Objective: The present study investigated the current status of fruit and vegetable intake among seniors and assessed the relationship between personal background factors, social psychological factors and environmental factors of the study participants and their fruit and vegetable consumption behaviour. Design: Research data were collected through individual interviews using a questionnaire developed by the authors. SPSS for Windows 15·0 statistical software was used to process and analyse the data. Setting: Elderly individuals sampled from all twenty-nine administration units of Keelung City's Renai District were interviewed. Subjects: Study participants included 398 residents aged 65 years or older. Results: On average, study participants ate five daily servings of fruits and vegetables on 2·86 d/week. The important variables influencing fruit and vegetable consumption were education level, outcome expectancy, social support, self-efficacy, frequency of dining out and role modelling. Educated participants consumed more fruits and vegetables than those without education. Outcome expectancy, social support, self-efficacy and role modelling had positive impacts on fruit and vegetable intake, but frequency of dining out had a negative impact on fruit and vegetable intake. The significant predictors of fruit and vegetable intake behaviour were education level, outcome expectancy, social support and frequency of dining out. Among those variables, social support was the most influential factor. Conclusions: Our findings supported the conclusion that health education strategies to increase fruit and vegetable intake among seniors should include the variables of social support and outcome expectancy.

BackgroundRoutine health check-up is associated with improved lifespan and reduced medical cost. Traditional Chinese medicine (TCM) serves as a cost-effective modality in healthcare system. We examined the correlations of TCM syndromes with modern medical indicators in health check-up population.MethodsWe studied 5231 subjects undergoing health check-up between January 1st 2008 and December 31, 2016. Physical indexes such as body weight and blood pressure and biomedical indicators like live function and tumour markers were measured. All subjects underwent colonoscopy. All subjects were classified and differentiated into five different TCM syndromes. An artificial neural network (ANN) was employed to evaluate the predictive value of TCM syndrome differentiation.ResultsOf enrolled subjects, SADH accounted for 85.8% and IDSIBSB was found in 4576 subject (87.5%). YaDSK and YiDLK accounted for 99.5% (5207) and 80.9% (4232) respectively. We found that YiDLK is correlated with abnormality of liver function indexes. The results showed that SADH is correlated with level of cholesterol in health check-up population. The results showed that the predictive ANN model showed a good fitting with an accuracy of 100%.ConclusionThe results demonstrated that TCM syndromes were closely correlated with clinical laboratory indexes regardless of health status. TCM syndrome differentiation is suggested to contribute to routine health examination as screening measure with its non-invasive nature.