The effectiveness of the "SMG" model for health-promoting lifestyles among empty nesters: a community intervention trial

Determinants and outcomes of health-promoting lifestyle among people with schizophrenia

BACKGROUND

Healthy lifestyle is an important protective factor of developing cardiovascular disease in people with schizophrenia. However, little is known about the determinants of lifestyle and its contribution to metabolic syndrome. This study aimed to explore the influencing factors of health-promoting lifestyle (HPL) and its association with metabolic syndrome among people with schizophrenia.

METHODS

A cross-sectional study was conducted in twenty-two primary health centers of Guangzhou, China between December 2022 and April 2023. A total of 538 patients with schizophrenia were recruited through convenience sampling. Self-administered scales, questionnaires, and clinical data were collected. Scales and questionnaires included social-demographic information, Health-Promoting Lifestyles Profile (HPLP-C), UCLA Loneliness Scale (ULS), and International Physical Activity Questionnaire-Short Form (IPAQ-SF). Cluster analyses were used to divide participants into two groups based on the distribution characteristics of HPLP-C scores. Logistic regression models were used to identify factors associated with HPL and the association between HPL and metabolic syndrome.

RESULTS

There were 271 participants in the high HPL group and 267 participants in the low HPL group. Logistic regression analysis revealed that loneliness posed a risk factor for high HPL, while high education and moderate-vigorous physical activity served as protective factors for high HPL. Low HPL was a risk factor for the prevalence of metabolic syndrome.

CONCLUSIONS

Promotion of high education literacy and a physically active lifestyle should be priority targets in the health management of schizophrenia. Primary healthcare providers can play a pivotal role in assisting patients to mitigate metabolic syndrome by reinforcing healthy lifestyle strategies.

Health Promoting Behaviors, Health Needs and Associated Factors among Older Adults in Jordan: A Cross-Sectional Study

BACKGROUND

Several factors affect older adults' engagement in HPBs. This study aimed to examine HPBs, health needs, and associated factors among older adults in Jordan.

METHODS

A cross-sectional study was conducted on 220 older adults at one governmental and one university hospital, which were selected using convenience sampling for geographical closeness to the researchers. All older adults with no cognitive or communication problems who attended the outpatient clinics of the two hospitals from December 2018 to April 2019 were included in the study. This time period was chosen based on the convenience of the participants and researchers. Data were collected by An Arabic version of the Health-Promoting Lifestyle Profile (HPLP) and a demographic questionnaire. The Statistical Package for Social Science (SPSS) 25.0 software was used for the descriptive and inferential analysis of the study data. The level of significance was set at P<0.05.

RESULTS

The mean score of the total HPLP was 125.33±19.09. The marital status and educational level of the participants were associated with the total HPLP (P<0.001) in all its dimensions, except for the dimension of interpersonal relations. Participants with chronic diseases had lower scores than those without diseases for the total HPLP (P<0.001) in all the six dimensions. Family income was positively correlated with the dimensions of nutrition (P=0.007) and exercise (P=0.002).

CONCLUSION

Despite the good overall mean score of older adults for total HPLP and some of its subscales, their levels of exercise and physical activity need to be promoted. The scores of older adults were related to various demographic and clinical factors.

Mapping the Chinese Version of the EORTC QLQ-BR53 Onto the EQ-5D-5L and SF-6D Utility Scores

OBJECTIVE

This study aimed to develop mapping algorithms from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-BR53, including EORTC QLQ-C30 and QLQ-BR23) onto the 5-level EQ-5D (EQ-5D-5L) and Short Form 6D (SF-6D) utility scores.

METHODS

The data were taken from 607 breast cancer patients in mainland China. The EQ-5D-5L and SF-6D instruments were scored using Chinese-specific tariffs. Three model specifications and seven statistical techniques were used to derive mapping algorithms, including ordinary least squares (OLS), Tobit, censored least absolute deviation (CLAD) model, generalized linear model (GLM), robust MM-estimator, finite mixtures of beta regression model for directly estimating health utility, and using ordered logit regression (OLOGIT) to predict response levels. A five-fold cross-validation approach was conducted to test the generalizability of each model. Two key goodness-of-fit statistics (mean absolute error and mean squared error) and three secondary statistics were employed to choose the optimal models.

RESULTS

Participants had a mean ± standard deviation (SD) age of 49.0 ± 9.8 years. The mean ± SD health state utility scores were 0.828 ± 0.184 (EQ-5D-5L) and 0.646 ± 0.125 (SF-6D). Mapping performance was better when both the QLQ-C30 and QLQ-BR23 dimensions were considered rather than when either of these dimensions were used alone. The mapping functions from the optimal direct mapping and indirect mapping approaches were reported.

CONCLUSIONS

The algorithms reported in this paper enable EORTC QLQ-BR53 breast cancer data to be mapped into utilities predicted from the EQ-5D-5L and SF-6D. The algorithms allow for the calculation of quality-adjusted life years for use in breast cancer cost-effectiveness analyses studies.