High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study.

BACKGROUND: Mediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable. Hence, it's an essential part of high-dimensional mediation analysis (HDMA) to adjust for the potential confounders. Although the propensity score (PS) related method such as propensity score regression adjustment (PSR) and inverse probability weighting (IPW) has been proposed to tackle this problem, the characteristics with extreme propensity score distribution of the PS-based method would result in the biased estimation. METHODS: In this article, we integrated the overlapping weighting (OW) technique into HDMA workflow and proposed a concise and powerful high-dimensional mediation analysis procedure consisting of OW confounding adjustment, sure independence screening (SIS), de-biased Lasso penalization, and joint-significance testing underlying the mixture null distribution. We compared the proposed method with the existing method consisting of PS-based confounding adjustment, SIS, minimax concave penalty (MCP) variable selection, and classical joint-significance testing. RESULTS: Simulation studies demonstrate the proposed procedure has the best performance in mediator selection and estimation. The proposed procedure yielded the highest true positive rate, acceptable false discovery proportion level, and lower mean square error. In the empirical study based on the GSE117859 dataset in the Gene Expression Omnibus database using the proposed method, we found that smoking history may lead to the estimated natural killer (NK) cell level reduction through the mediation effect of some methylation markers, mainly including methylation sites cg13917614 in CNP gene and cg16893868 in LILRA2 gene. CONCLUSIONS: The proposed method has higher power, sufficient false discovery rate control, and precise mediation effect estimation. Meanwhile, it is feasible to be implemented with the presence of confounders. Hence, our method is worth considering in HDMA studies.

Outlier detection in spatial error models using modified thresholding-based iterative procedure for outlier detection approach.

BACKGROUND: Outliers, data points that significantly deviate from the norm, can have a substantial impact on statistical inference and provide valuable insights in data analysis. Multiple methods have been developed for outlier detection, however, almost all available approaches fail to consider the spatial dependence and heterogeneity in spatial data. Spatial data has diverse formats and semantics, requiring specialized outlier detection methodology to handle these unique properties. For now, there is limited research exists on robust spatial outlier detection methods designed specifically under the spatial error model (SEM) structure. METHOD: We propose the Spatial-Θ-Iterative Procedure for Outlier Detection (Spatial-Θ-IPOD), which utilizes a mean-shift vector to identify outliers within the SEM. Our method enables an effective detection of spatial outliers while also providing robust coefficient estimates. To assess the performance of our approach, we conducted extensive simulations and applied it to a real-world empirical study using life expectancy data from multiple countries. RESULTS: Simulation results showed that the masking and JD (Joint Detection) indicators of our Spatial-Θ-IPOD method outperformed several commonly used methods, even in high-dimensional scenarios, demonstrating stable performance. Conversely, the Θ-IPOD method proved to be ineffective in detecting outliers when spatial correlation was present. Moreover, our model successfully provided reliable coefficient estimation alongside outlier detection. The proposed method consistently outperformed other models (both robust and non-robust) in most cases. In the empirical study, our proposed model successfully detected outliers and provided valuable insights in the modeling process. CONCLUSIONS: Our proposed Spatial-Θ-IPOD offers an effective solution for detecting spatial outliers for SEM while providing robust coefficient estimates. Notably, our approach showcases its relative superiority even in the presence of high leverage points. By successfully identifying outliers, our method enhances the overall understanding of the data and provides valuable insights for further analysis.

Dietary vitamins, carotenoids and their sources in relation to age-related macular degeneration risk in China: a population-based case-control study.

Mechanistic studies have suggested that antioxidants have beneficial effects on age-related macular degeneration (AMD). This study aimed to investigate the association between the types and sources of dietary vitamin and carotenoid intakes and AMD risk in China. A matched case-control study of 260 AMD cases and 260 matched controls was performed. The participants were interviewed for dietary information and potential confounders, and comprehensive ophthalmic examinations were performed. Conditional logistic models were used to estimate the odds ratio (OR) and 95 % confidence interval (CI) of specific vitamins and carotenoids and their main sources. When comparing the extreme quartiles, the ORs (95 % CI) were 0·30 (0·10, 0·88) for lutein and 0·28 (0·11, 0·74) for ß-cryptoxanthin. The associations for other dietary vitamin and carotenoid intakes were generally weaker and non-significant. Higher intakes of spinach and egg, which are important sources of lutein, were associated with a reduced odds of AMD. ORs (95% CIs) comparing extreme categories were 0·42 (0·20, 0·88) for spinach and 0·52 (95% CI: 0·27, 0·98) for egg. Participants who were in the highest category of both egg intake and spinach intake had a much greater reduced odds of having AMD (OR: 0·23; 95% CI: 0·08, 0·71) than those in the lowest category of egg intake and spinach intake. In conclusion, a higher intake of lutein and lutein-rich foods was associated with a significantly decreased odds of AMD. These findings provide further evidence of the benefits of lutein and lutein-rich foods in the prevention of AMD.

Bayesian two-stage design for phase II oncology trials with binary endpoint.

In phase II oncology trials, two-stage design allowing early stopping for futility and/or efficacy is frequently used. However, this design based on frequentist statistical approaches could not guarantee a high posterior probability of attending the pre-specified clinically interesting rate from a Bayesian perspective. Here, we proposed a new Bayesian design enabling early terminating for efficacy as well as futility. In addition to the clinically uninteresting and interesting response rate, a prior distribution of response rate, the minimum posterior threshold probabilities and the lengths of the highest posterior density intervals were specified in the design. Finally, we defined the feasible design with the highest total effective predictive probability. We studied the properties of the proposed design and applied it to an oncology trial as an example. The proposed design ensured that the observed response rate fell within prespecified levels of posterior probability. The proposed design provides an alternative design to single-arm two-stage trials.

The effect of sociodemographic factors on COVID-19 incidence of 342 cities in China: a geographically weighted regression model analysis.

BACKGROUND: Since December 2019, the coronavirus disease 2019 (COVID-19) has spread quickly among the population and brought a severe global impact. However, considerable geographical disparities in the distribution of COVID-19 incidence existed among different cities. In this study, we aimed to explore the effect of sociodemographic factors on COVID-19 incidence of 342 cities in China from a geographic perspective. METHODS: Official surveillance data about the COVID-19 and sociodemographic information in China's 342 cities were collected. Local geographically weighted Poisson regression (GWPR) model and traditional generalized linear models (GLM) Poisson regression model were compared for optimal analysis. RESULTS: Compared to that of the GLM Poisson regression model, a significantly lower corrected Akaike Information Criteria (AICc) was reported in the GWPR model (61953.0 in GLM vs. 43218.9 in GWPR). Spatial auto-correlation of residuals was not found in the GWPR model (global Moran's I = - 0.005, p = 0.468), inferring the capture of the spatial auto-correlation by the GWPR model. Cities with a higher gross domestic product (GDP), limited health resources, and shorter distance to Wuhan, were at a higher risk for COVID-19. Furthermore, with the exception of some southeastern cities, as population density increased, the incidence of COVID-19 decreased. CONCLUSIONS: There are potential effects of the sociodemographic factors on the COVID-19 incidence. Moreover, our findings and methodology could guide other countries by helping them understand the local transmission of COVID-19 and developing a tailored country-specific intervention strategy.

Identification of prognostic miRNA biomarkers for predicting overall survival of colon adenocarcinoma and bioinformatics analysis: A study based on The Cancer Genome Atlas database.

OBJECT: This study was conducted to identify the prognostic microRNA (miRNA) for the prediction of survival in colon adenocarcinoma (CA). METHODS: miRNA profiling of patients with CA was downloaded from The Cancer Genome Atlas (TCGA) database. After data processing, univariate Cox regression was performed to select potential prognostic miRNAs. Least absolute shrinkage and selection operator approach was conducted to identify the key prognostic miRNA biomarkers. Log-rank test was performed to compare survival outcome between patients with different regulation type of identified miRNAs. Then, bioinformatics analysis including Gene Ontology, Disease Ontology, and pathway enrichment analysis was performed on the selected prognostic miRNAs. A nomogram was generated based on the multivariate Cox proportional hazard model to illustrate the association between the identified miRNAs and the survival of patients with colorectal cancer (CRC). All analyses were conducted with packages in the R software. RESULTS: A total of 1881 miRNAs were obtained from TCGA database in which 15 miRNAs were finally selected in multianalysis with covariates and incorporated into functional annotation analyses. Log-rank test suggested that the identified miRNAs were associated with the survival of CA. Seven out of 15 selected miRNAs were identified for the first time in CA. Bioinformatics analysis suggested that the identified miRNAs were associated with the development and progress of CRC. The association between the identified miRNAs and the survival of patients with CRC were presented in a nomogram. CONCLUSION: The seven newly identified miRNAs might be potential prognostic biomarkers for the survival of CA. Further research about the selected miRNAs were worth to conduct.

Integrated analysis identifying new lncRNA markers revealed in ceRNA network for tumor recurrence in papillary thyroid carcinoma and build of nomogram.

OBJECT: The risk of tumor recurrence is currently the focus of clinical attention in the treatment of papillary thyroid carcinoma (PTC). This study focuses on the identification of novel prognostic long noncoding RNA (lncRNA) signatures for tumor recurrence in PTC. METHOD: RNA sequencing profiling of patients with PTC was obtained from the TCGA and Gene Expression Omnibus databases. Differently expressed lncRNA, microRNA (miRNA), and messenger RNA (mRNA) signatures between patients with and without tumor recurrence were selected. The lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network for tumor recurrence in PTC was constructed to identify lncRNAs associated with tumor relapse in papillary carcinoma. Functional enrichment analysis was performed. Adjusted odds ratios were estimated to identify candidate prognostic lncRNAs considering clinical covariates. Validation analysis was conducted. Nomogram was built based on the verified prognostic lncRNAs and clinical features. RESULTS: The lncRNA-miRNA-mRNA ceRNA network for tumor recurrence in PTC was constructed. Functional enrichment analysis suggested that the identified lncRNAs were associated with PTC. Adjusted odds ratios indicated that 5 of the 16 selected lncRNAs were candidate biomarkers predicting tumor recurrence of thyroid carcinoma. Among which, TTTY10 was verified as novel prognostic markers in validation analysis. Nomogram was built based on the newly identified lncRNA biomarker and clinical covariates. CONCLUSION: In this study, lncRNA TTTY10 was identified as potential novel prognostic markers predicting tumor recurrence in PTC. It may provide useful information for future molecular and cohort studies focusing on the prognosis of PTC.

Integration analysis for novel lncRNA markers predicting tumor recurrence in human colon adenocarcinoma.

BACKGROUND: Numerous evidence has suggested that long non-coding RNA (lncRNA) acts an important role in tumor biology. This study focuses on the identification of novel prognostic lncRNA biomarkers predicting tumor recurrence in human colon adenocarcinoma. METHODS: We obtained the research data from The Cancer Genome Atlas (TCGA) database. The interaction among different expressed lncRNA, miRNA and mRNA markers between colon adenocarcinoma patients with and without tumor recurrence were verified with miRcode, starBase and miRTarBase databases. We established the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network based on the verified association between the selected markers. We performed the functional enrichment analysis to obtain better understanding of the selected lncRNAs. Then we use multivariate logistic regression to identify the prognostic lncRNA markers with covariates. We also generated a nomogram predicting tumor recurrence risk based on the identified lncRNA biomarkers and clinical covariates. RESULTS: We included 12,727 lncRNA, 1881 miRNA and 47,761 mRNA profiling and clinical features for 113 colon adenocarcinoma patients obtained from the TCGA database. After filtration, we used 37 specific lncRNAs, 60 miRNAs and 148 mRNAs in the ceRNA network analysis. We identified five lncRNAs as prognostic lncRNA markers predicting tumor recurrence in colon adenocarcinoma, in which four of them were identified for the first time. Finally, we generated a nomogram illustrating the association between the identified lncRNAs and the tumor recurrence risk in colon adenocarcinoma. CONCLUSIONS: The four newly identified lncRNA biomarkers might be potential prognostic biomarkers predicting tumor recurrence in colon adenocarcinoma. We recommend that further clinical and fundamental researches be conducted on the identified lncRNA markers.

Socioeconomic disparity in the diet quality of pregnant women in Northwest China.

BACKGROUND AND OBJECTIVES: Few studies have described the socioeconomic disparity of dietary quality in Northwest China. The present study aimed to evaluate the diet quality of pregnant women in Shaanxi province of Northwest China by using the Diet Balance Index for Pregnancy (DBI-P) and explored the relationships with socioeconomic status (SES). METHODS AND STUDY DESIGN: A cross-sectional analysis of data from 7,630 women who were pregnant during 2012-2013 was performed. Dietary intake during the whole pregnancy was assessed by FFQ within 12 months (median, 3 months; 10th-90th percentile, 0-7 months) after delivery. Diet quality evaluated by the DBI-P was related to socioeconomic factors. RESULTS: Most women had insufficient consumption of vegetables (72.27%), dairy (89.58%), meat (82.07%), fish and shrimp (92.23%), eggs (62.54%), and dietary variety (97.92%). 67.76% of women had excessive intake of grains, and 87.77% and 69.79% of participants had surplus consumption of edible oil and salt respectively. Women with higher education, occupation and household wealth index (HWI) consumed more vegetables, fruit, dairy, soybean and nuts, meat, fish and shrimp, eggs, edible oil, alcohol and dietary variety but less grains and salt. After adjusting for confounders, education, occupation and HWI were negatively associated with the level of inadequate dietary intake. Conversely, individuals with medium HWI had higher level of excessive dietary intake compared to low HWI groups. CONCLUSIONS: The diet quality of pregnant women in Northwest China was associated with SES. Socioeconomic disparities in diet quality should be considered when planning nutrition interventions for pregnant women.

Discriminating MGMT promoter methylation status in patients with glioblastoma employing amide proton transfer-weighted MRI metrics.

OBJECTIVES: To explore the feasibility of using amide proton transfer-weighted (APTw) MRI metrics as surrogate biomarkers to identify the O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in glioblastoma (GBM). METHODS: Eighteen newly diagnosed GBM patients, who were previously scanned at 3T and had a confirmed MGMT methylation status, were retrospectively analysed. For each case, a histogram analysis in the tumour mass was performed to evaluate several quantitative APTw MRI metrics. The Mann-Whitney test was used to evaluate the difference in APTw parameters between MGMT methylated and unmethylated GBMs, and the receiver-operator-characteristic analysis was further used to assess diagnostic performance. RESULTS: Ten GBMs were found to harbour a methylated MGMT promoter, and eight GBMs were unmethylated. The mean, variance, 50th percentile, 90th percentile and Width10-90 APTw values were significantly higher in the MGMT unmethylated GBMs than in the MGMT methylated GBMs, with areas under the receiver-operator-characteristic curves of 0.825, 0.837, 0.850, 0856 and 0.763, respectively, for the discrimination of MGMT promoter methylation status. CONCLUSIONS: APTw signal metrics have the potential to serve as valuable imaging biomarkers for identifying MGMT methylation status in the GBM population. KEY POINTS: • APTw-MRI is applied to predict MGMT promoter methylation status in GBMs. • GBMs with unmethylated MGMT promoter present higher APTw-MRI than methylated GBMs. • Multiple APTw histogram metrics can identify MGMT methylation status. • Mean APTw values showed the highest diagnostic accuracy (AUC = 0.825).

Efficient statistical tests to compare Youden index: accounting for contingency correlation.

Youden index is widely utilized in studies evaluating accuracy of diagnostic tests and performance of predictive, prognostic, or risk models. However, both one and two independent sample tests on Youden index have been derived ignoring the dependence (association) between sensitivity and specificity, resulting in potentially misleading findings. Besides, paired sample test on Youden index is currently unavailable. This article develops efficient statistical inference procedures for one sample, independent, and paired sample tests on Youden index by accounting for contingency correlation, namely associations between sensitivity and specificity and paired samples typically represented in contingency tables. For one and two independent sample tests, the variances are estimated by Delta method, and the statistical inference is based on the central limit theory, which are then verified by bootstrap estimates. For paired samples test, we show that the estimated covariance of the two sensitivities and specificities can be represented as a function of kappa statistic so the test can be readily carried out. We then show the remarkable accuracy of the estimated variance using a constrained optimization approach. Simulation is performed to evaluate the statistical properties of the derived tests. The proposed approaches yield more stable type I errors at the nominal level and substantially higher power (efficiency) than does the original Youden's approach. Therefore, the simple explicit large sample solution performs very well. Because we can readily implement the asymptotic and exact bootstrap computation with common software like R, the method is broadly applicable to the evaluation of diagnostic tests and model performance.

Validation of the Chinese version of the FOUR score in the assessment of neurosurgical patients with different level of consciousness.

BACKGROUND: The Glasgow Coma Scale (GCS) is currently the most widely used scoring system for comatose patients. A decade ago, the Full Outline of Unresponsiveness (FOUR) score was devised to better capture four functional aspects of consciousness (eye, motor responses, brainstem reflexes, and respiration). This study aimed to validate the Chinese version of the FOUR score in patients with different levels of consciousness. METHODS: The study had two phases: (1) translation of the FOUR score, and (2) assessment of its reliability and validity. The Chinese version of the FOUR score was developed according to a standardized protocol. One hundred-twenty consecutive patients with acute brain damage, admitted to Nanfang Hospital (Southern Medical University, Guangdong, China) from November 2014 to February 2015, were enrolled. The inter-rater agreement for the FOUR score and GCS was evaluated using intraclass correlation coefficient (ICC). Receiver operating characteristic (ROC) curves were established to determine the scales' abilities to predict outcome. RESULTS: The rater agreement was excellent both for FOUR (ICC = 0.970; p < 0.001) and GCS (ICC = 0.958; p < 0.001). The FOUR score yielded an excellent test-retest reliability (ICC = 0.930; p < 0.001). Spearman's correlation coefficients between GCS and the FOUR score were high: r = 0.932, first rating; r = 0.887, second rating (all p < 0.001). Areas under the curve (AUC) for mortality were 0.834 (95 % CI, 0.740-0.928) and 0.815 (95 % CI, 0.723-0.908) for the FOUR score and GCS, respectively. CONCLUSIONS: The Chinese version of the FOUR score is a reliable scale for evaluating the level of consciousness in patients with acute brain injury.

Age-dependent Changes in Skeletal Muscle Mass and Visceral Fat Area in a Chinese Population.

OBJECTIVE: The present study was conducted to demonstrate the age-dependent changes in skeletal muscle mass and visceral fat area in a population of Chinese adults aged 30-92 years old. METHODS: A total of 6669 healthy Chinese men and 4494 healthy Chinese women aged 30-92 years old were assessed for their skeletal muscle mass and visceral fat area. RESULTS: The results showed age-dependent decreases in the total skeletal muscle mass indexes in both men and women aged 40-92 years old as well as age-dependent increases in the visceral fat area in men aged 30-92 years old and in women aged 30-80 years old. Multivariate regression models showed that the total skeletal muscle mass index was positively associated with the body mass index and negatively associated with the age and visceral fat area in both sexes. CONCLUSION: The loss of skeletal muscle mass becomes obvious at approximately 50 years of age, and the visceral fat area commences to increase at approximately 40 years of age in this Chinese population.

Association between Dietary Patterns and the Risk of Hyperemesis Gravidarum.

(1) Background: Although studies have suggested that dietary interventions may have potential benefits over conventional medical treatments, research on the association between dietary patterns and hyperemesis gravidarum (HG) in pregnant women is scarce. (2) Methods: To explore the relationship between dietary patterns and the risk of HG, a cross-sectional study was conducted in Xi'an, China from April 2021 to September 2022. Dietary intake was assessed by a semi-quantitative food-frequency questionnaire, and then factor analysis was used to derive dietary patterns. HG was defined as persistent and severe nausea and vomiting with weight loss ≥ 5%, pregnancy-unique quantification of emesis (PUQE) score ≥ 13, or hospitalization due to vomiting. Logistic regression models were used to estimate ORs and 95% CIs for HG according to dietary pattern scores. Stratified analyses and tests for interaction were performed by potential confounders. (3) Results: Of the 3122 pregnant women enrolled, 2515 individuals (mean age: 31.2 ± 3.4 years) were included in the final analysis. In total, 226 (8.9%) pregnant women were identified as having HG. Five dietary patterns were identified. After adjusting for covariates, the highest quartile of the "fish, shrimp and meat" and "egg, milk and water drinking" patterns was associated with a 37% and 58% lower risk of HG compared with the lowest quartile, respectively (p-trend < 0.05). Conversely, the highest quartile of the "beverage" pattern was associated with a 64% higher risk of HG compared with the lowest quartile (p-trend = 0.02). Furthermore, significant interactions were observed between the "egg, milk and water drinking" pattern and parity, employment status and nutritional supplement use (p-interaction < 0.05). (4) Conclusions: A diet rich in eggs, milk, seafood and unprocessed poultry and animal meat may be a protective factor against HG, while a diet high in beverages may be detrimental to HG. These associations may vary by parity, employment status and nutritional supplement use.

Association of rate pressure product trajectories at an early age with left ventricular hypertrophy in midlife: a prospective cohort study.

The joint effect of blood pressure (BP) and heart rate (HR) on cardiovascular disease is unclear. Rate pressure product (RPP), the product of systolic BP and HR, is assessed in this study. This study aimed to determine the longitudinal patterns of RPP from childhood to adulthood and to explore the relationship between RPP trajectories in early life and left ventricular hypertrophy (LVH) in midlife. We included individuals with 3 or more RPP values from 7 visits over a 30-year follow-up period in the Hanzhong Adolescent Hypertension Study cohort to fit trajectory groups and performed logistic regression to evaluate the relative risk of developing LVH. Three discrete trajectories in RPP were identified among 2412 participants assessed from childhood to middle-aged adulthood, which were tagged as "low stable," "moderate stable," and "moderate increasing". A higher waist-to-hip ratio, smoking, alcohol consumption, hypertension, diabetes, and hyperlipidemia were associated with increased RPP trajectories. The Cornell voltage product was positively correlated with RPP in 2017 and was higher in the moderate-stable and moderate-increasing groups than in the low-stable group in RPP trajectories. Compared with the low-stable group, the ORs of LVH were 1.65 (1.13, 2.92) for the moderate-stable and 3.56 (2.26, 5.44) for the moderate-increasing group. Subjects with moderate-stable and moderate-increasing trajectories showed higher probabilities of LVH at an elderly age than those in the low stable trajectory group even after adjusting for multiple cardiovascular risk factors. RPP trajectories are identifiable from childhood and are associated with LVH in midlife. Monitoring RPP trajectories from early life may be an effective approach to predict cardiovascular health status later in life.

Instrumental variable-based high-dimensional mediation analysis with unmeasured confounders for survival data in the observational epigenetic study.

Background: High dimensional mediation analysis is frequently conducted to explore the role of epigenetic modifiers between exposure and health outcome. However, the issue of high dimensional mediation analysis with unmeasured confounders for survival analysis in observational study has not been well solved. Methods: In this study, we proposed an instrumental variable based approach for high dimensional mediation analysis with unmeasured confounders in survival analysis for epigenetic study. We used the Sobel's test, the Joint test, and the Bootstrap method to test the mediation effect. A comprehensive simulation study was conducted to decide the best test strategy. An empirical study based on DNA methylation data of lung cancer patients was conducted to illustrate the performance of the proposed method. Results: Simulation study suggested that the proposed method performed well in the identifying mediating factors. The estimation of the mediation effect by the proposed approach is also reliable with less bias compared with the classical approach. In the empirical study, we identified two DNA methylation signatures including cg21926276 and cg26387355 with a mediation effect of 0.226 (95%CI: 0.108-0.344) and 0.158 (95%CI: 0.065-0.251) between smoking and lung cancer using the proposed approach. Conclusion: The proposed method obtained good performance in simulation and empirical studies, it could be an effective statistical tool for high dimensional mediation analysis.

Associations between trajectories of cardiovascular risk factor change and cognitive impairment in Chinese elderly: A nationwide cohort study.

Objectives: This study aimed to investigate the relationship between long-term trajectories of changes in cardiovascular risk factors (CVRFs) and the risk of cognitive impairment among Chinese adults over 60 years old. Methods: Data were obtained from the Chinese Longitudinal Healthy Longevity Survey 2005-2018. Cognitive function was evaluated longitudinally through the Chinese version of the Mini-Mental State Examination (C-MMSE), and cognitive impairment (C-MMSE ≤23) was used as the main outcome variable. The cardiovascular risk factors, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), pulse pressure (PP), and body mass index (BMI), were continuously measured in the follow-up duration. The patterns of trajectories of changes in CVRFs were derived from the latent growth mixture model (LGMM). The Cox regression model was used to evaluate the cognitive impairment hazard ratio (HR) across different CVRF trajectories. Results: A total of 5,164 participants aged ≥60 years with normal cognitive function at baseline were included in the study. After a median follow-up of 8 years, 2,071 participants (40.1%) developed cognitive impairment (C-MMSE ≤ 23). The four-class trajectories of SBP and BMI were obtained by means of LGMM, and the trajectories of DBP, MAP, and PP were grouped into a three-class subgroup. In the final adjusted Cox model, the lowered SBP [adjusted HR (aHR): 1.59; 95% CI: 1.17-2.16], lowered PP (aHR: 2.64; 95% CI: 1.66-4.19), and progressively obese (aHR: 1.28; 95% CI: 1.02-1.62) and stable slim (aHR: 1.13; 95% CI: 1.02-1.25) were associated with the higher risk of cognitive impairment. Low stable DBP (aHR: 0.80; 95% CI: 0.66-0.96) and elevated PP (aHR: 0.76; 95% CI: 0.63-0.92) decreased the risk for cognitive impairment among participants. Conclusion: Lowered SBP, lowered PP, progressive obesity, and stable slim increased the risk for cognitive impairment in the Chinese elderly. Low stable DBP and elevated PP were protective against cognitive impairment, but more DBP lowering and ≥25 mmHg growth in PP contributed to a higher risk of cognitive impairment. The findings have important implications for preventing cognitive impairment in elder adults based on the long-term trajectories of changes in CVRFs.

Geographical specific association between lifestyles and multimorbidity among adults in China.

The relationship between lifestyles and multimorbidity is well established, but previous studies have often neglected the role of spatial heterogeneity. Thus, this study is the first to explore this association in Chinese adults from a spatial perspective using a geographically weighted logistic regression (GWLR) model and describe the geographical characteristics across different regions. According to 2018 China Health and Retirement Longitudinal Study (CHARLS) database, a total of 7101 subjects were finally included, with 124 prefecture-level administrative regions in China. Non-spatial and GWLR model were used for analysis, and gender stratification analysis was also performed. Data were visualized through ArcGIS 10.7. The results showed that a total prevalence of approximately 5.13% of multimorbidity, and among participants with multimorbidity, the separate prevalence of hypertension, diabetes or high blood sugar, heart disease, and stroke were 4.45%, 2.32%, 3.02%, and 1.41%, respectively. The GWLR model indicated that current (OR: 1.202-1.220) and former smokers (OR: 1.168-1.206) may be important risk factors for multimorbidity in adults, especially in north and west among male. Past drinkers (OR: 1.233-1.240), especially in eastern China, contribute to the development of the multimorbidity in men but not in women. Vigorous-intensity activities (OR: 0.761-0.799) were negatively associated with multimorbidity in the west, with no gender difference. Depression (OR: 1.266-1.293) appeared to increase the risk for multimorbidity, with the weakest effects in central China and no gender difference. There was an interaction between light activities and gender (P = 0.024). The prevalence of multimorbidity differed across various areas of the province. The role of geographical variations in lifestyles and multimorbidity may provide valuable information for developing site-specific intervention strategies.

Longitudinal associations between specific types/amounts social contact and cognitive function among middle-aged and elderly Chinese: A causal inference and longitudinal targeted maximum likelihood estimation analysis.

BACKGROUND: Social contact has demonstrated associations with cognitive function, while the literature on the effect of specific social relationship subdomains on cognitive function is limited. This study aimed to examine the causal effects of specific types/amounts of social contact on cognitive function among middle-aged and elderly Chinese. METHODS: A total of 38,883 middle-aged and elderly adults from the China Health and Retirement Longitudinal Study were involved. Social contact in this study included interaction with families, taking care of grandchildren, interaction with friends, and participation in three types of social activities. We performed the linear mixed-effects model analysis with propensity score approach and the longitudinal targeted maximum likelihood-based estimation analysis after adjusting for potential covariates and confounders. RESULTS: Interaction with families, caring for grandchildren, interaction with friends and participation in social activities were all associated with cognitive z-scores. Participants who interacted with families "2-3 times a week" and "once a week" versus "almost every day" had higher cognitive z-scores. Those who interacted with friends and participated in social activities "almost every week" versus "almost daily" had higher cognitive z-scores. LIMITATIONS: The assessment of cognition was biased against people with poor education due to elements of language and mathematical testing, and against those with visual impairment. CONCLUSIONS: Social contact was associated with better cognitive function among middle-aged and elderly Chinese. Social contact "1-3 times a week" was optimal for cognitive function. More social contact in middle-aged and elderly Chinese led to less cognitive decline in later life than in their inactive peers.

Explainable Machine Learning with Pairwise Interactions for Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease Utilizing Multi-Modalities Data.

BACKGROUND: Predicting cognition decline in patients with mild cognitive impairment (MCI) is crucial for identifying high-risk individuals and implementing effective management. To improve predicting MCI-to-AD conversion, it is necessary to consider various factors using explainable machine learning (XAI) models which provide interpretability while maintaining predictive accuracy. This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different follow-up periods while providing interpretability. METHODS: This retrospective case-control study is conducted with data obtained from the ADNI database, with records of 1042 MCI patients from 2006 to 2022 included. The exposures included in this study were MRI biomarkers, cognitive scores, demographics, and clinical features. The main outcome was AD conversion from aMCI during follow-up. The EBM model was utilized to predict aMCI converting to AD based on three feature combinations, obtaining interpretability while ensuring accuracy. Meanwhile, the interaction effect was considered in the model. The three feature combinations were compared in different follow-up periods with accuracy, sensitivity, specificity, and AUC-ROC. The global and local explanations are displayed by importance ranking and feature interpretability plots. RESULTS: The five-years prediction accuracy reached 85% (AUC = 0.92) using both cognitive scores and MRI markers. Apart from accuracies, we obtained features' importance in different follow-up periods. In early stage of AD, the MRI markers play a major role, while for middle-term, the cognitive scores are more important. Feature risk scoring plots demonstrated insightful nonlinear interactive associations between selected factors and outcome. In one-year prediction, lower right inferior temporal volume (<9000) is significantly associated with AD conversion. For two-year prediction, low left inferior temporal thickness (<2) is most critical. For three-year prediction, higher FAQ scores (>4) is the most important. During four-year prediction, APOE4 is the most critical. For five-year prediction, lower right entorhinal volume (<1000) is the most critical feature. CONCLUSIONS: The established glass-box model EBMs with multimodal features demonstrated a superior ability with detailed interpretability in predicting AD conversion from MCI. Multi features with significant importance were identified. Further study may be of significance to determine whether the established prediction tool would improve clinical management for AD patients.