Subtypes of depression in a nationally representative sample

Psychological Resilience Mediates the Association Between Childhood Maltreatment and Self-Harm Phenotype in Chinese Early Adolescents

Self-harm (SH) increases significantly in early adolescence with great variability, and childhood maltreatment (CM) contributes to this increase. Understanding the developmental pathway from CM to SH could provide clues for SH prevention. This study used latent class analysis (LCA) to detect the phenotype of SH and explored the role of psychological resilience in the pathway from the CM to SH phenotype among 5724 early adolescents (52.5% male). Three interpretable phenotypes of SH were identified: low SH (57.8%), medium SH (29.0%), and high SH (13.2%). Furthermore, CM was positively associated with the SH phenotype, psychological resilience mediated the association between CM and the SH phenotype (all ps < 0.001), and a larger mediating effect was observed in the medium SH (22.41%). Our findings offer new perspectives that improving psychological resilience can be used as an efficient intervention to reduce the risk of SH among early adolescents who have experienced CM.

Tissue-specific gene expression of genome-wide significant loci associated with major depressive disorder subtypes

Major depressive disorder (MDD) is a clinically and genetically heterogeneous disorder. To reduce heterogeneity, large-scale genome-wide association studies have recently identified genome-wide significant loci associated with seven MDD subtypes. However, it was unclear in which tissues the genes near those loci are specifically expressed. We investigated whether genes related to specific MDD subtypes would be preferably expressed in a specific tissue. At 14 novel subtype-specific loci related to seven MDD subtypes-(1) non-atypical-like features MDD, (2) early-onset MDD, (3) recurrent MDD, (4) MDD with suicidal thoughts, (5) MDD without suicidal thoughts, (6) MDD with moderate impairment, and (7) postpartum depression, we investigated whether 22 genome-wide significant genetic variant-mapped genes were tissue-specifically expressed in brain, female reproductive, male specific, cardiovascular, gastrointestinal, or urinary tissues in the Genotype-Tissue Expression (GTEx) subjects (n ≤ 948). To confirm the tissue-specific expression in the GTEx, we used independent Human Protein Atlas (HPA) RNA-seq subjects (n ≤ 95). Of 22 genes, nine and five genes were tissue-specifically expressed in brain and female reproductive tissues, respectively (p < 2.27 × 10-3). RTN1, ERBB4, and AMIGO1 related to early-onset MDD, recurrent MDD, or MDD with suicidal thoughts were highly expressed in brain tissues (d = 1.19-2.71), while OAS1, LRRC9, DHRS7, PSMA5, SYPL2, and GULP1 related to non-atypical-like features MDD, early-onset MDD, MDD with suicidal thoughts, or postpartum depression were expressed at low levels in brain tissues (d = -0.17--1.48). DFNA5, CTBP2, PCNX4, SDCCAG8, and GULP1, which are related to early-onset MDD, MDD with moderate impairment, or postpartum depression, were highly expressed in female reproductive tissues (d = 0.80-2.08). Brain and female reproductive tissue-specific expression was confirmed in the HPA RNA-seq subjects. Our findings suggest that brain and female reproductive tissue-specific expression might contribute to the pathogenesis of MDD subtypes.

Fear of progression among colorectal cancer patients: a latent profile analysis

PURPOSE

Fear of progression (FoP) leads to poor clinical outcomes in colorectal cancer patients. The study aimed to clarify the profiles and influencing factors of FoP among colorectal cancer patients.

METHODS

A cross-sectional study was conducted with 409 colorectal cancer patients. Convenience sampling method was used to select colorectal cancer patients hospitalized in a tertiary-level hospital in Nanjing as the survey subjects. General information questionnaire, Fear of Progression Questionnaire-Short Form, Distress Disclosure Index, and Social Support Rating Scale were used to collect the data. Latent profile analysis was used to explore the latent profiles of FoP in colorectal cancer patients. Additionally, the influencing factors of profiles were explored by Univariate Analysis and Binomial Logistic Regression Analysis.

RESULTS

Latent profile analysis identified two subgroups of fear of disease progression: the "fear low-risk profile (83%)", and the "severe fear profile (17%)." Patients with low age, low social support utilization, first hospital admission, severe healthcare burden, and preoperative bowel symptoms were prone to severe fear of disease progression.

CONCLUSIONS

There is some heterogeneity in the level of postoperative fear of disease progression in colorectal cancer patients. Doctors and nurses should focus on patients with severe fear and take targeted preventive and psychological care for patients' fear of disease progression as early as possible according to the distribution characteristics of different categories.

Latent Profiles and Transitions of Bedtime Procrastination Among Chinese College Students: The Predictive Roles of Anxiety, Depression, Problematic Smartphone Use and Self-Control

Background

Bedtime procrastination (BP) has become an important factor affecting individual well-being. This study aimed to assess the stability and changes in BP and examine risk and protective factors.

Methods

The study recruited 1423 respondents. Latent profile analysis was used to identify subgroups of BP and latent transition analysis to determine transition probabilities for each subgroup. Logistic regression examined associations between identified classes and related factors.

Results

Three subgroups of BP were identified. In terms of stability and changes, the moderate bedtime procrastination group showed the highest stability (66%), followed by the severe bedtime procrastination group (62.4%), and the mild bedtime procrastination group had a 52% probability of switching to moderate bedtime procrastination. In terms of influencing factors, more problematic phone use (PSU) (OR: 1.08; 95% CI = 1.05-1.12), more depression (OR: 1.17; 95% CI = 1.06-1.29) and anxiety (OR: 1.16; 95% CI = 1.05-1.28) are all factors that aggravate the transition from mild to moderate sleep procrastination. Similarly, PSU (OR: 1.15; 95% CI = 1.12-1.19), anxiety (OR: 1.10; 95% CI = 1.06-1.14), and depression (OR: 1.10; 95% CI = 1.06-1.14) increased the risk of severe bedtime procrastination. Self-control emerged as a protective factor against BP.

Conclusion

This study identified three subgroups of BP at two time points and the rule of transition for each subgroup. Our findings indicate that BP were relatively stable, with some changes over time. The results also highlight the important function that PSU, depression, anxiety, and self-control can play in preventing and intervening in BP.

Latent profile analysis of depression in US adults with obstructive sleep apnea hypopnea syndrome

Objective

This study used latent profile analysis to explore the level of depression among US adults with obstructive sleep apnea hypopnea syndrome (OSAHS) symptoms and to identify different latent categories of depression to gain insight into the characteristic differences between these categories.

Methods

The data of this study were obtained from the National Health and Nutrition Examination Survey (NHANES) database, and the subjects with OSAHS symptoms were aged 18 years and older. The latent profile analysis (LPA) method was used to fit the latent depression categories in subjects with OSAHS symptoms. The chi-square test, rank sum test, and binary logistic regression were used to analyze the influencing factors of depression subgroups in subjects with OSAHS symptoms.

Results

Three latent profiles were identified: low-level (83.7%), moderate-level (14.5%) and high-level (1.8%) depression. The scores of 9 items in the high-level depression group were higher than those in the other two groups. Among them, item 4 "feeling tired or lack of energy" had the highest score in all categories.

Conclusion

Depression in subjects with OSAHS symptoms can be divided into low-level, moderate-level and high-level depression. There are significant differences among different levels of depression in gender, marital status, PIR, BMI, smoking, general health condition, sleep duration and OSAHS symptom severity.

Latent profile of the insomnia severity index: A longitudinal study

STUDY OBJECTIVES

To identify the distinct classification of insomnia symptoms and to explore their association with sleep problems and depression.

METHODS

Latent profile analysis was used to examine patterns of insomnia symptoms in two samples. Discovery and replication samples comprised 1043 (Mean age at baseline = 18.95 ± 0.93 years, 62.2% females) and 729 (Mean age at baseline = 18.71 ± 1.02 years, 66.4% females) college students, respectively. Participants completed measures of sleep problems (insomnia symptoms, sleep quality, susceptibility to insomnia, perceived consequences of insomnia, dream recall frequency, and percentage of recurring nightmares) and other psychological variables (rumination and depression). Binary logistic regression was used to analyze the effects of different types of insomnia symptoms at baseline on sleep problems and depression two years later.

RESULTS

Four classes of insomnia symptoms were identified, and classified as "non-insomnia" (class 1, 45.7%), "mild subjective symptoms but severe subjective feelings" (class 2, 23.9%), "severe subjective symptoms but mild subjective feelings" (class 3, 22.0%), and "high insomnia risk" (class 4, 8.4%), respectively. Compared with the group classified as non-insomnia group, other classifications significantly predicted insomnia two years later, only class 4 significantly predicted depression, and class 3 significantly predicted susceptibility to insomnia, after adjusting gender, insomnia, depression, and susceptibility to insomnia at baseline.

CONCLUSIONS

The findings highlighted the importance of identifying the patterns of insomnia symptoms, and the need for tailored intervention to improve sleep problems. Additionally, when screening for insomnia symptoms, simplified screening using Insomnia Severity Index (ISI) dimensions or items should be considered.

A latent profile analysis of resilience and their relation to differences in sleep quality in patients with lung cancer

PURPOSE

Sleep problems are a significant issue in patients with lung cancer, and resilience is a closely related factor. However, few studies have identified subgroups of resilience and their relationship with sleep quality. This study aimed to investigate whether there are different profiles of resilience in patients with lung cancer, to determine the sociodemographic characteristics of each subgroup, and to determine the relationship between resilience and sleep quality in different subgroups.

METHODS

A total of 303 patients with lung cancer from four tertiary hospitals in China completed the General Sociodemographic sheet, the Connor-Davidson Resilience Scale, and the Pittsburgh Sleep Quality Index. Latent profile analysis was applied to explore the latent profiles of resilience. Multivariate logistic regression was used to analyze the sociodemographic variables in each profile, and ANOVA was used to explore the relationships between resilience profiles and sleep quality.

RESULTS

The following three latent profiles were identified: the "high-resilience group" (30.2%), the "moderate-resilience group" (46.0%), and the "low-resilience group" (23.8%). Gender, place of residence, and average monthly household income significantly influenced the distribution of resilience in patients with lung cancer.

CONCLUSION

The resilience patterns of patients with lung cancer varied. It is suggested that health care providers screen out various types of patients with multiple levels of resilience and pay more attention to female, rural, and poor patients. Additionally, individual differences in resilience may provide an actionable means for addressing sleep problems.

A mitochondrial nexus in major depressive disorder: Integration with the psycho-immune-neuroendocrine network

Nervous system processes, including cognition and affective state, fundamentally rely on mitochondria. Impaired mitochondrial function is evident in major depressive disorder (MDD), reflecting cumulative detrimental influences of both extrinsic and intrinsic stressors, genetic predisposition, and mutation. Glucocorticoid 'stress' pathways converge on mitochondria; oxidative and nitrosative stresses in MDD are largely mitochondrial in origin; both initiate cascades promoting mitochondrial DNA (mtDNA) damage with disruptions to mitochondrial biogenesis and tryptophan catabolism. Mitochondrial dysfunction facilitates proinflammatory dysbiosis while directly triggering immuno-inflammatory activation via released mtDNA, mitochondrial lipids and mitochondria associated membranes (MAMs), further disrupting mitochondrial function and mitochondrial quality control, promoting the accumulation of abnormal mitochondria (confirmed in autopsy studies). Established and putative mechanisms highlight a mitochondrial nexus within the psycho-immune neuroendocrine (PINE) network implicated in MDD. Whether lowering neuronal resilience and thresholds for disease, or linking mechanistic nodes within the MDD pathogenic network, impaired mitochondrial function emerges as an important risk, a functional biomarker, providing a therapeutic target in MDD. Several treatment modalities have been demonstrated to reset mitochondrial function, which could benefit those with MDD.

The association between inflammation-related biomarkers and the subtypes of cancer-related cognitive impairment in colorectal cancer patients: A latent profile analysis

PURPOSE

Cancer-related cognitive impairment (CRCI) has garnered considerable attention, yet limited research has delved into nuanced distinctions among varying degrees of CRCI in colorectal cancer survivors. This study aimed to identify distinct subgroups based on the patterns of CRCI, assess the heterogeneity among different subgroups, and investigate the potential correlations between the subgroups of CRCI and inflammation-related biomarkers.

METHODS

268 colorectal cancer patients were enrolled in this cross-sectional study, followed by the Functional Assessment of Cancer Therapy-Cognitive Function. The determination of CRCI subgroups was accomplished by the latent profile analysis (LPA). The effects of inflammation-related biomarkers on CRCI were examined using the binary logistic regression analysis. The receiver operating characteristic (ROC) curves assessed the diagnostic efficacy of inflammation-related biomarkers.

RESULTS

Two latent profiles were identified: CRCI (n = 64, 23.88%) and non-CRCI (n = 204, 76.12%). Independent factors for CRCI in colorectal cancer patients were SIRI (OR = 3.248, 95%CI [1.197-8.807], P = 0.021) and ALI (OR = 0.962, 95%CI [0.937-0.989], P = 0.005). The areas under the curve (AUCs) for SIRI and ALI in predicting CRCI were 0.781 and 0.774, with the optimal cut-off values being 0.70 and 37.04, respectively.

CONCLUSIONS

Colorectal cancer patients exhibited divergent cognitive performance profiles, categorized into two subgroups based on LPA. SIRI and ALI were identified as independent factors for CRCI, demonstrating strong diagnostic accuracy. These two inflammation-related biomarkers may potentially be novel indicators to identify and manage the development of CRCI among colorectal cancer patients.

Latent profile and network analysis of risk perception among a sample of Chinese university students during the COVID-19 pandemic: a cross-sectional and longitudinal study

Background

The risk perception of contracting COVID-19 is an important topic for assessing and predicting COVID-19 infection and health education during the pandemic. However, studies that use latent profiles and network analysis together to measure the risk perception of COVID-19 are rare. Therefore, this study combined latent profile analysis and network analysis to measure risk perception toward COVID-19 among Chinese university students through a cross-sectional and longitudinal study.

Methods

A sample of 1,837 Chinese university students (735 males, 40%) completed the cross-sectional study with an eight-item risk perception questionnaire in January 2020, while 334 Chinese university students (111 males, 33.2%) completed the longitudinal study at three time points.

Results

A two-class model including a low risk perception class (n = 1,005, 54.7%) and a high risk perception class (n = 832, 45.3%) was selected for the cross-sectional study. Nodes rp6 ("Average people have chances of contracting COVID-19'') and rp7 ("Average people worry about catching COVID-19") had the strongest edge intensity (r = 0.491), while node rp5 ("The COVID-19 outbreak affects the whole country") had the highest strength centrality in the cross-sectional study. The risk perception of contracting COVID-19 decreased continuously at the three time points. Moreover, the network structures and global strengths had no significant differences in the longitudinal study.

Conclusions

The risk perception of contracting COVID-19 decreased continually during the COVID-19 pandemic, which indicated the importance of cultural influence and effective government management in China. In addition, university students displayed strong trust and confidence in the government's ability to fight COVID-19. The results indicate that the government should take strong measures to prevent and intervene in various risks and reinforce the public's trust through positive media communications.

The longitudinal bidirectional association between sarcopenia and cognitive function in community-dwelling older adults: Findings from the China Health and Retirement Longitudinal Study

Background

Although an association between sarcopenia and cognitive function has been demonstrated, the directional association remains unclear. The present study aimed to evaluate the longitudinal reciprocal relationship and identify the possible temporal sequence between sarcopenia and cognitive function in older Chinese adults.

Methods

Data were collected from the China Health and Retirement Longitudinal Study (CHARLS) baseline survey in 2011 and the follow-up survey in 2015. Cognitive function was measured by episodic memory and executive function. Sarcopenia status (non-sarcopenia, possible sarcopenia and sarcopenia) was defined based on the Asian Working Group for Sarcopenia 2019 criteria. Linear regression analysis and ordinal logistic regression analysis were employed to investigate the relationship between baseline sarcopenia status and follow-up cognition, as well as the association of baseline cognition with follow-up sarcopenia status, respectively. A cross-lagged panel analysis was performed to simultaneously evaluate the bidirectional association and the strength of the temporal relationship.

Results

Of 2689 participants, the median age was 65.0 years and 1249 (46.5%) were female. After adjusting for potential confounders and baseline measurements, baseline sarcopenia status was dose-dependently associated with subsequent cognitive scores (β = -0.45; P for trend = 0.001), and baseline cognitive scores (in tertiles) were also dose-dependently associated with subsequent sarcopenia status (odds ratio (OR) = 0.86; P for trend = 0.017). The cross-lagged panel analysis indicated that the standardised effect size of sarcopenia status on cognitive function (β = -0.09; P < 0.001) is larger relative to the effect of cognitive function on sarcopenia status (β = -0.05; P = 0.019).

Conclusions

There is a longitudinal, bidirectional relationship between sarcopenia status and cognitive function in older Chinese adults. Sarcopenia is likely the driving force in these dynamic associations. These findings imply that interventions in either sarcopenia or cognitive decline may have the ability to generate reciprocal benefits over time. More research is warranted to confirm these findings and to further elucidate underlying causal pathways.

Distinct dyadic quality of life profiles among patient-caregiver dyads with advanced lung cancer: a latent profile analysis

PURPOSE

This study aimed to identify the heterogeneity of dyadic quality of life (QoL) profiles, determine whether these profiles differ in terms of demographic and medical factors, neuroticism, resilience, and family functioning, and explore the combined effect of patient and caregiver neuroticism, resilience, and family functioning on dyadic QoL profiles.

METHODS

A cross-sectional study was conducted with 304 advanced lung cancer patient-caregiver dyads. Self-report questionnaires were administered to patient-caregiver dyads to assess demographic and medical characteristics, neuroticism, resilience, family functioning, and QoL.

RESULTS

The latent profile analysis identified four subgroups of dyadic QoL: patient-low-caregiver-high profile (38.82%), patient-high-caregiver-high profile (22.37%), patient-high-caregiver-low profile (19.74%), and patient-low-caregiver-low profile (19.08%). Additionally, when both patients and their caregivers had a high level of neuroticism or low level of resilience and low family functioning, compared with only member having them, there was a higher risk of poorer dyadic QoL.

CONCLUSIONS

Our study identified the four heterogeneities of dyadic QoL profiles among advanced lung cancer patient-caregiver dyads. Future dyadic interventions should consider the heterogeneity of dyadic QoL in this population and prioritize patient-caregiver dyads at risk of poor dyadic QoL. Furthermore, when high neuroticism, low resilience, or family functioning coexist between patients and their caregivers, both parties exhibit much lower dyadic QoL.

Subgroups of depressive symptoms in Korean police officers: A latent class analysis

The prevalence of depressive symptoms is common among police officers; however, studies that identify the patterns of depressive symptoms in police officers and occupational characteristics related to the specific subgroups of depressive symptoms are scarce. A total of 493 police officers in South Korea participated in this descriptive cross-sectional study between October and December 2019. Depressive symptoms were measured using the Patient Health Questionnaire-9. Latent class analysis was used to identify the subgroups of depressive symptoms. To identify the characteristics and predictors of the subgroup, χ2 tests, analysis of variance, and multinomial logistic regression analysis were performed. Four latent classes of depressive symptoms were identified: "at-risk" (10.8%), "anhedonic" (21.5%), "somatic" (17.2%), and "minimal" (50.5%). Compared to the minimal group, drinking behaviors were higher in the at-risk group (odds ratio [OR] = 1.10, 95% confidence interval [CI] [1.03, 1.11]), and working hours were greater in the somatic group (OR = 1.01, 95% CI [1.00, 1.02]). Additionally, sleep quality (OR = 1.35, 95% CI [0.82, 2.22]) and fatigue (OR = 1.02, 95% CI [1.00, 1.04]) were found to be related in the anhedonic group. This study identified the heterogeneity of depressive symptoms among police officers. It is necessary to accurately identify the factors associated with the depression subgroups of police officers to develop support strategies and prevent an increase in their depression severity. The association between risk factors such as working hours and drinking behaviors might inform strategies to reduce depression in police offers.

Depression Subtypes in Systolic Heart Failure: A Secondary Analysis From a Randomized Controlled Trial

BACKGROUND

Heart failure (HF) is associated with an elevated risk of morbidity, mortality, hospitalization, and impaired quality of life. One potential contributor to these poor outcomes is depression. Yet the effectiveness of treatments for depression in patients with HF is mixed, perhaps due to the heterogeneity of depression.

METHODS

This secondary analysis applied latent class analysis (LCA) to data from a clinical trial to classify patients with systolic HF and comorbid depression into LCA subtypes based on depression symptom severity, and then examined whether these subtypes predicted treatment response and mental and physical health outcomes at 12 months follow-up.

RESULTS

In LCA of 629 participants (mean age 63.6 ± 12.9; 43% females), we identified 4 depression subtypes: mild (prevalence 53%), moderate (30%), moderately severe (12%), and severe (5%). The mild subtype was characterized primarily by somatic symptoms of depression (e.g., energy loss, sleep disturbance, poor appetite), while the remaining LCA subtypes additionally included nonsomatic symptoms of depression (e.g., depressed mood, anhedonia, worthlessness). At 12 months, LCA subtypes with more severe depressive symptoms reported significantly greater improvements in mental quality of life and depressive symptoms compared to the LCA mild subtype, but the incidence of cardiovascular- and noncardiovascular-related readmissions, and mortality was similar among all subtypes.

CONCLUSIONS

In patients with depression and systolic heart failure those with the LCA mild depression subtype may not meet full criteria for major depressive disorder, given the overlap between HF and somatic symptoms of depression. We recommend requiring depressed mood or anhedonia as a necessary symptom for major depressive disorder in patients with HF.

Moderating role of mental health literacy on the relationship between bullying victimization during the life course and symptoms of anxiety and depression in Chinese college students

BACKGROUND

Exposure to persistent bullying victimization across multiple periods results in a high risk of worse consequences. Although amples studies support the association between bullying victimization and symptoms of anxiety and depression, whether mental health literacy can serve as a moderator on this relationship remains unknown. Therefore, the aim of this study was to examine the patterns of bullying victimization across the life course, and disentangle the moderating effect of mental health literacy between bullying victimization patterns and symptoms of anxiety and depression in Chinese college students.

METHODS

A total of 4036 college students were enrolled by cluster sampling from November 2020 to January 2021. Bullying victimization, mental health literacy, and symptoms of anxiety and depression were measured by self-report validated questionnaires. A latent class analysis was applied to identify bullying patterns. The PROCESS program was conducted to analyze whether mental health literacy moderates the link between bullying victimization patterns and symptoms of anxiety and depression.

RESULTS

Three latent patterns of bullying victimization were identified as follows: persistent bullying pattern (6.2%), moderate bullying pattern (10.5%), and low bullying pattern (83.3%). Logisitic regression analysis of anxiety and depressive symptoms indicated that compared with low bullying pattern, persistent bullying pattern had the highest risk. Specifically, mental health literacy moderated the association between bullying victimization pattern and anxiety symptoms (B = -0.039, P < 0.05).

CONCLUSIONS

It is important for practitioners to examine bullying victimization across the life course concurrently rather than a single period in isolation. Interventions and research should enhance mental health literacy to improve the mental health in college students with a history of bullying victimization.

The More, the Better? Social Capital Profiles and Adolescent Internalizing Symptoms: A Latent Profile Analysis

Past research suggests that offline and online social capital are empirically linked to adolescent psychological adjustment. However, little is known regarding the implications of distinctive combinations of social capital for adolescent internalizing symptoms. The present study aimed to examine adolescent social capital patterns and their associations with internalizing symptoms by using latent profile analysis. A cross-sectional web-based survey was conducted among 1595 Chinese adolescents (mean age = 14.30 years, 50.7% male). All adolescents completed self-report questionnaires on their perceived offline and online social capital, depressive symptoms and anxiety symptoms. Latent profile analysis revealed four profiles of social capital: (1) Low Social Capital, (2) Moderate Social Capital, (3) High Social Capital, and (4) Only High Offline Social Capital. Further, analysis of covariance demonstrated that the Only High Offline Social Capital profile had significantly fewer internalizing symptoms than other three profiles. No statistical differences of internalizing symptoms were found between the other three profiles, except that the Moderate Social Capital profile showed fewer anxiety symptoms than the Low Social Capital profile. These findings suggest that more social capital does not equal to better mental health status. The social capital profiles and their associations with adolescent internalizing symptoms may provide practitioners with meaningful implications regarding the role of offline and online social capital in adolescent psychological adjustment.

Identification of high-risk patterns of myopia in Chinese students based on four major behavioral risk factors: a latent class analysis

BACKGROUND

Myopia is prevalent in children and adolescents. Understanding the effect of multiple behaviors and their latent patterns on ocular biometric parameters may help clinicians and public health practitioners understand the behavioral risk pattern of myopia from a person-centered perspective. The purpose of this study was to identify the patterns of four major behavioral risk factors associated with myopia, including time spent outdoors, digital screen time, sleep duration, and performance of Chinese eye exercises. The study also examined the relationships between these behavioral patterns and myopia as well as ocular biometric parameters in a sample of Chinese college students.

METHODS

This study included 2014 students from the Dali University Students Eye Health Study. The average age of the subjects was 19.0 ± 0.9 years old, ranging from 15.7 to 25.1 years old. Each participant's refractive status was measured using an autorefractor without cycloplegia and ocular biometric parameters were measured using an IOL Master. Behavioral risk factors were collected using a pre-designed self-administered questionnaire. Latent class analysis (LCA) was performed to identify cluster patterns of various behaviors.

RESULTS

The prevalence of myopia was 91.8% in this population. The 2-class model was selected for the LCA based on goodness-of-fit evaluation metrics. Among the overall study sample, 41.1% and 58.9% were assigned into the high-risk and low-risk class, respectively. The risk of myopia [odds ratio (OR) = 2.12, 95% confidence interval (CI) = 1.52-3.14], high myopia (OR = 1.43, 95% CI = 1.14-1.78) and axial length/corneal radius (AL/CR) ratio of more than 3.0 (OR = 1.82, 95% CI = 1.22-2.72) were significantly higher in the high-risk compared with low-risk class.

CONCLUSIONS

Chinese university students showed differential risks of myopia and could be subdivided into high- and low-risk clusters based on four behavioral variables.

Profiles of depressive symptoms in Peru: An 8-year analysis in population-based surveys

Background Profiles of depressive symptoms have been described due to heterogeneity in symptomatology and presentation. In our study, we estimate depressive symptom profiles and relate these symptom profiles to risk factors in the Peruvian population. Methods We carried out an observational study based on the Peruvian Demographic and Health Survey (2014-2022). Men and women aged 15 years and older living in urban and rural areas in all regions of Peru were included. The Patient Health Questionnaire-9 was used to define depressive symptom profiles. We estimated latent class models to define the profiles and performed a Poisson regression analysis to determine the associated factors. Results A total of 259,655 participants were included. The three-class model was found to be the most appropriate, and the classes were defined according to the severity of depressive symptoms (moderate-severe symptoms, mild symptoms, and without depressive symptoms). Also, it was found that the three classes identified have not changed during the years of evaluations, presenting very similar prevalence over the years. In addition, women are more likely than men to belong to a class with more severe depressive symptoms; and the older the age, the higher the probability of belonging to a class with greater severity of depressive symptoms. Conclusions Our study found that at the population level in Peru, depressive symptoms are grouped into three classes according to the intensity of the symptomatology present (no symptoms, mild symptoms and moderate-severe symptoms).

Symptoms of depression and anxiety in Chinese adolescents: heterogeneity and associations with executive function

BACKGROUND

Depression and anxiety are common symptoms associated with significant morbidity in adolescents. Few studies have explored the relationship between latent profiles of adolescent depression-anxiety symptoms and executive function (EF), which is also a major pediatric public health concern.

METHODS

The sample included 1,306 participants who were recruited from two schools in Ningxia. The Depression Self-Rating Scale for Children (DSRSC) and the Screen for Child Anxiety Related Emotional Disorders (SCARED) were used to assess the level of depression-anxiety symptoms in adolescents, and their executive function state was assessed using the Behavior Rating Inventory of Executive Function-Self-Report version (BRIEF-SR). Latent profile analysis (LPA) was carried out using Mplus 7.0 to explore the most likely number of profiles based on the subscales of DSRSC and SCARED. The relationship between adolescents' executive function and depression-anxiety symptoms were analyzed by multivariable logistic regression, and the odds ratio were used to test the impact of this relationship.

RESULTS

The LPA results show that the three-profile model was the best-fitting model for adolescent depression and anxiety symptoms. The proportions of Profile-1 ("Healthy Group"), Profile-2 ("Anxiety Disorder Group"), and Profile-3 ("Depression-Anxiety Disorder Group") were 61.4%, 23.9%, and 14.7%, respectively. Additional analyses using multivariable logistic regression suggested that poor shifting capacity and emotional control were significantly more likely to be classified into the depression and/or anxiety groups, and worse working memory, task completion, and better inhibition were significantly more likely to be classified into the anxiety group.

CONCLUSIONS

The findings contribute to our understanding of the heterogeneity of adolescents' depression-anxiety symptoms and highlight the important role of executive function in influencing mental health outcomes. These findings will guide the improvement and delivery of interventions for the treatment of anxiety and depression in adolescents, mitigating functional impairments in patients and reducing disease risk.

Supportive care needs of patients with colorectal cancer undergoing anticancer therapy: A latent class analysis

Objective

This study was aimed at identifying the potential subgroups of supportive care needs among Chinese patients with colorectal cancer (CRC) through latent class analysis (LCA) and clarifying the characteristics of patients with high needs.

Methods

From January to September 2020, a cross-sectional survey was conducted in the Oncology Department and Radiotherapy Department of four tertiary grade A hospitals in Suzhou by using the general information questionnaire and Comprehensive Needs Assessment Tool for patients with cancer. Potential subgroups of supportive care needs were identified through LCA, and the association between the subgroups and statistical variables was analyzed with chi-square tests to clarify the demographic characteristics of the high-need group. This study was not registered.

Results

A total of 403 patients with CRC were included in the survey. LCA indicated two subgroups of supportive care needs in patients with CRC: a high-need group (51.86% of patients) and a low-need group (48.14% patients). In both groups, the probability of healthcare staff and information needs was high (> 50%). Single/divorced/widowed patients had greater supportive care needs than married patients, and patients with rectal cancer had greater supportive care needs than those with colon cancer.

Conclusions

Patients' healthcare staff and information needs are of critical importance. Focus should be placed on unmarried, patients with rectal cancer, as well as those receiving chemotherapy plus radiotherapy or palliative treatment.

Approaches to Learning of Preschool Children in China: A Comparison between Only Children and Non-Only Children

Preschool children are at the initial stage of individual development and at a critical period in cultivating their approaches to learning. In the context of China's frequently adjusted birth policies, further research is necessary on children's approaches to learning in families of different sizes. A questionnaire survey was administered to 5454 only child and 4632 non-only child parents from the east, middle, and west of China. The study found that children's approaches to learning generally developed well, but non-only children's approaches to learning was significantly lower than those of only children. There are four profiles of approaches to learning for both the only children and the non-only children. This study also found that gender, social skills, family income, and type of preschool exert significant influences on children's approaches to learning. Parents' educational background had a significant influence on only children's approaches to learning but had no significant influence on non-only children's approaches to learning. We provide practical implications for promoting children's approaches to learning in families of different sizes.

Variations in sociodemographic and health-related factors are linked to distinct clusters of individuals with depression based on the PHQ-9 instrument: NHANES 2007-2018

BACKGROUND

Depression is a heterogeneous disease. Identification of latent depression subgroups and differential associations across these putative groups and sociodemographic and health-related factors might pave the way toward targeted treatment of individuals.

METHODS

We used model-based clustering to identify relevant subgroups of 2900 individuals with moderate to severe depression (defined as scores ≥10 on the PHQ-9 instrument) from the NHANES cross-sectional survey. We used ANOVA and chi-squared tests to assess associations between cluster membership and sociodemographics, health-related variables, and prescription medication use.

RESULTS

We identified six latent clusters of individuals, three based on depression severity and three differentially loaded by somatic and mental components of the PHQ-9. The Severe mental depression cluster had the most individuals with low education and income (P < 0.05). We observed differences in the prevalence of numerous health conditions, with the Severe mental depression cluster showing the worst overall physical health. We observed marked differences between the clusters regarding prescription medication use: the Severe mental depression cluster had the highest use of cardiovascular and metabolic agents, while the Uniform severe depression cluster showed the highest use of central nervous system and psychotherapeutic agents.

LIMITATIONS

Due to the cross-sectional design we cannot make conclusions about causal relationships. We used self-reported data. We did not have access to a replication cohort.

CONCLUSIONS

We show that socioeconomic factors, somatic diseases, and prescription medication use are differentially associated with distinct and clinically relevant clusters of individuals with moderate to severe depression.

Heterogeneity of non-suicidal self-injury behavior in adolescents with depression: latent class analysis

BACKGROUND

Non-suicidal self-injury (NSSI) by adolescent patients with depression has become a serious public health problem. This cross-sectional study aims to identify subgroups of adolescents based on NSSI and explore the factors related to these subgroups.

METHODS

The study recruited 326 in- and out-patient adolescents (263 girls and 63 boys) aged 12 to 18 years (mean = 14.7, SD = 1.6) who had self-injured in the past year. Latent class indicators included 12 NSSI variables, as well as suicidal ideation. Logistic regression examined associations between identified classes and related factors.

RESULTS

In this study, two distinct subgroups were identified: a "high suicidal ideation NSSI group" (n = 129, 39.6%) and a "low suicidal ideation NSSI group" (n = 197, 60.4%). Depression (OR = 1.10; 95% CI, 1.05-1.16), female (OR = 2.01; 95% CI, 1.09-3.69), left-behind experience (OR = 2.08; 95% CI, 1.17-3.71), single-parent family (OR = 1.84; 95% CI, 1.11-3.04) and peer victimization (OR = 1.04; 95% CI, 1.02-1.05) increases the probability of belonging to the "high suicidal ideation NSSI group". A high level of perceived social support (OR = 0.99; 95% CI, 0.97-0.99) was a protective factor towards NSSI.

CONCLUSIONS

This study identifies two subgroups of NSSI and the factors associated with each subgroup. The early identification of high-risk groups for major NSSI in adolescents diagnosed with depression is possible due to the identification of correlating factors. Different treatment plans can be developed for different subtypes of NSSI to improve the effectiveness of prevention and intervention, promoting the healthy physical and mental development of adolescents with depression.

The Relationship Between Cumulative Ecological Risk and Problematic Smartphone Use Among Chinese College Students: Based on Latent Profile Analysis

The aim of the current study is to explore the number of classes of cumulative ecological risk with latent profile analysis. Furthermore, the relationships between the classes of cumulative ecological risk and problematic smartphone use (PSU) among 2050 Chinese college students were researched. The results showed that there are four latent classes of cumulative ecological risk among college students, namely, low risk - medium peer relationship risk group, medium risk - high belonging risk group, high identity risk - very high friend conflict risk group and high risk group, accounting for 11.71%, 30.54%, 9.75% and 48.00%, respectively. The number of the high risk group is the largest with the highest family risk, school risk, peer risk and social risk. The students in the medium risk - high belonging risk group have a particularly high risk of belonging, which should be paid attention to. The students in the low risk - medium peer relationship risk group are with a low level of ecological risk. The high identity risk - very high friend conflict risk group have the fewest students, indicating that only a few students have high school identity risk and very high risk of friend conflict. In addition, cumulative ecological risk is significantly positively correlated with PSU, and the PSU level of the high risk group is significantly higher than that of other groups. These findings indicate that there is considerable heterogeneity in cumulative ecological risk, and there is different correlation between cumulative ecological risk and PSU among college students. The current study not only enriches the biological ecological model, showing that the combined action of multiple ecological risks has a greater impact on PSU, but also provides a basis for classified intervention of college students of different classes.

The impact of age on antidepressant response: A mega-analysis of individuals with major depressive disorder

INTRODUCTION

Understanding how age affects antidepressant response in patients with major depressive disorder has been complicated by small and heterogeneous studies. Yet, understanding how age-across the lifespan-contributes to variation in response could inform treatment selection across the lifespan. This study sought to identify how age impacts antidepressant response using participant-level data from large, NIH-sponsored trials in individuals with MDD aged 12-74 years.

MATERIALS AND METHODS

Participant-level data were abstracted from three NIH-sponsored trials of pharmacotherapy (Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) Study, Treatment of Adolescent Depression Study (TADS), and the Combining Medications to Enhance Depression Outcomes Study (COMED)) in patients with MDD. Bayesian Hierarchical Models (BHMs) of individual treatment trajectories were developed using Hamiltonian Monte Carlo No U-Turn Sampling. The individual trajectory of improvement in depressive symptoms (Clinical Global Impression-Severity [CGI-S] and CGI-S equivalent from COMED) was modeled across studies and across individuals with logarithmic trend "random effects" coefficients BHMs. Age and sex (and their interaction) were examined categorically across patients.

RESULTS

Study participants (N = 907) were 29.7 ± 17 years of age, 66.3% women, and had a mean baseline CGI-S score of 4.6 ± 0.9. Patients ≤21 years and those >55 years had slower and less response to pharmacotherapy compared to those aged 21-35. Additionally, women improved more than men, and this effect did not differ across ages.

DISCUSSION

The patient's age should be considered in predicting antidepressant response, particularly in older and younger individuals who may benefit from other interventions to enhance treatment response.

Measuring childhood trauma in young adults with depression: A latent profile analysis

Childhood traumas are important risk factors for depression in young adults. However, the co-occurrence of childhood traumas is complex, and the specific effects of different types of childhood traumas on depression need further exploration. The aim of this study was to assess the co-occurrence of childhood traumas and the impact of different profiles of childhood trauma on depression. A total of 1053 young adults with depression in China participated. PHQ-9, SHAPS, GAD-7, CTQ-SF, and NLES were evaluated. Latent profile analysis (LPA) was conducted to identify profiles of childhood trauma. The effects of different childhood trauma profiles on depression, anxiety, and anhedonia were assessed using stepwise linear regression. LPA suggested three profiles: no or low childhood traumas, moderate childhood trauma with emotional abuse and childhood neglect, and high childhood trauma with high levels of all trauma types. Regression analyses suggested that high levels of emotional abuse and childhood neglect significantly affected anhedonia. Childhood adverse events cluster in young adults with depression, allowing grouping into three distinct profiles. Specific childhood trauma patterns predict anhedonia symptoms in adult depression.

The Relationship Between Psychological Flexibility and Depression, Anxiety and Stress: A Latent Profile Analysis

Purpose

To explore the potential classification of psychological flexibility (PF) among Chinese college students, analyze whether there is group heterogeneity in PF, and discuss the differences in the latent profile of PF in the negative emotions of depression, anxiety, and stress.

Methods

A total of 1769 college students were investigated using the Psychological Flexibility Questionnaire and Depression-Anxiety-Stress Self-rating Scale, and heterogeneity was tested by latent profile analysis.

Results

The PF of college students can be divided into three latent profiles: self-contradiction group (19.2%), high PF group (34.1%), and low PF group (46.7%). The scores of depression, anxiety, and stress are significantly different among the groups.

Conclusion

There is obvious group heterogeneity in the PF of college students, and they can be divided into the self-contradiction group, the high PF group, and the low PF group. The self-contradiction and low PF groups score significantly higher on the negative emotions of depression, anxiety, and stress than the high PF group.

An exploration on COVID-19 vaccination motivation patterns from the perspective of the Chaxu culture in metropolis of China: A multi-center study

Objectives

Chaxugeju is a very special Chinese culture following a self-centered and outward expanding social network, which might be a significant culture factor for vaccination behavior. This study aimed to identify the motivation pattern in China, and paid special focus on socio-economic status (SES), region, and migration.

Methods

We used a latent class analysis, with a sample of 12,432 participants collected in China from April to June, to identify the COVID-19 vaccination motivation patterns. Multinomial logistic regression models were utilized to separately explore associations between SES, migration, region, and COVID-19 vaccination motivation patterns.

Results

Three COVID-19 vaccination motivation patterns were identified: Self-protection (41.9%), Trust and Self-protection (38.5%), and Trust and Differential Protection (19.6%). Participants with higher income were more likely to be Trust and Self-protection, and when income is more than 50,000 CNY per month, they are more likely to be self-protection. Professional/white collar were more likely to be Self-protection. Participants from Shenzhen were more likely to be Trust and Differential protection. The moderating effects of gender were found for income and region. Gender does not moderate the associations of occupation or migration and COVID-19 vaccination motivation patterns.

Conclusion

Three motivational patterns were identified in which the Trust & Differential Pattern followed the traditional self-family-community Chaxu circle. However, the Chaxu motivation pattern was not the dominant one which might be weakened by SES. Migration and Shenzhen preserved the traditional social network, keeping in the trust and differential pattern. All of these factors in various cultural contexts should be considered when promoting vaccines.

Unusual Experience in the COVID-19 Pandemic: Young Children's Readjustment from Home to Preschool following School Closures in Different Risk Regions

Children's readjustment to preschool following long-term school closures during the COVID-19 pandemic merits special attention. This study examined children's preschool readjustment using a survey of 1008 teachers in a high-risk region and 1399 teachers in a fluctuating-risk region of China. Results found are as follows. (1) children's preschool readjustment was at a medium level after the long-term school closures. However, children's preschool readjustment scores in the fluctuating-risk region were significantly lower than those in the high-risk region. (2) Children in both regions were divided into four profiles based on their preschool readjustment: low-level, middle-level, upper-middle-level, and high-level groups. (3) Preschool transition practices and teachers' turnover intention are common factors relating to preschool readjustment in both regions. Teachers' professional development support impacted children's preschool readjustment only in the high-risk region. The findings inform the design of targeted interventions to help children readjust to preschool across different risk regions.

Is depression the missing link between inflammatory mediators and cancer?

Patients with cancer are at greater risk of developing depression in comparison to the general population and this is associated with serious adverse effects, such as poorer quality of life, worse prognosis and higher mortality. Although the relationship between depression and cancer is now well established, a common underlying pathophysiological mechanism between the two conditions is yet to be elucidated. Existing theories of depression, based on monoamine neurotransmitter system dysfunction, are insufficient as explanations of the disorder. Recent advances have implicated neuroinflammatory mechanisms in the etiology of depression and it has been demonstrated that inflammation at a peripheral level may be mirrored centrally in astrocytes and microglia serving to promote chronic levels of inflammation in the brain. Three major routes to depression in cancer in which proinflammatory mediators are implicated, seem likely. Activation of the kynurenine pathway involving cytokines, increases tryptophan catabolism, resulting in diminished levels of serotonin which is widely acknowledged as being the hallmark of depression. It also results in neurotoxic effects on brain regions thought to be involved in the evolution of major depression. Proinflammatory mediators also play a crucial role in impairing regulatory glucocorticoid mediated feedback of the hypothalamic-pituitary-adrenal axis, which is activated by stress and considered to be involved in both depression and cancer. The third route is via the glutamatergic pathway, whereby glutamate excitotoxicity may lead to depression associated with cancer. A better understanding of the mechanisms underlying these dysregulated and other newly emerging pathways may provide a rationale for therapeutic targeting, serving to improve the care of cancer patients.

Distinct patterns of problematic smartphone use and related factors in Chinese college students

BACKGROUND

This study aimed to categorize different subgroups of problematic smartphone use in Chinese college students. Differences in gender and psychosocial characteristics of the categorized groups were also examined.

METHODS

A total of 1123 participants completed the Mobile Phone Addiction Index Scale, the Center for Epidemiologic Studies Depression Scale, the Perceived Social Support Scale, and the Perceived Stress Scale. Using latent profile analysis, we identified different subgroups of problematic smartphone use in college students. Multivariate logistic regression analysis was implemented to examine the relationship between latent classes and demographic and psychosocial covariates.

RESULTS

The four following latent classes were identified: a low-risk group, a moderate-risk with no evasiveness group, a moderate-risk with evasiveness group, and high-risk group that accounted for 11%, 24.1%, 35.5%, and 29.4% of the total sample, respectively. Further analysis revealed that female participants were more likely to be in the moderate-risk with evasiveness and high-risk groups, and individuals with depressed mood were more likely to be in the moderate-risk and high-risk groups.

CONCLUSIONS

Classifying college students according to the features of problematic smartphone use is potentially useful for understanding risk factors and developing targeted prevention and intervention programs.

Longitudinal Trajectories of Depressive Symptoms Among Patients With Knee Osteoarthritis: The Role of Pain Intensity

BACKGROUND

Pain is the primary symptom of knee osteoarthritis (KOA), significantly associated with depressive symptoms. Whether the early pain intensity could distinguish different trajectories of depressive symptoms is not well understood among patients with KOA.

AIMS

To identify heterogeneous depressive symptoms trajectories among patients with KOA, and investigate the association between depressive symptoms subgroups and pain intensity.

DESIGN

Secondary analysis of a cohort sample.

SETTING

Three waves of data from the China Health and Retirement Longitudinal Study was collected in 28 provinces across China.

PARTICIPANTS

702 patients with KOA aged ≥ 45 years completed the Center for Epidemiologic Studies Depression Scale biennially from 2011 to 2015.

METHODS

Latent class growth analysis was performed to identify the optimal trajectory shape and number of classes. Multinomial logistic regression analysis was conducted to compare pain intensity across the trajectories.

RESULTS

Four distinct trajectories were identified as follows: no depressive symptoms, highly stable, decreasing, and increasing. In multivariate analysis, compared with the "no depressive symptoms" class, patients in the "highly stable" class and "increasing" class were more likely to report moderate pain (p < 0.05) and severe pain (p < 0.05). In addition, there was no significant difference in pain intensity between "no depressive symptoms" class and "decreasing" class (p > 0.05).

CONCLUSIONS

These results suggest important heterogeneity in depressive symptom trajectories among patients with KOA. Pain intensity could predict different depressive symptom trajectories in patients with KOA. Efforts to improve the depressive symptoms in patients with KOA must incorporate strategies to address pain.

Derived patterns of musculoskeletal symptoms and their relationships with ergonomic factors among electronic assembly workers: A latent class analysis

INTRODUCTION

Multi-site musculoskeletal symptoms (MSS) are considered to be more common and have more serious consequences than single-site MSS. This study aimed to determine whether derived patterns of MSS may be identified in electronic assembly workers and if extracted MSS classes are associated with personal and work-related factors.

METHOD

A cross-sectional questionnaire study was performed with 700 participating electronic assembly workers. The questionnaire included individual factors, psychosocial and physical exposures, and MSS. The derived patterns of MSS and their relationships with ergonomic factors were analyzed using latent class analysis (LCA) and multinomial logistic regression models (MLRM).

RESULTS

The 1-year prevalence of MSS affecting only one body site or two or more body sites was 14.9% and 32.7%, respectively. The results of LCA showed three distinct classes of MSS patterns, which were labelled 'MSS in most sites' (5.0%), 'MSS in neck and shoulder' (27.0%), and 'MSS in one or no site' (68.0%). The results of MLRM showed that the 'MSS in neck and shoulder' was associated with job tenure (OR 5.579, 95% CI 2.488-12.511), excessive dynamic and static loads (OR 3.868, 95% CI 1.702-8.793 and OR 5.270, 95% CI 2.020-13.747, respectively); while the 'MSS in most sites' was associated with high job demands (OR 4.528, 95% CI 1.647-12.445) and excessive dynamic loads (OR 111.554, 95% CI 4.996-2490.793).

CONCLUSIONS

The results showed unique patterns of MSS among electronic assembly workers that were associated with personal and work-related factors.

PRACTICAL APPLICATIONS

The findings highlight that the high prevalence of multi-site MSS in this group should be a focus. It also provides further evidence that LCA considering the number and location of anatomical sites involving MSS can be used to determine distinct classes of MSS patterns, which is of great significance for the epidemiological study and management of MSS in the future.

Identifying patterns of clinical conditions among high-cost older adult health care users using claims data: a latent class approach

Objectives

To identify patterns of clinical conditions among high-cost older adults health care users and explore the associations between characteristics of high-cost older adults and patterns of clinical conditions.

Methods

We analyzed data from the Shanghai Basic Social Medical Insurance Database, China. A total of 2927 older adults aged 60 years and over were included as the analysis sample. We used latent class analysis to identify patterns of clinical conditions among high-cost older adults health care users. Multinomial logistic regression models were also used to determine the associations between demographic characteristics, insurance types, and patterns of clinical conditions.

Results

Five clinically distinctive subgroups of high-cost older adults emerged. Classes included “cerebrovascular diseases” (10.6% of high-cost older adults), “malignant tumor” (9.1%), “arthrosis” (8.8%), “ischemic heart disease” (7.4%), and “other sporadic diseases” (64.1%). Age, sex, and type of medical insurance were predictors of high-cost older adult subgroups.

Conclusions

Profiling patterns of clinical conditions among high-cost older adults is potentially useful as a first step to inform the development of tailored management and intervention strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-022-01688-3.

Association between dietary patterns and stroke in patients with type 2 diabetes mellitus in China: a propensity score-matched analysis

OBJECTIVE

This study aimed to examine the impact of different dietary patterns on stroke outcomes among type 2 diabetes mellitus (T2DM) patients in China.

DESIGN

Participants were enrolled by a stratified random cluster sampling method in the study. After collecting dietary data using a quantified food frequency questionnaire, latent class analysis was used to identify dietary patterns, and propensity score matching was used to reduce confounding effects between different dietary patterns. Binary logistic regression and conditional logistic regression were used to analyze the relationship between dietary patterns and stroke in patients with T2DM.

SETTING

A cross-sectional survey available from December 2013 to January 2014.

PARTICIPANTS

A total of 13731 Chinese residents aged 18 years or over.

RESULTS

Two dietary patterns were identified: 61.2% of T2DM patients were categorized in the High-fat dietary pattern while 38.8% of patients were characterized by the Balanced dietary pattern. Compared to the High-fat dietary pattern, the Balanced dietary pattern was associated with reduced stroke risk (OR=0.63, 95%CI: 0.52-0.76, P<0.001) after adjusting for confounding factors. The protective effect of the balanced model did not differ significantly (interaction P>0.05).

CONCLUSION

This study provides sufficient evidence to support the dietary intervention strategies to prevent stroke effectively. Maintaining a Balanced dietary pattern, especially with moderate consumption of foods rich in quality protein and fresh vegetables in T2DM patients, might decrease the risk of stroke in China.

Latent profiles of emotion regulation strategies associated with alexithymia, nonsuicidal self-injury and resilience among nursing students

The present study sought to better understand the complex nature of emotion regulation in nursing students by exploring patterns of emotion regulation strategies (ERSs), and to examine the relationships between these unique profiles with alexithymia, nonsuicidal self-injury (NSSI) and resilience. A total of 1960 nursing students (M_age  = 19.56, SD = 1.13 years) were recruited. Using latent profile analysis, nursing students were classified into four profiles based on their ERS use: high reaction profile (HRP; 11.53%), medium reaction profile (MRP; 55.46%), adaptive reaction profile (ARP; 22.86%) and low reaction profile (LRP; 10.15%). This study found that relative to HRP and MRP, ARP and LRP showed a lower incidence of NSSI and alexithymia; HRP and ARP showed a higher level of resilience than MRP and LRP. Furthermore, LRP had the lowest level of resilience. This study highlights the importance of identifying the different ERS profiles among nursing students. Targeted programs are needed to enhance adaptive strategies and reduce maladaptive strategies to improve nursing students' psychological and behavioural performance.

Patterns of six behaviors and psychosomatic symptoms in adolescents: A six-province study in China

BACKGROUND

Psychosomatic symptoms are often related with behaviors. However, the association between different behaviors and their latent patterns and psychosomatic health status is unclear. Current study aimed to identify the patterns of six behaviors and explore the association between different patterns and psychosomatic symptoms in a school-based sample of Chinese adolescents.

METHODS

From November 2015 to January 2016, the study enrolled 22,628 students from six cities in China (15.36 ± 1.79 years). Six behaviors [unintentional injury (UI), non-suicidal self-injury (NSSI), suicidal behaviors (SB), drinking, smoking, screen time (ST)] and psychosomatic symptoms (psychological and physical symptoms) were measured by self-report validated questionnaires.

RESULTS

Six behaviors were all related to psychosomatic symptoms, among which SB was the strongest. Four patterns of behaviors were be identified as follows: low-risk pattern (64.0%), substance use pattern (4.5%), injury pattern (28.8%) and high-risk pattern (2.7%). Logistic regression analysis of psychological symptoms indicated that compared with low-risk pattern, high-risk pattern had the highest risk, followed by injury pattern, substance use pattern showed the lowest risk. Compared with low-risk pattern, the results of physical symptoms suggested the degree of risk was high-risk pattern, injury pattern and substance use pattern, respectively.

LIMITATIONS

Cross-sectional data were used in the study that could not evaluate causal relationships between six behaviors and psychosomatic symptoms.

CONCLUSIONS

Six behaviors and their latent patterns are related to psychosomatic symptoms among Chinese adolescents differently, so different intervention and prevention protocol need to be taken for different patterns of adolescents.

Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling

BACKGROUND

It is increasingly recognized that existing diagnostic approaches do not capture the underlying heterogeneity and complexity of psychiatric disorders such as depression. This study uses a data-driven approach to define fluid depressive states and explore how patients transition between these states in response to cognitive behavioural therapy (CBT).

METHODS

Item-level Patient Health Questionnaire (PHQ-9) data were collected from 9891 patients with a diagnosis of depression, at each CBT treatment session. Latent Markov modelling was used on these data to define depressive states and explore transition probabilities between states. Clinical outcomes and patient demographics were compared between patients starting at different depressive states.

RESULTS

A model with seven depressive states emerged as the best compromise between optimal fit and interpretability. States loading preferentially on cognitive/affective v. somatic symptoms of depression were identified. Analysis of transition probabilities revealed that patients in cognitive/affective states do not typically transition towards somatic states and vice-versa. Post-hoc analyses also showed that patients who start in a somatic depressive state are less likely to engage with or improve with therapy. These patients are also more likely to be female, suffer from a comorbid long-term physical condition and be taking psychotropic medication.

CONCLUSIONS

This study presents a novel approach for depression sub-typing, defining fluid depressive states and exploring transitions between states in response to CBT. Understanding how different symptom profiles respond to therapy will inform the development and delivery of stratified treatment protocols, improving clinical outcomes and cost-effectiveness of psychological therapies for patients with depression.

Association Between the Patterns of Five Unhealthy Behaviors and Suicidal Behaviors Among Adolescents in Six Provinces of China

BACKGROUND

In adolescents, multiple unhealthy behaviors frequently occur together and are likely to be associated with suicidal behaviors (SBs), increasing the risk of suicide. This study aimed to clarify the potential patterns of unhealthy behaviors in Chinese adolescents and to examine the associations between the different patterns of unhealthy behaviors and SBs.

METHODS

A total of 22,628 middle school students were enrolled in this study. Self-reported unhealthy behaviors and SBs were investigated using questionnaires. Latent class analysis (LCA) was performed based on five unhealthy behaviors [smoking, alcohol use (AU), diet pill use (DPU), screen time (ST), and problematic mobile phone use (PMPU)]. Multivariate logistic regressions were used to examine associations between the different patterns of unhealthy behaviors and SBs.

RESULTS

Four subgroups of unhealthy behaviors were identified by LCA, including high-risk class (smoking/AU/DPU/PMPU/ST), moderate-risk class 1 (DPU/PMPU), moderate-risk class 2 (smoking/AU/ST), and low-risk class. Compared with the low-risk class, moderate-risk class 1, moderate-risk class 2, and high-risk class had higher risks of suicidal ideation, suicide plan, and suicide attempt.

CONCLUSIONS

These findings suggested that patterns of unhealthy behaviors were related to SBs in Chinese adolescents. Accordingly, considerations of different classes of unhealthy behaviors may be essential for developing effective preventive programs.

Identifying subtypes of depression in clinician-annotated text: a retrospective cohort study

Current criteria for depression are imprecise and do not accurately characterize its distinct clinical presentations. As a result, its diagnosis lacks clinical utility in both treatment and research settings. Data-driven efforts to refine criteria have typically focused on a limited set of symptoms that do not reflect the disorder's heterogeneity. By contrast, clinicians often write about patients in depth, creating descriptions that may better characterize depression. However, clinical text is not commonly used to this end. Here we show that clinically relevant depressive subtypes can be derived from unstructured electronic health records. Five subtypes were identified amongst 18,314 patients with depression treated at a large mental healthcare provider by using unsupervised machine learning: severe-typical, psychotic, mild-typical, agitated, and anergic-apathetic. Subtypes were used to place patients in groups for validation; groups were found to be associated with future outcomes and characteristics that were consistent with the subtypes. These associations suggest that these categorizations are actionable due to their validity with respect to disease prognosis. Moreover, they were derived with automated techniques that might theoretically be widely implemented, allowing for future analyses in more varied populations and settings. Additional research, especially with respect to treatment response, may prove useful in further evaluation.

Patterns of physical activity and their relationship with depression among community-dwelling older adults in Shanghai, China: a latent class approach

Background

Few studies have explored patterns of physical activity (PA) and examined their relationship with depression among community-dwelling older adults. We aimed to identify the patterns of PA through a person-centered analytical approach and examine the association between quantity and patterns of PA, and depression among community-dwelling older adults.

Methods

We conducted a cross-sectional survey study in the Minhang district, Shanghai, China, in August 2019, and used a self-administered questionnaire to collect data through home visits. The total sample included 2525 older adults. This study used the Physical Activity Scale for the Elderly (PASE) to assess the quantity of PA in older adults. Depression was evaluated with the Geriatric Depression Scale (GDS). Latent class analysis (LCA) was used to identify subpopulations by shared item response patterns. Logistic regressions were performed to estimate the relationship between PASE score, patterns of PA, and depression. An exploratory analysis of joint levels and patterns of PA effects on depression was based on sample subgroups with combinations of levels and patterns of PA. Logistic regression was used to calculate the odds ratio for combined subgroups.

Results

Four latent classes were identified: “domestic types,” “athletic types,” “gardening/caring types,” and “walkers.” PASE scores and patterns of PA both were associated with depression. Older adults who were the most active (PASE quartile: 75–100%) and the athletic types had the strongest significant association with depression (OR = 0.19, 95% CI: 0.06–0.65), followed by those who were the most active (PASE quartile: 75–100%) and the walkers (OR = 0.28, 95% CI: 0.14–0.57) when compared with older adults with the least activity (PASE quartile: 0–25%) and domestic types.

Conclusion

This study suggests both the quantity and patterns of physical activity are associated with depressive symptoms among community-dwelling older adults. Population-level intervention should encourage community-dwelling older adults to increase their quantity of PA to reduce the risk of depression. Athletics and walkers are recommended. To develop individual-level tailored interventions, more attention should be paid to older adults who are highly engaged in gardening/caring for others.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02537-8.

Latent Profile Analysis of Perceptions and Attitudes Towards COVID-19 in a Sample of Chinese People

Background: The novel coronavirus-2019 (COVID-19) disease has spread quickly throughout China and around the world, endangering human health and life. Individuals' perceptions and attitudes as well as related health education measures may affect disease progression and prognosis during the COVID-19 outbreak. To promote and implement health education, research must focus on the perceptions and attitudes towards COVID-19 among Chinese people. The present study aimed to examine the profiles and predictive factors of the perceptions and attitudes towards COVID-19 in a sample of Chinese people.

Methods: A sample of 2,663 Chinese people comprising medical staff and members of the general public completed an online survey on Wenjuanxing. The survey measured demographic variables (e.g., gender, age, education level, and place of residence) and perceptions and attitudes towards COVID-19.

Results: Two profiles of perceptions and attitudes towards COVID-19 (positive and negative perceptions and attitudes) were identified in the sample. Place of residence during the COVID-19 pandemic and first response to COVID-19 were found to be independent predictive factors for COVID-19 related perceptions and attitudes.

Conclusion: In addition to drug therapy and mental health services, the perceptions and attitudes of Chinese people towards COVID-19 should be considered when promoting health education during the COVID-19 pandemic.

Vulnerable Older Adults' Identification, Geographic Distribution, and Policy Implications in China

With the population aging and urbanization in China, vulnerable older adults tend to show more complex characteristics, bringing great challenges to public health policies. Using China Longitudinal Aging Social Survey data 2014, this paper builds a comprehensive index system for the identification of vulnerable older adults from three dimensions, including health, economy, and social support, then divides older adults into four support levels and six small classes by using the typological method. The results show that older adults in urgent need of assistance or priority are those poor in health and economic conditions, 1.46% of them are highly vulnerable because of the lack of social support; 12.76% of them obtain a certain social support are moderately vulnerable; and 34.72% of them are slightly vulnerable with disadvantage in only one dimension. The geographic distribution of different types of vulnerable older adults varies significantly. The paper provides evidence to design more feasible and specific policies with comprehensive considerations for different types of vulnerable older adults residing in different regions.

Depression subtypes and their response to cognitive behavioral therapy: A latent transition analysis

BACKGROUND

Depression is a heterogeneous condition, with multiple possible symptom-profiles leading to the same diagnosis. Descriptive depression subtypes based on observation and theory have so far proven to have limited clinical utility.

AIM

To identify depression subtypes and to examine their time-course and prognosis using data-driven methods.

METHODS

Latent transition analysis was applied to a large (N = 8380) multi-service sample of depressed patients treated with cognitive behavioral therapy (CBT) in outpatient clinics. Patients were classed into initial latent states based on their responses to the Patient Health Questionnaire-9 of depression symptoms, and transition probabilities to other states during treatment were quantified. Qualitatively similar states were clustered into overarching depression subtypes and we statistically compared indices of treatment engagement and outcomes between subtypes using post hoc analyses.

RESULTS

Fourteen latent states were clustered into five depression subtypes: mild (2.7%), severe (9.8%), cognitive-affective (23.7%), somatic (21.4%), and typical (42.4%). These subtypes had high temporal stability, and the most common transitions during treatment were from severe toward milder states within the same subtype. Differential response to treatment was evident, with the highest improvement rate (63.6%) observed in the cognitive-affective subtype.

CONCLUSION

Replicated evidence indicates that depression subtypes are temporally stable and associated with differential response to CBT.

Association of Unhealthy Behaviors with Self-Harm in Chinese Adolescents: A Study Using Latent Class Analysis

Previous studies have demonstrated the link between individual unhealthy behaviors and self-harm, but little is known about the influence of multiple unhealthy behaviors on self-harm among adolescents. This study aims to identify the potential patterns of unhealthy behaviors and to examine their associations with self-harm, which may become a useful tool for the screening of self-harm in adolescents. A total of 22,628 middle school students (10,990 males and 11,638 females) in six cities was enrolled in this study by multistage stratified cluster sampling from November 2015 to January 2016. Latent class analysis (LCA) was performed based on five kinds of unhealthy behaviors (unhealthy losing weight (ULW), tobacco use (TU), alcohol use (AU), screen time (ST), and mobile phone dependence (MPD)). Multivariate logistic regressions were used to examine associations between identified subgroups and self-harm. Four subgroups of unhealthy behaviors were identified. Class 1 (71.2%) had the lowest engagement in unhealthy behaviors. Class 2 ((ULW/MPD), 22.3%) had a relatively high prevalence of ULW and MPD. Class 3 ((TU/AU/ST), 3.2%) had a relatively high prevalence of TU, AU, and ST. Class 4 (3.3%) consistently engaged in unhealthy behaviors. Compared to class 1, class 2 (ULW/MPD), class 3 (TU/AU/ST), and class 4 showed OR (95%CI) values of 2.101 (1.964–2.248), 2.153 (1.839–2.520), and 3.979 (3.407–4.645) (p < 0.001 for each), respectively. Class 1, class 2 (ULW/MPD), and class 3 (TU/AU/ST) engagement in unhealthy behaviors was associated with increased self-harm. These findings strongly suggested that self-harm prevention efforts focusing on multiple unhealthy behaviors should be seriously considered for early detection of self-harm.

A distress-continuum, disorder-threshold model of depression: a mixed-methods, latent class analysis study of slum-dwelling young men in Bangladesh

BACKGROUND

Binary categorical approaches to diagnosing depression have been widely criticized due to clinical limitations and potential negative consequences. In place of such categorical models of depression, a 'staged model' has recently been proposed to classify populations into four tiers according to severity of symptoms: 'Wellness;' 'Distress;' 'Disorder;' and 'Refractory.' However, empirical approaches to deriving this model are limited, especially with populations in low- and middle-income countries.

METHODS

A mixed-methods study using latent class analysis (LCA) was conducted to empirically test non-binary models to determine the application of LCA to derive the 'staged model' of depression. The study population was 18 to 29-year-old men (n = 824) from an urban slum of Bangladesh, a low resource country in South Asia. Subsequently, qualitative interviews (n = 60) were conducted with members of each latent class to understand experiential differences among class members.

RESULTS

The LCA derived 3 latent classes: (1) Severely distressed (n = 211), (2) Distressed (n = 329), and (3) Wellness (n = 284). Across the classes, some symptoms followed a continuum of severity: 'levels of strain', 'difficulty making decisions', and 'inability to overcome difficulties.' However, more severe symptoms such as 'anhedonia', 'concentration issues', and 'inability to face problems' only emerged in the severely distressed class. Qualitatively, groups were distinguished by severity of tension, a local idiom of distress.

CONCLUSIONS

The results indicate that LCA can be a useful empirical tool to inform the 'staged model' of depression. In the findings, a subset of distress symptoms was continuously distributed, but other acute symptoms were only present in the class with the highest distress severity. This suggests a distress-continuum, disorder-threshold model of depression, wherein a constellation of impairing symptoms emerge together after exceeding a high level of distress, i.e., a tipping point of tension heralds a host of depression symptoms.

Associations between depression subtype and functional impairment and treatment utilization in a national sample of adolescents

BACKGROUND

Prior studies have characterized distinct major depressive episode (MDE) subtypes among adults, yet limited evidence exists regarding variation in MDE during adolescence.

METHODS

Using 2008-2016 National Survey of Drug Use and Health data, latent class analysis (LCA) was used to characterize depression subtypes (based on symptom presentation) among 9,896 youth ages 12-17 with recent first-onset MDE. Logistic regression was used to estimate associations of MDE subtype with functional outcomes and treatment utilization, adjusting for demographic characteristics and depression severity (i.e., number of MDE diagnostic criteria and recurrence status) RESULTS: A 5-class LCA model provided optimal fit. Three distinct categories of MDE symptoms generally clustered together, which we termed "somatic," "cognitive," and "self-worth;" classes were differentiated by distinct combinations of symptoms across these 3 categories. Subtypes were characterized as: Highly Symptomatic (39% of youth); Somatic & Cognitive (24%), Somatic (22%), Diffuse Symptoms (8%), and Somatic & Self-Worth (6%). The majority of youth reported at least moderate impairment across multiple domains; subtype was a significant predictor of functional impairment. Only 34% of youth received any past-year depression-related treatment; treatment utilization was significantly higher for MDE subtypes with the highest prevalences of suicidal ideation.

LIMITATIONS

Due to cross-sectional data, we cannot establish causal directionality.

CONCLUSIONS

Subtype was significantly predictive of functional impairment and treatment utilization, above and beyond number of MDE diagnostic criteria or recurrence status. Understanding distinct profiles of adolescent depression, as well as potential differential associations with impairment, can inform prevention, diagnosis, and treatment of depression among youth.