Mendelian randomization analysis using multiple biomarkers of an underlying common exposure.

Mendelian randomization (MR) analysis is increasingly popular for testing the causal effect of exposures on disease outcomes using data from genome-wide association studies. In some settings, the underlying exposure, such as systematic inflammation, may not be directly observable, but measurements can be available on multiple biomarkers or other types of traits that are co-regulated by the exposure. We propose a method for MR analysis on latent exposures (MRLE), which tests the significance for, and the direction of, the effect of a latent exposure by leveraging information from multiple related traits. The method is developed by constructing a set of estimating functions based on the second-order moments of GWAS summary association statistics for the observable traits, under a structural equation model where genetic variants are assumed to have indirect effects through the latent exposure and potentially direct effects on the traits. Simulation studies show that MRLE has well-controlled type I error rates and enhanced power compared to single-trait MR tests under various types of pleiotropy. Applications of MRLE using genetic association statistics across five inflammatory biomarkers (CRP, IL-6, IL-8, TNF-α, and MCP-1) provide evidence for potential causal effects of inflammation on increasing the risk of coronary artery disease, colorectal cancer, and rheumatoid arthritis, while standard MR analysis for individual biomarkers fails to detect consistent evidence for such effects.

Comparison of predictive models using logistic regression, classification tree, and structural equation model for severe dengue.

BACKGROUND: The aim of this study was to compare the predictive performance of three statistical models-logistic regression, classification tree, and structural equation model (SEM)-in predicting severe dengue illness. METHODS/FINDINGS: We adopted modified classification of dengue illness severity based on WHO 1997 guideline. Predictive models were constructed using demographic factors and laboratory indicators on the day of fever occurrence. We developed statistical predictive models using data from two hospital cohorts in Thailand, consisting of 257 Thai children. Different predictive models for each category of severe dengue illness were developed employing logistic regression, classification tree, and SEM. The probability of discrimination of each model for severe output of disease was analyzed with external validation data sets from 55 and 700 patients not used in model development. From external validation using predictors on the day of presentation to the hospital, the area under the receiver operating characteristic curve was between 0.65 and 0.84 for the regression model. It was between 0.73 and 0.85 for SEM models. Classification tree models showed good results of sensitivity, ranging from 0.95 to 0.99. However, they showed poor specificity ranging from 0.10 to 0.44. CONCLUSIONS: Our study showed that SEM is comparable to logistic regression or classification tree, which was widely used for more severe form of dengue prediction.

Related barriers to using HIV pre-exposure prophylaxis among MSM: A multicentre cross-sectional survey.

OBJECTIVE: The objective of this study was to gain insight into the barriers hindering the use of pre-exposure prophylaxis (PrEP) among men who have sex with men (MSM) in five cities in China. METHODS: MSM were recruited via community-based organizations in an online "snowball" manner. Participants completed the questionnaire anonymously and shared it with key MSM peers (seeds) in five cities in China. Based on the results of univariate analysis, we used a structural equation model to analyse the role of PrEP knowledge awareness, PrEP counselling, and other behavioural variables on PrEP use. RESULTS: The study collected a total of 4223 valid questionnaires, and 18.2% of participants reported PrEP use. The results of the standardized total effects showed that the following paths were statistically significant (p < 0.05): from the age of first sex with men to PrEP knowledge awareness (ß = -0.113) and PrEP use (ß = 0.042); from high-risk sexual behaviour scores to PrEP counselling (ß = 0.039) and PrEP use (ß = 0.103); from the number of HIV tests in the last year to PrEP knowledge awareness (ß = 0.034), PrEP counselling (ß = 0.170), and PrEP use (ß = 0.197); from the level of self-perceived risk of HIV infection to PrEP counselling (ß = -0.115); from PrEP knowledge awareness to PrEP use (ß = -0.049); and from PrEP counselling to PrEP use (ß = 0.420). CONCLUSIONS: The proportion of PrEP use among MSM was relatively low. Age at first sex with men, number of HIV tests, high-risk sexual behaviour, and PrEP counselling had a positive effect on PrEP use, whereas PrEP knowledge awareness had an inverse effect on PrEP use.

Early-life matters: The role of fetal adrenal steroids in the relationship between cytokines within the placental circulation and cognitive development among infants in the Philippines.

Prenatal exposure to inflammation is related to the risk for cognitive impairment in offspring. However, mechanisms underlying the link between inflammatory cytokines at the maternal-fetal interface and human cognitive development are largely unknown. This study addressed this research gap by examining whether i) cytokines within the placenta are associated with different domains of neurocognitive development during infancy, and ii) if DHEA-S in cord blood mediates these associations. We also explored the role of early-life socioeconomic status (SES) in moderating the effect of fetal adrenal steroids on cognitive development in low- and middle-income country contexts. A cohort of 242 mother-infant dyads in Leyte, the Philippines participated in the study and all of them were followed from early pregnancy until 12-months. Concentrations of pro- and anti-inflammatory cytokines in the placenta, and DHEA-S in cord blood collected at delivery were evaluated. The multifactorial aspects of the infant's cognitive functioning were assessed based on the Bayley Scales of Infant Development, third edition (BSID-III). We used Structural Equation Modelling (SEM) with an orthogonal rotation to examine associated paths among latent variables of pro- and anti-inflammatory cytokines in the placenta, fetal neuroendocrine factors, and cognitive development. Pathway analyses showed that both pro- and anti-inflammatory cytokines in the placenta were indirectly related to cognitive (p < 0.05) and language developmental outcomes (p < 0.1) via DHEA-S in cord blood among the low SES group. Yet, we found no statistically significant indirect effect of pro- or anti-inflammatory cytokines on neurocognitive development among the high SES sub-sample. This study extends our understanding of how early-life socioeconomic conditions modify biological pathways underlying the relationship between prenatal factors and postpartum cognitive development.

PathGPS: discover shared genetic architecture using GWAS summary data.

The increasing availability and scale of biobanks and "omic" datasets bring new horizons for understanding biological mechanisms. PathGPS is an exploratory data analysis tool to discover genetic architectures using Genome Wide Association Studies (GWAS) summary data. PathGPS is based on a linear structural equation model where traits are regulated by both genetic and environmental pathways. PathGPS decouples the genetic and environmental components by contrasting the GWAS associations of "signal" genes with those of "noise" genes. From the estimated genetic component, PathGPS then extracts genetic pathways via principal component and factor analysis, leveraging the low-rank and sparse properties. In addition, we provide a bootstrap aggregating ("bagging") algorithm to improve stability under data perturbation and hyperparameter tuning. When applied to a metabolomics dataset and the UK Biobank, PathGPS confirms several known gene-trait clusters and suggests multiple new hypotheses for future investigations.

Identifying temporal pathways using biomarkers in the presence of latent non-Gaussian components.

Time-series data collected from a network of random variables are useful for identifying temporal pathways among the network nodes. Observed measurements may contain multiple sources of signals and noises, including Gaussian signals of interest and non-Gaussian noises, including artifacts, structured noise, and other unobserved factors (eg, genetic risk factors, disease susceptibility). Existing methods, including vector autoregression (VAR) and dynamic causal modeling do not account for unobserved non-Gaussian components. Furthermore, existing methods cannot effectively distinguish contemporaneous relationships from temporal relations. In this work, we propose a novel method to identify latent temporal pathways using time-series biomarker data collected from multiple subjects. The model adjusts for the non-Gaussian components and separates the temporal network from the contemporaneous network. Specifically, an independent component analysis (ICA) is used to extract the unobserved non-Gaussian components, and residuals are used to estimate the contemporaneous and temporal networks among the node variables based on method of moments. The algorithm is fast and can easily scale up. We derive the identifiability and the asymptotic properties of the temporal and contemporaneous networks. We demonstrate superior performance of our method by extensive simulations and an application to a study of attention-deficit/hyperactivity disorder (ADHD), where we analyze the temporal relationships between brain regional biomarkers. We find that temporal network edges were across different brain regions, while most contemporaneous network edges were bilateral between the same regions and belong to a subset of the functional connectivity network.

Causal mediation analysis with a three-dimensional image mediator.

Causal mediation analysis is increasingly abundant in biology, psychology, and epidemiology studies and so forth. In particular, with the advent of the big data era, the issue of high-dimensional mediators is becoming more prevalent. In neuroscience, with the widespread application of magnetic resonance technology in the field of brain imaging, studies on image being a mediator emerged. In this study, a novel causal mediation analysis method with a three-dimensional image mediator is proposed. We define the average casual effects under the potential outcome framework, explore several sufficient conditions for the valid identification, and develop techniques for estimation and inference. To verify the effectiveness of the proposed method, a series of simulations under various scenarios is performed. Finally, the proposed method is applied to a study on the causal effect of mother's delivery mode on child's IQ development. It is found that cesarean section may have a negative effect on intellectual performance and that this effect is mediated by white matter development. Additional prospective and longitudinal studies may be necessary to validate these emerging findings.

A latent variable mixed-effects location scale model that also considers between-person differences in the autocorrelation.

In public health research an increasing number of studies is conducted in which intensive longitudinal data is collected in an experience sampling or a daily diary design. Typically, the resulting data is analyzed with a mixed-effects model or mixed-effects location scale model because they allow one to examine a host of interesting longitudinal research questions. Here, we introduce an extension of the mixed-effects location scale model in which measurement error of the observed variables is considered by a latent factor model and in which-in addition to the mean-or location-related effects-the residual variance of the latent factor and the parameters of the autoregressive process of this latent factor can differ between persons. We show how to estimate the parameters of the model with a maximum likelihood approach, whose performance is also compared with a Bayesian approach in a small simulation study. We illustrate the models using a real data example and end with a discussion in which we suggest questions for future research.

Determining pathways of effect between correlates and outcomes of transport-related physical activity at differing timepoints across the lifecourse: A structural equation modelling approach.

Transport-related physical activity levels differ across the lifecourse; however, the nature of these differences is poorly understood. This study examined the relationship between correlates of transport-related physical activity and how they differ in strength, pathway, and direction across the lifecourse. Structural Equation Modelling assessed relationships between correlates (e.g., age, smoking, education) and transport-related physical activity (assessed via the International Physical Activity Questionnaire) at four timepoints of the Australian Childhood Determinants of Adult Health study: childhood (7-15y; n = 6302), early-adulthood (26-36y; n = 2700), early/mid-adulthood (31-41y; n = 1649), and mid-adulthood (36-49y; n = 1794). Several pathways were consistent across the lifecourse. Self-rated health directly associated with transport-related physical activity across all timepoints. During adulthood greater body mass index and smoking frequency were indirectly associated with lower levels of transport-related physical activity via self-rated health; similarly, lower educated adults, who smoked more frequently, and had poorer health, had lower transport-related physical activity. Urban residence was directly associated with greater transport-related physical activity in childhood and early-adulthood; having more children in early/mid- and mid-adulthood was directly associated with less transport-related physical activity. This is the first study to report pathways of direct and indirect association between correlates and transport-related physical activity at key lifecourse stages. The pathways highlighted can inform policy and practice to aid in the development of age-specific lifecourse interventions.

Time-lagged associations between two adverse childhood experiences and later-life cognitive function through educational attainment and stroke.

OBJECTIVE: Adverse childhood experiences (ACEs) have been associated with worse cognitive health in older adulthood. This study aimed to extend findings on the specificity, persistence, and pathways of associations between two ACEs and cognition by using a comprehensive neuropsychological battery and a time-lagged mediation design. METHOD: Participants were 3304 older adults in the Health and Retirement Study Harmonized Cognitive Assessment Protocol. Participants retrospectively reported whether they were exposed to parental substance abuse or experienced parental physical abuse before age 18. Factor scores derived from a battery of 13 neuropsychological tests indexed cognitive domains of episodic memory, executive functioning, processing speed, language, and visuospatial function. Structural equation models examined self-reported years of education and stroke as mediators, controlling for sociodemographics and childhood socioeconomic status. RESULTS: Parental substance abuse in childhood was associated with worse later-life cognitive function across all domains, in part via pathways involving educational attainment and stroke. Parental physical abuse was associated with worse cognitive outcomes via stroke independent of education. CONCLUSIONS: This national longitudinal study in the United States provides evidence for broad and persistent indirect associations between two ACEs and cognitive aging via differential pathways involving educational attainment and stroke. Future research should examine additional ACEs and mechanisms as well as moderators of these associations to better understand points of intervention.

Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis.

Mediation analysis aims to assess if, and how, a certain exposure influences an outcome of interest through intermediate variables. This problem has recently gained a surge of attention due to the tremendous need for such analyses in scientific fields. Testing for the mediation effect (ME) is greatly challenged by the fact that the underlying null hypothesis (i.e. the absence of MEs) is composite. Most existing mediation tests are overly conservative and thus underpowered. To overcome this significant methodological hurdle, we develop an adaptive bootstrap testing framework that can accommodate different types of composite null hypotheses in the mediation pathway analysis. Applied to the product of coefficients test and the joint significance test, our adaptive testing procedures provide type I error control under the composite null, resulting in much improved statistical power compared to existing tests. Both theoretical properties and numerical examples of the proposed methodology are discussed.

Effects of Intestinal Microbiota on the Biological Transformation of Arsenic in Zebrafish: Contribution and Mechanism.

Both the gut microbiome and their host participate in arsenic (As) biotransformation, while their exact roles and mechanisms in vivo remain unclear and unquantified. In this study, as3mt-/- zebrafish were treated with tetracycline (TET, 100 mg/L) and arsenite (iAsIII) exposure for 30 days and treated with probiotic Lactobacillus rhamnosus GG (LGG, 1 × 108 cfu/g) and iAsIII exposure for 15 days, respectively. Structural equation modeling analysis revealed that the contribution rates of the intestinal microbiome to the total arsenic (tAs) and inorganic As (iAs) metabolism approached 44.0 and 18.4%, respectively. Compared with wild-type, in as3mt-/- zebrafish, microbial richness and structure were more significantly correlated with tAs and iAs, and more differential microbes and microbial metabolic pathways significantly correlated with arsenic metabolites (P < 0.05). LGG supplement influenced the microbial communities, significantly up-regulated the expressions of genes related to As biotransformation (gss and gst) in the liver, down-regulated the expressions of oxidative stress genes (sod1, sod2, and cat) in the intestine, and increased arsenobetaine concentration (P < 0.05). Therefore, gut microbiome promotes As transformation and relieves As accumulation, playing more active roles under iAs stress when the host lacks key arsenic detoxification enzymes. LGG can promote As biotransformation and relieve oxidative stress under As exposure.

Phase-Transitions in Disgust During Self-Initiated Eating Among Adolescents With Anorexia Nervosa and Related Low-Weight Eating Disorders and Matched Controls.

BACKGROUND: Understanding the emotional context of feeding behavior may help identify causal mechanisms of food avoidance among individuals with anorexia nervosa. Although predominant food avoidance models assume fear of fat drives feeding behavior, disgust may be more theoretically and proximally relevant to moment-to-moment experiences of feeding. This study, therefore, aimed to examine affect and food avoidance using automated affect analysis from facial response by measuring time-specific transitions in disgust during a laboratory eating paradigm. We hypothesized that phase transitions in disgust would distinguish temporally self-initiated eating from food avoidance. METHODS: Sixty-three adolescents with anorexia nervosa or another low-weight eating disorder (LWED) and 27 age- and sex-matched controls were recruited as part of a larger study; 45 patients and 22 controls provided data on autonomous eating and facial affect during a laboratory meal. Dynamic structural equation models quantified moment-to-moment relationships between disgust and feeding behavior. RESULTS: Self-initiated eating was associated with greater increases in disgust, but not fear, intensity among those with LWED relative to control participants and greater disgust intensity predicted lower likelihood of self-initiated eating. DISCUSSION: Phasic transitions in disgust provide moment-to-moment evidence of affective influence on self-initiated eating and lend credibility to the hypothesis that disgust contributes to food avoidance and initiation in individuals with LWED.

Links between Aggressive Sexual Fantasies and Sexual Coercion: A Replication and Extension of a Multifactorial Model.

Current research indicates that aggressive sexual fantasies (ASF) are related to sexual aggression, above and beyond other risk factors for this behavior. There have, however, rarely been explicitly considered in multifactor models aiming to explain sexual aggression. One exception is the multifactorial Revised Confluence Model of Sexual Aggression that was replicated in two samples of male individuals who were convicted of sexual offenses and a small sample of men from the general population and evidenced a high relevance of ASF, respectively. There were, however, no further attempts to replicate the model in larger samples from the general population. We, therefore, used a subsample from the Finnish Genetics of Sexuality and Aggression project including 3269 men (age: M = 26.17 years, SD = 4.76) to do so. Cross-sectional latent structural equation models corroborated previous research and the assumption that ASF are a central component in multifactor models that aim to explain sexual aggression: ASF and antisocial behavior/aggression were equally important associates of sexual coercion when also considering adverse childhood experiences, hypersexuality, and callous-unemotional traits. Additionally, ASF mediated the links between hypersexuality, callous-unemotional traits, as well as childhood sexual abuse and sexual coercion. These links held stable when entering further risk factors, that is, distorted perceptions, rape-supportive attitudes, and violent pornography consumption into the model. Contrasting assumptions, alcohol consumption and antisocial behavior/aggression did not interact. These results illustrate the potential importance of ASF for sexual aggression. They indicate that ASF require consideration by research on sexual aggression as well as in the treatment and risk assessment of sexual perpetrators.

High prevalence of hyperuricemia and the association with metabolic syndrome in the rural areas of Southwestern China: A structural equation modeling based on the Zhuang minority cohort.

BACKGROUND AND AIMS: The prevalence of hyperuricemia (HUA) and metabolic syndrome (MetS) in the Zhuang minority had not been examined. We aimed to determine the prevalence of HUA and MetS, and explore the interrelationship among the serum uric acid to creatinine (SUA/Cr) ratio, MetS, and its components. METHODS AND RESULTS: A cross-sectional study was conducted with structured questionnaire and physical examination based on the Zhuang minority cohort. A Structural Equation Model was performed to examine the hypothesis link between the SUA/Cr ratio, MetS, and its components. 10,902 aged 35-74 years Zhuang minority adults were included. The total prevalence of HUA and MetS was 17.5% and 23.7%, respectively. The SUA/Cr ratio had a positive effect on MetS (the standardized coefficient ßr was 0.311 in males and 0.401 in females). The SUA/Cr ratio was positively associated with obesity (ßr = 0.215), dyslipidemia (ßr = 0.177), and high blood pressure (ßr = 0.034) in males and was positively associated with obesity (ßr = 0.303), dyslipidemia (ßr = 0.162), and hyperglycemia (ßr = 0.036) in females. CONCLUSIONS: The prevalence of HUA in the aged 35-74 years Zhuang minority adults was high while the prevalence of MetS was relatively low. As HUA is an earlier-onset metabolic disorder and the SUA/Cr ratio had a positive effect on MetS and its components, the prevention measures of MetS should be strengthened. And the SUA/Cr ratio can be used as an early warning sign to implement the intervention measures of MetS.

Associations of vegetable and fruit intake, physical activity, and school bullying with depressive symptoms in secondary school students: the mediating role of internet addiction.

BACKGROUND: Few studies have simultaneously focused on the associations of vegetable and fruit intake, physical activity, school bullying, and Internet addiction (IA) with depressive symptoms. This study aimed to explore the direct and indirect effects of the above factors on depressive symptoms in adolescents by constructing a structural equation model (SEM). METHODS: This study was conducted in Qingdao from September to November 2021. A total of 6195 secondary school students aged 10-19 years were included in the analysis. Information on all variables was assessed using a self-administered questionnaire. An SEM was constructed with depressive symptoms as the endogenous latent variable, IA as the mediating variable, and vegetable and fruit intake, physical activity, and school bullying as the exogenous latent variables. The standardized path coefficients (ß) were the direct effects between the latent variables, and the indirect effects were obtained by the product of direct effects between relevant latent variables. RESULTS: The median value with the interquartile range of depressive symptom scores was 7 (3,12). Vegetable and fruit intake (ß=-0.100, P<0.001) and physical activity (ß=-0.140, P<0.001) were directly negatively related to depressive symptoms. While school bullying (ß=0.138, P<0.001) and IA (ß=0.452, P<0.001) were directly positively related to depressive symptoms. IA had the greatest impact on depressive symptoms. Vegetable and fruit intake, physical activity, and school bullying could not only directly affect depressive symptoms, but also indirectly affect depressive symptoms through the mediating effect of IA, the indirect effects and 95% confidence intervals (CIs) were -0.028 (-0.051, -0.007), -0.114 (-0.148, -0.089) and 0.095 (0.060, 0.157), respectively. The results of the multi-group analysis showed that the SEM we constructed still fit in boy and girl groups. CONCLUSIONS: The results indicated that vegetable and fruit intake, physical activity, school bullying, and IA had a significant direct impact on depressive symptoms, among which IA had the greatest impact. In addition, both vegetable and fruit intake, school bullying, and physical activity indirectly affected depressive symptoms through the mediating effect of IA. The impact of IA on depressive symptoms should be given extra attention by schools and parents. This study provides a scientific and effective basis for the prevention and control of adolescent depressive symptoms.

The built environment, purpose-specific walking behaviour and overweight: evidence from Wuhan metropolis in central China.

The impact of objective and subjective environmental factors on health outcomes has been a topic of significant debate, with a growing body of research acknowledging the role of a physically active lifestyle in promoting health. However, consensus regarding their precise influence remains elusive. This study contributes to these discussions by exploring how individual health outcomes correlate with transport and leisure walking behaviours, set against both the objective and subjective aspects of environmental influences in the context of Wuhan, an inland Chinese megacity. Street view images, multi-source geospatial data and a questionnaire survey were employed to characterise the "5D + Greenery" objective and perceived characteristics of the neighbourhood environment. Multi-group structural equation modelling was utilised to unravel the complex relationship and gender heterogeneity among environmental factors, purpose-specific walking, and overweight. Our results suggest that both objective land use diversity and perceived convenience are significantly associated with overweight. The accessibility of local service facilities and visible greenery promote both transport and leisure walking. While perceived neighbourhood safety encourages transport walking, perceived walkability is positively correlated with leisure walking. Notably, leisure walking, usually considered beneficial, presents a positive association with overweight conditions, acting as a mediation. Gender disparities exist in pathways between the environment and purpose-specific walking, as well as weight. The findings lend support to the planning of an activity-supporting built environment as a crucial strategy for obesity prevention.

Effects of family support system on the self-management behaviour of patients with T2DM: a multi-centre cross-sectional study in community settings.

BACKGROUND: The burden of type 2 diabetes mellitus (T2DM) in China continues to escalate. OBJECTIVE: To investigate the impact of family support system on the self-management behaviour of patients with T2DM. METHODS: In this cross-sectional study, 1,042 participants were sampled using a multistage stratified probability-proportionate-to-size method. On-site interviews were conducted using a structured questionnaire administered by 122 family doctors from 13 community health service centres in 8 administrative districts. A structural equation model was established to investigate the impact of individual factors and family support system on the self-management behaviour of T2DM patients. Statistical analysis was performed using the SPSS 25.0 software. RESULTS: The self-management behaviour pass rate among individuals with T2DM was 40.9%. In terms of individual factors, those with a high school education level or above demonstrated higher self-management behaviour scores than those with a junior high school education level or lower. The structural equation model revealed a path of interactions among individual factors, family support system-related factors, and the self-management behaviour of patients with T2DM: Family function → Family support → Patients' self-management behaviour → Quality of life. The coefficient of the direct path from family function to family support was 0.74 (P < 0.001), while the coefficient of the direct path from family support to self-management behaviour was 0.68 (P = 0.001). CONCLUSION: There is significant room for improvement in the self-management behaviour of T2DM patients in China. Family function can enhance the self-management behaviour of T2DM patients by promoting family support.

Association between social integration and loneliness among the female migrant older adults with children: the mediating effect of social support.

BACKGROUND: The number of migrant older adults with children (MOAC) in China has been increasing in recent years, and most of them are women. This study aimed to explore the mediating effect of social support between social integration and loneliness among the female MOAC in Jinan, China. METHODS: In this study, 418 female MOAC were selected using multi-stage cluster random sampling in Jinan, Shandong Province, China. Loneliness was measured by the eight-item version of the University of California Los Angeles Loneliness Scale (ULS-8), and social support was measured by The Social Support Rating Scale (SSRS). Descriptive analyses, t-tests, ANOVA, and structural equation modeling (SEM) were used to illustrate the relationship between social integration, social support, and loneliness. RESULTS: The average scores of ULS-8 and SSRS were 12.9 ± 4.0 and 39.4 ± 5.9 among female MOAC in this study. Social integration and social support were found to be negatively related to loneliness, and the standardized direct effect was -0.20 [95% CI: -0.343 to -0.068] and -0.39 [95% CI: -0.230 to -0.033], respectively. Social support mediated the relationship between social integration and loneliness, and the indirect effect was -0.16 [95% CI: -0.252 to -0.100]. CONCLUSION: The female MOAC's loneliness was at a relatively lower level in this study. It was found that social integration was negatively associated with loneliness, and social support mediated the relationship between them. Helping female MOAC integrate into the inflow city and improving their social support could be beneficial for alleviating their loneliness.

Does digital technology make people healthier: the impact of digital use on the lifestyle of Chinese older adults.

BACKGROUND: With the arrival of the era of large-scale production, sharing and application of data, digital use has gradually changed people's daily entertainment, consumption, social interaction, learning and other behaviors in its efficient form. This paper mainly discusses whether this fast and convenient behavior leads Chinese older adults to adopt healthier lifestyles. METHODS: Using the most recent information from the Chinese Family Panel Studies (CFPS) in 2020, this paper conducted a descriptive statistical analysis on the basic situation of digital use and lifestyles among Chinese older adults and used a structural equation model to analyse the influence of frequency and types of digital use in a variety of different aspects of the real life of Chinese older adults. RESULTS: Research revealed that the quality of life of Chinese older adults improved significantly as a result of their use of digital technology. The frequency of digital use (FDU) significantly improved Chinese older adults' diet, sleep, exercise, smoking and drinking, and relieved their depression. The types of digital use (TDU) had a significant positive correlation with the lifestyle of Chinese older adults, especially in the influence of digital entertainment (DE), digital consumption (DC) and digital social interaction (DI) on the lifestyle of Chinese older adults. CONCLUSIONS: Digital use can improve the health of Chinese older adults by promoting a healthy lifestyle through various means. The findings of this study have a substantial positive impact on bridging the digital divide that Chinese older adults face, as well as fostering the integration of digital use into their healthy lifestyles.