ABSTRACT
Objective To assess the current status and factors associated with the mental health condition of older adults. Methods A convenience sampling survey was conducted using symptom check list 90 (SCL-90) among the Chinese older adults aged 60 or above from January to March, 2018. The older adults aged 80 or above were selected for this study. Chi-square test and binary logistic regression model were used to analyze the influencing factors. Results The total participants were 485. The SCL-90 positive detection rate was 20.21%. The symptoms of the four highest detection rates were somatization (39.38%), others (25.15%), obsessive-compulsive symptoms (24.33%) and depression (22.68%). The older adults with normal BMI (OR=0.537, 95% CI: 0.250-0.857, P=0.027) and lived in county town (OR=0.224, 95% CI:0.075-0.667, P=0.007) showed lower SCL-90 positive detection rate. These who had been educated for 1-5 years (OR=11.092, 95% CI: 4.446-27.671, P<0.001), 6-8 years (OR=9.800, 95% CI: 3.464-27.721, P<0.001), 9~11 years (OR=19.279, 95% CI : 6.722-55.297, P<0.001), 12 years and above (OR=24.321, 95% CI: 7.894-74.929, P<0.001) had higher SCL-90 positive detection rate compared with those who were uneducated. Conclusion The mental health condition of Chinese older adults is mainly influenced by residence place, education level, family income self-evaluation and BMI status.
ABSTRACT
Objective To establish a predictive model for inpatients of cardio-cerebrovascular disease in rural areas of Wugang through time series analysis, and predict the changing trend of cardio-cerebrovascular disease, so as to offer guidance for the health care resources allocation and prevention and control of cardio-cerebrovascular disease. Methods The seasonal autoregressive integrated moving average model (SARIMA) was constructed based on the monthly number of cases of cardio-cerebrovascular disease in rural areas from January 2013 to December 2016 by Stata 14.0 software, and the predictive effect of the model was verified with the monthly number of inpatients of cardio-cerebrovascular disease in 2017. Results The final fitting model of inpatients of cardio-cerebrovascular disease was SARIMA (2, 1, 1)×(0, 1, 0)12. The residual sequence of the model was diagnosed. Results of Ljung-Box Q test showed that the residual sequence was white noise sequence (Q=11.12, P=0.68). In addition, the 2017 forecast was basically consistent with the observations, the overall relative error was around -1.2%. The results showed that the summer was the peak period of cardiovascular and cerebrovascular hospitalization. Conclusion SARIMA model can accurately predict the number of inpatients of cardio-cerebrovascular disease in Wugang, which can provide data support for the hospital administrator to rationally allocate medical resources in the cardiovascular according to the needs of cardio-cerebrovascular treatment in different months.