. Mortality outcomes were extracted from the NHANES mortality file, and BMI was segmented into eight categories. Essential covariates such as age, sex, race, and various health factors were incorporated. The statistical analysis encompassed Cox regression, generalized additive models, smooth curve fitting, and stratified analyses. During 1,005 person-years with 201 all-cause and 57 CVD deaths, we observed L-shaped and U-shaped correlations of BMI with all-cause and CVD mortality, featuring a pivotal inflection at 26.69 and 27.40 kg/m2. Above this BMI threshold of 26.69 and 27.4 kg/m2, all-cause mortality association was not significant while CVD mortality was positive. This study highlights a unique BMI-mortality association in AFF occupations, diverging from standard patterns. The rigorous labor and environmental conditions in AFF jobs suggest that a certain range of higher BMI could reduce mortality risk. This highlights the necessity for tailored health guidelines in different occupations. Future research should concentrate on diverse health indicators and enhanced risk assessment for physically strenuous occupations.

Development and evaluation of interpretable machine learning regressors for predicting femoral neck bone mineral density in elderly men using NHANES data.

Osteoporotic femoral neck fractures (OFNFs) pose a significant orthopedic challenge in the elderly population, accounting for up to 40% of all osteoporotic fractures and leading to considerable health deterioration and increased mortality. In addressing the critical need for early identification of osteoporosis through routine screening of femoral neck bone mineral density (FNBMD), this study developed a user-friendly prediction model aimed at men aged 50 years and older, a demographic often overlooked in osteoporosis screening. Utilizing data from the National Health and Nutrition Examination Survey (NHANES), the study involved outlier detection and handling, missing value imputation via the K nearest neighbor (KNN) algorithm, and data normalization and encoding. The dataset was split into training and test sets with a 7:3 ratio, followed by feature screening through the least absolute shrinkage and selection operator (LASSO) and the Boruta algorithm. Eight different machine learning algorithms were then employed to construct predictive models, with their performance evaluated through a comprehensive metric suite. The random forest regressor (RFR) emerged as the most effective model, characterized by key predictors such as age, body mass index (BMI), poverty income ratio (PIR), serum calcium, and race, achieving a coefficient of determination (R²) of 0.218 and maintaining robustness in sensitivity analyses. Notably, excluding race from the model resulted in sustained high performance, underscoring the model's adaptability. Interpretations using Shapley additive explanations (SHAP) highlighted the influence of each feature on FNBMD. These findings indicate that our predictive model effectively aids in the early detection of osteoporosis, potentially reducing the incidence of OFNFs in this high-risk population.

A Comprehensive Youth Diabetes Epidemiological Data Set and Web Portal: Resource Development and Case Studies.

The prevalence of type 2 diabetes mellitus (DM) and pre-diabetes mellitus (pre-DM) has been increasing among youth in recent decades in the United States, prompting an urgent need for understanding and identifying their associated risk factors. Such efforts, however, have been hindered by the lack of easily accessible youth pre-DM/DM data. We aimed to first build a high-quality, comprehensive epidemiological data set focused on youth pre-DM/DM. Subsequently, we aimed to make these data accessible by creating a user-friendly web portal to share them and the corresponding codes. Through this, we hope to address this significant gap and facilitate youth pre-DM/DM research. Building on data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we cleaned and harmonized hundreds of variables relevant to pre-DM/DM (fasting plasma glucose level ≥100 mg/dL or glycated hemoglobin ≥5.7%) for youth aged 12-19 years (N=15,149). We identified individual factors associated with pre-DM/DM risk using bivariate statistical analyses and predicted pre-DM/DM status using our Ensemble Integration (EI) framework for multidomain machine learning. We then developed a user-friendly web portal named Prediabetes/diabetes in youth Online Dashboard (POND) to share the data and codes. We extracted 95 variables potentially relevant to pre-DM/DM risk organized into 4 domains (sociodemographic, health status, diet, and other lifestyle behaviors). The bivariate analyses identified 27 significant correlates of pre-DM/DM (P<.001, Bonferroni adjusted), including race or ethnicity, health insurance, BMI, added sugar intake, and screen time. Among these factors, 16 factors were also identified based on the EI methodology (Fisher P of overlap=7.06×106). In addition to those, the EI approach identified 11 additional predictive variables, including some known (eg, meat and fruit intake and family income) and less recognized factors (eg, number of rooms in homes). The factors identified in both analyses spanned across all 4 of the domains mentioned. These data and results, as well as other exploratory tools, can be accessed on POND. Using NHANES data, we built one of the largest public epidemiological data sets for studying youth pre-DM/DM and identified potential risk factors using complementary analytical approaches. Our results align with the multifactorial nature of pre-DM/DM with correlates across several domains. Also, our data-sharing platform, POND, facilitates a wide range of applications to inform future youth pre-DM/DM studies.

Association between biological ageing and periodontitis: Evidence from a cross-sectional survey and multi-omics Mendelian randomization analysis.

To investigate the relationship and potential causality between biological ageing and periodontitis. We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis. We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration. Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

The Relationship Between Mental Health and Periodontal Disease: Insights from NHANES Data

Introduction and aim Periodontal disease, initiated by dental biofilm and influenced by various local and systemic factors, includes stress as a potential contributor to its progression. Despite associations with severe forms like acute necrotizing ulcerative gingivitis, a comprehensive large-sample study linking stress to periodontal disease is lacking. This study aims to investigate the relationship between mental health and periodontal disease. Materials and Methods Leveraging data from the National Health and Nutrition Examination Survey (NHANES), relevant information was extracted. Mental health was the exposure variable, and periodontal disease, assessed through indices following Eke et al.'s definition, served as the outcome. Covariates impacting periodontal disease were considered, and demographic and disease status analyses employed the Rao-Scott chi-squared test. A logistic regression model assessed mental health's impact on periodontal disease. Results Logistic regression indicated higher odds of periodontal disease among individuals feeling bad about themselves for more than half of the day (OR 1.170, 95% CI 0.533-2.474), though statistical significance was not reached. Periodontitis prevalence significantly varied based on marital status, with 6.6% of married and 10.8% of unmarried subjects affected. Notably, a statistically significant difference in periodontitis prevalence existed between subjects with health insurance (8.3%) and those without (16.5%). Conclusion Within study limitations, it is concluded that no significant difference exists in periodontal status between individuals with compromised mental health and those without. The findings underscore potential associations between mental health, marital status, and access to health insurance with periodontal disease.

Identifying Populations at Risk for Lung Cancer Mortality from the National Health and Nutrition Examination Survey (2001-2018) Using the 2021 USPSTF Screening Guidelines.

Lung cancer (LC) is the leading cause of cancer mortality in the United States. To combat this predicament, early screening and critically assessing its risk factors remain crucial. The aim of this study was to identify the value of specific factors from the National Health and Nutrition Examination Survey (NHANES) from 2001-2018, as they relate to lung cancer mortality in the US Preventive Services Task Force (USPSTF)-eligible population. A total of 3545 adults who met USPSTF criteria were extracted from 81,595 NHANES participants. The LC Death Risk Assessment Tool was used to calculate the number of deaths per 1000 individuals. The Mann-Whitney U test and one-way ANOVA determined the statistical significance of the factors involved in LC mortality. Male sex, African and Hispanic ethnicity, lower education attainment, and secondhand exposure to cigarette smoke correlated with an increased risk of LC mortality. Additionally, the factor of emotional support from NHANES data was analyzed and did not show any benefit to reducing risk. By identifying individuals at high-risk, preventative measures can be maximized to produce the best possible outcome.

Ratio of Red Blood Cell Distribution Width to Albumin Level and Risk of Mortality.

The ratio of red blood cell distribution width (RDW) to albumin concentration (RAR) has emerged as a reliable prognostic marker for mortality in patients with various diseases. However, whether RAR is associated with mortality in the general population remains unknown. To explore whether RAR is associated with all-cause and cause-specific mortality and to elucidate their dose-response association. This population-based prospective cohort study used data from participants in the 1998-2018 US National Health and Nutrition Examination Survey (NHANES) and from the UK Biobank with baseline information provided from 2006 to 2010. Included participants had complete data on serum albumin concentration, RDW, and cause of death. The NHANES data were linked to the National Death Index records through December 31, 2019. For the UK Biobank, dates and causes of death were obtained from the National Health Service Information Centre (England and Wales) and the National Health Service Central Register Scotland (Scotland) to November 30, 2022. Potential associations between RAR and the risk of all-cause and cause-specific mortality were evaluated using Cox proportional hazards regression models. Restricted cubic spline regressions were applied to estimate possible nonlinear associations. In NHANES, 50 622 participants 18 years of age or older years were included (mean [SD] age, 48.6 [18.7] years; 26 136 [51.6%] female), and their mean (SD) RAR was 3.15 (0.51). In the UK Biobank, 418 950 participants 37 years of age or older (mean [SD], 56.6 [8.1] years; 225 038 [53.7%] female) were included, and their mean RAR (SD) was 2.99 (0.31). The NHANES documented 7590 deaths over a median (IQR) follow-up of 9.4 (5.1-14.2) years, and the UK Biobank documented 36 793 deaths over a median (IQR) follow-up of 13.8 (13.0-14.5) years. According to the multivariate analysis, elevated RAR was significantly associated with greater risk of all-cause mortality (NHANES: hazard ratio [HR], 1.83 [95% CI, 1.76-1.90]; UK Biobank: HR, 2.08 [95% CI, 2.03-2.13]), as well as mortality due to malignant neoplasm (NHANES: HR, 1.89 [95% CI, 1.73-2.07]; UK Biobank: HR, 1.93 [95% CI, 1.86-2.00]), heart disease (NHANES: HR, 1.88 [95% CI, 1.74-2.03]; UK Biobank: HR, 2.42 [95% CI, 2.29-2.57]), cerebrovascular disease (NHANES: HR, 1.35 [95% CI, 1.07-1.69]; UK Biobank: HR, 2.15 [95% CI, 1.91-2.42]), respiratory disease (NHANES: HR, 1.99 [95% CI, 1.68-2.35]; UK Biobank: HR, 2.96 [95% CI, 2.78-3.15]), diabetes (NHANES: HR, 1.55 [95% CI, 1.27-1.90]; UK Biobank: HR, 2.83 [95% CI, 2.35-3.40]), and other causes of mortality (NHANES: HR, 1.97 [95% CI, 1.86-2.08]; UK Biobank: HR, 2.40 [95% CI, 2.30-2.50]) in both cohorts. Additionally, a nonlinear association was observed between RAR levels and all-cause mortality in both cohorts. In this cohort study, a higher baseline RAR was associated with an increased risk of all-cause and cause-specific mortality in the general population. These findings suggest that RAR may be a simple, reliable, and inexpensive indicator for identifying individuals at high risk of mortality in clinical practice.

Osteoarthritis and hypertension: observational and Mendelian randomization analyses

BackgroundThe association between osteoarthritis (OA) and hypertension is a subject of ongoing debate in observational research, and the underlying causal relationship between them remains elusive.MethodsThis study retrospectively included 24,871 participants in the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2020. Weighted logistic regression was performed to investigate the connection between OA and hypertension. Additionally, Mendelian randomization (MR) analysis was conducted to explore the potential causal relationship between OA and hypertension.ResultsIn the NHANES data, after adjusting for multiple confounding factors, there was no significant relationship between OA and hypertension (OR 1.30, 95% CI, 0.97–1.73, P = 0.089). However, among males, OA appeared to be associated with a higher risk of hypertension (OR 2.25, 95% CI, 1.17–4.32, P = 0.019). Furthermore, MR results indicate no relationship between multiple OA phenotypes and hypertension: knee OA (IVW, OR 1.024, 95% CI: 0.931–1.126, P = 0.626), hip OA (IVW, OR 0.990, 95% CI: 0.941–1.042, P = 0.704), knee or hip OA (IVW, OR 1.005, 95% CI: 0.915–1.105, P = 0.911), and OA from UK Biobank (IVW, OR 0.796, 95% CI: 0.233–2.714, P = 0.715). Importantly, these findings remained consistent across different genders and in reverse MR.ConclusionsOur study found that OA patients had a higher risk of hypertension only among males in the observational study. However, MR analysis did not uncover any causal relationship between OA and hypertension.

Sleep duration time and human papillomavirus infection risk: The U-shaped relationship revealed by NHANES data.

This study aims to investigate the relationship between sleep factors (sleep duration time [SDT] and obstructive sleep apnea [OSA]) and human papillomavirus (HPV)/high-risk HPV(HR-HPV) infection, utilizing data from the National Health and Nutrition Examination Survey (NHANES). We conducted a cross-sectional analysis using NHANES data, focusing on SDT and OSA's association with HPV/HR-HPV infection. The primary statistical methods included weighted multivariate linear regression and logistic regression to assess the association between SDT, OSA, and HPV/HR-HPV infection. The study employed restricted cubic splines (RCS) for evaluating potential non-linear relationships between SDT and HPV/HR-HPV infection. Subgroup analyses were conducted. Interaction terms were used to examine the heterogeneity in associations across different subgroups. The study identified a U-shaped relationship between SDT and HPV infection. Specifically, 7 hours of sleep was associated with the lowest risk of HPV infection. In comparison, SDT less than 7 hours resulted in a 26.3% higher risk of HPV infection (Odds Ratio [OR] = 1.26, 95% Confidence Interval [CI]: 1.029, 1.549), and more than 9 hours of sleep showed a 57.4% increased risk (OR = 1.574, 95% CI: 1.116, 2.220). The relationship between SDT and HR-HPV infection was significant in the first two models, but not in the fully adjusted model. No significant interaction was found between sleep duration and other covariates. There was no association between OSA and HPV/HR-HPV infection. The study underscores the complex relationship between sleep duration and HPV infection risk, suggesting both very short and very long sleep durations may increase HPV infection likelihood. The findings highlight the need for further research to explore the biological mechanisms underpinning this association and to consider broader population groups and more precise sleep assessment methods in future studies.

Adherence to oxidative balance score is inversely associated with the prevalence of stroke: results from National Health and Nutrition Examination Survey 1999-2018.

The relationship between oxidative balance score (OBS), an emerging integrative metric for assessing individual redox homeostasis, and the prevalence of stroke in the general population remains unknown. We aimed to explore these relationships in the National Health and Nutrition Examination Survey (NHANES). We investigated the relationship between the oxidative balance score (OBS) and stroke prevalence using NHANES data from 1999-2018. We included eligible individuals from NHANES 1999-2018. OBS calculations were based on previously validated methods, and stroke diagnoses were based on self-reports in questionnaires. Multivariable logistic regression analyses were used to examine the independent associations of overall, dietary, and lifestyle OBS with stroke prevalence. In addition, restricted cubic spline (RCS), stratified analysis, and sensitivity analysis were used. We included 25,258 participants aged 20-85 years, in which the prevalence of stroke was 2.66%. After adjusting for all confounders, overall and dietary OBS, but not lifestyle OBS, were inversely associated with the prevalence of stroke [odds ratios and 95% confidence intervals of 0.97 (0.96, 0.99) and 0.98 (0.96, 0.99) for overall and dietary OBS, respectively, both p < 0.05]. In addition, there was a dose-response relationship between overall and dietary OBS and stroke prevalence. The RCS showed that these relationships were linear. Stratified analyses indicated that socioeconomic status (SES) significantly influenced the relationship between all OBS and stroke prevalence. Dietary OBS, but not lifestyle OBS, had an inverse relationship with the prevalence of stroke in the general population. SES significantly influenced the protective effect of OBS against stroke. These findings emphasize the importance of integrated antioxidant properties from diet for stroke prevention.

Development and validation of a risk score nomogram model to predict the risk of 5-year all-cause mortality in diabetic patients with hypertension: A study based on NHANES data

BackgroundThe present study aimed to develop and validate a prediction nomogram model for 5-year all-cause mortality in diabetic patients with hypertension. MethodsData were extracted from the National Health and Nutrition Examination Survey (NHANES). A total of 3291 diabetic patients with hypertension in the NHANES cycles for 1999–2014 were selected and randomly assigned at a ratio of 8:2 to the training cohort (n = 2633) and validation cohort (n = 658). Multivariable Cox regression was conducted to establish a visual nomogram model for predicting the risk of 5-year all-cause mortality. Receiver operating characteristic curves and C-indexes were used to evaluate the discriminant ability of the prediction nomogram model for all-cause mortality. Survival curves were created using the Kaplan–Meier method and compared by the log-rank test. ResultsThe nomogram model included eight independent predictors: age, sex, education status, marital status, smoking, serum albumin, blood urea nitrogen, and previous cardiovascular disease. The C-indexes for the model in the training and validation cohorts were 0.76 (95% confidence interval: 0.73–0.79, p < 0.001) and 0.75 (95% confidence interval: 0.69–0.81, p < 0.001), respectively. The calibration curves indicated that the model had satisfactory consistency in the two cohorts. The risk of all-cause mortality gradually increased as the tertiles of the nomogram model score increased (log-rank test, p < 0.001). ConclusionThe newly developed nomogram model, a readily useable and efficient tool to predict the risk of 5-year all-cause mortality in diabetic patients with hypertension, provides a novel risk stratification method for individualized intervention.

Abstract P508: Comparisons of Cardiovascular Health in US Adults by Chronic Disease Status: National Health and Nutrition Examination Survey (NHANES), 2013-2018

Introduction: Cardiovascular health (CVH) assessment is typically applied to younger, healthy individuals in the setting of primordial prevention, but the concept may have important benefits for those with chronic diseases of aging (CDAs) at increased risk for incident cardiovascular disease (CVD). No studies have assessed CVH in adults with CDAs vs. healthy adults without CDAs using the new Life’s Essential 8 (LE8) metrics. Methods: We used NHANES data from 2013-2018 to identify presence of 15 CDAs by participant self-report of diagnosis. We included adults ages 20 to 79. CVH was defined by AHA’s LE8 metrics. Overall mean LE8 (range 0-100, higher = better CVH) and individual LE8 metric scores were calculated according to disease status for all participants and stratified by self-identified sex and race/ethnicity. Results: There were 12,296 adults, with mean age 46 years; 51% self-identified as female, 65% as White, 16% Hispanic, 11% Black, 5% Asian, 4% multiracial. Significantly, and often substantially, lower CVH scores were noted for adults with CDA (12 of 15 CDAs) vs. healthy adults, including all subtypes of CVD and lung diseases, liver disease, arthritis, cognitive decline, and depression. Greatest mean LE8 differences were detected for COPD, emphysema, and congestive heart failure. For example, mean overall LE8 score was 14.0 points lower in those with vs. without COPD (51.0 vs. 65.0, P&lt;0.0001) with smoking and physical activity having the largest absolute differences in individual metric scores (36.4 and 23.6, respectively). There were no significant differences in LE8 scores for participants with vs. without cancer, HIV, or osteoporosis. Males and Black adults consistently had lower LE8 scores. Conclusions: CVH is significantly poorer in adults with many of the CDAs compared to healthy adults. These data establish the utility of the LE8 CVH score to identify groups for targeted optimization of CVH to enhance primary and secondary prevention efforts for CVD and potentially for other concomitant CDAs.

The obesity challenge in joint replacement: a multifaceted analysis of self-reported health status and exercise capacity using NHANES data - a population-based study.

Joint replacement is successful for end-stage osteopathy, with obesity linked to evaluated risk. But the impact of obesity on self-reported health and exercise capacity among joint replacement patients remains complex and requires investigation. This study utilizes data from the National Health and Nutrition Examination Survey (NHANES) to examine the relationship between obesity severity, demographic factors, medical comorbidities, and self-reported health status. The relationship between general health status and BMI was analyzed using multivariable regression, and further illustrated using a restricted cubic spline. Additionally, a bibliometric analysis and systemic review was done to frame the research within the broader context of existing knowledge and demographic specifics. Analysis of NHANES data involving 327 joint replacement patients yielded intriguing insights. The difference in self-reported health between BMI groups did not achieve conventional statistical significance (P=0.06), and multivariable analysis showed that even severely obese patients did not exhibit significantly elevated risk of poor/fair self-reported health compared to normal weight subjects. Among severely obese individuals (BMI>40), 40.63% still rated their health positively. However, stratified analyses indicated that obesity correlated with negative health reports across gender, age, and education strata. Notably, physical functioning emerged as a robust predictor of self-reported health, with those reporting no walking difficulties having significantly lower odds of poor/fair health (Odds Ratio=0.37, P=0.01). The study highlights the need for healthcare providers to consider individual physical abilities and comorbidities alongside obesity severity when discussing treatment options with joint replacement patients. It supports tailored interventions and informed shared decision-making. Future research could explore effective weight management strategies for obese individuals undergoing joint replacement.

Comparative efficacy of anthropometric indices in predicting 10-year ASCVD risk: insights from NHANES data.

Cardiovascular diseases remain a leading cause of morbidity and mortality worldwide. Accurately predicting the 10-year risk of Atherosclerotic Cardiovascular Disease (ASCVD) is crucial for timely intervention and management. This study aimed to evaluate the predictive performance of six anthropometric indices in assessing the 10-year ASCVD risk. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018), the study involved 11,863 participants after applying exclusion criteria. Six anthropometric indices-waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and waist-to-height0.5 ratio (WHT.5R)-were calculated. The 10-year ASCVD risk was assessed using the 2013 ACC/AHA guidelines & pooled cohort equations model. Participants were divided into two groups based on an ASCVD risk threshold of 7.5%. Statistical analysis included chi-square tests, odds ratios, and receiver operating characteristic (ROC) curves. The study found significant differences in baseline characteristics between participants with ASCVD risk less than 7.5% and those with a risk greater than or equal to 7.5%, stratified by gender. In both male and female groups, individuals with higher ASCVD risk exhibited higher age, waist circumference, BMI, and a higher prevalence of health-compromising behaviors. ABSI emerged as the most accurate predictor of ASCVD risk, with the highest area under the curve (AUC) values in both genders. The optimal cut-off values for ABSI was established for effective risk stratification (cut-off value = 0.08). The study underscores the importance of anthropometric indices, particularly ABSI, in predicting the 10-year risk of ASCVD. These findings suggest that ABSI, along with other indices, can be instrumental in identifying individuals at higher risk for ASCVD, thereby aiding in early intervention and prevention strategies.