RESUMO
Objective To investigate current status of obesity and its relationship with hypertension in the elderly over 65 in Fujian. Methods From February 2018 to March 2020, cluster sampling method was used to select 11 203 elderly people over 65 years old from residential areas and villages with concentrated population, representative medical and economic development level in Fujian, such as Fuzhou, Xiamen, Zhangzhou, Quanzhou, Sanming, Putian, Nanping, Longyan and Ningde. All the selected individuals completed the questionnaires, and the basic data including height, weight, waist circumference, hip circumference and blood pressure were measured. Results Among the 11 203 elderly people over the age of 65 in 9 city, there were 5 224 males, 5 979 females, 4 545 patients aged 65-70 years, 3 239 patients aged 70-75 years, 2 200 patients aged 75-80 years, and 1219 patients aged > 80 years. There were 309 cases of low weight (2.76%), 4 971 cases of normal weight (44.37%), 4 362 cases of overweight (38.94%) and 1561 cases of obesity (13.93%). The obesity rate of females was significantly higher than that of males, and the height and overweight rates of males were significantly higher than that of females (P80 age group were lower than those of other age groups, and the detection rate of hypertension was significantly higher than that of other age groups (P<0.05). Conclusion Overweight is more common among the elderly over 65 in Fujian, and the prevalence of hypertension is relatively high among people with low BMI.
RESUMO
Objective To analyze the incidence and death of stroke and its influencing factors, to explore the relationship between a stroke and its influencing factors, and to provide a scientific basis for the formulation and evaluation of health policies for the prevention and treatment of stroke. Methods Using a multi-stage stratified random cluster sampling method, a cross-sectional survey was conducted among 18 942 permanent residents over 40 years old . A unified questionnaire was used to analyze and understand the demographic characteristics of the research subjects. The statistical analysis was performed to compare the prevalence of stroke by gender, age, urban and rural areas, education, marital status and occupation. According to the results of single factor analysis, the Logistic model and artificial neural network model of influencing factors of stroke in the city were established. Results There were 522 stroke cases with a prevalence rate of 2.76%. There were 7 cases of death, accounting for 1.34%. The prevalence of stroke increased with the increase of age, and the trend test showed a statistical significance (P<0.01). The prevalence of stroke in primary school was higher than that in junior high school and above (P<0.01). The prevalence in rural areas was higher than that in urban areas (P<0.01). The prevalence in smokers and drinkers was higher than that in non-smokers and non-drinkers (P<0.01). Physical examination and laboratory examination showed that the waist circumference, BM, SBP, DBP, FPG, TC, TG and HDL of stroke patients were higher than those of non-stroke patients (P<0.01). The ankle brachial index and LDL value were significantly lower than those of non-stroke patients (P<0.01). Multivariate analysis showed that after adjusting gender, age, and urban and rural areas, smoking, drinking, waist length, high blood pressure measurement and high-density lipoprotein abnormality were positively correlated to stroke. Conclusion Smoking, drinking, waist length, high blood pressure and HDL were positive influencing factors of stroke. It is suggested that the intervention measures should be formulated according to the characteristics of different populations to effectively prevent and control strokes.