Association between biological aging and the risk of mortality in individuals with non-alcoholic fatty liver disease: A prospective cohort study.

BACKGROUND: The biological process of aging plays an important role in nonalcoholic fatty liver disease (NAFLD) development. However, epidemiological evidence about the association of biological aging with mortality risk among people with NAFLD is limited. METHODS: A total of 2199 participants with NAFLD from the National Health and Nutrition Examination Surveys (NHANES) III were included. The outcomes were all-cause and cause-specific (cardiovascular disease [CVD], cancer, and diabetes) mortality. We computed three BA measures, the Klemera-Doubal method (KDM) age, Phenotypic age, and homeostatic dysregulation (HD), by using 18 age-associated clinical biomarkers, and assessed their associations with mortality risk using Cox proportional hazards (CPH) models. RESULTS: After a median follow-up of 16 years, a total of 1077 deaths occurred. People with NAFLD who died during follow-up period exhibited higher baseline biological age (BA) and biological age accelerations (BAAs). The multivariate-adjusted CPH suggested that a one-standard deviation (SD) increase in KDM age acceleration, Phenotypic age acceleration, or HD was associated with a 3 %, 7 %, or 39 % elevated risk of all-cause mortality, respectively. The results of age-varying HRs showed that the associations of KDM age accelerations (AAs) and Phenotypic AAs with all-cause mortality appeared to be stronger in people with NAFLD younger than 45 years. CONCLUSIONS: Biological aging was positively associated with both all-cause and cause-specific mortality among people with NAFLD, particularly among younger individuals.

Prevalence of nonalcoholic fatty liver disease and liver cirrhosis in Chinese adults with type 2 diabetes mellitus.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and liver cirrhosis are significant clinical concerns, especially among individuals with type 2 diabetes mellitus (T2DM). However, in China, there is a paucity of reliable evidence detailing the characteristics of NAFLD and liver cirrhosis in T2DM. Furthermore, the relationship between blood glucose levels and NAFLD prevalence remains unclear. METHODS: Data from the Shanghai Suburban Adult Cohort and Biobank were analyzed, including 6621 participants with T2DM. NAFLD was diagnosed by ultrasonography and liver cirrhosis was performed according to the health information systems. Logistic regression and restricted cubic spline analysis were used to explore the potential risk factors for NAFLD and liver cirrhosis. RESULTS: The prevalence of NAFLD was 59.36%, and liver cirrhosis was 1.43% among T2DM patients. In these patients, factors like age, being female, marital status, and obesity significantly increased the risk of NAFLD. Specifically, obesity had a strong positive association with NAFLD (odds ratio [OR] = 4.70, 95% confidence interval [CI]: 4.13-5.34). The higher glycated hemoglobin (HbA1c) quartile was associated with a heightened NAFLD risk compared to the lowest quartile (all p < .001). The HbA1c-NAFLD relationship displayed a linear that mimicked an inverted L-shaped pattern. A significant positive association existed between HbA1c levels and NAFLD for HbA1c <8.00% (OR = 1.59, 95% CI: 1.44-1.75), but this was not observed for HbA1c >8.00% (OR = 1.03, 95% CI: 0.92-1.15). CONCLUSION: Systematic screening for NAFLD is essential in T2DM patients, especially with poor glucose control and obesity in female.

Machine-learning-based plasma metabolomic profiles for predicting long-term complications of cirrhosis.

BACKGROUND AND AIMS: The complications of liver cirrhosis occur after long asymptomatic stages of progressive fibrosis and are generally diagnosed late. We aimed to develop a plasma metabolomic-based score tool to predict these events. APPROACH AND RESULTS: We enrolled 64,005 UK biobank participants with metabolomic profiles. Participants were randomly divided into the training (n=43,734) and validation cohorts (n=20,271). Liver cirrhosis complications were defined as hospitalization for liver cirrhosis or presentation with HCC. An interpretable machine-learning framework was applied to learn the metabolomic states extracted from 168 circulating metabolites in the training cohort. An integrated nomogram was developed and compared to conventional and genetic risk scores. We created 3 groups: low-risk, middle-risk, and high-risk through selected cutoffs of the nomogram. The predictive performance was validated through the area under a time-dependent receiver operating characteristic curve (time-dependent AUC), calibration curves, and decision curve analysis. The metabolomic state model could accurately predict the 10-year risk of liver cirrhosis complications in the training cohort (time-dependent AUC: 0.84 [95% CI: 0.82-0.86]), and outperform the fibrosis-4 index (time-dependent AUC difference: 0.06 [0.03-0.10]) and polygenic risk score (0.25 [0.21-0.29]). The nomogram, integrating metabolomic state, aspartate aminotransferase, platelet count, waist/hip ratio, and smoking status showed a time-dependent AUC of 0.930 at 3 years, 0.889 at 5 years, and 0.861 at 10 years in the validation cohort, respectively. The HR in the high-risk group was 43.58 (95% CI: 27.08-70.12) compared with the low-risk group. CONCLUSIONS: We developed a metabolomic state-integrated nomogram, which enables risk stratification and personalized administration of liver-related events.

Establishment of a mild cognitive impairment risk model in middle-aged and older adults: a longitudinal study.

BACKGROUND: Early identification individuals at high risk of mild cognitive impairment (MCI) is essential for prevention and intervention strategies of dementia, such as Alzheimer's disease. MCI prediction considering the interdependence of predictors in longitudinal data needs to be further explored. We aimed to employ machine learning (ML) to develop and verify a prediction model of MCI. METHODS: In a longitudinal population-based cohort of China Health and Retirement Longitudinal Study (CHARLS), 8390 non-MCI participants were enrolled. The diagnosis of MCI was based on the aging-associated cognitive decline (AACD), and 13 factors (gender, education, marital status, residence, diabetes, hypertension, depression, hearing impairment, social isolation, physical activity, drinking status, body mass index and expenditure) were finally selected as predictors. We implemented a long short-term memory (LSTM) to predict the MCI risks in middle-aged and older adults within 7 years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model. RESULTS: Through 7 years of follow-up, 1925 participants developed MCI. The model for all incident MCI achieved an AUC of 0.774, and its deployment to the participants followed 2, 4, and 7 years achieved results of 0.739, 0.747, and 0.750, respectively. The model was well-calibrated with predicted probabilities plotted against the observed proportions of cognitive impairment. Education level, gender, marital status, and depression contributed most to the prediction of MCI. CONCLUSIONS: This model could be widely applied to medical institutions, even in the community, to identify middle-aged and older adults at high risk of MCI.

Prognostic factors for competing risk in patients with AIDS-related Kaposi's sarcoma: A SEER population-based study.

OBJECTIVES: Despite the improved survival of patients with AIDS and Kaposi's sarcoma (KS), competing events are a non-negligible issue affecting the survival of such patients. In this study, we explored the prognostic factors of KS-specific and non-KS-specific mortality in patients with AIDS-related KS (AIDS-KS), accounting for competing risk. METHODS: We identified 17 103 patients with AIDS-KS aged 18-65 years between 1980 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) 18 registry database. Prognostic factors for KS-specific and non-KS-specific mortality were determined by the Fine and Grey proportional subdistribution hazard model. We built competing risk nomograms and assessed their predictive performance based on the identified prognostic factors. RESULTS: In total, 12 943 (75.68%) patients died, 1965 (15.50%) of whom died from competing events. The KS-specific mortality rate was 14 835 per 100 000 person-years, and the non-KS specific mortality rate was 2719 per 100 000 person-years. Specifically, age >44 years was associated with an 11% decrease in the subdistribution hazard of KS-specific mortality compared with age <43 years but a 50% increase in the subdistribution hazard of non-KS-specific mortality. Being male was associated with a 26% increase in the subdistribution hazard of KS-specific mortality compared with being female but a 32% decrease in the subdistribution hazard of non-KS-specific mortality. Notably, being in the antiretroviral therapy (ART) era consistently showed a decrease in the subdistribution hazard of both KS-specific and non-KS-specific mortality than being in the pre-ART era. CONCLUSIONS: Competing events commonly occurred among patients with AIDS-KS, which deserves further attention to improve the prognosis of these patients.

Global epidemiology of early-onset liver cancer attributable to specific aetiologies and risk factors from 2010 to 2019.

Background: Considering its emergence as a public health concern worldwide, with potential spatial-temporal heterogeneities, we aimed to determine the global burden of early-onset liver cancer attributable to aetiologies and concomitant risk factors. Methods: We used data from the Global Burden of Diseases Study 2019 to determine age-standardised disability-adjusted life-year (DALY) rates for early-onset liver cancer by aetiologies and the population DALYs attributable to concomitant risk factors between 2010 and 2019. We also calculated estimated annual percentage changes (EAPCs) to measure temporal trends. Results: There were 2.9 million DALYs related to early-onset liver cancer globally in 2019. East Asia contributed over half of DALYs, which increased annually by 1.23% (95% confidence interval (CI) = 0.71, 1.76) between 2010 and 2019. Non-alcoholic steatohepatitis was the only growing aetiology. The proportion of DALYs attributed to metabolic risks increased by 22.50% (95% CI = 14.33, 38.13), while behavioral risks remained stable. Obesity surpassed smoking as the most prevalent nondeterministic aetiological risk factor from 2010 to 2019, while the population DALY attributable to hepatitis B combined with obesity increased by 29.93% (95% CI = 8.49, 60.77) in the same period, making it the principal joint contributor. Conclusions: Early-onset liver cancer poses considerable disability and continues to increase in many regions, especially in East Asia. Metabolic risk factors, particularly when hepatitis B and obesity coexist, are the fastest-growing contributors to this type of cancer. More targeted interventions are imperative to curb the growing burden of early-onset liver cancer due to metabolic risks.

Changing prevalence of chronic hepatitis B virus infection in China between 1973 and 2021: a systematic literature review and meta-analysis of 3740 studies and 231 million people.

OBJECTIVE: China concentrates a large part of the global burden of HBV infection, playing a pivotal role in achieving the WHO 2030 global hepatitis elimination target. METHODS: We searched for studies reporting HBV surface antigen (HBsAg) seroprevalence in five databases until January 2023. Eligible data were pooled using a generalised linear mixed model with random effects to obtain summary HBsAg seroprevalence. Linear regression was used to estimate annual percentage change (APC) and HBsAg prevalence in 2021. RESULTS: 3740 studies, including 231 million subjects, were meta-analysed. HBsAg seroprevalence for the general population decreased from 9.6% (95% CI 8.4 to 10.9%) in 1973-1984 to 3.0% (95% CI 2.1 to 3.9%) in 2021 (APC=-3.77; p<0.0001). Decreases were more pronounced in children <5 years (APC=-7.72; p<0.0001) and 5-18 years (-7.58; p<0.0001), than in people aged 19-59 years (-2.44; p<0.0001), whereas HBsAg seroprevalence increased in persons ≥60 years (2.84; p=0.0007). Significant decreases were observed in all six major Chinese regions, in both men (APC=-3.90; p<0.0001) and women (-1.82; p<0.0001) and in high-risk populations. An estimated 43.3 million (95% uncertainty interval 30.7-55.9) persons remained infected with HBV in China in 2021 (3.0%), with notable heterogeneity by region (<1.5% in North China to>6% in Taiwan and Hong Kong) and age (0.3%, 1.0%, 4.7% and 5.6% for <5 years, 5-18 years, 19-59 years and ≥60 years, respectively). CONCLUSIONS: China has experienced remarkable decreases in HBV infection over the last four decades, but variations in HBsAg prevalence persist in subpopulations. Ongoing prevention of HBV transmission is needed to meet HBV elimination targets by 2030. TRIAL REGISTRATION NUMBER: PROSPERO (CRD42021284217).

Associations of healthy lifestyle and three latent socioeconomic status patterns with physical multimorbidity among middle-aged and older adults in China.

BACKGROUND: Multimorbidity is an emerging global public health concern. However, complex associations of healthy lifestyle and socioeconomic status (SES) with multimorbidity have not been identified. METHODS: This population-based prospective cohort study used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) to explore these relationships. Physical multimorbidity was measured using 12 non-communicable diseases. Latent class analysis (LCA) was conducted to determine the optimal SES patterns based on annual per-capita household expenditure, occupation, education level, and health insurance. The healthy lifestyle score (0-5) was constructed comprising information on smoking, drinking, physical activity, sleep, and body shape. RESULTS: Of 17,708 participants in the CHARLS, 7776 were eligible for inclusion in our analysis (13.3% with high SES, 26.1% with medium SES, and 60.6% with low SES). Compared with high SES participants, those with low SES had higher risks of incident physical multimorbidity (OR 1.22, 95% CI 1.05, 1.42), which was competitively mediated by lifestyle (mediation proportion, -10.17%, 95% CI -19.12%, -1.23%). Significant interactions were observed between lifestyle factors and SES in patients with incident diabetes. Participants with low SES and no or one healthy lifestyle factor had a higher risk of incident physical multimorbidity than those with high SES and four to five healthy lifestyle factors (OR 2.19, 95% CI 1.57, 3.04). CONCLUSION: Healthy lifestyles competitively mediate a fractional proportion of socioeconomic inequity in incident physical multimorbidity. Furthermore, healthy lifestyles were associated with lower multimorbidity risk in the SES subgroups, supporting the important role of lifestyle in reducing physical multimorbidity burden.

Impact of sarcosine on diabetic retinopathy: Findings based on weighted gene co-expression network analysis and machine learning techniques.

AIM: To quantify the association between serum sarcosine and diabetic retinopathy (DR) using weighted gene co-expression network analysis (WGCNA). METHODS: We measured serum metabolites in 69 pairs of type 2 diabetes (T2D) patients with and without DR matched by age, gender, body mass index（BMI and HbA1c, using a propensity score matching-based approach. To identify modules and metabolites linked to DR, pathway analysis was performed using WGCNA, the Kyoto Encyclopedia of Genes and Genomes and Small-Molecule Pathway Database. The association of sarcosine with DR was estimated by restricted cubic spline and conditional logistic regression models. Its joint effects with covariates on DR were also extensively examined. RESULTS: With per interquartile range elevation of sarcosine, the adjusted odds ratio (AOR) of DR significantly decreased by 67% (AOR: 0.33, 95% confidence interval [CI]: 0.19-0.58). Similar results were also found in the tertile analysis. Compared with those in the first tertile of sarcosine, the AOR significantly decreased by 54% (AOR: 0.46, 95% CI: 0.18-1.17) and 78% (AOR: 0.22, 95% CI: 0.08-0.59) for subjects in the second and third tertiles, respectively. Compared with subjects with lower sarcosine and lower HDL-C levels, those with higher sarcosine and lower HDL-C levels had the lowest odds of DR (OR: 0.13, 95% CI: 0.04, 0.43). CONCLUSIONS: Serum sarcosine was inversely related to DR, especially in T2D patients with insufficient HDL-C. This study provides insights on a possible novel target for DR precision prevention and control, as well as a better understanding of the DR mechanism.

Application Areas of Intermittent Pneumatic Compression in the Prevention of Deep Vein Thrombosis During Dixon Surgery: A Randomized, Controlled Trial.

PURPOSE: Deep vein thrombosis (DVT) is common in the lithotomy position after laparoscopic surgery. Intermittent pneumatic compression (IPC) plays an important role in DVT prevention. However, few studies have compared the different compression areas of IPC application. It was hypothesized that the location of the compression sleeves could have an impact on the effects of thromboprophylaxis. METHODS: In this randomized, controlled trial performed from August 2020 to March 2021, 164 patients scheduled to undergo laparoscopic Dixon surgery were randomly assigned to one of four groups, based on the bilateral placement of compression sleeves during surgery: feet, calves, thighs, or control (no IPC). Both lower extremities were monitored for DVT on days 1 and 7 after surgery, using ultrasonographic assessment of mean blood velocity, blood flow volume, and diameter of the common femoral veins. Thrombosis-related hematologic analysis was performed. FINDINGS: On day 1 after surgery, IPC of the feet or calves was associated with a reduced prevalence of DVT compared with controls (both: P = 0.024; OR = 0.09; 95% CI, 0.01-0.72), while IPC of the thighs had no significant benefit (P = 0.781; OR = 0.86; 95% CI, 0.29-2.55). The prevalence of DVT in the left extremity was lower with IPC of the feet and calves compared with controls (both, P = 0.048). The mean blood velocity in the common femoral vein was significantly increased after surgery with IPC of the left and right feet (P = 0.006 and 0.007, respectively) and calves (P = 0.011 and P = 0.026, respectively) compared with controls. Similarly, the volume of blood flow in the left common femoral vein was greater with IPC of the feet and calves (P = 0.03 and 0.027, respectively). However, on day 7 after surgery, the between-group differences in the prevalences of DVT and hematologic indicators of thrombosis were not significant. IMPLICATIONS: On day 1 after surgery, IPC application at the feet or calves facilitated venous return and, hence, reduced the prevalence of DVT, especially in the left extremities. However, there were no significant differences in the prevalences of DVT or thrombosis-related hematologic indicators among the four groups on the day 7 after surgery. Chinese Clinical Trial Registration identifier: ChiCTR2000035325.

Composite Interventions on Outcomes of Severely and Critically Ill Patients with COVID-19 in Shanghai, China.

Background: The sixty-day effects of initial composite interventions for the treatment of severely and critically ill patients with COVID-19 are not fully assessed. Methods: Using a Bayesian piecewise exponential model, we analyzed the 60-day mortality, health-related quality of life (HRQoL), and disability in 1082 severely and critically ill patients with COVID-19 between 8 December 2022 and 9 February 2023 in Shanghai, China. The final 60-day follow-up was completed on 10 April 2023. Results: Among 1082 patients (mean age, 78.0 years, 421 [38.9%] women), 139 patients (12.9%) died within 60 days. Azvudine had a 99.8% probability of improving 2-month survival (adjusted HR, 0.44 [95% credible interval, 0.24-0.79]), and Paxlovid had a 91.9% probability of improving 2-month survival (adjusted HR, 0.71 [95% credible interval, 0.44-1.14]) compared with the control. IL-6 receptor antagonist, baricitinib and a-thymosin each had a high probability of benefit (99.5%, 99.4%, and 97.5%, respectively) compared to their controls, while the probability of trail-defined statistical futility (HR > 0.83) was high for therapeutic anticoagulation (99.8%; HR, 1.64 [95% CrI, 1.06-2.50]) and glucocorticoid (91.4%; HR, 1.20 [95% CrI, 0.71-2.16]). Paxlovid, Azvudine, and therapeutic anticoagulation showed a significant reduction in disability (p < 0.05) Conclusions: Among severely and critically ill patients with COVID-19 who received 1 or more therapeutic interventions, treatment with Azvudine had a high probability of improved 60-day mortality compared with the control, indicating its potential in a resource-limited scenario. Treatment with an IL-6 receptor antagonist, baricitinib, and a-thymosin also had high probabilities of benefit in improving 2-month survival, among which a-thymosin could improve HRQoL. Treatment with Paxlovid, Azvudine, and therapeutic anticoagulation could significantly reduce disability at day 60.

Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study.

OBJECTIVE: Early identification of diabetic retinopathy (DR) is key to prioritizing therapy and preventing permanent blindness. This study aims to propose a machine learning model for DR early diagnosis using metabolomics and clinical indicators. METHODS: From 2017 to 2018, 950 participants were enrolled from two affiliated hospitals of Wenzhou Medical University and Anhui Medical University. A total of 69 matched blocks including healthy volunteers, type 2 diabetes, and DR patients were obtained from a propensity score matching-based metabolomics study. UPLC-ESI-MS/MS system was utilized for serum metabolic fingerprint data. CART decision trees (DT) were used to identify the potential biomarkers. Finally, the nomogram model was developed using the multivariable conditional logistic regression models. The calibration curve, Hosmer-Lemeshow test, receiver operating characteristic curve, and decision curve analysis were applied to evaluate the performance of this predictive model. RESULTS: The mean age of enrolled subjects was 56.7 years with a standard deviation of 9.2, and 61.4% were males. Based on the DT model, 2-pyrrolidone completely separated healthy controls from diabetic patients, and thiamine triphosphate (ThTP) might be a principal metabolite for DR detection. The developed nomogram model (including diabetes duration, systolic blood pressure and ThTP) shows an excellent quality of classification, with AUCs (95% CI) of 0.99 (0.97-1.00) and 0.99 (0.95-1.00) in training and testing sets, respectively. Furthermore, the predictive model also has a reasonable degree of calibration. CONCLUSIONS: The nomogram presents an accurate and favorable prediction for DR detection. Further research with larger study populations is needed to confirm our findings.

Development and validation of a novel nomogram for predicting the occurrence of myopia in schoolchildren: A prospective cohort study.

PURPOSE: Myopia is a major public health issue and occurs at young ages. Apart from its high prevalence, myopia results in high costs and irreversible blinding diseases. Accurate prediction of the risk of myopia onset is crucial for its precise prevention. We aimed to develop and validate an effective nomogram for predicting myopia onset in schoolchildren. DESIGN: School-based prospective cohort study. METHODS: A total of 1073 schoolchildren were enrolled from November 2014 to May 2019 in China, and were divided into the training and validation cohorts. Myopia was defined as a spherical equivalent refraction (SER) ≤-0.5 diopters. Predictors of myopia were determined through the least absolute shrinkage and selection operator regression and multivariable Cox proportional hazard model based on the training cohort. The predictive performance of the nomogram was validated internally through time-dependent receiver operating characteristic (ROC) curves, calibration plot, decision curve analysis, and Kaplan-Meier curves. RESULTS: Independent predictors at baseline including gender, SER, axial length, corneal refractive power, and positive relative accommodation were included in the nomogram prediction model. This nomogram demonstrated excellent calibration, clinical net benefit, and discrimination, with all the area under the ROC curves (AUCs) between 0.74 and 0.86 in the training and validation cohorts. The Kaplan-Meier curves showed that 3 distinct risk groups stratified through X-tile analysis were well discriminated and robust among subgroups. The Harrell's C-index and net reclassification improvement demonstrated that the nomogram substantially improved compared with previous models. An online myopia risk calculator was generated for better individual prediction. CONCLUTIONS: The nomogram provides accurate and individual prediction of myopia onset in schoolchildren. External validation is needed to verify the generalizability of this nomogram.

High-Coverage Serum Metabolomics Reveals Metabolic Pathway Dysregulation in Diabetic Retinopathy: A Propensity Score-Matched Study.

Background: Diabetic retinopathy (DR) is a major diabetes-related disease linked to metabolism. However, the cognition of metabolic pathway alterations in DR remains scarce. We aimed to corroborate alterations of metabolic pathways identified in prior studies and investigate novel metabolic dysregulations that may lead to new prevention and treatment strategies for DR. Methods: In this case-control study, we tested 613 serum metabolites in 69 pairs of type 2 diabetic patients (T2DM) with DR and propensity score-matched T2DM without DR via ultra-performance liquid chromatography-tandem mass spectrometry system. Metabolic pathway dysregulation in DR was thoroughly investigated by metabolic pathway analysis, chemical similarity enrichment analysis (ChemRICH), and integrated pathway analysis. The associations of ChemRICH-screened key metabolites with DR were further estimated with restricted cubic spline analyses. Results: A total of 89 differentially expressed metabolites were identified by paired univariate analysis and partial least squares discriminant analysis. We corroborated biosynthesis of unsaturated fatty acids, glycine, serine and threonine metabolism, glutamate and cysteine-related pathways, and nucleotide-related pathways were significantly perturbed in DR, which were identified in prior studies. We also found some novel metabolic alterations associated with DR, including the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives in DR. Conclusions: The results suggest that the metabolism disorder in DR can be better understood through integrating multiple biological knowledge databases. The progression of DR is associated with the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives.

Individual and joint effects of trehalose and glutamate on diabetic retinopathy: a propensity score-matched case-control study.

Although previous studies demonstrate that trehalose can help maintain glucose homeostasis in healthy humans, its role and joint effect with glutamate on diabetic retinopathy (DR) remain unclear. We aimed to comprehensively quantify the associations of trehalose and glutamate with DR. This study included 69 pairs of DR and matched type 2 diabetic (T2D) patients. Serum trehalose and glutamate were determined via ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry system. Covariates were collected by a standardized questionnaire, clinical examinations and laboratory assessments. Individual and joint association of trehalose and glutamate with DR were quantified by multiple conditional logistic regression models. The adjusted odds of DR averagely decreased by 86% (odds ratio (OR): 0.14; 95% CI: 0.06, 0.33) with per interquartile range increase of trehalose. Comparing with the lowest quartile, adjusted OR (95% CI) were 0.20 (0.05, 0.83), 0.14 (0.03, 0.63) and 0.01 (<0.01, 0.05) for participants in the second, third and fourth quartiles of trehalose, respectively. In addition, as compared to their counterparts, T2D patients with lower trehalose (

Whole-blood magnesium and blood lipids are individually and jointly associated with an elevated likelihood of youngsters being overweight or obese: A matched case-control study using the propensity score.

OBJECTIVES: Youngsters who are overweight or obese (YOO) have become an important global health concern. Some micronutrients may be modifiable influential factors. This study aimed to investigate the individual and joint association of whole-blood magnesium (WBMg) and total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in YOO. METHODS: This is a propensity score matching-based case-control study. YOO was defined depending on age- and sex-specific body mass index z-score, calculated with SAS macros (%group_standard and %WHO2007) from the World Health Organization website. WBMg, blood lipids, and covariates were carefully measured by trained technicians using a whole-blood, five-element, basic analyzer and atomic absorption spectrometer or automatic biochemical analyzer. Locally weighted scattered plot smoothing and multivariable conditional logistic regression models were applied to estimate the associations of WBMg and blood lipids in YOO. RESULTS: WBMg was positively associated with YOO. The adjusted likelihood of YOO significantly increased by 21% (odds ratio: 1.21; 95% confidence interval [CI], 1.10-1.33) with per-interquartile range elevation of WBMg. Compared with the 1st quartile, adjusted odds ratios among youngsters in the 2nd, 3rd, and 4th quartiles of WBMg were 1.11 (95% CI, 0.92-1.35), 1.29 (95% CI, 1.06-1.57), and 1.47 (95% CI, 1.18-1.83), respectively. Furthermore, the relationship between WBMg and YOO was moderated by lipid profiles. Compared with those having lower (< median) WBMg and TC, TG, LDL-C, or higher (≥ median) HDL-C, youngsters with both higher WBMg and TC, TG, LDL-C, or lower HDL-C had higher YOO odds, which averagely increased by 188%, 250%, 339%, and 369%, respectively. CONCLUSIONS: WBMg was an independent risk factor of YOO, and the associations were stronger among those with unhealthy blood lipids. Our findings can help to guide clinical and public health policies on the relevance of magnesium nutritional status.