Screening influencing factors of blood stasis constitution in traditional Chinese medicine

Objective To study the influencing factors of blood stasis constitution and provide a basis for treating blood stasis-related diseases by traditional Chinese medicine(TCM) constitution identification.Methods Data were collected using the self-developed TCM constitution identification platform based on B/S model by the project team. The obtained data were divided into blood stasis constitution and normal constitution groups. The differences of the categorical type influencing factors(gender, birth mode, feeding mode within four months of birth, family history, marital status, eating habits, sleeping habits, exercise habits, emotional state, stress situation, and living environment) and the quantitative type influencing factors(sleep time, age,and mother’s age at birth) on the constitution of the two groups were analyzed. In the singlefactor analysis, the Pearson’s chi-square test was selected for the categorical variable, and the independent sample t test and Mann-Whitney U nonparametric test were selected for the quantitative variables according to whether they conformed to the positive-terrestrial distribution;the binary logistic stepwise regression method was selected for the multi-factor analysis.Results The data of 318 cases were collected from the TCM composition identification platform, and 159 cases of blood stasis constitution were used as the experimental group and 159 cases of normal constitution were used as the control group. The Pearson’s chi-square test yielded significant differences(P < 0.05) in the effects of gender, pressure situation, family history, living environment, emotional state, exercise habits, and dietary habits on blood stasis constitution. The independent samples t test yielded differences in sleep duration between the blood stasis constitution and normal constitution populations(P < 0.05), which meant sleep duration of the blood stasis constitution population was less than that of the normal constitution population. The Mann-Whitney U nonparametric test results accepted the original hypothesis that there was no difference in the distribution of age and mother’s age at birth across constitution types(P > 0.05). Binary logistic regression analysis showed that gender, family history, marital status, living environment, exercise habits, and emotional state were risk factors for blood stasis constitution(P < 0.05).Conclusion Gender, family history, living environment, emotional state, and exercise habits were significant influencing factors of blood stasis constitution. Blood stasis constitution populations can pay more attention to these influencing factors in their daily life for the prevention and reconciliation of blood stasis constitution.

Analysis on Nutritional Risk Screening and Influencing Factors of Hospitalized Patients in Central Urban Area

Rational nutritional support shall be based on nutritional screening and nutritional assessment. This study is aimed to explore nutritional risk screening and its influencing factors of hospitalized patients in central urban area. It is helpful for the early detection of problems in nutritional supports, nutrition management and the implementation of intervention measures, which will contribute a lot to improving the patient＇s poor clinical outcome. A total of three tertiary medical institutions were enrolled in this study. From October 2015 to June 2016, 1202 hospitalized patients aged ≥18 years were enrolled in Nutrition Risk Screening 2002（NRS2002） for nutritional risk screening, including 8 cases who refused to participate, 5 cases of same-day surgery and 5 cases of coma. A single-factor chi-square test was performed on 312 patients with nutritional risk and 872 hospitalized patients without nutritional risk. Logistic regression analysis was performed with univariate analysis（P〈0.05）, to investigate the incidence of nutritional risk and influencing factors. The incidence of nutritional risk was 26.35% in the inpatients, 25.90% in male and 26.84% in female, respectively. The single-factor analysis showed that the age ≥60, sleeping disorder, fasting, intraoperative bleeding, the surgery in recent month, digestive diseases, metabolic diseases and endocrine system diseases had significant effects on nutritional risk（P〈0.05）. Having considered the above-mentioned factors as independent variables and nutritional risk（Y=1, N=0） as dependent variable, logistic regression analysis revealed that the age ≥60, fasting, sleeping disorders, the surgery in recent month and digestive diseases are hazardous factors for nutritional risk. Nutritional risk exists in hospitalized patients in central urban areas. Nutritional risk screening should be conducted for inpatients. Nutritional intervention programs should be formulated in consideration of those influencing factors, which enable to reduce the nutritional risk and to promote the rehabilitation of inpatients.