Socioeconomic position, perceived weight, lifestyle risk, and multimorbidity in young adults aged 18 to 35 years: a Multi-country Study

Impact of age and gender differences in the prevalence and patterns of multimorbidity in the Thai Cohort Study

BACKGROUND

The study aims to identify the common patterns of multimorbidity and their distribution by age and gender.

METHOD

This cross-sectional study collected self-reported data from 42 785 Thai Cohort Study members through mailed questionnaires. Employing prevalence-based analysis, it identified common multimorbidity (coexistence of two or more chronic conditions) patterns, analysing the three most common patterns stratified by age and sex. P for trend (p-trend) was used to test the linear trend for associations between age and prevalence of these chronic conditions in the multimorbidity patterns.

RESULTS

Chronic conditions with the highest prevalence were related to metabolic syndromes: obesity (28.5%), hyperlipidaemia (13.2%) and hypertension (7.2%). A positive linear age-multimorbidity association was observed (p-trend = 0.0111). The 60+ participants averaged 1.20 diseases, with 33.7% multimorbidity prevalence. Hyperlipidaemia + obesity was most prevalent in the under-40 multimorbid group (38.7%). Men exhibited a higher prevalence of multimorbidity and associated patterns involving hypertension, hyperlipidaemia and obesity than women.

CONCLUSION

Metabolic syndrome components were the prominent factors driving multimorbidity. Significant age and gender differences were also revealed in multimorbidity prevalence. People aged 60+ faced high risk of multimorbidity, while younger individuals tended towards the multimorbidity pattern of obesity and hyperlipidaemia. Men were more susceptible to multimorbidity patterns associated with metabolic syndromes. Future studies for metabolic-related multimorbidity should consider these differences, addressing age and gender issues.

Analysis of Health-Related Quality of Life in Elderly Patients with Stroke Complicated by Hypertension in China Using the EQ-5D-3L Scale

Purpose

To evaluate the health-related quality of life(HRQoL)status of elderly patients with hypertensive stroke, to understand the factors influencing it, and to provide a basis for the development of health intervention policies.

Patients and Methods

This study used the EQ-5D-3L scale to assess the HRQoL among elderly patients who experienced a stroke related to high blood pressure. Various analytical methods were employed to examine the factors that influenced the patient's quality of life. Univariate analysis, Tobit regression, random forest, and XGBoost models were applied to analyze the HRQoL of the patients. Furthermore, to interpret the machine learning results, the SHAP method was utilized. This method involved assessing the importance of each feature, examining the effect of each feature on the prediction result of a single sample, and determining the impact of individual features on the overall prediction.

Results

The study found that the median health utility value for elderly patients with hypertensive stroke was 0.427, with an interquartile range of 0.186 to 0.745. The results of the Tobit regression model, Random Forest, and XGBoost model were compared. The results of the model evaluation show that the performance of the machine learning model and the Tobit regression model are not very different. The XGBoost model performs slightly better relative to the random forest model. The factors that strongly influenced the health utility value of patients included BMI, social activities, smoking, education level, alcohol consumption, urban/rural residence, annual income, physical activity level, and hours of sleep at night.

Conclusion

Health-related quality of life in hypertensive stroke patients is influenced by a variety of factors. Health-related quality of life can be positively influenced by modifying these factors and making lifestyle adjustments. Maintaining a healthy weight, being socially active, quitting smoking, improving living conditions, increasing physical activity levels and getting enough sleep are recommended. Lifestyle changes need to be developed for each individual on a case-by-case basis and by medical advice.

Self-Reported Mood and Lifestyle-Related Physical Activity of Young Adults With Major Depressive Disorder

We investigated whether mood and lifestyle-related indicators of physical health are differentially expressed according to self-reported levels of depressive symptoms among young adults with a current episode of major depression. In a cross-sectional study, we recruited 94 young adults (females = 67, 71.3%; males = 27, 28.7%; aged 18-35 years) with a current episode of major depression. We assessed their mood with the Profile of Mood States (POMS), and Beck Anxiety Inventory-(BAI), sleep with the Pittsburgh Sleep Quality Index (PSQI), physical activity with the Simple Physical Activity Questionnaire (SIMPAQ), and their cardiorespiratory fitness. Participants' depression levels were classified as follows using established cut-points: (a) Mild Depressive Symptoms (MIDS, BDI-II 14-19 points, n = 17), (b) Moderate Depressive Symptoms (MODS, BDI-II 20-28 points, n = 37) or (c) Severe Depressive Symptoms (SEDS, BDI-II 29-63 points, n = 40). As expected, we found that young adults with SEDS, when compared to those with MODS and MIDS, showed higher depressive mood on the POMS, and they exhibited greater anxiety symptoms, lower reported 'vigor' on physical activity measures, worse sleep quality as expressed by their global score sleep; daytime dysfunction; and sleep disturbance, and they showed lower cardiorespiratory fitness. Those with moderate depressive symptoms only differed from those with mild symptoms with respect to hostility, fatigue and mood disturbance. Although there was a gradient whereby worse mental and physical health indicators were more closely related to the SEDS depression categorization, while healthier indicators were associated with the MIDS category, some parameters were not different between the MDD severity groups, particularly when comparing MIDS and MODS. Clinicians treating patients with MDD should consider these factors when designing lifestyle-based interventions.

Association between body weight perception and intuitive eating among undergraduate students in China: the mediating role of body image

Background

The association between body weight perception and intuitive eating among undergraduate students in China remains insufficiently understood. In the present study, we were aimed to examine the correlation between body weight perception, body image, and intuitive eating and determine whether the link between body weight perception and intuitive eating was influenced by body image.

Methods

A total of 1,050 undergraduate students completed the survey. Participants provided self-reported demographic details and completed two structured scales. The Body Esteem Scale for Adolescents and Adults (BESAA) and the Intuitive Eating Scale-2 (IES-2) were employed to assess body image and intuitive eating. Analysis of the mediation model was conducted using version 4.1 of the PROCESS Macro. Results with a value of p less than 0.05 were deemed statistically significant.

Results

The average age of the participants was 20.08 years (SD = 1.64). Among the students, 837 (79.7%) were female, and 212 (20.3%) were male. Body image (r = -0.429, p < 0.001) and intuitive eating (r = -0.313, p < 0.001) exhibited significant negative associations with body weight perception. Furthermore, body image showed a significant positive correlation with intuitive eating (r = 0.318, p < 0.001). Significant mediating effects of body image were identified concerning intuitive eating and body weight perception in the right weight (95% bootstrap CI = 0.007, 0.040) and overweight groups (95% bootstrap CI = -0.048, -0.009). The indirect effects of body image constituted 12.19% and 15.33% of the total effects of intuitive eating in these two groups.

Conclusion

Although the indirect effects were not substantial, these outcomes shed light on the partial understanding of how body weight perception impacted intuitive eating via body image. Importantly, our findings emphasized the significance of body image and body weight perception, offering a novel insight for prospective interventions targeting undergraduate students.