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Clinical metabolomics is growing as an essential tool for precision medicine. However, classical machine learning algorithms struggle to comprehensively encode and analyze the metabolomics data due to their high dimensionality and complex intercorrelations. This article introduces a new method called MetDIT, designed to analyze intricate metabolomics data effectively using deep convolutional neural networks (CNN). MetDIT comprises two components: TransOmics and NetOmics. Since CNN models have difficulty in processing one-dimensional (1D) sequence data efficiently, we developed TransOmics, a framework that transforms sequence data into two-dimensional (2D) images while maintaining a one-to-one correspondence between the sequences and images. NetOmics, the second component, leverages a CNN architecture to extract more discriminative representations from the transformed samples. To overcome the overfitting due to the small sample size and class imbalance, we introduced a feature augmentation module (FAM) and a loss function to improve the model performance. Furthermore, we systematically optimized the model backbone and image resolution to balance the model parameters and computational costs. To demonstrate the performance of the proposed MetDIT, we conducted extensive experiments using three different clinical metabolomics data sets and achieved better classification performance than classical machine learning methods used in metabolomics, including Random Forest, SVM, XGBoost, and LightGBM. The source code is available at the GitHub repository at https://github.com/Li-OmicsLab/MetDIT, and the WebApp can be found at http://metdit.bioinformatics.vip/.
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Background: The effect of serum lycopene on the progression of cardiovascular diseases (CVDs) and their longevity remains a controversial topic. The purpose of this study was to evaluate the associations of different isomeric forms of serum lycopene with CVD and all-cause mortality in the American population. Methods: The National Health and Nutrition Examination Survey (NHANES) is a large population survey to investigate public health in the US. We analyzed data from 2003-2006 linked with mortality data obtained in 2015. Cox proportional hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated to assess the risk of CVD and all-cause mortality caused by serum lycopene. Results: Among 7452 participants (aged 20-85 years, 46.7% male), 298 died from CVDs among the total 1213 deaths during a median follow-up of 10.7 years. Serum lycopene is a protective factor for all-cause and CVD mortality. In multivariable-adjusted models, the hazard ratio (with 95% confidence intervals) associated with Q4 compared to Q1 of serum total-lycopene, trans-lycopene and cis-lycopene was 0.49 (0.38,0.63), 0.49 (0.39,0.63) and 0.55 (0.43,0.70) for all-cause mortality (Ptrend<0.05), and was 0.53 (0.32,0.96), 0.48 (0.32,0.72) and 0.63 (0.41,0.97) for CVD mortality (Ptrend<0.05). The subgroup analyses showed that different isomeric forms of lycopene showed varied associations with CVD and all-cause mortality based on age, drinking status, history of hypertension and diabetes. Conclusions: Serum lycopene concentration was significantly associated with the risk of CVD and all-cause mortality. Cis-lycopene had a U-shaped relationship with mortality, while trans-lycopene had an inverse relationship with it.
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Doenças Cardiovasculares , Hipertensão , Humanos , Masculino , Estados Unidos/epidemiologia , Feminino , Licopeno , Inquéritos Nutricionais , Inquéritos e Questionários , Fatores de RiscoRESUMO
INTRODUCTION: Chinese herbal medicines have been utilized for thousands of years to prevent and treat diseases. Accurate identification is crucial since their medicinal effects vary between species and varieties. Metabolomics is a promising approach to distinguish herbs. However, current metabolomics data analysis and modeling in Chinese herbal medicines are limited by small sample sizes, high dimensionality, and overfitting. OBJECTIVES: This study aims to use metabolomics data to develop HerbMet, a high-performance artificial intelligence system for accurately identifying Chinese herbal medicines, particularly those from different species of the same genus. METHODS: We propose HerbMet, an AI-based system for accurately identifying Chinese herbal medicines. HerbMet employs a 1D-ResNet architecture to extract discriminative features from input samples and uses a multilayer perceptron for classification. Additionally, we design the double dropout regularization module to alleviate overfitting and improve model's performance. RESULTS: Compared to 10 commonly used machine learning and deep learning methods, HerbMet achieves superior accuracy and robustness, with an accuracy of 0.9571 and an F1-score of 0.9542 for distinguishing seven similar Panax ginseng species. After feature selection by 25 different feature ranking techniques in combination with prior knowledge, we obtained 100% accuracy and an F1-score for discriminating P. ginseng species. Furthermore, HerbMet exhibits acceptable inference speed and computational costs compared to existing approaches on both CPU and GPU. CONCLUSIONS: HerbMet surpasses existing solutions for identifying Chinese herbal medicines species. It is simple to use in real-world scenarios, eliminating the need for feature ranking and selection in classical machine learning-based methods.
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Background: Stroke is the predominant cause of death worldwide. We aimed to investigate the association of serum beta-2 microglobulin ( ß 2M) concentrations with risk of stroke and all-cause mortalities in a cohort study. Methods: Overall, 4914 U.S. adults (mean age = 63.0 years, 44.3% male) were recruited from the National Health and Nutrition Examination Survey (NHANES â ¢). During a median follow-up of 19.4 years, 254 stroke deaths and 3415 all-cause deaths were identified by the National Center for Health Statistics. The associations of ß 2M with stroke and all-cause mortalities were investigated by using weighted Cox proportional hazard regression models. Results: ß 2M was positively associated with stroke and all-cause mortality in unadjusted models and multivariable-adjusted models. The multivariable HR (95% CI) for stroke mortality in Q5 VS Q1 of serum ß 2M concentrations was 3.45 (1.33-8.91; p for trend = 0.001) and that for all-cause mortality was 3.95 (3.05-5.12; p for trend < 0.001). In subgroup analyses, the association of ß 2M and stroke mortality did not vary by different levels of sociodemographic and general stroke risk factors (p interaction > 0.05). In addition, the magnitude of positive association between ß 2M with all-cause mortality did vary by age, ratio of family income to poverty, smoking status, and history of hypertensive (p interaction < 0.05). Conclusions: Our findings suggest that support that ß 2M may be a marker of stroke and all-cause mortality, which provides a new perspective for the study of cerebrovascular health and long-term survival in the future.
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BACKGROUND: In recent years, the physical fitness situation of college students is worrying in China. Exercise motivation is of great importance for the physical activity and physical fitness. However, existing studies have paid limited attention to the specific effect between exercise motivation, physical activity and physical fitness, and even less to the different genders and exercise motivation dimensions. This study aimed to investigate the promoting effect of sport motivation on physical fitness with different gender and dimension in college students. METHODS: Physical fitness levels of 2544 college students in Wuhan and Jingzhou city were measured. Exercise motivation and physical activity was assessed using the Chinese version of the motives for physical activities measure-revised scale and the physical activity survey scale, respectively. Correlation analysis and structural equation model were used to explore the relationship between exercise motivation, physical activity and physical fitness. Bootstrap method was used to test the mediating effect. Multilevel regression analysis was used to examine the effects of different dimensions of exercise motivation on PF. RESULTS: The exercise motivation of college students was directly related to physical fitness (effect value: 0.307) or indirectly related through the mediating effect of physical activity (effect value: 0.092). The mediation effect percentage of physical activity on exercise motivation and physical fitness in male (51.20%) was greater than female (27.18%), and the standardized regression coefficient of the health dimension to PF was ß = 0.151, P < 0.001, and the competence dimension to PF was ß = 0.189, P < 0.001. CONCLUSIONS: The exercise motivation of college students can directly influence PF or indirectly influence PF through the mediating effect of PA. The promoting effect of exercise motivation and PA on PF in college students is related to gender and dimensions of exercise motivation. Therefore, we can improve physical fitness levels of college students by promoting their exercise motivation (especially for health motivation and competence motivation) and increasing their participation in physical activity. This study provides new strategies for improving physical fitness in college students.
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Motivação , Esportes , Humanos , Masculino , Feminino , Exercício Físico , Aptidão Física , EstudantesRESUMO
BACKGROUND: Since coronavirus disease 2019 (COVID-19) outbreak, its terrible infectiousness has caused great panic, anxiety and poor sleep quality to the vulnerable adolescent populations. METHODS: This cross-sectional online survey recruited 10 569 Chinese junior and senior high school adolescents during 31 January to 9 February 2020. Basic socio-demographic information, Pittsburgh Sleep Quality Index (PSQI), Self-rating Anxiety Scale (SAS) and Fear of negative evaluation (FNE) were included in the survey. The χ2 and logistic regression analyses were used to identify factors correlated with poor sleep quality. RESULTS: The prevalence of poor sleep quality was 18.6% in the Chinese adolescent population. The average score of PSQI was 3.39 (SD = 2.64), which was significantly correlated with scores for anxiety (r = 0.50, p < 0.01), and FNE (r = 0.36, p < 0.01). Adjusted logistic regression indicated that gender (females) and education (senior high school) were associated with poor sleep quality, while living in Hubei Province and time spent on the COVID-19 information were inversely associated with poor sleep quality. Having a family member or friend infected/suspected and spending time on electronics were associated with higher odds of having poor sleep quality. Adolescents with anxiety were 8 times, and those with FNE were three times more likely than ones without anxiety or FNE to have poor sleep quality. In addition, the number of meals, exercise time and diet quality were also significantly associated with sleep quality. (p < 0.05). CONCLUSIONS: Poor sleep quality was common during the COVID-19 pandemic in Chinese adolescents. Understanding several factors associated with the poor sleep quality will offer some important insights into determining potential interventions to improve sleep quality during the COVID-19 pandemic.
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COVID-19 , Pandemias , Adolescente , China/epidemiologia , Estudos Transversais , Feminino , Humanos , SARS-CoV-2 , Instituições Acadêmicas , Sono , Inquéritos e QuestionáriosRESUMO
The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism's phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. This review provides an introduction to common metabolic network models and their construction methods. It also explores the diverse applications of metabolic networks in elucidating disease mechanisms, predicting and diagnosing diseases, and facilitating drug development. Additionally, it discusses potential future directions for research in metabolic networks. Ultimately, this review serves as a valuable reference for researchers interested in metabolic network modeling, analysis, and their applications.
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Objective: To investigate the association between the dietary intake of linoleic acid (LA) and alpha linolenic acid (ALA) with mortality outcomes in patients with diabetes. Participants: 3,112 U.S. adults aged≥20 years. Setting: Basic information was collected at baseline of the National Health and Nutrition Examination Survey (NHANES). Serum CRP (mg/dL), total protein (g/L), waist circumference (cm), fasting blood glucose (mmol/L), white blood cell count, serum LDL-C, and serum HDL-C were also measured. Daily diets were also recorded using a 24-hour dietary review to produce the individuals' intake of LA and ALA. The association between tertiles of LA and ALA intake with mortality was analyzed by weighted Cox models adjusted for the main confounders. Main outcome measures: The study included 3,112 adults with diabetes from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2008. Death outcomes were ascertained by linkage to the database records through 31 December 2015. Results: Subjects with a high intake of LA (T3) had 17% [hazard ratio (HR) 0.83, 95% CI 0.70 to 0.99) and 48% (HR=0.52, 0.35 to 0.80)] reductions in all-cause mortality and cardiovascular mortality, respectively, compared with subjects with lowest intake (T1). Similar results were observed for ALA, HR of cardiovascular mortality was 0.55 (0.38 to 0.81) and for all-cause mortality was 0.85 (0.69 to 1.04) comparing the highest to lowest intake tertiles. Conclusion: Higher intakes of LA and ALA were inversely associated with CVD and all-cause deaths in patients with diabetes. Proper dietary intakes of LA and ALA could contribute to the cardiovascular health and the long-term survival of patients with diabetes.
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Puberty is a vulnerable period for the onset of major depressive disorder (MDD) due to considerable neurodevelopmental changes. Prior diffusion tensor imaging (DTI) studies in depressed youth have had heterogeneous participants, making assessment of early pathology challenging due to illness chronicity and medication confounds. This study leveraged whole-brain DTI and graph theory approaches to probe white matter (WM) abnormalities and disturbances in structural network topology related to first-episode, treatment-naïve pediatric MDD. Participants included 36 first-episode, unmedicated adolescents with MDD (mean age 15.8 years) and 29 age- and sex-matched healthy controls (mean age 15.2 years). Compared to controls, the MDD group showed reduced fractional anisotropy in the internal and external capsules, unveiling novel regions of WM disruption in early-onset depression. The right thalamus and superior temporal gyrus were identified as network hubs where betweenness centrality changes mediated links between WM anomalies and depression severity. A diagnostic model incorporating demographics, DTI, and network metrics achieved an AUROC of 0.88 and a F1 score of 0.80 using a neural network algorithm. By examining first-episode, treatment-naïve patients, this work identified novel WM abnormalities and a potential causal pathway linking WM damage to symptom severity via regional structural network alterations in brain hubs.
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The prevalence of metabolic disorders has been found to increase concomitantly with alternations in habitual diet and lifestyle, indicating the importance of metabolic health monitoring for early warning of high-risk status and suggesting effective intervention strategies. Hippuric acid (HA), as one of the most abundant metabolites from the gut microbiota, holds potential as a regulator of metabolic health. Accordingly, it is imperative to establish an efficient, sensitive, and affordable method for large-scale population monitoring, revealing the association between HA level and metabolic disorders. Upon systematic screening of macrocycleâ¢dye reporter pair, a supramolecular architecture (guanidinomethyl-modified calix[5]arene, GMC5A) was employed to sense urinary HA by employing fluorescein (Fl), whose complexation behavior was demonstrated by theoretical calculations, accomplishing quantification of HA in urine from 249 volunteers in the range of 0.10 mM and 10.93 mM. Excitedly, by restricted cubic spline, urinary HA concentration was found to have a significantly negative correlation with the risk of metabolic disorders when it exceeded 0.76 mM, suggesting the importance of dietary habits, especially the consumption of fruits, coffee, and tea, which was unveiled from a simple questionnaire survey. In this study, we accomplished a high throughput and sensitive detection of urinary HA based on supramolecular sensing with the GMC5Aâ¢Fl reporter pair, which sheds light on the rapid quantification of urinary HA as an indicator of metabolic health status and early intervention by balancing the daily diet.
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Biomarcadores , Hipuratos , Hipuratos/urina , Humanos , Biomarcadores/urina , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Corantes Fluorescentes/químicaRESUMO
Purpose: While observational studies have identified obesity as a potential risk factor for gastric cancer, the causality remains uncertain. This study aimed to evaluate the causal relationship between obesity and gastric cancer and identify the shared molecular signatures linking obesity to gastric cancer. Methods: A two-sample Mendelian randomization (MR) analysis was conducted using the GWAS data of body fat percentage (exposure, n = 331,117) and gastric cancer (outcome, n = 202,308). Bioinformatics and meta-analysis of multi-omics data were performed to identify key molecules mediating the causality. The meta-analysis of the plasma/serum proteome included 1,662 obese and 3,153 gastric cancer patients. Obesity and gastric cancer-associated genes were identified using seven common gene ontology databases. The transcriptomic data were obtained from TCGA and GEO databases. The Bioinformatic findings were clinically validated in plasma from 220 obese and 400 gastric cancer patients across two hospitals. Finally, structural-based virtual screening (SBVS) was performed to explore the potential FDA-approved drugs targeting the identified mediating molecules. Results: The MR analysis revealed a significant causal association between obesity and gastric cancer (IVW, OR = 1.37, 95% CI:1.12-1.69, P = 0.0028), without pleiotropy or heterogeneity. Bioinformatic and meta-analysis of multi-omics data revealed shared TNF, PI3K-AKT, and cytokine signaling dysregulation, with significant upregulation of AKT1, IL-6, and TNF. The clinical study confirmed widespread upregulation of systemic inflammatory markers in the plasma of both diseases. SBVS identified six novel potent AKT1 inhibitors, including the dietary supplement adenosine, representing a potentially preventive drug with low toxicity. Conclusion: Obesity causally increases gastric cancer, likely mediated by persistent AKT1/IL-6/TNF upregulation. As a potential AKT1 inhibitor, adenosine may mitigate the obesity-to-gastric cancer transition. These findings could inform preventive drug development to reduce gastric cancer risk in obesity.
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In the general population, there is little evidence of a link between blood urea nitrogen (BUN) and long-term mortality. The goal of this study was to explore whether higher BUN concentration is a predictor of cardiovascular disease (CVD) and all-cause mortality. From 1999 to 2006, the National Health and Nutrition Examination Survey (NHANES) included 17,719 adult individuals. Death outcomes were ascertained by linkage to the database records through 31 December 2015. The Cox proportional hazard regression model was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD and all-cause mortality in individuals. We also performed stratified analyses based on age, gender, drinking, smoking, history of hypertension and diabetes. During a mean follow-up 11.65 years, a total of 3628 deaths were documented, of which 859 were due to CVD. Participants with higher BUN had a higher risk of CVD and all-cause death compared to those with lower BUN. After multifactor adjustment for demographics, major lifestyle factors, and hypertension and diabetes history, higher BUN levels compared with lower levels were significantly associated with higher risk of CVD (HR: 1.48 [1.08, 2.02], P-trend < 0.001) and all-cause mortality (HR: 1.48 [1.28, 1.72], P-trend < 0.001). In subgroup analyses, we found that the trend in the association of BUN with the risk of death remained strong in female subjects. Greater BUN levels were linked to higher CVD and all-cause mortality in the NHANES of American adults. The importance of BUN in predicting death is supported by our research.
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Doenças Cardiovasculares , Diabetes Mellitus , Hipertensão , Humanos , Adulto , Feminino , Estados Unidos/epidemiologia , Doenças Cardiovasculares/epidemiologia , Inquéritos Nutricionais , Nitrogênio da Ureia Sanguínea , Hipertensão/epidemiologiaRESUMO
Among patients with diabetes mellitus, limited studies have investigated the relationship between anthropometric parameters and cardiovascular disease (CVD), with all-cause mortality. We examined the associations of arm circumference (AC), arm-to-waist ratio (AC/WC), and CVD, with all-cause mortality among patients with diabetes. This is a cohort study of 5497 diabetic individuals aged 20 or over who were recruited in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014. Cox proportional hazards regression models were used to analyze the associations between AC, AC/WC, and CVD, with all-cause mortality. We also conducted stratified analyses and explored the possible non-linear relation by restricted cubic splines. During a median follow-up of 7.2 years, there were 271 and 1093 cases of CVD and all-cause death. The multivariable adjusted hazard ratios (HRs) with 95% confidence intervals (Cis) of CVD mortality in Q2, Q3, and Q4 groups compared with Q1 group were 0.37 (0.22, 0.62), 0.24 (0.12, 0.48), 0.18 (0.07, 0.46) for AC, and 0.18 (0.07, 0.46), 0.34 (0.20, 0.60), 0.28 (0.15, 0.53) for AC/WC. Similar results were observed in the analysis for all-cause mortality risk. AC and AC/WC were both inversely associated with CVD and all-cause mortality among individuals with diabetes. It is important to pay attention to these anthropometric parameters of diabetic patients.
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Doenças Cardiovasculares , Diabetes Mellitus , Humanos , Inquéritos Nutricionais , Fatores de Risco , Estudos de Coortes , Braço , Circunferência da Cintura , Índice de Massa CorporalRESUMO
Objectives: Evidence of the relationship between android fat mass and gynoid fat mass with the mortality prediction is still limited. Current study analyzed the NHANES database to investigate the relationship between android fat mass, gynoid fat mass and CVD, with all-cause mortality. Method: The study subjects were NHANES participants over 20 years old, two indicators of regional body composition, android fat and gynoid fat were measured by Dual Energy x-ray Absorptiometry (DEXA). The other various covariates data obtained from the NHANES questionnaire and laboratory measurements, including age, gender, education, race/ethnicity, uric acid, total serum cholesterol, albumin, Vitamin C, folate, alcohol drinking, smoking status, history of diabetes, and hypertension. Mortality status was ascertained from a linked mortality file prepared by the National Center for Health Statistics. The study population was divided quartiles based on the distribution of android fat mass and gynoid fat mass. The relationship between these two indicators with cardiovascular and all-cause mortality was investigated by using Cox regression. The covariates age, gender, smoking status, drinking status, history of diabetes, and history of hypertension were stratified. Results: In the fully adjusted model, Q3 had the lowest HR in android fat mass and gynoid fat mass. When examining the relationship between android fat mass and CVD mortality, current smokers and drinkers had the lowest CVD risk in Q2 [smoking: 0.21 (0.08, 0.52), drinking: 0.14 (0.04, 0.50)]. In diabetic patients, compared with Q1, other groups with increased android fat mass can significantly reduce the risk of CVD [Q4: 0.17 (0.04, 0.75), Q3: 0.18 (0.03, 1.09), Q2: 0.27 (0.09, 0.83)]. In ≥60 years old and female, the greater the gynoid fat mass, the smaller the HR of all-cause mortality [Q4 for ≥60 years old: 0.57 (0.33, 0.96), Q4 for female: 0.37 (0.23, 0.58)]. People <60 years old had a lower risk of all-cause mortality with gynoid fat mass in Q3 than those ≥60 years old [<60 years: 0.50 (0.27, 0.91), ≥60 years: 0.65 (0.45, 0.95)]. Among subjects without hypertension, the group with the largest android fat mass had the lowest risk of CVD mortality, and the group with the largest gynoid fat mass had the lowest risk of all-cause mortality [Android fat mass: 0.36 (0.16, 0.81), gynoid fat mass: 0.57 (0.39, 0.85)]. Conclusion: Moderate android fat mass and gynoid fat mass (Q3) had the most protective effect. Smokers and drinkers need to control their body fat. Being too thin is harmful to people with diabetes. Increased gynoid fat mass is a protective factor for all-cause mortality in older adults and females. Young people's gynoid fat mass is more protective in the moderate range than older people's. If no high blood pressure exists, people with more android and gynoid fat mass have a lower risk of CVD or all-cause mortality.
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To collect relevant literature on the impact of rural residents' sleep quality on the incidence of agricultural injuries, the search time range is 1990ï½2019. We use RevMan 5.3 software for statistical processing. A total of 7 articles were included. Meta-analysis showed that sleep quality was closely related to agricultural injury. The combined effect was 1.49, 95%CI [1.31, 1.70], Z = 5.93, P < 0.00001. The difference was statistically significant, so poor sleepers had a higher incidence of agricultural injuries than good sleepers. Sleep disturbances and agricultural injuries are two common and significant health problems. Investigations suggest that sleep might increase the risk of agricultural injuries. The aim of the present study was to systematically review and meta-analyze the predictive effect of sleep on agricultural injuries.
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Qualidade do Sono , Transtornos do Sono-Vigília , Humanos , Incidência , Transtornos do Sono-Vigília/epidemiologiaRESUMO
Few prospective studies explored the association of beta-2-microglobulin (B2M) with coronary heart disease (CHD) mortality. The primary objective of this study was to examine the association of serum B2M with CHD and all-cause mortality. This is a prospective cohort study of a nationally representative sample of 4,885 adults, aged 40-85 years, who participated in the National Health and Nutrition Examination Survey (NHANES III) from 1988 to 1994. The relationships between B2M and CHD and all-cause mortality were estimated using Cox proportional hazards regression models. During a median follow-up of 15.5 years, 845 CHD and 3,388 all-cause deaths occurred among 4,885 participants [2,568 women (55.7%); mean (S.D.) age, 66.4 (12.5) years], respectively. In the unadjusted model, B2M concentration was strongly linearly associated with CHD and all-cause mortality (p-trend < 0.001). After adjusting multivariable factors, a positive linear association between B2M and all-cause mortality was still observed (H.R. for Q4 vs. Q1 5.90; 95% CI: 5.31-6.57; p-trend < 0.001). In the multivariable adjustment model, B2M was significantly associated with an increased risk of CHD mortality (H.R. for Q4 vs. Q1 2.72; 95% CI: 2.07-3.57; p-trend < 0.001). In the stratified analyses, the associations of B2M with CHD and all-cause mortality varied by risk factors, such as age, smoking status, and history of hypertension. The findings suggest a significant relationship between the higher serum B2M concentration and increased risk for CHD and all-cause mortality. Further large-scale follow-up studies are also needed to validate this association.
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Introduction: The evidence on eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) intake status and long-term mortality among people with diabetes is scarce. This study aimed to investigate the relationship between EPA and DHA intakes with all-cause and cause-specific mortality in adults with diabetes. Methods: This study included 2,991 adults with diabetes from the National Health and Nutrition Examination Survey (NHANES) 1999-2008. Death outcomes were ascertained by linkage to the database records through 31 December 2015. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for mortality from all causes, cardiovascular disease (CVD), and coronary heart disease (CHD) in patients with diabetes. Results: Among 2,991 patients with diabetes, the mean age was 61.9 years (55.2% males). During the mean follow-up duration of 9.4 years, a total of 1,091 deaths were documented, of which 273 were due to CVD, including 227 CHD deaths. EPA and DHA intakes were associated with lower mortality risks, especially that of CVD. After adjusting for demographic, major lifestyle factors, overall dietary intake patterns, and history of hypertension and dyslipidemia, the multivariable HRs (95% CIs) of mortality risk comparing Q4 to Q1 of EPA intake were 0.55 (0.33-0.92; P-trend = 0.019) for CHD, 0.55 (0.36-0.83; P-trend = 0.005) for CVD, and 0.91 (0.70-1.18; P-trend = 0.264) for all-cause. The respective HRs (95% CIs) comparing Q4 to Q1 of DHA were 0.60 (0.37-0.98; P-trend = 0.051) for CHD, 0.58 (0.38-0.89; P-trend = 0.014) for CVD, and 0.92 (0.72-1.18; P-trend = 0.481) for all-cause. In subgroup analysis, we found that the association trends of EPA and DHA intakes with death risk remained robust among patients with diabetes, especially among those who are old, female, those with higher BMI, and dyslipidemia patients with CVD and CHD. Discussion: In the USA, higher EPA and DHA intakes were associated with a lower risk of CHD and CVD mortality in patients with diabetes. Our study supports the benefits of adequate EPA and DHA intakes in promoting the health of patients with diabetes.
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Limited evidence investigated the combined influence of early-adulthood weight change and later physical activity on the risk of cardiovascular (CVD) and all-cause mortality. The aim of this study is to explore the associations of early-adulthood weight change and later physical activity with CVD and all-cause mortality. This is a cohort study of 23,193 US adults aged 40 to 85 years from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2014. Cox proportional hazards regression was used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) of CVD and all-cause mortality associated with early-adulthood weight change and later physical activity. During a median follow-up of 9.2 years, there were 533 and 2734 cases of CVD and all-cause deaths. Compared with being physically inactive, the HRs of the CVD mortality of being physically active were 0.44 (0.26 to 0.73), 0.58 (0.19 to 1.82), 0.38 (0.17 to 0.86) and 0.46 (0.21 to 1.02) among individuals with stable normal, stable obese, non-obese to obese and maximum overweight early-adulthood weight change patterns. Using stable normal patterns that were physically active later as the reference, other early-adulthood weight change patterns did not show a significantly higher risk of CVD mortality when participants were physically active in later life; later physically inactive participants had a significantly increased risk of CVD mortality, with HRs of 2.17 (1.30 to 3.63), 5.32 (2.51 to 11.28), 2.59 (1.29 to 5.18) and 2.63 (1.32 to 5.26) in the stable normal, stable obese, non-obese to obese and maximum overweight groups, respectively. Similar results can be seen in the analyses for all-cause mortality. Our findings suggest that inadequate physical activity worsens the negative impact of unhealthy early-adulthood weight change patterns, which is worthy of being noted in the improvement of public health.
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Doenças Cardiovasculares , Adulto , Humanos , Inquéritos Nutricionais , Estudos de Coortes , Fatores de Risco , Exercício Físico , Obesidade/complicações , Sobrepeso/epidemiologia , Sobrepeso/complicaçõesRESUMO
Objective: The potential effects of pulmonary dysfunction on cardiovascular diseases (CVD) and all-cause mortality are receiving attention. The current study aimed to explore whether reduced lung function predicts CVD and all-cause mortality in people with diabetes. Methods: A total of 1,723 adults with diabetes (mean age 60.2 years) were included in the National Health and Nutrition Examination Survey (NHANES III). Death outcomes were ascertained by linkage to the database records through 31 December 2015. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for coronary heart disease (CHD), CVD, and all-cause mortalities. We conducted stratified analyses based on age, body mass index (BMI), history of hypertension, and dyslipidemia. Results: During a mean follow-up of 14.62 years (25,184 person-year), a total of 1,221 deaths were documented, of which 327 were CHD, 406 were CVD, and 197 were cancer. After multi-factor adjustment, participants with lower FEV1 and FVC had a higher risk of CHD, CVD, and all-cause mortality. This association was also found in lower FVC and a higher risk of cancer mortality [HR: 3.85 (1.31-11.32); P for trend = 0.040], but the association of FEV1 was attenuated after adjustment for covariates [HR:2.23 (0.54-9.17); P for trend = 0.247]. In subgroup analysis, we found that the adverse associations of FEV1 and FVC with CVD mortality were observed in subgroups of age, BMI, and history of hypertension and dyslipidemia. Conclusion: Declined lung function was associated with a higher risk of CVD and all-cause mortality in people with diabetes. Lung function tests, especially FEV1 and FVC, should be encouraged to provide prognostic and predictive information for the management of CVD and all-cause mortality in patients with diabetes.
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To assess the correlation between plasma total homocysteine (tHcy) level and gestational diabetes mellitus (GDM) in a Chinese Han population. This case-control study included 350 GDM patients and 346 gestational week-matched normal glucose tolerance (NGT) pregnant women. Plasma tHcy and insulin levels were analyzed by HPLC and ELISA respectively. Logistic regression analysis was used to investigate the correlation between plasma tHcy level and risk of GDM. Women with GDM had a higher plasma tHcy level than NGT women (6.61 ± 1.32 vs. 6.17 ± 1.29 µmol/L, P = 0.001)). The GDM risk was 1.79 (OR = 1.79, 95% CI 1.18-2.72, P = 0.006) times higher in women whose plasma tHcy level was ≥ 7.29 µmol/L compared to women with plasma tHcy level < 5.75 µmol/L. Stratified analysis showed the GDM risk were much higher when HOMA-IR index ≥ 2 (OR = 5.42, 95% CI 2.51-11.74, P < 0.001), age ≥ 30 years (OR = 5.14, 95% CI 2.78-9.52, P < 0.001), or women with a family history of type 2 diabetes mellitus (T2DM) (OR = 4.13, 95% CI 1.78-9.56, P = 0.001). In the Chinese Han population, an elevated plasma tHcy level may increase the overall risk of GDM especially in women with a high HOMA-IR index, increasing age or with family history of T2DM.