Dataset Information

Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

ABSTRACT: Self-injurious behavior (SIB) among adolescents is an important public health issue worldwide. It is still uncertain whether homogeneous subgroups of SIB can be identified and whether constellations of SIBs can co-occur due to the high heterogeneity of these behaviors. In this study, a cross-sectional study was conducted on a large school-based sample and latent class analysis was performed (n = 10,069, mean age = 15 years) to identify SIB classes based on 11 indicators falling under direct SIB (DSIB), indirect SIB (ISIB), and suicide attempts (SAs). Social and psychological characteristics of each subgroup were examined after controlling for age and gender. Results showed that a four-class model best fit the data and each class had a distinct pattern of co-occurrence of SIBs and external measures. Class 4 (the baseline/normative group, 65.3%) had a low probability of SIB. Class 3 (severe SIB group, 3.9%) had a high probability of SIB and the poorest social and psychological status. Class 1 (DSIB+SA group, 14.2%) had similar scores for external variables compared to class 3, and included a majority of girls [odds ratio (OR) = 1.94]. Class 2 (ISIB group, 16.6%) displayed moderate endorsement of ISIB items, and had a majority of boys and older adolescents (OR = 1.51). These findings suggest that SIB is a heterogeneous entity, but it may be best explained by four homogenous subgroups that display quantitative and qualitative differences. Findings in this study will improve our understanding on SIB and may facilitate the prevention and treatment of SIB.

SUBMITTER: Xin X

PROVIDER: S-EPMC4938421 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

Xin Xiuhong X Ming Qingsen Q Zhang Jibiao J Wang Yuping Y Liu Mingli M Yao Shuqiao S

PloS one 20160708 7

Self-injurious behavior (SIB) among adolescents is an important public health issue worldwide. It is still uncertain whether homogeneous subgroups of SIB can be identified and whether constellations of SIBs can co-occur due to the high heterogeneity of these behaviors. In this study, a cross-sectional study was conducted on a large school-based sample and latent class analysis was performed (n = 10,069, mean age = 15 years) to identify SIB classes based on 11 indicators falling under direct SIB ...[more]

PMID: 27392132

Similar Datasets

Project description:It is known that health risk behaviors (HRBs) can lead to a variety of physical and mental health problems among adolescents, but few studies have paid attention to the relationship between latent classes of HRBs and adolescent diseases. The purpose of this study was to use latent class analysis (LCA) to clarify the potential subgroups of HRBs (smoking, drinking, screen time, non-suicidal self-injuries, suicidal behaviors, and unintentional injuries) and examine the association between the subgroups of HRBs and physical disorders (diarrhea, fever, cough, and vomiting) with multiple logistic regression analysis, in Chinese adolescents. Self-reported HRBs and physical disorders were used to evaluate 22,628 middle school students in six cities of China, from November 2015 to January 2016, based on a multistage stratified cluster sampling approach. The prevalence of diarrhea, fever, cough, and vomiting was 23.5%, 15.9%, 50.6%, and 10.7%, respectively. We identified four latent classes of HRBs by LCA, including low-risk class, moderate-risk class 1 (smoking, drinking, and screen time), moderate-risk class 2 (non-suicidal self-injuries and suicidal behaviors, unintentional injuries), and high-risk class (smoking, drinking, screen time, non-suicidal self-injuries, suicidal behaviors, and unintentional injuries), which were 64.0%, 4.5%, 28.8% and 2.7% of participants, respectively. Compared to the low-risk class, all other classes showed higher risk for these physical disorders (P < 0.01 for each). In particular, the high-risk class had the highest risk (diarrhea (odds ratio (OR) = 2.628, 95% confidence interval (CI) 2.219 to 3.113), fever (OR = 3.103, 95% CI 2.591 to 3.717), cough (OR = 2.142, 95% CI 1.805 to 2.541), and vomiting (OR = 3.738, 95% CI 3.081 to 4.536). In conclusion, these results indicated that heterogeneity exists in HRBs, and subgroups of HRBs were correlated to the occurrence of common physical disorders in Chinese adolescents. Therefore, multiple HRBs rather than single factors should be considered for the prevention of common physical disorders in schools.

Project description:Research into the clinical importance of spinal MRI findings in patients with low back pain (LBP) has primarily focused on single imaging findings, such as Modic changes or disc degeneration, and found only weak associations with the presence of pain. However, numerous MRI findings almost always co-exist in the lumbar spine and are often present at more than one lumbar level. It is possible that multiple MRI findings are more strongly associated with LBP than single MRI findings. Latent Class Analysis is a statistical method that has recently been tested and found useful for identifying latent classes (subgroups) of MRI findings within multivariable datasets. The purpose of this study was to investigate the association between subgroups of MRI findings and the presence of LBP in people from the general population.To identify subgroups of lumbar MRI findings with potential clinical relevance, Latent Class Analysis was initially performed on a clinical dataset of 631 patients seeking care for LBP. Subsequently, 412 participants in a general population cohort (the 'Backs on Funen' project) were statistically allocated to those existing subgroups by Latent Class Analysis, matching their MRI findings at a segmental level. The subgroups containing MRI findings from the general population were then organised into hypothetical pathways of degeneration and the association between subgroups in the pathways and the presence of LBP was tested using exact logistic regression.Six subgroups were identified in the clinical dataset and the data from the general population cohort fitted the subgroups well, with a median posterior probability of 93%-100%. These six subgroups described two pathways of increasing degeneration on upper (L1-L3) and lower (L4-L5) lumbar levels. An association with LBP was found for the subgroups describing severe and multiple degenerative MRI findings at the lower lumbar levels but none of the other subgroups were associated with LBP.Although MRI findings are common in asymptomatic people and the association between single MRI findings and LBP is often weak, our results suggest that subgroups of multiple and severe lumbar MRI findings have a stronger association with LBP than those with milder degrees of degeneration.

Project description:Background: Unhealthy dietary and lifestyle behaviors are associated with a higher prevalence of non-communicable chronic diseases and higher mortality in adults. However, there remains some uncertainty about the magnitude of the associations between lifestyle behaviors and cardiovascular factors in adolescents. Methods: We conducted a school-based cross-sectional study of 895 Chinese adolescents aged 15-19 years. They participated in a questionnaire survey, physical examination, and blood sample collection. Latent class analysis (LCA) was used to identify heterogeneous subgroups of lifestyle behaviors. A set of 12 latent class indicators, which reflected lifestyle behaviors including dietary habits, physical activity, sleep duration, screen time, and pressure perception, were included in the analysis. Logistic regression analysis was performed to determine whether the derived classes were related to a cardiometabolic risk. Results: In total, 13.7 and 5.6% of the participants were overweight and obese, respectively, and 8.4 and 14.1% reported having pre-hypertension and hypertension, respectively. A two-class model provided the best fit with a healthy lifestyle pattern (65.8%) and a sub-healthy lifestyle pattern (34.2%). There were more female participants with a healthy lifestyle (56.2 vs. 43.8%), whereas there were more males with a sub-healthy lifestyle (45.4 vs. 54.6%), (all P = 0.002). Increased risk of cardiometabolic abnormality (BMI categories, blood pressure and lipids) was not significant across lifestyle patterns, except for waist circumference (70.5 vs 69.1 cm, P = 0.044). There was no significant difference in physical activity and intake of fruit and vegetable between the two patterns. Conclusion: Primary prevention based on lifestyle modification should target patterns of behaviors at high risk in adolescents. Due to the complex effect of lifestyle clusters on cardiometabolic risks, well-designed and prospective studies in adolescents are needed in the future.

Project description:Background: Current evidence suggests that the information needs of people with diabetes mellitus differ across patient groups. With a view to being able to provide individualized information, this study aims to identify (i) the diabetes-related information needs of people with diabetes mellitus; (ii) different subgroups of people with specific information needs; and (iii) associated characteristics of the identified subgroups, such as sociodemographic characteristics, diabetes-related comorbidities, and well-being.Methods: This cross-sectional study was based on data from 837 respondents with diabetes mellitus who participated in the population-based KORA (Cooperative Health Research in the Augsburg Region) Health Survey 2016 in Southern Germany (KORA GEFU 4 study) (45.6% female, mean age 71.1?years, 92.8% Type 2 diabetes). Diabetes-related information needs were assessed with a questionnaire asking about patients' information needs concerning 11 diabetes-related topics, e.g. 'long-term complications' and 'treatment/therapy'. Subgroups of people with different information needs and associated characteristics were identified using latent class analysis.Results: We identified the following four classes of people with different information needs: 'high needs on all topics', 'low needs on all topics', 'moderate needs with a focus on complications and diabetes in everyday life', and 'advanced needs with a focus on social and legal aspects and diabetes research'. The classes differed significantly in age, years of education, type of diabetes, diabetes duration, diabetes-related comorbidities, smoking behaviour, diabetes education, current level of information, and time preference.Conclusions: Knowledge about different patient subgroups can be useful for tailored information campaigns or physician-patient interactions. Further research is needed to analyse health care needs in these groups, changes in information needs over the course of the disease, and prospective health outcomes.

Dataset Information

Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

Publications

Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure