Interaction between trouble sleeping and depression on hypertension in the NHANES 2005-2018

The association between nutritional-inflammatory status and chronic kidney disease prognosis: a population-based study

BACKGROUND

Chronic kidney disease (CKD) prognosis is closely tied to the interplay between nutrition and inflammation. However, comprehensive nutritional-inflammatory indices for prognostic evaluation are rare in CKD. This study explored the association of the advanced lung cancer inflammation index (ALI) with estimated glomerular filtration rate (eGFR) and all-cause mortality in CKD patients.

METHODS

A total of 1,982 CKD patients from the National Health and Nutrition Examination Survey (NHANES) database (2011-2018) were included in the analysis. Analytical methods included linear regression, cox regression, and restricted cubic spline (RCS) analysis. Subgroup and sensitivity analyses were performed, and further evaluation was conducted using the receiver operating characteristic (ROC) curve and C-index for all-cause mortality across different CKD stages.

RESULTS

Among CKD patients, 1,103 patients (55.7%) were classified as stage I-II, and 879 patients (44.3%) as stage III-V. After adjusting covariates, ALI was found to be positively correlated with eGFR (Beta = 0.11; 95% CI: 0.07-0.15), and negatively related with all-cause mortality (HR = 0.72; 95% CI: 0.63-0.83). Subgroup analysis showed that the positive correlation between ALI and eGFR was stronger in CKD stage III-V compared to stage I-II. However, ALI's protective effect on mortality was weaker in stage III-V. The C-index for ALI was 0.648 in stage I-II and 0.660 in stage III-V.

CONCLUSION

ALI was significantly associated with eGFR and all-cause mortality in CKD patients. Nutritional and anti-inflammatory interventions in early-stage CKD may improve prognosis, and ALI may have great potential as a multifaceted biomarker to influence the prognosis of CKD, particularly in stages III-V.

Association between ketogenic diets and depression: A cross-sectional analysis of the NHANES 2005-2023 August

BACKGROUND

The ketogenic diet (KD) is widely used for epilepsy and neurodegenerative diseases. Glutamate, the excitatory neurotransmitter in the body, has been found to be significantly elevated in the brains of some patients with depression. Ketone bodies, the main products of KD, may negatively regulate the metabolic activity of glutamate, which suggests a potential role in the onset and progression of depression. However, the relationship between KD and depression risk remains uncertain.

METHODS

This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and August 2023 to investigate the association between the ketogenic diet ratio (KDR) and depression risk. Multiple logistic regression analysis was employed to examine this association, whereas nonlinear relationships were assessed using restricted cubic splines. Stratification analysis was employed to examine the association between KDR and depression severity. Subgroup analyses were also performed.

RESULTS

In a fully adjusted model accounting for confounding variables, KDR was significantly associated with depression risk. Two-piecewise linear regression analysis better fitted the association (KDR < 0.35, OR: 0.11; 95%CI: 0.03-0.35; P < 0.001). Subgroup analyses indicated that this association between KDR and depression was particularly pronounced in certain specific populations. We further observed a significant correlation between KDR and depression severity (P < 0.001).

CONCLUSION

Higher KDR was associated with a reduced risk of depression, with potentially greater efficacy observed in specific populations. Additionally, KDR has been found to be significantly associated with the severity of depression. Further study could investigate their potential mechanism.

Association of sleep duration with hypertension in young and middle-aged adults: A systematic review and meta-analysis

Background

Hypertension is a primary risk factor for cardiovascular and cerebrovascular diseases. A number of studies have suggested that sleep duration play an important role in the development of hypertension. Hypertension in young and middle-aged individuals is characterized by low awareness and treatment rates, increasing the risk of adverse events. To further elucidate the relationship between sleep duration and hypertension risk in young and middle-aged individuals, we conducted a meta-analysis.

Methods

This study searched PubMed, Embase, and the Cochrane Library from January 2003 to November 5, 2023. Data analysis was performed using STATA 17. Using Q test and I2-statistic, heterogeneity test for the included studies was conducted. Potential small-sample effects were evaluated based on the symmetry of funnel plots, and publication bias in included studies was evaluated using Egger's test.

Results

Data analysis of sleep duration was conducted for 16 studies, which revealed that both long sleep duration (OR, 1.10; 95 % CI, 1.05-1.15) and short sleep duration (RR: 1.10, 95 % CI: 1.05 to 1.15) were associated with hypertension in young and middle-aged individuals, particularly in Asian populations.

Conclusions

This meta-analysis revealed an association between sleep duration (short [<7 h] and long [≥9 h]) and the development of hypertension in young and middle-aged adults, particularly in Asian populations. Sleep is a behavior that can be modified. Clinicians and health professionals should be encouraged to intensify efforts to promote healthy sleep for all and reduce the occurrence of high blood pressure in young and middle-aged individuals.

Dyslipidemia and aging: the non-linear association between atherogenic index of plasma (AIP) and aging acceleration

BACKGROUND

Dyslipidemia has been proved to play a pivotal role in biological aging. Atherogenic Index of Plasma (AIP), derived from serum triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C), is an effective biomarker of dyslipidemia. However, whether AIP can be used as an indicator of biological aging remains unclear. This study aims to investigate the relationship between AIP and biological aging in the US adult population.

METHODS

4,471 American adults with age over 20 years from the National Health and Nutrition Examination Survey (NHANES) database were included in this study. Biological aging was assessed by phenotypic age acceleration (PhenoAgeAccel). Multivariable linear regression models, subgroup analyses and interaction tests were employed to explore the association between AIP and PhenoAgeAccel. Furthermore, adjusted restricted cubic spline (RCS) analyses were employed to assess potential nonlinear relationships, while mediation analysis was utilized to identify the mediating effects of homeostatic model assessment of insulin resistance (HOMA-IR). Besides, network pharmacology was performed to determine the potential mechanisms underlying dyslipidemia-related aging acceleration.

RESULTS

A total of 4,471 participants were included in this study, the median chronological age, PhenoAge and PhenoAgeAccel for the overall population were 49 (35-64) years, 42.85 (27.30-59.68) years, and - 6.92 (- 10.52 to -2.46) years, respectively. In the fully adjusted model, one unit increase of AIP was correlated with 1.820-year increase in PhenoAgeAccel (β = 1.820, 95% CI: 1.085-2.556), which was more pronounced among individuals being female, diabetic and hypertensive. Furthermore, RCS analysis revealed a nonlinear relationship between AIP and PhenoAgeAccel, with an inflection point identified at -0.043 for AIP via threshold and saturation effect analysis. AIP demonstrated a positive correlation with PhenoAgeAccel both before (β = 6.550, 95% CI: 5.070-8.030) and after (β = 3.898, 95% CI: 2.474-5.322) this inflection point. Additionally, HOMA-IR was found to mediate 39.21% of the association between AIP and PhenoAgeAccel. Finally, network pharmacology analysis identified INS, APOE, APOB, IL6, IL10, PPARG, MTOR, ACE, PPARGC1A, and SERPINE1 as core targets in biological aging, which were functionally linked to key signaling pathways like AMPK, apelin, JAK-STAT, FoxO, etc. CONCLUSIONS: An elevated AIP was notably and positively correlated with accelerated aging, suggesting that AIP may serve as an effective predictor to evaluate accelerated aging.

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records

BACKGROUND

Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogeneous electronic health record (EHR) data. Integrating this data can provide a more comprehensive understanding of depression and anxiety in T2DM patients, leading to more personalized treatment strategies.

OBJECTIVE

This study aims to develop and validate a deep learning model, the Regional EHR for Depression and Anxiety Prediction Model (REDAPM), using regional EHR data to predict depression and anxiety in patients with T2DM.

METHODS

A case-control development and validation study was conducted using regional EHR data from the Nanjing Health Information Center (NHIC). Two retrospective, matched (1:3) datasets were constructed from the full cohort for the model's internal and external validation. These two datasets were selected from the NHIC data of 2020 and 2022, respectively. The REDAPM incorporates both structured and unstructured EHR data, capturing the temporal dependency of clinical events. The performance of REDAPM was compared to a set of baseline models, evaluated using the area under the receiver operating characteristic curve (ROC-AUC) and the area under the precision-recall curve (PR-AUC). Subgroup, ablation, and interpretation analyses were conducted to identify relevant clinical features available from EHRs.

RESULTS

The internal and external validation datasets comprised 24,724 and 34,340 patients, respectively. The REDAPM outperformed baseline models in both datasets, achieving ROC-AUC scores of 0.9029±0.008 and 0.7360±0.005, and PR-AUC scores of 0.8124±0.011 and 0.5504±0.009. Ablation and subgroup experiments confirmed the significant contribution of patients' medical history text to the model's performance. Integrated gradient score analysis identified the predictive importance of other mental disorders.

CONCLUSION

The REDAPM effectively leverages the heterogeneous characteristics of regional EHR data, demonstrating strong predictive performance for depression onset in diabetic patients. It also shows potential for discovering significant clinical features, indicating considerable promise for clinical utility.

A Bibliometric Analysis of hypertension and anxiety from 2004 to 2022

BACKGROUND

A growing body of clinical evidence points to an association between hypertension and anxiety, but the mechanisms by which the two occur are unclear. This article aims to explore possible common influences and associations between hypertension and anxiety.

METHODS

We searched for publications on hypertension and anxiety from January 01, 2004 to December 31, 2022 in Web of Science and performed bibliometrics using CiteSpace, VOSviewer, Scimago Graphica and Gephi.

RESULTS

A total of 3216 related articles were retrieved from the Web of Science database. After screening, 3051 articles were included. The number of published articles has increased over the past 19 years. The United States has more researches in this area and has strong collaborative relationships with other countries, which gives it some credibility and authority. The words that appear in the burst keywords are gender, age, obesity, depression, panic disorder, pregnancy induced hypertension, coronary heart disease, chronic kidney disease, and pituitary adrenal axi, which are co-related with hypertension and anxiety.

CONCLUSION

There is a link between hypertension and anxiety, and the 2 influence each other, usually in a positive way. Common influences on hypertension and anxiety include age, gender, obesity, depression, panic attacks, pregnancy, coronary heart disease and chronic kidney disease. Recent research hotspots have focused on population aging and comorbidities. Future research hotspots are likely continue to focus on influencing factors, clinical research and prognosis.

The impact of sugar-sweetened beverages consumption on constipation: evidence from NHANES

BACKGROUND

The consumption of sugar-sweetened beverages (SSBs) has increased substantially over recent decades, raising concerns about its various physiological effects on bodily function. However, the relationship between SSBs intake and constipation remains insufficiently understood.

METHODS

Data from 7,979 participants sourced from the National Health and Nutrition Examination Survey (NHANES) were analyzed in this study. Dietary intake of SSBs was assessed using two 24-hour dietary recall interviews, and constipation was defined according to the Bristol Stool Form Scale (BSFS) Cards. We employed weighted logistic regression analysis to examine the relationship between SSBs consumption (quantified in grams and kilocalories) and the risk of constipation, while stratified and restricted cubic spline (RCS) analyses explored population variability.

RESULTS

After adjusting for all relevant variables, SSBs quantified in grams (SSBs-grams) (ORQ3 vs. Q1 = 1.419, 95% CI: 1.064-1.893, p = 0.019; p for trend = 0.02) and SSBs quantified in kilocalories (SSBs-kcal) (ORQ4 vs. Q1 = 1.567, 95% CI: 1.100-2.234, p = 0.015; p for trend = 0.016) showed a significant positive association with constipation. Furthermore, the weighted RCS and stratified analyses indicated that the association varied among subgroups, with a non-linear relationship between SSBs-kcal and constipation (SSBs-grams: p non-linear = 0.100, SSBs-kcal: p non-linear = 0.026).

CONCLUSIONS

Our findings indicated that increased SSBs consumption is associated with a higher risk of constipation. The results underscore the need for public health interventions aimed at reducing the intake of SSBs and promoting healthier alternatives.

Association between physical activity, trouble sleeping, and obesity among older Americans: a cross-sectional study based on NHANES data from 2007 to 2018

BACKGROUND

As the global population ages, obesity among older adults has become an increasing public health concern. Lifestyle factors, including physical activity (PA) and sleep, play a critical role in obesity prevention. These behaviors occur within a 24-hour cycle, yet research on the impact of different PA patterns, trouble sleeping, and their combination on obesity in older adults remains limited. This study aimed to explore: (1) the relationship between PA patterns, trouble sleeping, and obesity among older Americans; and (2) the combined effect of PA patterns and trouble sleeping on obesity in this population.

METHODS

A total of 10,891 participants aged 60 and older (55.0% female) from the National Health and Nutrition Examination Survey 2007-2018 were included. Trouble sleeping was assessed using the Sleep Disorder Questionnaire, and PA was measured using the Global Physical Activity Questionnaire. Body mass index (BMI) was calculated from objectively measured weight and height. Multivariate linear regression models were used to estimate the association between PA patterns, trouble sleeping, and BMI.

RESULTS

Compared to the inactive group, participants in the insufficiently active group (β = -0.75; 95% CI = -1.27 to -0.23; P = 0.005), weekend warrior group (β = -1.08; 95% CI = -1.88 to -0.28; P = 0.009), and regularly active group (β = -1.58; 95% CI = -2.02 to -1.14; P < 0.001) had a significant negative association with BMI. Participants with trouble sleeping exhibited a positive association with BMI compared to those without trouble sleeping (β = 0.39; 95% CI = 0.02 to 0.75; P = 0.040). Conversely, among participants with trouble sleeping, those who were regularly active exhibited a negative association with BMI (β = -0.56; 95% CI = -1.05 to -0.07; P = 0.027). Additionally, compared to sufficiently active group, both the inactive and insufficiently active groups exhibited a positive association with BMI, regardless of the presence of trouble sleeping.

CONCLUSION

Insufficient PA and trouble sleeping in older adults are positively associated with obesity. Engaging in either a weekend warrior or regular PA lifestyle is negatively associated with obesity. Furthermore, adopting a regularly active lifestyle may mitigate the negative impact of trouble sleeping on obesity. However, regardless of the presence of trouble sleeping, insufficient PA remains positively associated with obesity in older adults.

Gender difference in the association between composite dietary antioxidant index and all-cause mortality

Background

Existing studies on the association between the composite dietary antioxidant index (CDAI) and all-cause mortality are controversial. We aimed to analyze the association of CDAI with all-cause mortality, and determine the influence of gender on this association.

Methods

The data of adult participants (age ≥ 18) from the National Health and Nutrition Examination Survey (NHANES) cycles spanning 2001 to 2018 were analyzed. The NHANES-issued identifiers for participants enabled the linkage of data from the NHANES Public Use Linked Mortality File.

Results

The study encompassed a sample of 15,651 individuals. The mean CDAI was 0.52 ± 6.06. The restricted cubic spline revealed that the hazard ratio (HR) of all-cause mortality decreased significantly with increasing CDAI. However, this negative association existed only when the CDAI was less than 5. Multivariate Cox regression analysis showed that compared to the first CDAI quartile, the HR of all-cause mortality was significantly decreased in the third and fourth quartiles (both p < 0.001), and the p-value of the trend test was <0.001. In the subgroup analysis, a notably strong negative association between CDAI and the risk of all-cause mortality was only observed in men (p for interaction <0.001).

Conclusion

Higher CDAI is associated with a reduced risk of all-cause mortality exclusively in adult males, underscoring the substantial influence of gender on this relationship.

Association between diabetes prevalence and weekend warrior activity patterns

OBJECTIVE

To investigate the association between the Weekend Warrior (WW) pattern and diabetes prevalence in American adults.

STUDY DESIGN

Cross-sectional analysis of data from the 2007-2016 National Health and Nutrition Examination Survey (NHANES).

METHODS

We examined the relationship between four physical activity (PA) patterns-inactive, insufficiently active, WW, and regularly active-and diabetes prevalence. Multivariable logistic regression, marginal average population effects (MAPE), subgroup, and sensitivity analyses were performed to assess these associations. Odds ratios (ORs) and average marginal effects (AME), along with 95 % confidence intervals (CIs) were calculated.

RESULTS

Individuals engaging in the WW pattern (OR = 0.60, 95 % CI: 0.40 to 0.89, p = 0.013; AME = -0.05, 95 % CI: -0.09 to -0.02, p = 0.004) and the regularly active pattern (OR = 0.69, 95 % CI: 0.60 to 0.80, p < 0.001; AME = -0.04, 95 % CI: -0.06 to -0.03, p < 0.001) showed significantly lower diabetes prevalence than those classified as inactive. Compared to individuals classified as inactive, those categorized as insufficiently active demonstrated no significant difference in diabetes prevalence. No significant difference was observed between the WW and regularly active patterns (OR = 0.86, 95 % CI: 0.56 to 1.35, p = 0.5; AME = -0.01, 95 % CI: -0.06 to 0.03, p = 0.501). Subgroup interaction analyses revealed no significant effect modification (all p for interaction >0.05), and sensitivity analyses confirmed the robustness of these findings.

CONCLUSION

Both the WW and regularly active patterns are associated with a lower prevalence of diabetes compared with inactive individuals.

The prevalence and risk factors of sleep disturbances in community-dwelling older adults: a systematic review and meta-analysis

PURPOSE

Sleep disturbance is one of the most prevalent health issues among community-dwelling older adults. This systematic review aims to assess the prevalence of sleep disturbances among these adults living in the community and identify associated risk factors.

METHODS

A comprehensive literature search was performed using PubMed, Web of Science, Embase, and the Cochrane Library databases. We screened studies focusing on the prevalence of sleep disturbances in community-dwelling older adults (≥ 60 years). A random-effects model was used to calculate the pooled prevalence of sleep disturbances. Sensitivity and subgroup analyses were conducted to investigate sources of heterogeneity, and funnel plots were used to assess publication bias.

RESULTS

Our systematic review included 41 articles, encompassing a total sample of 71,607 participants from 13 countries. The pooled prevalence of sleep disturbances, measured by PSQI, was found to be 45% (95% CI: 40-50%). Notably, the prevalence of sleep disturbances was significantly higher among individuals aged 70 years and older (48%) compared to those aged 60 years and older (41%). Common risk factors for sleep disturbances included depression, advanced age, females, chronic diseases (hypertension, coronary heart disease, chronic obstructive pulmonary disease) and poor external support (poor social support and poor family relationships).

CONCLUSION

The findings highlight the necessity for comprehensive assessments and management strategies targeting this population with depression, advanced age, females, hypertension, coronary heart disease, chronic obstructive pulmonary disease, and poor external support while also underscoring the significance of healthcare planners and policymakers in enhancing sleep quality for older adults.

Association Between Triglyceride-Glucose Related Index and Endometriosis Varies According to Educational Level

BACKGROUND

The association between the triglyceride-glucose (TyG) level, its obesity-related derivatives, and the occurrence of endometriosis (EMS) remains ambiguous, particularly in individuals with higher levels of education. This study sought to explore the relationship between TyG, its obesity-related derivatives, and EMS across various educational backgrounds.

METHODS

This study utilized a substantial dataset obtained from four cycles of the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2006. To explore the relationship between TyG, its obesity-related derivatives, and EMS, we employed a variety of analytical methods, including multivariable logistic regression models, smooth curve fitting, threshold effect analysis, and subgroup analysis, which were applied to participants with varying educational levels.

RESULTS

Among the 2347 participants, 203 (8.65%) were diagnosed with EMS. In the overall population, only the TyG, TyG-waist-to-height ratio (TyG-WHtR), and TyG-waist circumference (TyG-WC) variables demonstrated a positive association with EMS. However, within the group with high educational attainment, TyG, TyG-WHtR, TyG-WC, and TyG-body mass index (TyG-BMI) all exhibited positive correlations with EMS. These associations remained robust after adjustment for multiple potential confounding variables. The subgroup analysis demonstrated that these associations were consistent across different subgroups (p > 0.05). Furthermore, both linear and nonlinear relationships were observed between TyG and its obesity-related derivatives and EMS, as evidenced by the smooth curve fittings and threshold effect analyses. In contrast, no significant associations were identified in the group with lower levels of education.

CONCLUSIONS

Our study suggests that there is variation in the association between TyG and its obesity-related derivatives and EMS across different educational levels, warranting further investigation. In individuals with higher education, elevated levels of TyG and its obesity-related derivatives were associated with a higher prevalence of EMS. Conversely, this correlation was not observed among those with lower educational levels.

Associations between body mass index, high-sensitivity C-reactive protein, and depressive symptoms: NHANES 2015-2016

Objective

Studies have shown associations between Body Mass Index (BMI), High-Sensitivity C-reactive protein (HSCRP), and depressive symptoms(DP). However, the complex relationship between them remains uncertain. The objective of this research is to examine the correlation between them in a substantial sample that is representative of the national level.

Methods

Our analysis was based on the 2015-2016National Health and Nutrition Examination Survey (NHANES).DP was measured by the Patient Health Questionnaire-9 (PHQ-9). Using multivariable logistic regression analysis and stratified analysis, we examined the relationship between BMI, HSCRP, and DP. We applied generalized additive models to explore the non-linear relationships among variables.

Results

This study included a total of 4834 participants. The results revealed that BMI (P=0.002) and HSCRP (P=0.008) were risk factors for DP. The relationship between BMI and DP (P=0.035), BMI and HSCRP (P<0.001) were non-linear. The nonlinear association between HSCRP and DP (P=0.031), BMI and DP (P=9e-04) is significant in females when stratified by gender. No nonlinear association was found between BMI and DP (P =0.677) and between HSCRP and DP (P =0.439) in males. The results of the interaction test reveal a significant interaction between HSCRP and gender.

Conclusions

Research has found both BMI and HSCRP are risk factors for DP and the relationship between them was non-linear. The nonlinear associations between BMI and DP, as well as between HSCRP and DP, are gender-dependent.

A predictive model for depression risk in individuals with hypertension: evidence from NHANES 2007-2020

OBJECTIVE

Hypertension increases the prevalence of depression to a certain extent and identification and diagnosis of depression frequently pose challenges for clinicians. The study aimed to construct and validate a scoring model predicting the prevalence of depression with hypertension.

METHODS

6124 individuals with hypertension were utilized from the 2007 to 2020 National Health and Nutrition Examination Survey database (NHANES), including 645 subjects that were assessed to have depressive symptoms, 390 in the development group and 255 in the validation group. Univariable and multivariable analyses were applied to analyze the impact of each parameter on depression with hypertension, resulting in establishment of a predictive model. Finally, the discriminability, calibration ability, and clinical efficacy of the model were verified for both the derivation set and validation set.

RESULTS

Ten variables comprised this model: age, gender, race, poverty to income ratio (PIR), smoke, sleep hours, exercise, diabetes, congestive heart failure, stroke. The area under the receiver operating characteristic curve for the derivation and validating sets was 0.790 and 0.723, respectively, which showed excellent discriminability. The model also fitted well with the actual prevalence of depression with hypertension in calibration and decision curve analysis (DCA) demonstrated that the depression model was practically useful.

CONCLUSION

This scoring model may provide an additional perspective for evaluating the underlying risk factors of depression for hypertensive individuals.

Association between the platelet/high-density lipoprotein cholesterol ratio and depression: A cross-sectional analysis in United States adults

BACKGROUND

The primary objective of this study was to elucidate the relationship between the platelet/high-density lipoprotein cholesterol ratio (PHR) and the risk of depression in adults in the US.

METHODS

We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2016. Depression was assessed using the PHQ-9 questionnaire. Weighted multivariable logistic regression models and restricted cubic spline (RCS) models were used to study the relationship between PHR and the risk of depression. Subgroup and interaction analyses were performed to further understand these associations.

RESULTS

A total of 21,454 participants were included in this study. After full adjustment, PHR was significantly positively correlated with depression (OR = 1.33, 95%CI: 1.03-1.73). When PHR was converted into a categorical variable based on quartiles (Q1-Q4), the highest quartile of PHR was associated with an increased risk of depression compared to the lowest reference group (OR = 1.22, 95%CI: 1.01-1.48). There was a linear dose-response relationship between PHR and the risk of depression (P-non-linear = 0.8038). The association remained significant in several subgroup analyses. However, the interaction test showed that none of the stratified variables were significant (all P for interaction >0.05).

LIMITATION

Using self-assessment scales and inability to assess causality.

CONCLUSION

This population-based cross-sectional study elucidated that PHR is significantly associated with an increased prevalence of depression in adults in the US.

The relationship between physical activity and sleep disorders in adolescents: a chain-mediated model of anxiety and mobile phone dependence

BACKGROUND

Adolescent sleep disorders have emerged as a significant global public health issue. This study aims to investigate the relationship between physical activity and sleep disorders in adolescents, and to further analyze the chain mediating effects of anxiety and mobile phone dependence, with the goal of providing empirical evidence for related clinical research.

METHODS

This cross-sectional study collected data through an offline questionnaire survey conducted in 2024. The survey assessed physical activity, sleep disorders, anxiety, and mobile phone dependence. Descriptive statistics and correlation analyses were utilized to construct a chain mediation model.

RESULTS

A total of 495 valid samples were obtained, with 227 girls (45.9%) and 268 boys (54.1%). The average age of the participants was 13.37 years (SD = 1.05). The results indicated significant negative correlations between physical activity and adolescent anxiety, mobile phone dependence, and sleep disorders. Anxiety and mobile phone dependence fully mediated the relationship between physical activity and sleep disorders.

CONCLUSION

This study provides further insight into the underlying mechanisms linking physical activity and sleep disorders in adolescents. Physical activity not only has a direct negative effect on sleep disorders but also indirectly predicts sleep disorders through its impact on anxiety and mobile phone dependence. It is recommended that families and schools encourage increased physical activity among adolescents, as it can reduce anxiety and mobile phone dependence, thereby alleviating sleep disorders.

Blood cadmium levels and overactive bladder in middle-aged and older adults in the United States: Insights from NHANES 2007-2020 data

Cadmium is a common environmental pollutant associated with various health risks. Its neurotoxic, muscle-damaging, and pro-inflammatory properties may be related to overactive bladder (OAB), though few studies have assessed its impact on urinary function. This study aimed to examine the potential link between cadmium exposure and OAB. Using data from the 2007-2020 National Health and Nutrition Examination Survey (NHANES), we analyzed adults aged 40 and older (n = 15,467) in a cross-sectional design. OAB was defined by the refined Overactive Bladder Symptom Score (OABSS). Weighted multivariate logistic regression examined the associations between blood cadmium levels and OAB and its components. Age and gender stratifications were performed, and restricted cubic splines (RCS) were used to explore non-linear associations between blood cadmium and OAB. Sensitivity analyses and co-exposure analyses with other pollutants were conducted to assess OAB definition stability, subgroup differences, and exposure collinearity. The prevalence of OAB was 26.2%. While blood cadmium showed a small, non-significant positive association with overall OAB, it was inversely associated with nocturia severity (OR = 0.85, 95% CI 0.74-0.98, p < 0.05). Blood cadmium was also linked to more severe urinary incontinence in the 50-59 age group and among non-Hispanic Black adults. A non-linear association between blood cadmium and OAB was observed (p for nonlinearity = 0.016, p < 0.05). In co-exposure analyses, cadmium remained a dominant and independent factor. These findings suggest that cadmium exposure may have a complex association with OAB and may relate differently to its various components. Further research is needed to explore these relationships.

Association of the number of pregnancies and births with cognitive performance in older postmenopausal women: a cross-sectional study

OBJECTIVE

Cognitive impairment in the elderly is a serious public health problem. However, the effect of the number of pregnancies and births in the early years of life on cognitive function in postmenopausal women remains controversial. This study aims to investigate the relationship between these two factors.

METHODS

We used the National Health and Nutrition Examination Survey 2011-2014 data on women aged ≥60 years. This study included sociodemographic data, history of estrogen use, and contraceptive use as confounding variables. The combined scores of the Consortium to Establish a Registry for Alzheimer's Disease Word Learning (CERAD-WL), delayed word recall (CERAD-DR), the Animal Fluency test (AF), and the Digit Symbol Substitution Test (DSST) were used to assess the cognitive performance of participants. Hierarchical multiple regression analysis explored the relationship between the number of pregnancies and births and cognitive function.

RESULTS

The study screened 1,259 postmenopausal women and found that 24.3% had low cognitive performance. The study found a significant increase in low cognitive performance among older adults, Mexican Americans, those with a lower education level and poverty-income ratio, those who were widowed, and those with diabetes and hypertension (P < 0.001). In the multiple regression analysis, the number of pregnancies remained a significant determinant of cognitive performance (B = -0.188, P < 0.001).

CONCLUSIONS

The number of pregnancies was associated with cognitive performance in a population of postmenopausal women in the United States. A lower number of pregnancies is associated with better cognitive performance.

Association between cardiometabolic index and kidney stones in US diabetic patients: NHANES 2007-2018

BACKGROUND

The cardiometabolic index (CMI), encompassing obesity and lipid metrics, is potentially linked to kidney stone prevalence in diabetic patients. However, studies on this association are sparse. This research evaluates CMI's impact on kidney stone occurrence in this group.

METHODS

Utilizing data from the 2007-2018 National Health and Nutrition Examination Survey, we explored the relationship between CMI and kidney stones in diabetic patients through multivariate logistic regression, generalized additive models, and smoothed curve fitting. Robustness checks included subgroup analyses and propensity score matching (PSM).

RESULTS

This study comprised 2714 participants in total, where the prevalence of kidney stones was found to be 16.82%. Using weighted multivariate logistic regression and fully adjusted models, it was revealed that elevated CMI levels are positively associated with an increased likelihood of developing kidney stones (OR = 1.17, 95% CI: 1.06, 1.30). Smooth curve fitting demonstrated that there was no non-linear relationship between CMI and kidney stones (log-likelihood ratio test P = 0.236). Subgroup analyses and interactions indicated that the association between CMI and kidney stone prevalence was notably stronger in individuals who were living with a partner /married and had a poverty income ratio (PIR) of 1.5 to less than 3.5 (P for interaction < 0.05). propensity score matching (PSM) further verified the robustness of our results.

CONCLUSION

Elevated CMI correlates with greater kidney stone prevalence in diabetic individuals, particularly those married or living with a partner and within certain economic statuses. This study supports the hypothesis linking CMI and kidney stones in U.S. diabetic population, suggesting a target demographic for preventive strategies.

The impact of Composite Dietary Antioxidant Index on the relationship between eczema and depression symptoms in US adults

Aims

The study aims to explore the associations of eczema, Composite Dietary Antioxidant Index (CDAI), with depression symptoms in adults based on the National Health and Nutrition Examination Surveys (NHANES) database.

Methods

In total, 3,402 participant data were extracted from the NHANES 2005-2006. The relationship between eczema, CDAI, and depression symptoms was explored by utilizing weighted univariate and multivariate logistic regression models, presenting as odds ratios (ORs) and 95% confidence intervals (CIs). The additive interaction between eczema, CDAI, and depression symptoms was measured by relative excess risk due to interaction (RERI) and the attributable proportion of interaction (AP). Subsequently, the associations of eczema, CDAI, with depression were also explored in different gender, body mass index (BMI), and smoking subgroups.

Results

Of the 3,402 participants included, the mean age was 46.76 (0.83) years old, and 174 (5.11%) participants had depression symptoms. In the adjusted model, both eczema (OR = 3.60, 95%CI: 2.39-5.40) and CDAI (OR = 1.97, 95%CI: 1.19-3.27) were associated with a higher prevalence of depression symptoms. Compared to the participants with high CDAI and no eczema, those participants with low CDAI (eczema: OR = 7.30, 95%CI: 4.73-11.26; non-eczema: OR = 1.84, 95%CI: 1.06-3.19) have higher odds of depression symptoms, no matter have eczema or not. When under low CDAI levels, eczema was associated with increased odds of depression symptoms (OR = 3.76, 95%CI: 2.34-6.03). When under low CDAI level, eczema was also related to elevated odds of depression symptoms in those males, females, BMI <25, BMI ≥25, non-smoking, and smoking.

Conclusion

CDAI could modulate the association of eczema with depression symptoms in adults.

Association between fibrosis-4 index and cognitive impairment in elderly patients with hypertension: A cross-sectional study

The fibrosis-4 index (FIB-4) is a noninvasive fibrosis test that is recommended for patients who are at risk of developing hepatic fibrosis. The aim of the study was to explore the correlation between FIB-4 index and the decline of cognitive function among older patients with hypertension. The study used a cross-sectional design to analyze data obtained from the NHANES 2011-2014. The significance of the FIB-4 index correlation with cognitive function in individuals over the age of 60 was evaluated via multivariate regression models. The nonlinear link was described and fitted smoothed curves. There were a total of 2039 participants in the study, and those with a higher FIB-4 index were more susceptible to developing cognitive decline. In the completely adjusted model, the association remained statistically significant between the FIB-4 index and poor cognitive function as measured by CERAD: Total Score (OR = 0.72, 0.57-0.91), Animal Fluency Score (OR = 0.66, 0.48-0.91), and Digit Symbol Score (OR = 0.36, 0.17-0.77). A nonlinear association was found between the FIB-4 and poor cognitive ability: Total Score, CERAD: Score Delayed Recall, Digit Symbol Score, and Animal Fluency Score. In elderly patients with hypertension, a high FIB-4 index is correlated with an increased prevalence of cognitive decline. Hence, the FIB-4 index could potentially serve as a valuable tool for determining individuals with hypertension who are susceptible to both liver-related complications and cognitive impairment.

Interaction between the systemic immune-inflammation index and trouble sleeping in nonalcoholic fatty liver disease: a cross-sectional study of the NHANES 2005-2018 data

BACKGROUND

The systemic immune-inflammation index (SII) and trouble sleeping are independent risk factors for nonalcoholic fatty liver disease (NAFLD). Nevertheless, studies investigating the combined effects of the SII and troubled sleeping on NAFLD are lacking. In this study, we investigated the independent relationships and interactions between trouble sleeping and the SII among patients with NAFLD.

METHODS

Data from seven survey cycles of the National Health and Nutrition Examination Survey (NHANES) (2005-2018) were analyzed. The SII was obtained by counting platelets, neutrophils, and lymphocytes. NAFLD was diagnosed using the US fatty liver index. Trouble sleeping was diagnosed using a sleep disorder questionnaire. The correlation between trouble sleeping and the SII in NAFLD was investigated using multiple regression analysis, subgroup stratification, interaction tests, and restricted cubic spline, and the presence or absence of additive or multiplicative interactions was determined. Additionally, mediation analyses were performed to explore the role of the SII in mediating the effects of trouble sleeping on NAFLD.

RESULTS

The survey included 10 963 participants. Multivariate logistic regression revealed that SII (OR: 1.21, 95% CI 1.08-1.35) and trouble sleeping (OR: 1.24, 95% CI 1.05-1.47) were positively correlated with NAFLD. For NAFLD, an additive but not multiplicative interaction was noted between the SII and trouble sleeping. The SII partially mediated the association between trouble sleeping and NAFLD, accounting for approximately 3.11% of the total effect (95% CI 0.01-0.05).

CONCLUSION

The SII and trouble sleeping were independently correlated with NAFLD risk. Furthermore, a combined effect may exist between SII and trouble sleeping, which increases the risk of NAFLD.

Association between platelet to high-density lipoprotein cholesterol ratio (PHR) and hypertension: evidence from NHANES 2005-2018

BACKGROUND

The Platelet to High-Density Lipoprotein cholesterol Ratio (PHR) is a novel indicator of inflammatory response and metabolic disorders, linked to various chronic diseases. This study aims to investigate the relationship between PHR and hypertension.

METHODS

Data from the National Health and Nutrition Examination Survey (NHANES), collected across seven consecutive cycles from 2005 to 2018, were analyzed. The dataset included participants' hypertension status as reported by a doctor, their use of antihypertensive medications, and the average of three blood pressure measurements to identify hypertensive adults, along with complete information for PHR calculation. PHR was calculated based on Platelet (PLT) count and High-Density Lipoprotein cholesterol (HDL-C) using the following formula: PHR = [PLT (1000 cells/µL) / HDL-C (mmol/L)]. A multivariable logistic regression model was employed to assess the association between PHR and hypertension, and subgroup analyses were conducted to explore potential influencing factors. Additionally, Restricted Cubic Spline (RCS) curves were applied for threshold effect analysis to describe nonlinear relationships.

RESULTS

Higher PHR was associated with an increased prevalence of hypertension. After adjusting for various covariates, including race, education level, Family Poverty Income Ratio (PIR), smoking, alcohol consumption, sleep disturbances, waist circumference, diabetes, coronary heart disease, angina, heart attack, and stroke, the results remained significant (OR = 1.36; 95% CI, 1.32, 1.41, P < 0.001). Participants with the highest PHR levels had a 104% higher risk of hypertension compared to those with the lowest PHR levels (OR = 2.04; 95% CI, 1.89, 2.21, P < 0.001).

CONCLUSION

Elevated PHR levels are strongly associated with an increased risk of hypertension. Specifically, when PHR is below 280, the risk of hypertension increases in proportion to PHR. This suggests that regular monitoring of PHR may help identify patients at risk of hypertension early, allowing for timely interventions to slow disease progression. Larger cohort studies are necessary to confirm these findings.

Association between Ward's triangle bone mineral density levels and abdominal aortic calcification: Data from the national health and nutrition examination survey 2013-2014

BACKGROUND & AIMS

Despite extensive research into the cardiovascular implications of abdominal aortic calcification (AAC), there is a scarcity of robust studies exploring its association with Ward's triangle bone mineral density (BMD). This study aimed to evaluate this relationship in a nationally representative sample and compare the predictive value with femoral neck BMD and total femur BMD.

METHODS

We conducted a cross-sectional analysis of 2013-2014 National Health and Nutrition Examination Survey (NHANES) data, utilizing a complex, stratified, multistage, cluster sampling design. BMD measurements at Ward's triangle, femoral neck, and total femur were assessed using DXA scans. AAC severity was defined by a Kauppila score of ≥5. Predictors of AAC-24 scores were identified through correlation and linear regression models. Stratified regression and restricted cubic splines were applied to explore subgroup and dose-response relationships.

RESULTS

Of the 2965 participants representing 116, 562, 500 individuals in the U.S., 11 % had severe AAC. Ward's triangle BMD showed a significant negative association with AAC-24 scores (β = -1.90, 95 % CI: -2.80 to -1.00, P < 0.002) and a reduced risk of severe AAC (OR = 0.85, 95 % CI: 0.76 to 0.95, P = 0.010). Non-linear associations were observed between Ward's triangle BMD and AAC outcomes. Ward's triangle BMD outperformed femoral neck and total femur BMD in predicting AAC.

CONCLUSIONS

Higher Ward's triangle BMD is linked to lower odds of severe AAC, highlighting its potential for improved early detection of AAC over femoral neck and total femur BMD. Healthcare providers should consider the implications of reduced Ward's triangle BMD for systemic atherosclerosis and recommend early AAC screening for enhanced cardiovascular risk management.

Construction and verification of the prediction model for risk of sleep disturbance in elderly patients with hypertension: a cross-sectional survey based on NHANES database from 2005 to 2018

OBJECTIVE

To construct and verify a risk prediction model for sleep disturbance in elderly patients with hypertension, aiming to offer guidance for sleep management in this demographic.

METHODS

A cohort of 6,708 elderly hypertensive patients from the NHANES database, spanning 2005 to 2018, met the inclusion criteria and were selected for this study. Participants were randomly assigned to a development group (n = 4,696) and a verification group (n = 2,012) in a 7:3 ratio. The occurrence of sleep disturbance was assessed across the subjects. Independent risk factors for sleep disturbance were analyzed using weighted multivariate logistic regression within the development group. A predictive model for sleep disturbance risk in elderly hypertensive patients was developed and verified using Stata 17.0. The model's predictive accuracy and stability were evaluated using the verification group's data.

RESULTS

Of the 6,708 subjects, 2,014 (30.02%) were identified with sleep disturbance, and the weighted prevalence of sleep disturbance among elderly hypertensive patients was 33.283%. Weighted multivariate logistic regression analysis in the development group revealed that six factors were independently associated with sleep disturbance: higher total depression scores, higher education level, asthma, overweight, arthritis, and work restriction (OR > 1 and P < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) for the nomogram prediction model was 0.709 in the development group and 0.707 in the verification group, indicating good discrimination ability. Brier scores for the nomogram model were 0.185 in the development group and 0.189 in the verification group, both below 0.25, suggesting good calibration. Decision Curve Analysis (DCA) determined that the nomogram's clinical net benefit was maximized when the threshold probability for sleep disturbance in elderly hypertensive patients was 0.13-0.67 in the development group and 0.14-0.61 in the verification group, highlighting the model's clinical utility.

LIMITATIONS

This study is not without its limitations, including issues with data collection, the absence of external validation, and the non-extrapolation of results.

CONCLUSION

The prevalence of sleep disturbance among elderly hypertensive patients stands at 33.283%. The nomogram model, based on identified risk factors for sleep disturbance in this population, has demonstrated good predictive efficiency and clinical relevance. It serves as a valuable tool to assist healthcare providers in identifying elderly hypertensive patients at high risk for sleep disturbance.

Association of health behaviors in life's essential 8 and hypertension in adolescents: a cross-sectional study from the NHANES database

BACKGROUND

Hypertension is a common condition during adolescence with increasing prevalence globally, alongside the epidemic of unhealthy lifestyles and obesity. Health behaviors have been shown to be associated with hypertension risk in adults. Life's essential 8 (LE8), as a comprehensive indicator to evaluate cardiovascular health (CVH), includes 4 health factors and 4 health behaviors. This study aims to evaluate the association between health behaviors defined in LE8 and hypertension among adolescents.

METHODS

Data of this study were extracted from the National Health and Nutrition Examination Surveys (NHANES) 2007-2018. Health behaviors of LE8 including diet, physical activity and tobacco smoke exposure. The outcome was the odd of hypertension in adolescents. The weighted univariate and multivariate logistic regression was unitized to explore the relationship between CVH score and hypertension in adolescents. Subgroup analysis and sensitivity analysis were further conducted to explore the association across different populations.

RESULTS

Totally 3,941 adolescents aged 12-17 years were included, with the mean aged of 14.48 ± 0.04 years. Of whom, 203 (5.15%) had hypertension. After adjusted all covariates, high CVH score was associated with the lower odds of hypertension (OR = 0.32, 95%CI: 0.17-0.61), especially in boys (OR = 0.23, 95%CI: 0.11-0.51) and adolescents with overweight/obesity (OR = 0.24, 95%CI: 0.10-0.56). Sensitivity analysis reported that the association between CVH score and the odds of hypertension was also robust after excluding self-reported hypertension and medication taking (OR = 0.37, 95%CI: 0.18-0.74).

CONCLUSION

A high CVH score, indicating a greater adherence of health behaviors, was associated with a reduced odds of hypertension, especially among boys and overweight/obesity adolescents. Large-scale prospective cohort studies are needed to further explore the association between health behaviors defined in LE8 and hypertension among adolescents.

Expose to volatile organic compounds is associated with increased risk of depression: A cross-sectional study

With increasing prevalence rate of depression by years, more attention has been paid to the influence of environmental pollutants on depression, but relationship between exposure to volatile organic compounds (VOCs) and depression is rarely studied. Therefore, this cross-sectional study use the National Center for Health Statistics (NHANES) database (2013-2016 years) to explore association between exposure to multiple VOCs and depression in general population. Multiple linear and logistic regression models were used to analyze the association between urinary VOC metabolism (mVOCs) and depression. To further analyze effect of multiple mVOCs mixed exposure, Bayesian kernel machine regression (BKMR) models were performed. A total of 3240 participants and 16 mVOCs were included in the analysis. Results showed that 10 mVOCs exposure were positively correlated with depression by multiple linear and logistic regression models, especially CYMA and MHBMA3, which also showed significant positive association with depression in BKMR model. Mixed exposure of multiple mVOCs was significantly positively correlated with depression. Gender differences were existed in effects of some VOCs concentrations on depression. AAMA, CYMA and MA had significant positive correlations with depression by women, and DHBMA had significant positive correlations with depression by men. Hence, this study showed that exposing to VOCs might have negative impacts on depression, and impact of CYMA and MHBMA3 on depression may be more evident, which provide new ideas for prevention and control of depression. But further research and exploration are needed to clarify the mechanism and influence factors of this relationship, to demonstrate the reliability of these relationship.

Exploring the heart-brain and brain-heart axes: Insights from a bidirectional Mendelian randomization study on brain cortical structure and cardiovascular disease

INTRODUCTION

The bidirectional relationship between the brain cortex and cardiovascular diseases (CVDs) remains inadequately explored.

METHODS

This study used bidirectional Mendelian randomization (MR) analysis to explore the interactions between nine phenotypes associated with hypertension, heart failure, atrial fibrillation (AF), and coronary heart disease (CHD), and brain cortex measurements. These measurements included total surface area (SA), average thickness (TH), and the SA and TH of 34 regions defined by the Desikan-Killiany atlas. The nine traits were obtained from sources such as the UK Biobank and FinnGen, etc., while MRI-derived traits of cortical structure were sourced from the ENIGMA Consortium. The primary estimate was obtained using the inverse-variance weighted approach. A false discovery rate adjustment was applied to the p-values (resulting in q-values) in the analyses of regional cortical structures.

RESULTS

A total of 1,260 two-sample MR analyses were conducted. Existing CHD demonstrated an influence on the SA of the banks of the superior temporal sulcus (bankssts) (q=0.018) and the superior frontal lobe (q=0.018), while hypertension was associated with changes in the TH of the lateral occipital region (q=0.02). Regarding the effects of the brain cortex on CVD incidence, total SA was significantly associated with the risk of CHD. Additionally, 16 and 3 regions exhibited significant effects on blood pressure and AF risk, respectively (q<0.05). These regions were primarily located in the frontal, temporal, and cingulate areas, which are associated with cognitive function and mood regulation.

CONCLUSION

The detection of cortical changes through MRI could aid in screening for potential neuropsychiatric disorders in individuals with established CVD. Moreover, abnormalities in cortical structure may predict future CVD risk, offering new insights for prevention and treatment strategies.

Association between sleep quality, depressive symptoms, and suicidal ideation in college students

Suicide among college students is a challenging problem globally. Yet, the association between sleep quality, depressive symptoms, and suicidal ideation remains unclear. This study aims to understand if depressive symptoms mediate the relationship between sleep quality and suicide ideation and whether the interaction between depressive symptoms and sleep quality on suicidal ideation is additive. A total of 1182 college students were recruited, and sleep quality, depressive symptoms, and suicidal ideation were assessed using questionnaires. Univariate analysis, logistic regression analysis, linear regression models, and the Sobel test were performed. The results showed that, among college students, poor sleep quality was positively associated with suicidal ideation, and the association was mediated through depressive symptoms. Moreover, there was a significant additive interaction between poor sleep quality and depressive symptoms on suicidal ideation. These findings suggest that, in the process of preventing and treating suicidal ideation in college students with sleep disorders, we should focus on the evaluation and intervention of depressive symptoms and adopt multidisciplinary team interventions for college students with sleep disorders and depression.

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.

The impact of alcohol consumption on the relationship between depression and chronic diarrhea: a cross-sectional study analysis on NHANES (2005-2010)

Background

Alcohol consumption, depression, and chronic diarrhea are all public health issues of concern, with irreversible consequences for individual health and significant economic burdens on health care systems. Previous studies have shown that depression increases the risk of developing chronic diarrhea, but few studies have explored whether alcohol consumption has an effect on the relationship between depression and chronic diarrhea.

Objective

To explore the effect of alcohol consumption on the relationship between depression and chronic diarrhea.

Methods

12,538 adults (≥20 years) in NHANES from 2005-2010 were analyzed. Participants were stratified according to drinking status, and differences between the risk of depression and chronic diarrhea among participants who drank alcohol or not were assessed using multiple regression analysis and likelihood ratio tests.

Results

In this cross sectional, after adding possible confounders, the prevalence of depression with chronic diarrhea was higher in the drinking population than in the non-drinking population (OR,2.34, 95%CI:1.84-2.98 and 1.26, 95%CI:0.85-1.86), with a likelihood ratio test of P=0.024.

Conclusion

Our findings suggest that there is a significant association between depression and chronic diarrhea and that alcohol consumption may increase the correlation between depression and chronic diarrhea. However, these findings require further prospective studies to provide more evidence.

Association between brominated flame retardants (PBDEs and PBB153) exposure and hypertension in U.S. adults: results from NHANES 2005-2016

BACKGROUND

Brominated Flame Retardants (BFRs) have attracted widespread concern due to their environmental persistence and potential toxicity. This study aims to examine the association between BFRs exposure and hypertension.

METHODS

We used data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005 to 2016 for the cross-sectional analysis. To evaluate the individual and combined impacts of BFRs exposure on hypertension, we utilized multivariate models, including generalized additive models, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models.

RESULTS

9882 individuals (48% male) aged ≥ 20 were included in the final analysis, of whom 4114 had hypertension. After controlling for potential covariates, higher serum concentrations of PBDE100 (OR: 1.26; 95% CI: 1.01, 1.57) and PBDE153 (OR: 1.50; 95% CI: 1.18, 1.88) were significantly associated with hypertension. A nonlinear relationship between PBDE28 and hypertension was observed (P = 0.03). Moreover, BFRs mixture were positively associated with the prevalence of hypertension in both the WQS (β:1.09; 95% CI: 1.02, 1.17; P = 0.02) and BKMR models.

CONCLUSION

Our study suggested that BFRs exposure is positively associated with hypertension in the general population. To confirm this association and elucidate the mechanisms, further research is required.

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

BACKGROUND

Hypertension, sleep disorders, and depression represent notable public health issues, and their interconnected nature has long been acknowledged. The objective of this study is to explore the interplay between sleep disorders and depression in the context of hypertension.

METHODS

This cross-sectional study involved 42,143 participants aged 18 and above from the NHANES database across seven survey cycles between 2005 and 2018. After excluding those with missing data on depression, sleep disorders, and hypertension, as well as incomplete main variables, 33,383 participants remained. We used weighted logistic regression to examine the relationship between sleep disorders, depression, and hypertension. Additionally, we assessed the interaction between sleep disorders and depression on hypertension using both multiplicative and additive approaches to quantify their combined effect.

RESULTS

Compared to individuals without sleep disorders, those with sleep disorders have an increased risk of hypertension (OR = 1.51, 95% CI: 1.37-1.67). Furthermore, individuals with depression experience a significantly higher risk of hypertension compared to those with sleep disorders alone (OR = 2.34, 95% CI: 1.95-2.80). Our study reveals a positive interaction between sleep disorders and depression in relation to hypertension risk (OR = 1.07, 95% CI: 1.02-1.13). In addition, we observed the quantitative additive interaction indicators (RERI = 0.73, 95% CI: 0.56 ~ 0.92; API = 0.31, 95% CI: 0.11 ~ 0.46; SI = 2.19, 95% CI: 1.08-3.46) influencing hypertension risk. Furthermore, our research also identified that individuals with less than 7 h of sleep, a sleep latency period between 5 and 30 min, or a latency period exceeding 30 min experience a significantly increased risk of hypertension.

CONCLUSIONS

Our research uncovered separate links between sleep disorders, depression, and hypertension prevalence. Moreover, we identified an interaction between depression and sleep disorders in hypertension prevalence. Enhancing mental well-being and tackling sleep disorders could help prevent and manage hypertension. Yet, more investigation is required to establish causation and clarify mechanisms.

The association of physical activity and sedentary behavior with depression in US adults: NHANES 2007-2018

Objectives

Depression is largely preventable, and strategies that can effectively suppress its development are imperative. We aimed to examine whether physical activity and sedentary behavior were associated with depression and explore the possible mediatory role of complete blood count in this association.

Methods

In this cross-sectional study, data were integrated from the National Health and Nutrition Examination Study (2007-2018). Depression was defined using the Patient Health Questionnaire-9. The risk for depression, expressed as odds ratio (OR) and 95% confidence interval (CI), was quantified by survey-weighted logistic regression analyses.

Results

A total of 31,204 respondents were analyzed. Significance was identified for all, except walking or bicycling per week, types of physical activity, and sedentary behavior. Per 1 standard deviation (SD) increment in metabolic equivalent of task (MET) of weekly vigorous recreational physical activity was associated with 31.3% decreased depression risk (adjusted OR: 0.687, 95% CI: 0.5663-0.840). Per 1 SD increment in sitting time can increase depression risk by 22.4% (adjusted OR: 1.224, 95% CI: 1.131-1.325). In subsidiary analyses, the association with depression was reinforced in respondents aged ≤65 years and those overweight or obese. Mediation analyses revealed significant effects for red blood cell (RBC) on total MET (19.4%) and moderate work-related physical activity (MWPA) (22.0%), and for red cell distribution wide (RCDW) on vigorous work-related physical activity (17.7%), moderate work-related physical activity (13.1%), total MET (11.2%), and sitting time (16.4%) (p < 0.01).

Conclusion

Our findings indicate that more physical activity and less sitting time were associated with a lower likelihood of having depression among US adults, and this association was probably mediated by RBC and RCDW.

The Association between Autism Spectrum Disorder and Precocious Puberty: Considering Effect Modification by Sex and Neuropsychiatric Comorbidities

Limited knowledge is available about the association between autistic spectrum disorder (ASD) and precocious puberty. Our study examined the association between the two medical conditions and effect modification by sex and neuropsychiatric comorbidities in a nationwide population. To compare the risk of precocious puberty between ASD and non-ASD cases, we conducted a Cox regression analysis using ASD as the exposure and time to precocious puberty as the outcome. We adjusted for sex, attention-deficit/hyperactivity disorder (ADHD), tic disorder, obsessive-compulsive disorder (OCD), anxiety disorder, intellectual disability, and epilepsy. We performed a moderation analysis to examine the potential moderating effects of sex and comorbidities. Patients with ASD were prone to have precocious puberty, with an adjusted hazard ratio (aHR) of 1.80 (95% CI: 1.61-2.01). For effect modification, sex, specifically females, moderated the association between ASD and precocious puberty, with a relative excess risk due to interaction (RERI) of 7.35 (95% CI 4.90-9.80). No significant effect modification was found for any of the comorbidities within the scope of additive effect modification. We found that patients with ASD were prone to precocious puberty, regardless of sex or comorbid neuropsychiatric disorders. Girls with ASD are at a particularly higher risk of developing precocious puberty.

Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health

Background

EPs pose significant challenges to individual health and quality of life, attracting attention in public health as a risk factor for diminished quality of life and healthy life expectancy in middle-aged and older adult populations. Therefore, in the context of global aging, meticulous exploration of the factors behind emotional issues becomes paramount. Whether ADL can serve as a potential marker for EPs remains unclear. This study aims to provide new evidence for ADL as an early predictor of EPs through statistical analysis and validation using machine learning algorithms.

Methods

Data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) national baseline survey, comprising 9,766 samples aged 45 and above, were utilized. ADL was assessed using the BI, while the presence of EPs was evaluated based on the record of "Diagnosed with Emotional Problems by a Doctor" in CHARLS data. Statistical analyses including independent samples t-test, chi-square test, Pearson correlation analysis, and multiple linear regression were conducted using SPSS 25.0. Machine learning algorithms, including Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR), were implemented using Python 3.10.2.

Results

Population demographic analysis revealed a significantly lower average BI score of 65.044 in the "Diagnosed with Emotional Problems by a Doctor" group compared to 85.128 in the "Not diagnosed with Emotional Problems by a Doctor" group. Pearson correlation analysis indicated a significant negative correlation between ADL and EPs (r = -0.165, p < 0.001). Iterative analysis using stratified multiple linear regression across three different models demonstrated the persistent statistical significance of the negative correlation between ADL and EPs (B = -0.002, β = -0.186, t = -16.476, 95% CI = -0.002, -0.001, p = 0.000), confirming its stability. Machine learning algorithms validated our findings from statistical analysis, confirming the predictive accuracy of ADL for EPs. The area under the curve (AUC) for the three models were SVM-AUC = 0.700, DT-AUC = 0.742, and LR-AUC = 0.711. In experiments using other covariates and other covariates + BI, the overall prediction level of machine learning algorithms improved after adding BI, emphasizing the positive effect of ADL on EPs prediction.

Conclusion

This study, employing various statistical methods, identified a negative correlation between ADL and EPs, with machine learning algorithms confirming this finding. Impaired ADL increases susceptibility to EPs.

Association between cardiometabolic index and depression: National Health and Nutrition Examination Survey (NHANES) 2011-2014

BACKGROUND

Emerging evidence suggests a common pathophysiological basis for metabolic disorders and mental diseases. Despite the existence of reports suggesting a strong connection between dyslipidemia and depression, a comprehensive and reliable indicator to identify depression is still lacking. Cardiometabolic index (CMI) is an integrated index calculated from three vital metabolic indicators, including triglyceride (TG), high-density lipoprotein cholesterol (HDLC) and waist height ratio (WHtR).

OBJECTIVE

This study aims to explore the association between CMI and depression.

METHODS

Cross-sectional data of participants with complete information of CMI, depression, and other covariates were obtained from the National Health and Nutrition Examination Survey (NHANES). Weighted student's t-test and Chi-square test were used to identify the differences between two groups. Weighted multivariate logistic regression model, restricted cubic spline (RCS) regression analysis, subgroup analysis and interaction tests were conducted to explore the association between CMI and depression. Receiver operating curve (ROC) analysis and area under the curve (AUC) were also utilized to evaluate the performance of CMI in identifying depression.

RESULTS

A positive correlation between CMI and depression was observed in 3794 participants included in the study, which was further confirmed to be non-linear via RCS regression analysis, with two significant inflection points being identified, including 0.9522 and 1.58. In the crude or adjusted models, individuals with a CMI level ≥ 0.9522 exhibited remarkably increased risk for developing depression. CMI got an AUC of 0.748 in identifying depression. Subgroup analyses and interaction tests indicate that the association between CMI and depression remained consistent across different subgroups and was not modified by other covariates except drinking. Those who are current drinkers and with a high CMI are more susceptible to suffer depression.

CONCLUSIONS

An elevated CMI is linked to increased risk for depression. Addressing dyslipidemia and improving lipid levels may potentially lower the risk for depression.

Associations between sleep duration, sleep disturbance and cardiovascular disease biomarkers among adults in the United States

BACKGROUND

Sleep problems are associated with abnormal cardiovascular biomarkers and an increased risk of cardiovascular diseases (CVDs). However, studies investigating associations between sleep problems and CVD biomarkers have reported conflicting findings. This study examined the associations between sleep problems and CVD biomarkers in the United States.

METHODS

Data were from the National Health and Nutrition Examination Survey (NHANES) (2007-2018) and analyses were restricted to adults ≥ 20 years (n = 23,749). CVD biomarkers [C-reactive Protein (CRP), low-density lipoproteins, high-density lipoproteins (HDL), triglycerides, insulin, glycosylated hemoglobin (HbA1c), and fasting blood glucose] were categorized as abnormal or normal using standardized cut-off points. Sleep problems were assessed by sleep duration (short [≤ 6 h], long [≥ 9 h], and recommended [> 6 to < 9 h) and self-reported sleep disturbance (yes, no). Multivariable logistic regression models explored the associations between sleep duration, sleep disturbance, and CVD biomarkers adjusting for sociodemographic characteristics and lifestyle behaviors.

RESULTS

The mean sleep duration was 7.1 ± 1.5 h and 25.1% of participants reported sleep disturbances. Compared to participants with the recommended sleep duration, those with short sleep duration had higher odds of abnormal levels of HDL (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI] = 1.05-1.39), CRP (aOR = 3.08, 95% CI = 1.18-8.05), HbA1c (aOR = 1.25, 95% CI = 1.05-1.49), and insulin (aOR = 1.24, 95% CI = 1.03-1.51). Long sleep duration was associated with increased odds of abnormal CRP (aOR = 6.12, 95% CI = 2.19-17.15), HbA1c (aOR = 1.54, 95% CI = 1.09-2.17), and blood glucose levels (aOR = 1.45, 95% CI = 1.07-1.95). Sleep disturbance predicted abnormal triglyceride (aOR = 1.18, 95% CI = 1.01-1.37) and blood glucose levels (aOR = 1.24, 95% CI = 1.04-1.49).

CONCLUSION

Short and long sleep durations were positively associated with abnormal CRP, HDL, HbA1c, blood glucose, and insulin levels, while sleep disturbance was associated with abnormal triglyceride and blood glucose levels. Since sleep is a modifiable factor, adopting healthy sleeping habits may create a balanced metabolism and reduce the risk of developing a CVD. Our study may provide insights into the relationship between sleep duration, sleep disturbance, and CVD risk.

Association between systemic immunity-inflammation index and hypertension in US adults from NHANES 1999-2018

Hypertension is a disease closely related to inflammation, and the systemic immunity-inflammation index (SII) is a new and easily detectable inflammatory marker. We aimed to investigate the association between SII and hypertension risk in a adult population in the US. We utilized data from the National Health and Nutrition Examination Survey spanning from 1999 to 2018, incorporating comprehensive information from adults reporting hypertension. This included details on blood pressure monitoring, complete blood cell counts, and standard biochemical results. The SII was computed as the platelet count multiplied by the neutrophil count divided by the lymphocyte count. We employed a weighted multivariate logistic regression model to examine the correlation between SII and hypertension. Subgroup analyses were conducted to explore potential influencing factors. Furthermore, smooth curve fitting and two-piecewise logistic regression analysis were employed to describe non-linear relationships and identify inflection points. This population-based study involved 44,070 adults aged 20-85 years. Following Ln-transformation of the SII, multivariable logistic regression revealed that, in a fully adjusted model, participants in the highest quartile of Ln(SII) had a 12% increased risk of hypertension compared to those in the lowest quartile, which was statistically significant (OR:1.12; 95% CI 1.01, 1.24; P < 0.001), with a P for trend = 0.019. Subgroup analysis indicated no significant interactions between Ln(SII) and specific subgroups except for the body mass index subgroup (all P for interaction > 0.05). Additionally, the association between Ln(SII) and hypertension displayed a U-shaped curve, with an inflection point at 5.89 (1000 cells/μl). Based on this research result, we found a U-shaped correlation between elevated SII levels and hypertension risk in American adults, with a inflection point of 5.89 (1000 cells)/μl). To validate these findings, larger scale prospective surveys are needed to support the results of this study and investigate potential mechanisms.

Objective sleep characteristics and hypertension: a community-based cohort study

Objective

The link between sleep quality and hypertension risk is well-established. However, research on the specific dose-relationship between objective sleep characteristics and hypertension incidence remains limited. This study aims to explore the dose-relationship association between objective sleep characteristics and hypertension incidence.

Methods

A community-based prospective cohort study design was employed using data from the Sleep Heart Health Study (SHHS). A total of 2,460 individuals were included in the study, of which 780 had hypertension. Baseline personal characteristics and medical history were collected. Objective sleep characteristics were obtained through polysomnography (PSG). Multivariate logistic regression models were utilized for analysis. Restricted cubic splines (RCS) were used to examine dose-relationship associations.

Results

After adjusting for covariates, the percentage of total sleep duration in stage 2 (N2%) was positively associated with hypertension incidence, while the N3% was negatively associated with hypertension incidence Odds ratio (OR) = 1.009, 95% confidence interval (CI) [1.001, 1.018], P = 0.037; OR = 0.987, 95% CI: [0.979, 0.995], P = 0.028, respectively. For every 10% increase in N2 sleep, the risk of developing hypertension increases by 9%, while a 3% decrease in N3 sleep corresponds to a 0.1% increase in the incidence of hypertension. In the subgroup of non-depression, a positive association between N2% and hypertension was significant statistically (OR = 1.012, 95%CI, 1.002, 1.021, P = 0.013, Pinteraction = 0.013). RCS demonstrated that the risk of developing hypertension was lower when N2% ranged from 38% to 58% and rapidly increased thereafter (P = 0.002, non-linear P = 0.040). The lowest risk for hypertension incidence risk of N3% occurring at 25%, and a significant increase below 15% or above 40% (P = 0.001, non-linear P = 0.008).

Conclusions

There's a negative association between N3% and the incidence of hypertension, and a positive association between N2% and the incidence of hypertension, particularly among non-depression individuals. These associations exhibit strong non-linear dose-response relationships.

Systemic inflammation mediates the association between environmental tobacco smoke and depressive symptoms: A cross-sectional study of NHANES 2009-2018

BACKGROUND

Depression is associated with both environmental tobacco smoke (ETS) and inflammation. However, whether systemic inflammation mediates the ETS-depression relationship is unclear.

METHODS

We analyzed 19,612 participants from the 2009-2018 National Health and Nutrition Examination Survey (representing approximately 206,284,711 USA individuals), utilizing data of depressive symptoms (assessed by Patient Health Questionnaire-9), blood cotinine level (an ETS biomarker), dietary inflammatory index (DII, assessed by 24-h dietary recall) and inflammation, represented by immune-inflammation index (SII) and systemic inflammation response index (SIRI).

RESULTS

Weighted multivariable logistic regression showed that a higher blood cotinine level is significantly associated with a higher depressive symptoms risk (OR = 1.79, 1.35-2.38). After adjusting for covariates, the effect in smokers (OR = 1.220, 95 % CI: 1.140-1.309) is larger than that in non-smokers (OR = 1.150, 95 % CI: 1.009-1.318). Compared to the lowest level, depressive symptoms risks in participants with the highest level of SII, SIRI and DII are 19 % (OR = 1.19, 1.05-1.35), 15 % (OR = 1.15, 1.01-1.31) and 88 % (OR = 1.88, 1.48-2.39) higher, respectively. Weighted linear regression demonstrated positive correlations of SII (β = 0.004, 0.001-0.006), SIRI (β = 0.009, 0.005-0.012) and DII (β = 0.213, 0.187-0.240) with blood cotinine level. Restricted cubic splines model showed a linear dose-response relationship between blood cotinine and depressive symptoms (Pnon-linear = 0.410), with decreasing risk for lower DII. And SII and SIRI respectively mediate 0.21 % and 0.1 % of the association between blood cotinine and depressive symptoms.

LIMITATION

Cross-sectional design, and lack of medication data for depression.

CONCLUSIONS

Positive association of ETS (blood cotinine) with depressive symptoms risk is partly mediated by systemic inflammation, and anti-inflammatory diet could be beneficial.

Association between sleep duration and depression in menopausal women: a population-based study

Aims

This research investigated menopausal women older than 50 years to find whether there were any independent relationships between the duration of sleep they got and their prevalence of depression.

Methods

National Health and Nutrition Examination Survey (NHANES) datasets from 2011-2020 were utilized in a cross-sectional study. Using multivariate linear regression models, the linear relationship between sleep duration and depression in menopausal women was investigated. Fitted smoothing curves and thresholds impact evaluation were used to investigate the nonlinear relationship. Then, subgroup analyses were performed according to smoking, drinking alcohol, diabetes, hypertension, heart disease, and moderate activities.

Results

This population-based study included a total of 3,897 menopausal women (mean age 65.47 ± 9.06 years) aged≥50 years; 3,159 had a depression score <10, and 738 had a depression score≥10. After controlling for all covariates, the prevalence of depression was 17% higher among participants with short sleep duration [OR=1.17, 95%CI=(0.65, 1.70), P<0.0001] and 86% [OR=1.86, 95%CI=(1.05, 2.66), P<0.0001] compared to participants with normal sleep duration. In subgroup analyses stratified by smoking and diabetes, the sleep duration and depression scores of non-smokers [β=-0.18, 95%CI= (-0.33, -0.02), P=0.0241] and diabetics were independently negatively correlated [β=-0.32, 95%CI= (-0.63, -0.01), P=0.0416]. Using a two-segment linear regression model, we discovered a U-shaped relationship between sleep duration and depression scores with an inflection point of 7.5 hours. Less than 7.5 hours of sleep was associated with an increased risk of developing depression [β=-0.81, 95%CI= (-1.05, -0.57), P<0.001]. However, sleeping more than 7.5 hours per night increased the risk of depression considerably [β=0.80, 95%CI= (0.51, 1.08), P<0.001].

Conclusions

Depression is associated with sleep duration in menopausal women. Insufficient or excessive sleep may increase the risk of depression in menopausal women.

The mediating effect of sleep disturbance on the association between hypertension and depression: a national data analysis

BACKGROUND

Sleep disturbance is a common among people with hypertension. However, the mediating role of sleep disturbance in the association between hypertension and depression remains unclear. This study aims to investigate the mediating role of sleep disturbance in the association between hypertension and depression.

MATERIALS AND METHODS

This was cross-sectional study. The data were derived from the Indonesian Family Life Survey Fifth Wave (2014-2015). We include a total of 19,138 adults' participants with age range from 18 to 65 years old who completed response on the variable of hypertension, sleep disturbance, and depression. The mediating model analysis was processed using the PROCESS macro ins SPSS from Hayes model.

RESULTS

Depression was reported by 22% of total respondents. The group with hypertension showed a substantially higher prevalence of depression than non-hypertension group (P < 0.001). Hypertension had a significant overall effect on depression (β = 0.682; 95%CI 0.489 to 0.875, P < 0.001). The direct effect of hypertension on depression was significant (β = 0.418; 95%CI 0.244 to 0.592, P < 0.001) and the indirect effect that mediated by sleep disturbance was also significant (β = 0.264, 95%CI 0.174 to 0.356, P < 0.001). It is worth noting that sleep disturbance partially mediated the association between hypertension and depression.

CONCLUSION

The findings of this study indicated that sleep disturbance contributed to the etiology of depression and hypertension in adult populations. Nurses should be involved in managing sleep disturbances, such as using behavioral therapy, as it may serve as both a treatment and primary prevention measure for depression and hypertension.

The effect of a neonatal sleep intervention on maternal postpartum hypertension: a randomized trial

BACKGROUND

In nonpregnant adults, poor sleep is associated with higher blood pressure. Poor sleep is common in the postpartum period and is often attributed to infant caretaking needs. However, its effects on cardiovascular health in individuals with a hypertensive disorder of pregnancy are unknown.

OBJECTIVE

This study aimed to determine the effect of a neonatal sleep intervention on maternal postpartum blood pressure in individuals with a hypertensive disorder of pregnancy.

STUDY DESIGN

In this single-institution pilot randomized controlled trial from July 2021 to March 2022, 110 individuals with a hypertensive disorder of pregnancy were randomized to receive a neonatal sleep intervention (SNOO responsive bassinet) plus usual care of safe sleep education (n=54) or usual care alone (n=56). Remote follow-up visits were conducted at 1 week, 6 weeks, and 4 months after delivery and involved blood pressure and weights, sleep and mood questionnaires, and self-reported infant and maternal sleep logs. Based on institutional data, the sample size had 80% power to detect a 4.5-mm Hg difference in the primary outcome of mean arterial pressure at 6 weeks after delivery.

RESULTS

Baseline characteristics were similar between the arms. At 1 week after delivery, the intervention arm had lower mean arterial pressure and less antihypertensive medication use than the control arm (99±10 vs 103±7 mm Hg [P=.04] and 23% vs 35% [P=.15], respectively). At 6 weeks after delivery, mean arterial pressure was similar between arms (93±8 vs 94±8 mm Hg; P=.54), but there was a lower rate of antihypertensive use in the intervention arm (15% vs 26%; P=.19). Scores from maternal sleep and mood questionnaires at 6 weeks after delivery and self-reported infant and maternal sleep duration at 6 weeks and 4 months after delivery were similar between arms (P>.05).

CONCLUSION

The SNOO responsive bassinet as a neonatal sleep intervention did not result in improved mean arterial pressure at 6 weeks after delivery after hypertensive disorders of pregnancy.

Exploring the connection between caffeine intake and constipation: a cross-sectional study using national health and nutrition examination survey data

BACKGROUND

Caffeine has been reported to increase gastrointestinal motility and change intestinal microbiota. Constipation may be caused by colonic motor dysfunction and colonic microbiomeis disturbances. In this study, we aimed to explore the association between caffeine intake and constipation.

METHODS

This was a cross-sectional study based on the National Health and Nutrition Examination Survey (NHANES). Caffeine intake was assessed using 24-h dietary recall method, and constipation was defined based on stool consistency or stool frequency. Logistic regression analysis was used to assess the association between caffeine intake and constipation, and results were expressed as odds ratio (OR) with 95% confidence intervals (95%CI). Subgroup analysis was performed based on age.

RESULTS

A total of 13,816 participants were finally included for analysis. After adjusting potential confounders, high intake of caffeine was found to be associated with the low odds of constipation (Q3: OR = 0.60, 95%CI: 0.49-0.74; Q4: OR = 0.77, 95%CI: 0.59-0.99; Q5: OR = 0.72, 95%CI: 0.56-0.92). The similar association was found in young people and middle-age people (P < 0.05).

CONCLUSION

High caffeine intake was associated with the low odds of constipation. Our finding indicated that individuals should develop consciousness and habit of consuming caffeinated foods and drinks to prevent and relief the constipation.

A novel nomogram for predicting risk of hypertension in US adults with periodontitis: National Health and Nutrition Examination Survey (NHANES) 2009-2014

The goal of our study was to create a nomogram to predict the risk of developing hypertension in patients with periodontitis. Our study used data from a total of 3196 subjects from the National Health and Nutrition Examination Survey 2009 to 2014 who had ever been diagnosed with periodontitis. The data set was randomly divided into a training set and a validation set according to a 7:3 ratio. The data from the training set was utilized to build the prediction model, while the validation set were used to validate the model. To identify the risk variables, stepwise regression was used to perform successive univariate and multivariate logistic regression analysis. The predictive ability of the nomogram model was evaluated using receiver operating characteristic curve. Calibration plots were used to assess the consistency of the prediction model. The clinical value of the model was evaluated using decision curve analysis and clinical impact curve. A nomogram for the risk of hypertension in subjects with periodontitis was constructed in accordance with the 8 predictors identified in this study. The areas under the receiver operating characteristic curve values for the training set and validation set were 0.922 (95% confidence interval: 0.911-0.933) and 0.918 (95% confidence interval: 0.900-0.935), respectively, indicating excellent discrimination. The decision curve analysis and clinical impact curve suggested that the model has significant clinical applications, and the calibration plots of the training set and validation set demonstrated good consistency. The nomogram can effectively predict the risk of hypertension in patients with periodontitis and help clinicians make better clinical decisions.

Sleep time and quality associated with depression and social anxiety among children and adolescents aged 6-18 years, stratified by body composition

BACKGROUND

Sleep has been suggested as risk factors for depression and social anxiety in children and adolescents, but little is known about the role of individual body composition on these association.

METHOD

We conducted a cross-sectional survey of children and adolescents aged 6-18 years in Beijing, China, in 2020, and assessed body composition by using iDXA dual-energy X-ray bone densitometer. Generalized liner model (GLM) and restricted cubic spline (RCS) were employed to analyze the associations between sleep and depression and social anxiety with different body composition. The attributable fraction (AFs) to assess the benefits of improvements of sleep in reducing depression and social anxiety odds.

RESULTS

Depression and social anxiety accounted for 13.1 % and 30.3 % of the study population. Sleep time was significantly associated with depression (HR = 2.35[1.58, 3.50]), and social anxiety (HR = 1.65[1.24, 2.20]); and sleep quality was significantly associated with depression (HR = 7.27[4.87, 10.84]), and social anxiety (HR = 2.54 [1.99, 3.25]) among children and adolescents. The exposure to both insufficient sleep time and poor sleep quality were associated with a higher odd of depression and social anxiety, but lower BF%, higher muscle rate and FFM/FM alleviated the adverse effects of sleep quality on depression and social anxiety.

LIMITATIONS

Conclusions about causality remain speculative because of the cross-sectional design.

CONCLUSION

Insufficient sleep time, poor sleep quality, high BF%, low muscle rate and FFM/FM can jointly associate with anxiety and depression. This study provides new evidence support for accurate prevention and control of mental diseases in children and adolescents with different body types.

Development of a convenient and effective hypertension risk prediction model and exploration of the relationship between Serum Ferritin and Hypertension Risk: a study based on NHANES 2017-March 2020

Background

Hypertension is a major public health problem, and its resulting other cardiovascular diseases are the leading cause of death worldwide. In this study, we constructed a convenient and high-performance hypertension risk prediction model to assist in clinical diagnosis and explore other important influencing factors.

Methods

We included 8,073 people from NHANES (2017-March 2020), using their 120 features to form the original dataset. After data pre-processing, we removed several redundant features through LASSO regression and correlation analysis. Thirteen commonly used machine learning methods were used to construct prediction models, and then, the methods with better performance were coupled with recursive feature elimination to determine the optimal feature subset. After data balancing through SMOTE, we integrated these better-performing learners to construct a fusion model based for predicting hypertension risk on stacking strategy. In addition, to explore the relationship between serum ferritin and the risk of hypertension, we performed a univariate analysis and divided it into four level groups (Q1 to Q4) by quartiles, with the lowest level group (Q1) as the reference, and performed multiple logistic regression analysis and trend analysis.

Results

The optimal feature subsets were: age, BMI, waist, SBP, DBP, Cre, UACR, serum ferritin, HbA1C, and doctors recommend reducing salt intake. Compared to other machine learning models, the constructed fusion model showed better predictive performance with precision, accuracy, recall, F1 value and AUC of 0.871, 0.873, 0.871, 0.869 and 0.966, respectively. For the analysis of the relationship between serum ferritin and hypertension, after controlling for all co-variates, OR and 95% CI from Q2 to Q4, compared to Q1, were 1.396 (1.176-1.658), 1.499 (1.254-1.791), and 1.645 (1.360-1.989), respectively, with P < 0.01 and P for trend <0.001.

Conclusion

The hypertension risk prediction model developed in this study is efficient in predicting hypertension with only 10 low-cost and easily accessible features, which is cost-effective in assisting clinical diagnosis. We also found a trend correlation between serum ferritin levels and the risk of hypertension.

The dietary inflammatory index is positively associated with insulin resistance in underweight and healthy weight adults

The aim of this study was to explore the relationship between dietary inflammatory index (DII) and insulin resistance (IR) in underweight and healthy weight adults. This cross-sectional study involved 3205 participants from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. All dietary data used to calculate the DII were obtained based on the average of two 24-h dietary recall interviews. Participants were divided into an anti-inflammatory diet group and a pro-inflammatory diet group based on DII < 0 and DII ≥ 0, respectively. Fasting blood glucose and fasting insulin data used to calculate IR index (HOMA-IR) were from laboratory data in the NHANES database. According to the linear regression analysis results of DII and HOMA-IR, we found that there was a positive relationship between DII and IR. A positive association between DII and HOMA-IR was seen in the following groups after stratification: by age in 20-39-year olds, by sex in males, by race in Non-Hispanic Whites, by family history of diabetes in those without a family history of diabetes, by education level in those with high school education, by smoking status in current smokers and non-smokers, by hypertension in those with hypertension, by BMI in those with a BMI of 18.5-24.99, by hypertriglyceridemia (HTG) in those without HTG, by poverty impact ratio (PIR) in those with PIR ≤ 1.3 and >1.3, and by physical activity in those with moderate recreational activities. In conclusion, in underweight and healthy weight adults, DII was positively correlated with the risk of IR.