摘要
Objective: To understand the core knowledge level and influencing factors of chronic disease prevention and control in Adults in China, and to provide a scientific basis for formulating chronic disease prevention and control measures. Methods: In this study, cross-sectional survey and quota sampling were used to recruit 173 819 permanent residents aged 18 and above from 302 counties of adult chronic diseases and nutrition surveillance in China to conduct an online questionnaire survey, including basic information and core knowledge of chronic diseases. The scores of the core knowledge of chronic disease prevention and control were described by median and interquartile range, the Wilcoxon rank sum test or the Kruskal Wallis test was used for the inter-group comparison, and the correlation factors of the total score were analyzed by the multilinear regression model. Results: A total of 172 808 participants were surveyed in 302 counties and districts, of which 42.60%(73 623) were male and 57.40%(99 185) were female; The proportion of respondents aged 18-44, 45-59, and 60 years old and above was 54.74% (94 594), 30.91% (53 423) and 14.35% (24 791), respectively. The total score of the core knowledge of chronic prevention and control in the total population was 66(13), and the scores of different characteristic groups were different, and the differences were statistically significant: the eastern region had the highest score at 67(11) (H=840.66, P<0.01), the urban 66(12) was higher than the rural 65(14) (Z=-31.35, P<0.01), and the male 66(14) was lower than female 66(12) (Z=-11.66, P<0.01), 18-24 years old 64(13) was lower than other age groups(H=115.80, P<0.01), and undergraduate degree and above had the highest score compared to other academic qualifications, with 68(9) points(H=2 547.25, P<0.01). Multivariate analysis showed that eastern (t=27.42, P<0.01), central (t=17.33, P<0.01), urban (t=5.69, P<0.01), female (t=17.81, P<0.01), high age (t=46.04, P<0.01) and high education (t=57.77, P<0.01) had higher scores of core knowledge of chronic disease prevention and control than other groups, the scores of core knowledge of chronic disease prevention and control of professional and technical personnel (t=8.63, P<0.01), state enterprises and institutions (t=38.67, P<0.01), agriculture, forestry, animal husbandry, fishery and water conservancy production (t=5.30, P<0.01), production, transportation and commercial personnel (t=24.87, P<0.01), and other workers (t=8.89, P<0.01) were higher than those of non-employed people. Conclusion: There are differences in the total scores of the core knowledge of chronic disease prevention and control in different characteristics of people in China, and in the future, health education on the prevention and treatment of chronic diseases should be strengthened for specific groups to improve the knowledge level of residents.
Subject(s)
Female , Humans , Male , China/epidemiology , Chronic Disease , Cross-Sectional Studies , East Asian People , Occupations , Surveys and Questionnaires , Health Knowledge, Attitudes, Practice摘要
Objective: To forecast mortality, age-standardized mortality, and probability of premature mortality from diabetes, and to simulate the impact of controlling risk factors by 2030 in China. Methods: We simulated the burden of disease from diabetes in six scenarios according to the development goals of risk factors control by the WHO and Chinese government. Based on the theory of comparative risk assessment and the estimates of the burden of disease for China from the Global Burden of Disease Study 2015, we used the proportional change model to project the number of deaths, age-standardized mortality, and probability of premature mortality from diabetes under different scenarios of risk factors control in 2030. Results: If the trends in exposures to risk factors from 1990 to 2015 continued. Mortality, age-standardized mortality, and probability of premature mortality from diabetes would increase to 32.57/100 000, 17.32/100 000, and 0.84% by 2030, respectively. During that time, mortality, age-standardized mortality and probability of premature mortality for males would all be higher than for females. If the goals of controlling risk factors were all achieved, the number of deaths from diabetes in 2030 would decrease by 62.10% compared to the predicted numbers based on the historical trends in exposure to risk factors, and the probability of premature mortality would drop to 0.29%. If only the exposure to a single risk factor were achieved by 2030, high fasting plasma glucose control would have the greatest impact on diabetes, resulting in a 56.00% reduction in deaths compared to the predicted numbers based on the historical trends, followed by high BMI (4.92%), smoking (0.65%), and low physical activity (0.53%). Conclusions: Risk factors control plays an important role in reducing the number of deaths, age-standardized mortality rate, and probability of premature mortality from diabetes. We suggest taking comprehensive measures to control relevant risk factors for certain populations and regions, to achieve the goal of reducing the burden of disease from diabetes as expected.
Subject(s)
Male , Female , Humans , Risk Factors , Diabetes Mellitus/epidemiology , Mortality, Premature , Smoking , Cost of Illness , China/epidemiology , Global Burden of Disease摘要
Objective: based on summarizing the simulation and prediction of tobacco control measures across the globe and sorting out the various scenarios of tobacco control measures, the potential short-term effects of seven tobacco control measures in different scenarios were systematically analyzed. Methods: Until April 2022, PubMed, Embase, EconLit, PsychINFO, and CINAHL databases were used to retrieve literature about tobacco control measures simulation and prediction models across the globe. Inclusion and exclusion criteria were strictly followed. Meta-analysis for the potential short-term effects of seven tobacco control measures in different scenarios was performed using the R software. Results: A total of 22 papers covering 16 countries were selected. Five studies were conducted in the United States, three in Mexico, and two in Italy. There were all papers with the measures to tax increases, smoke-free air laws, and mass media campaigns, 21 papers with youth access restrictions, 20 with marketing restrictions, and 19 with cessation treatment programs and health warnings. The tax increases had diverse influences on the price elasticity of different age groups. The price elasticity in the age group 15-17 years was the highest, which was 0.044 (95%CI: 0.038-0.051). The potential short-term effects of smoke-free air laws in workplaces were higher than in restaurants and other indoor public places. The effects of youth access restrictions were greater in the age group <16 years than in the age group 16-17. The stronger the implementation of other measures, the greater the potential short-term effects. A comparison of seven tobacco control measures showed that the cessation treatment programs increase in cessation rate was the highest, 0.404 (95%CI: 0.357-0.456). The reduction in smoking rate and reduction in initiation rate of youth access restrictions strongly enforced and publicized was the highest in the age group <16 years, 0.292 (95%CI: 0.269-0.315), and 0.292 (95%CI: 0.270-0.316). Conclusions: The potential short-term effects of seven tobacco control measures in different scenarios were evaluated more accurately and objectively through Meta-analysis. In the short term, cessation treatment programs will substantially increase smoking cessation rates, and strong youth access enforcement will sharply reduce smoking and initiation rates among adolescents under 16. These results also offer strong data-related support for the simulation and prediction of tobacco control measures in China and other countries.
Subject(s)
Adolescent , Humans , United States , Tobacco Control , Prevalence , Computer Simulation , Smoking Cessation , Health Behavior , Smoking Prevention摘要
Objective: To analyze the allocation of human resources for chronic disease prevention and control of district/county-level centers for disease control and prevention(CDC) in China in 2020. Methods: Survey subjects were from National Chronic Noncommunicable Disease and Risk Factor Surveillance Sites and National Demonstration Areas for Chronic Noncommunicable Disease Prevention and Control (demonstration areas). A survey examining the allocation of human resources for chronic disease prevention and control at district/county-level CDC was conducted in December 2021 through the National Demonstration Areas Management Information System. The number and rate of allocation of human resources for chronic disease prevention and control in district/county-level CDC were analyzed and the Wilcoxon rank sum test was used to compare the difference between demonstration and non-demonstration areas and between urban and rural areas. The Kruskal-Wallis H test was used to compare the difference in east, central and west regions. The Gini coefficient and Theil index were used to evaluate the balance of human resource for chronic disease prevention and control. Results: A total of 678 districts/counties were investigated, and 664 districts/counties responded effectively, with an effective response rate of 97.9%. The establishment rate of district/county-level CDC was 98.34% (653/664), and the establishment rate of chronic disease prevention and control departments of district/county-level CDC was 96.02% (627/653). In 627 district/county-level CDC with departments for chronic disease prevention and control, the median number of full-time technical personnel for chronic disease prevention and control was 4, the median number of full-time technical personnel in demonstration areas (4 persons) was higher than in non-demonstration areas (3 persons), highest in the east region (5 persons) than in the middle region (4 persons) and the west region (4 persons), higher in urban areas (4 persons) than in rural areas (4 persons) (all P values<0.05). The allocation rate was 0.71 people/100 000, which was higher in demonstration areas (0.73 people/100 000) than in non-demonstration areas (0.67 people/100 000), highest in the west region (0.82 people/100 000) than in the middle region (0.71 people/100 000) and east region (0.67 people/100 000), higher in rural areas (0.77 people/100 000) than in urban areas (0.68 people/100 000) (all P values<0.05). The Gini coefficient for the allocation by population size was 0.352 9. The total Theil index for demonstration and non-demonstration areas, different regions, and urban-rural areas were 0.067 8, 0.076 3, and 0.000 2, with the intra-group contribution of 97.35%, 99.52%, and 98.80%, respectively. Conclusion: In 2020, the allocation of human resources for chronic disease prevention and control in district/county-level CDC is relatively balanced. The variation in the allocation of human resources for chronic disease prevention and control exist between demonstration and non-demonstration areas, urban and rural areas, and across regions.
Subject(s)
Humans , Noncommunicable Diseases/prevention & control , Workforce , China , Risk Factors , Chronic Disease摘要
Objective: Predictive models were used to evaluate the impact of common risk factors on the number of cardio-cerebrovascular deaths and the probability of premature death. Methods: Using the data for China estimated by the Global Burden of Disease study 2015 (GBD 2015), we calculated the population attribution fraction (PAF) of risk factors. The proportional change model was used to estimate the number of unattributable deaths by 2030, and to predict the number of deaths, mortality, standardized mortality and probability of premature death by 2030. Results: According to the natural change trend of risk factors from 1990 to 2015, the number of deaths and mortality would reach 6.12 million and 428.53/100 000 by 2030, with an increase of 59.92% and 52.87%. By 2030, the probability of premature death from cardio-cerebrovascular diseases among Chinese aged 30-70 years old would continue to decline, from 11.43% to 11.28% for men, and from 5.79% to 4.43% for women. If the goals of all included risk factors were reached by 2030, 2 289 200 cardio-cerebrovascular deaths would be avoided. If only the exposure to a single risk factor was achieved by 2030, blood pressure, total cholesterol, and fine particulate matter exposure were the three most important factors affecting cardio-cerebrovascular deaths, which would reduce 1 332 800, 609 100 and 306 800 deaths, respectively. Among the involved risk factors, the control of blood pressure would mostly decrease the number of deaths due to ischemic heart disease and hemorrhagic stroke, about 677 300 and 391 100 deaths, accordingly. Conclusion: The control of risk factors is of great significance in reducing deaths and probability of premature death due to cardio-cerebrovascular diseases. If the control targets of all risk factors could be achieved by 2030, the burden of cardio-cerebrovascular diseases would be reduced greatly.
Subject(s)
Adult , Aged , Female , Humans , Male , Middle Aged , Blood Pressure , Cerebrovascular Disorders/epidemiology , China/epidemiology , Mortality, Premature , Risk Factors摘要
Objective: To predict the number of deaths, standardized mortality and probability of premature mortality caused by malignant cancer in the context of risk factor control at different levels in China in 2030, and assess the possibility of achieving the target of reducing the probability of premature mortality of malignant cancer. Methods: According to the risk factor control standard for malignant cancer used both at home and abroad, the results of China from Global Burden of Disease Study 2015 were used to calculate the population attributable fraction of the risk factors. Based on the comparative risk assessment theory, the deaths of malignant cancer were classified as attributable deaths and un-attributable deaths. Proportional change model was used to predict risk factor exposure and un-attributable deaths of malignant cancer in the future, then the number of deaths, standardized mortality rate and probability of premature mortality of malignant cancer in 2030 was estimated. Data analyses were performed by using software R 3.6.1. Results: If the risk factor exposure level during 1990-2015 remains, the number of deaths, standardized mortality rate, and probability of premature mortality of malignant cancer would increase to 3.62 million, 153.96/100 000 and 8.92% by 2030, respectively. If the risk factor exposure control level meets the requirement, the probability of premature mortality from cancer in people aged 30-70 years would drop to 7.57% by 2030. Conclusions: The control of risk factor exposure will play an important role in reducing deaths, standardized mortality rate and probability of premature mortality of malignant cancer. But more efforts are needed to achieve the goals of Health China Action.
Subject(s)
Adult , Aged , Humans , Middle Aged , China/epidemiology , Cost of Illness , Mortality, Premature , Neoplasms/epidemiology , Risk Factors摘要
Objective: To forecast the burden of chronic obstructive pulmonary disease (COPD) in China by 2030 and evaluate the effectiveness of controlling risk factors based on the predictive model. Methods: Based on the relationship between the death of COPD and exposure to risk factors and the theory of comparative risk assessment, we used the estimates of the Global Burden of Disease Study 2015 (GBD2015) for China, targets for controlling risk factors, and proportion change model to project the number of deaths, standardized mortality rate, and probability of premature mortality from chronic respiratory diseases by 2030 in different scenarios and to evaluate the impact of controlling the included risk factors to the disease burden of COPD in 2030. Results: If the trends in exposure to risk factors from 1990 to 2015 continued, the number of deaths and the mortality for COPD would be 1.06 million and 73.85 per 100 000 population in China by 2030, respectively, with an increase of 15.81% and 10.69% compared to those in 2015. Compared to 2015, the age-standardized mortality rate would decrease by 38.88%, and the premature mortality would reduce by 52.73% by 2030. If the smoking rate and fine particulate matter (PM2.5) concentration separately achieve their control targets by 2030, there would be 0.34 and 0.27 million deaths that could be avoided compared to the predicted numbers based on the natural trends in exposure to risk factors and the probability of premature death would reduce to 0.59% and 0.52%, respectively. If the control targets of all included risk factors were achieved by 2030, a total of 0.53 million deaths would be averted, and the probability of premature death would decrease to 0.44%. Conclusions: If the exposures to risk factors continued as showed from 1990 to 2015, the number of deaths and mortality for COPD would increase by 2030 compared to 2015, and the standardized mortality and the probability of premature death would decrease significantly, which would achieve the targets of preventing and controlling COPD. If the exposure to the included risk factors all achieved the targets by 2030, the burden of COPD would be reduced, suggesting that the control of tobacco use and air pollution should be enhanced to prevent and control COPD.
Subject(s)
Humans , Air Pollutants/analysis , Air Pollution/prevention & control , China/epidemiology , Cost of Illness , Environmental Exposure , Particulate Matter/analysis , Pulmonary Disease, Chronic Obstructive/prevention & control , Risk Factors摘要
<p><b>OBJECTIVE</b>To investigate the self-rated health status among Chinese residents in 2010.</p><p><b>METHODS</b>Data was from the Non-communicable Disease & Risk Factor Surveillance in China, 2010. A total of 98 638 adults aged ≥ 18 years were included in the study. Self-rated health was assessed by four questions: (1) Would you assess your health status as very good or good, general (not good/not poor), poor or very poor? (2) How many days was your health not good for physical illness during the past 30 days? (3) How many days was your health not good for injury during the past 30 days? (4) How many days was your health not good for mental illness, which include stress and problem with emotions depression during the past 30 days? After being weighed according to complex sampling scheme and post-stratification, the sample was used to estimate the prevalence of self-rated health. The Rao-scott χ(2) test with different samples was adopted for comparison among groups.</p><p><b>RESULTS</b>In total, 57.5% (95%CI:55.5%-59.5%) of the participants rated their health as being either very good or good, 36.2% (95%CI:34.5%-37.8%) as general, and only 6.3% (95%CI:5.7%-6.9%) as poor or very poor; In different age groups and gender, the differences were statistically significant (χ(2) values were 1179.88, 85.36, both P values were < 0.05) . The reported rate of poor or very poor health increased significantly with advancing age ranging from 2.0% (95%CI:1.5%-2.4%)in 18-24 year-old group to 14.9% (95%CI:12.6%-17.2%) in ≥ 75 year-old group; Females were more likely than males to rate their health as poor or very poor , respectively (7.2%; 95%CI 6.5%-7.9% and 5.4%; 95%CI:4.9%-5.9%). During the past 30 days 18.5% (95%CI:17.1%-19.8%) of the participants was not in good health for physical illness. The reported rate of physical illness increased significantly with advancing age (χ(2) = 211.99, P < 0.01), and it was the lowest in 25-34 year-old group (15.4%; 95%CI:13.7%-17.0%), and the highest in ≥ 75 year-old group (28.3%; 95%CI:24.9%-31.6%) . It was statistically higher among females (21.1%; 95%CI:19.5%-22.6%) compared to males (15.9%; 95%CI:14.6%-17.3%) (χ(2) = 231.81, P < 0.01); the reported rates of physical illness were 17.4% (95%CI:15.3%-19.5%) among residents in the east region, 17.2% (95%CI:14.7%-19.6%) in the middle region, and 21.5% (95%CI:18.7%-24.4%) in the western region(χ(2) = 6.75, P < 0.01). During the past 30 days 2.7% (95%CI:2.3%-3.2%) of the participants was not in good health for injure. The reported rate of injure decreased significantly with advancing age (χ(2) = 25.54, P < 0.01), and it was the highest in 18-24 year-old group (3.8%; 95%CI:2.6%-5.0%), and the lowest in 35-44 year-old group (2.3%; 95%CI:1.8%-2.7%) . It was statistically higher among males (3.0%; 95%CI:2.4%-3.5%) compared to females (2.5%; 95%CI:2.1%-2.9%) (χ(2) = 8.89 P < 0.01) ; the reported rates of injure were 2.3% (95%CI:1.9%-2.7%) among residents in the east region , 2.1% (1.7%-2.4%) in the middle region, and 4.1% (95%CI:2.6%-5.6%) in the west region (χ(2) = 16.26, P < 0.01). During the past 30 days 10.0% (95%CI:8.8%-11.3%) of the participants was not in good health for mental illness. The reported rate of mental illness decreased significantly with advancing age (χ(2) = 92.14 P < 0.01), and it was the highest in 18-24 year-old group (12.9%; 95%CI: 10.6%-15.2%), and the lowest in ≥ 75 year-old group (5.7%; 95%CI: 4.4%-7.0%) .It was statistically higher among females (10.8%; 95%CI:9.5%-12.1%) than males (9.2%; 95%CI:7.9%-10.5%) (χ(2) = 21.59, P < 0.01).</p><p><b>CONCLUSION</b>The self-rated health status among Chinese residents was good in 2010. Substantial variation exists in self-rated health status across age groups, between genders, and across regions. Considering these disparities will be important for developing health policy and allocating resources.</p>
Subject(s)
Adolescent , Adult , Aged , Female , Humans , Male , Middle Aged , Young Adult , China , Epidemiology , Diagnostic Self Evaluation , Health Status , Quality of Life摘要
<p><b>OBJECTIVE</b>To investigate the relationship of pre-pregnancy body weight, gestational weight gain and postpartum weight retention among women in Beijing.</p><p><b>METHODS</b>Using a cohort design, 600 pregnant women who went to district obstetrics and gynecology hospital in Beijing to establish preconception health care card from 5(th) February to 15(th) March 2009 were recruited. A total of 112 subjects (109 with valid data), 20% of that in baseline, were followed up at 6 months after delivery.70 subjects (66 with valid data) were followed up at one year after delivery. Weight, weight changes and postpartum weight retention were measured for low weight (BMI < 18.5 kg/m(2)), normal weight (18.5 kg/m(2) ≤ BMI ≤ 24.0 kg/m(2)) and overweight or obesity (BMI > 24.0 kg/m(2)) group.</p><p><b>RESULTS</b>The pre-pregnancy weight and antenatal weight were (54.8 ± 8.0) and (70.8 ± 9.3) kg respectively. Gestational weight gain was (16.0 ± 7.0) kg. The postpartum weight of 6 and 12 months were (60.5 ± 9.4) and (57.6 ± 8.6) kg respectively. Comparing to pre-pregnancy, postpartum weight retention in 6 months and 12 months were (5.7 ± 4.5) and (2.7 ± 4.5) kg, weight retention rates were (10.6 ± 8.6)% and (5.2 ± 9.3)%. Antenatal weight among low pre-pregnancy weight group, normal weight and overweight and obese women were (62.6 ± 5.7), (69.9 ± 6.6) and (84.2 ± 9.9) kg, and weight at postpartum 12 months among 3 groups were (49.3 ± 3.2), (56.5 ± 6.9) and (70.5 ± 6.0) kg respectively (F = 25.3, P < 0.01); At postpartum 12 months, low pre-pregnancy weight group ((5.6 ± 5.9) kg), overweight and obese women group ((4.7 ± 1.9) kg) postpartum weight retention was significantly higher than that of the normal weight group ((1.8 ± 4.3) kg) (F = 3.82, P < 0.05).</p><p><b>CONCLUSION</b>The pre-pregnancy body weight is a key risk factor in weight gain during pregnancy and postpartum weight retention.</p>