背景目前,慢性非传染性疾病(以下简称慢性病)成为影响我国人民群众健康的主要疾病。对慢性病防控资源配置的研究多为现况调查或公平性分析,且缺乏代表性强的结果评价指标。目的分析重庆市慢性病防控资源配置适宜程度的变化情况,探讨其...背景目前,慢性非传染性疾病(以下简称慢性病)成为影响我国人民群众健康的主要疾病。对慢性病防控资源配置的研究多为现况调查或公平性分析,且缺乏代表性强的结果评价指标。目的分析重庆市慢性病防控资源配置适宜程度的变化情况,探讨其对慢性病防控效果的影响。方法按照“穷尽”原则,系统收集政府、卫生健康委及相关部门网站、中国知网(CNKI)、Web of Science等公开数据库发布的重庆市2010—2021年慢性病领域所有文献资料,对文献进行摘录,对慢性病资源配置适宜程度进行量化分析。运用课题组前期构建的适宜公共健康体系定量标准,在系统收集信息资料后,分别从慢性病防控资源配置适宜程度的4个二级指标及13个三级指标展开研究,根据文献中资源配置的相关表述,采用“五分度评分”法半定量对其进行严重性评分,再对评分结果进行公式计算,最终得出资源配置的适宜程度。运用相关分析、线性回归分析资源配置适宜程度对慢性病防控效果的影响。结果2010—2021年重庆市慢性病防控资源配置适宜程度不断上升,由6.64%上升到27.57%;人力资源配置适宜程度从36.49%上升到46.59%,财力资源配置适宜程度从41.06%上升到50.28%,物力资源配置适宜程度从41.40%上升至42.96%,信息资源配置适宜程度从5.73%上升到24.09%。其中财力、物力资源配置适宜程度与重庆市慢性病过早死亡率呈显著负相关,相关系数分别为-0.722、-0.586。结论重庆市慢性病防控资源配置适宜程度逐年提高,但总体处于较低水平,信息资源配置程度较低是制约其发展的主要原因;应加快提升资源配置适宜水平来应对慢性病发病人数的迅速上升。展开更多
目的:本研究旨在探讨脑卒中与多重慢性病之间的关联,为多重慢性病患者的精准医疗和干预提供科学依据。方法:研究基于重庆市脑卒中高危人群筛查和干预项目,采用多阶段分层整群随机抽样方法,纳入2017~2019年间参与基线调查的40岁以上常住...目的:本研究旨在探讨脑卒中与多重慢性病之间的关联,为多重慢性病患者的精准医疗和干预提供科学依据。方法:研究基于重庆市脑卒中高危人群筛查和干预项目,采用多阶段分层整群随机抽样方法,纳入2017~2019年间参与基线调查的40岁以上常住人口33,827人。通过问卷调查、体格检查和实验室检查收集基线数据,并在2024年对研究对象进行随访,记录脑卒中发生情况。使用SPSS 26.0和R 4.3.1进行统计分析,采用多因素Logistic回归分析脑卒中与多重慢性病的独立关联。结果:共纳入33,827名研究对象,随访期间确诊986例新发脑卒中病例。单因素分析表明,性别、年龄、饮食习惯、心脏病、高血压、糖尿病等因素与脑卒中发生显著相关。多变量模型显示,年龄 ≥ 65岁(OR = 3.43, 95%CI: 2.92~4.03)、男性(OR = 1.52, 95%CI: 1.28~1.81)、多食肉食(OR = 1.50, 95%CI: 1.19~1.90)、素食为主(OR = 1.21, 95%CI: 1.01~1.46)、食用蔬菜3~4天/周(OR = 1.26, 95%CI: 1.03~1.53)、患心脏病(OR = 1.50, 95%CI: 1.15~1.95)、患高血压(OR = 1.42, 95%CI: 1.20~1.68)、患糖尿病(OR = 1.24, 95%CI: 1.03~1.50)、身高(OR = 0.98, 95%CI: 0.98~0.99)、收缩压(OR = 1.01, 95%CI: 1.00~1.01)、脉搏(OR = 1.01, 95%CI: 1.00~1.02)、FBG (OR = 1.06, 95%CI: 1.02~1.10)为脑卒中的独立危险因素。此外,患有一种慢病(OR = 1.29, 95%CI: 1.06~1.58)和患有≥2种慢性病(OR = 1.78, 95%CI: 1.43~2.22)高风险相关,在三种多因素模型中均有统计学意义(P Aim: This study aims to explore the association between stroke and multiple chronic diseases to provide a scientific basis for precision medicine and interventions for patients with multiple chronic diseases. Methods: The study is based on the Chongqing Stroke High-Risk Population Screening and Intervention Project. A multi-stage stratified cluster random sampling method was employed to enroll 33,827 permanent residents aged 40 years and above who participated in the baseline survey between 2017 and 2019. Baseline data were collected through questionnaires, physical examinations, and laboratory tests. Follow-up was conducted in 2024 to record the incidence of stroke. Statistical analysis was performed using SPSS 26.0 and R 4.3.1, with multivariate logistic regression used to analyze the independent association between stroke and multiple chronic diseases. Results: A total of 33,827 subjects were included in the study, with 986 new stroke cases diagnosed during the follow-up period. Univariate analysis indicated that gender, age, dietary habits, heart disease, hypertension, and diabetes were significantly associated with stroke incidence. The multivariable model showed that age ≥65 years (OR = 3.43, 95%CI: 2.92~4.03), male gender (OR = 1.52, 95%CI: 1.28~1.81), high meat consumption (OR = 1.50, 95%CI: 1.19~1.90), primarily vegetarian diet (OR = 1.21, 95%CI: 1.01~1.46), vegetable consumption 3~4 days/week (OR = 1.26, 95%CI: 1.03~1.53), heart disease (OR = 1.50, 95%CI: 1.15~1.95), hypertension (OR = 1.42, 95%CI: 1.20~1.68), diabetes (OR = 1.24, 95%CI: 1.03~1.50), height (OR = 0.98, 95%CI: 0.98~0.99), systolic blood pressure (OR = 1.01, 95%CI: 1.00~1.01), pulse rate (OR = 1.01, 95%CI: 1.00~1.02), and fasting blood glucose (OR = 1.06, 95%CI: 1.02~1.10) were independent risk factors for stroke. Additionally, having one chronic disease (OR = 1.29, 95%CI: 1.06~1.58) and having ≥2 chronic diseases (OR = 1.78, 95%CI: 1.43~2.22) were high-risk factors, significant in all three multivariable models (P < 0.05). Conclusion: The incidence of stroke in Chongqing is high. Advanced age, unbalanced diet, insufficient vegetable consumption, shorter height, high systolic blood pressure, pulse rate, fasting blood glucose, as well as heart disease, hypertension, and diabetes are risk factors for stroke. Multiple chronic diseases are independent risk factors for stroke.展开更多
文摘背景目前,慢性非传染性疾病(以下简称慢性病)成为影响我国人民群众健康的主要疾病。对慢性病防控资源配置的研究多为现况调查或公平性分析,且缺乏代表性强的结果评价指标。目的分析重庆市慢性病防控资源配置适宜程度的变化情况,探讨其对慢性病防控效果的影响。方法按照“穷尽”原则,系统收集政府、卫生健康委及相关部门网站、中国知网(CNKI)、Web of Science等公开数据库发布的重庆市2010—2021年慢性病领域所有文献资料,对文献进行摘录,对慢性病资源配置适宜程度进行量化分析。运用课题组前期构建的适宜公共健康体系定量标准,在系统收集信息资料后,分别从慢性病防控资源配置适宜程度的4个二级指标及13个三级指标展开研究,根据文献中资源配置的相关表述,采用“五分度评分”法半定量对其进行严重性评分,再对评分结果进行公式计算,最终得出资源配置的适宜程度。运用相关分析、线性回归分析资源配置适宜程度对慢性病防控效果的影响。结果2010—2021年重庆市慢性病防控资源配置适宜程度不断上升,由6.64%上升到27.57%;人力资源配置适宜程度从36.49%上升到46.59%,财力资源配置适宜程度从41.06%上升到50.28%,物力资源配置适宜程度从41.40%上升至42.96%,信息资源配置适宜程度从5.73%上升到24.09%。其中财力、物力资源配置适宜程度与重庆市慢性病过早死亡率呈显著负相关,相关系数分别为-0.722、-0.586。结论重庆市慢性病防控资源配置适宜程度逐年提高,但总体处于较低水平,信息资源配置程度较低是制约其发展的主要原因;应加快提升资源配置适宜水平来应对慢性病发病人数的迅速上升。
文摘目的:本研究旨在探讨脑卒中与多重慢性病之间的关联,为多重慢性病患者的精准医疗和干预提供科学依据。方法:研究基于重庆市脑卒中高危人群筛查和干预项目,采用多阶段分层整群随机抽样方法,纳入2017~2019年间参与基线调查的40岁以上常住人口33,827人。通过问卷调查、体格检查和实验室检查收集基线数据,并在2024年对研究对象进行随访,记录脑卒中发生情况。使用SPSS 26.0和R 4.3.1进行统计分析,采用多因素Logistic回归分析脑卒中与多重慢性病的独立关联。结果:共纳入33,827名研究对象,随访期间确诊986例新发脑卒中病例。单因素分析表明,性别、年龄、饮食习惯、心脏病、高血压、糖尿病等因素与脑卒中发生显著相关。多变量模型显示,年龄 ≥ 65岁(OR = 3.43, 95%CI: 2.92~4.03)、男性(OR = 1.52, 95%CI: 1.28~1.81)、多食肉食(OR = 1.50, 95%CI: 1.19~1.90)、素食为主(OR = 1.21, 95%CI: 1.01~1.46)、食用蔬菜3~4天/周(OR = 1.26, 95%CI: 1.03~1.53)、患心脏病(OR = 1.50, 95%CI: 1.15~1.95)、患高血压(OR = 1.42, 95%CI: 1.20~1.68)、患糖尿病(OR = 1.24, 95%CI: 1.03~1.50)、身高(OR = 0.98, 95%CI: 0.98~0.99)、收缩压(OR = 1.01, 95%CI: 1.00~1.01)、脉搏(OR = 1.01, 95%CI: 1.00~1.02)、FBG (OR = 1.06, 95%CI: 1.02~1.10)为脑卒中的独立危险因素。此外,患有一种慢病(OR = 1.29, 95%CI: 1.06~1.58)和患有≥2种慢性病(OR = 1.78, 95%CI: 1.43~2.22)高风险相关,在三种多因素模型中均有统计学意义(P Aim: This study aims to explore the association between stroke and multiple chronic diseases to provide a scientific basis for precision medicine and interventions for patients with multiple chronic diseases. Methods: The study is based on the Chongqing Stroke High-Risk Population Screening and Intervention Project. A multi-stage stratified cluster random sampling method was employed to enroll 33,827 permanent residents aged 40 years and above who participated in the baseline survey between 2017 and 2019. Baseline data were collected through questionnaires, physical examinations, and laboratory tests. Follow-up was conducted in 2024 to record the incidence of stroke. Statistical analysis was performed using SPSS 26.0 and R 4.3.1, with multivariate logistic regression used to analyze the independent association between stroke and multiple chronic diseases. Results: A total of 33,827 subjects were included in the study, with 986 new stroke cases diagnosed during the follow-up period. Univariate analysis indicated that gender, age, dietary habits, heart disease, hypertension, and diabetes were significantly associated with stroke incidence. The multivariable model showed that age ≥65 years (OR = 3.43, 95%CI: 2.92~4.03), male gender (OR = 1.52, 95%CI: 1.28~1.81), high meat consumption (OR = 1.50, 95%CI: 1.19~1.90), primarily vegetarian diet (OR = 1.21, 95%CI: 1.01~1.46), vegetable consumption 3~4 days/week (OR = 1.26, 95%CI: 1.03~1.53), heart disease (OR = 1.50, 95%CI: 1.15~1.95), hypertension (OR = 1.42, 95%CI: 1.20~1.68), diabetes (OR = 1.24, 95%CI: 1.03~1.50), height (OR = 0.98, 95%CI: 0.98~0.99), systolic blood pressure (OR = 1.01, 95%CI: 1.00~1.01), pulse rate (OR = 1.01, 95%CI: 1.00~1.02), and fasting blood glucose (OR = 1.06, 95%CI: 1.02~1.10) were independent risk factors for stroke. Additionally, having one chronic disease (OR = 1.29, 95%CI: 1.06~1.58) and having ≥2 chronic diseases (OR = 1.78, 95%CI: 1.43~2.22) were high-risk factors, significant in all three multivariable models (P < 0.05). Conclusion: The incidence of stroke in Chongqing is high. Advanced age, unbalanced diet, insufficient vegetable consumption, shorter height, high systolic blood pressure, pulse rate, fasting blood glucose, as well as heart disease, hypertension, and diabetes are risk factors for stroke. Multiple chronic diseases are independent risk factors for stroke.
