Objective To explore the impact of health management programs on hypertension related to their cost of the hypertensive,so as to provide evidence for related policy-making.Methods Data was from the 2011 China Non-communicable and Chronic Disease Survey Project which was developed in 161 counties (districts) and Xinjiang production and Construction Corps.Information regarding hypertensive patients were collected through a questionnaire.Two-part model was used to analyze the influence from health management scheme.Results This study included 1 1 294 participants who were 35 years old or beyond,with 4 904 (43.42％) males and 6 390 (56.58％) females.The median cost from the outpatient was 100 (30-200) Yuan,and the cost of patients under management program were significantly lower than those without (P＜0.05).Median pharmacy cost appeared as 30 (15-100) Yuan but there was no significant difference noticed between the cost from the managed or unmanaged patients (P＞0.05).Regarding the calculation on the outpatient cost,results showed that the patients under the management program were more likely to practice ‘outpatient-medical-behavior’ (OR=2.50,95％CI:2.26-2.76) with nearly three quarters of the cost from the unmanaged patients.Hypertensive patients from the urban areas were more likely to adopt ‘medical behavior’ (OR=1.31,95％CI:1.18-1.45) which was 1.69 times of the costs from the rural patients.Results of the pharmacy cost showed that the urban hypertension patients were more likely to purchase medicine (OR=1.10,95％CI:1.01-1.20) and was 1.19 times the costs of the rural patients.Conclusion Health management program on hypertension showed preliminary but promising results in reducing the out-patient cost in the treatment of hypertension,thus should be promoted and implemented.

Objective: To examine the effects and associated factors of the China Motivational Healthy Walking Program among occupational population. Methods: The 2016 China Motivational Healthy Walking Program recruited 29 224 participants from 139 demonstration areas for comprehensive prevention and control of chronic and non-communicable disease at national level and 70 at provincial level. Intervention on walking was carried out by adopting group and individual motivating measures. Walking steps were recorded by electronic pedometer. We used percent of days achieving 10 000 steps (P10 000), percent of days fulfilling continuous walking (PCW), and proportion of valid walking (PVW) steps to reflect walking quantity, pattern and quality of participants. Motivation intensity was measured by summing up scores of each motivating activity. Questionnaire-based online survey collected information about demographic characteristics, lifestyle risk factors and chronic diseases. This study finally included 12 368 individuals in the analysis. Multilevel logistic regression model was used to assess the effect of group and individual motivating measures on walking activity and corresponding associated factors. Results: Age of the study sample was (41.2±8.99) years, and 58.17% (7 194) of them were female. After 100-day intervention, the P10 000, PCW and PVW of all participants were 93.89%±14.42%,92.01%±15.97% and 81.00%±7.45%, respectively. The mean P10 000 and PCW increased with rising group-motivated scores, self-motivated scores and individual-activity scores (P<0.001 for all). The mean PVW decreased with both higher group-motivated scores and self-motivated scores (both P<0.05), and varied little among groups with different level individual-activity scores (P=0.525). According to the results from the multilevel model, those who had greater group-motivated scores and self-motivated scores tended to have more likelihood of high-level of P10 000 and PCW. Age, sex, smoking status, education attainment and alcohol drinking were associated with P10 000 and PCW (P<0.05 for all). Conclusion The Motivational Healthy Walking Program had positive effect on promoting healthy walking among occupational population. Group-motivated and self-motivated activities were associated with healthy walking.

Objective To quantify the effects of short?term walking intervention on body mass index (BMI), waist circumference, and related indicators of working population. Methods The China Motivational Healthy Walking Program in 2016 recruited 29 224 individuals from 139 demonstration areas for comprehensive prevention and control of chronic and non?communicable diseases at the national level and 70 areas at the provincial level. All subjects volunteered to participate into this program. The intervention lasted 100 days from June to September 2016. The walking behavior, height, weight and waist circumference of subjects were measured using a uniform pedometer, body composition tester, height tester and waist?to?hip caliper before and after the intervention. Daily average steps, daily average effective steps, and the percent of fulfilling continuous walking per day were used as main indicators in this study. Self?administered questionnaires were used to collect demographic characteristics, behaviors and chronic diseases. With the adjustment of potential confounding factors, multilevel regression was used to quantify the effect of walking on BMI and waist circumference, and multilevel logistic regression was used to quantify the effect on overweight or obesity and central obesity. Results A total of 12 368 subjects completed walking interventions and all measurements included in this study. The mean ± SD age of all subjects was (41.19 ± 8.99) years, and 5 155 (59.17%) of them were women. After 100?day intervention, all outcome variables decreased significantly. For every additional 1 000 steps per day, subjects would have extra decrease in BMI of 0.023 kg/m2 [β (95%CI ): -0.023 (-0.030, -0.017)], in waist circumference of 0.046 cm [β (95%CI ):-0.046 (-0.071, -0.020)], and the likelihood for becoming overweight or obesity was 0.97 times [OR (95%CI): 0.97 (0.95, 0.98)] that of before intervention. With additional 1 000 effective steps per day, the difference between baseline and endpoint increased by 0.028 kg/m2 [β (95%CI ): -0.028 (-0.035,-0.020)] in BMI and 0.062 cm [β (95%CI):-0.062 (-0.091,-0.033)] in waist circumference. The likelihood of progressing into overweight or obesity was 0.97 times [ OR (95%CI ): 0.97(0.95, 0.98)] that of before?intervention, and the likelihood of becoming central obesity was 0.98 times [OR (95%CI): 0.98(0.96, 0.99)] that of before?intervention. Compared to subjects with low level percent of fulfilling continuous walking per day, those with high level would have an extra decrease in BMI by 0.150 kg/m2 [β (95%CI):-0.150 (-0.22,-0.079)], in waist circumference by 0.340 cm [β (95%CI ):-0.340 (-0.620,-0.064)], and the likelihood of becoming overweight or obesity decreased to 0.74 times that of the low level group [ OR (95%CI ): 0.74(0.62, 0.89)] and the likelihood of becoming central obesity decreased to 0.78 times that of the low level group [ OR (95%CI ): 0.78 (0.68, 0.91)]. Conclusion Strengthening walking exercise in the short term has a positive effect on promoting working population to reduce BMI and waist circumference, and prevent overweight, obesity and central obesity.

Objective To quantify the effects of short?term walking intervention on body mass index (BMI), waist circumference, and related indicators of working population. Methods The China Motivational Healthy Walking Program in 2016 recruited 29 224 individuals from 139 demonstration areas for comprehensive prevention and control of chronic and non?communicable diseases at the national level and 70 areas at the provincial level. All subjects volunteered to participate into this program. The intervention lasted 100 days from June to September 2016. The walking behavior, height, weight and waist circumference of subjects were measured using a uniform pedometer, body composition tester, height tester and waist?to?hip caliper before and after the intervention. Daily average steps, daily average effective steps, and the percent of fulfilling continuous walking per day were used as main indicators in this study. Self?administered questionnaires were used to collect demographic characteristics, behaviors and chronic diseases. With the adjustment of potential confounding factors, multilevel regression was used to quantify the effect of walking on BMI and waist circumference, and multilevel logistic regression was used to quantify the effect on overweight or obesity and central obesity. Results A total of 12 368 subjects completed walking interventions and all measurements included in this study. The mean ± SD age of all subjects was (41.19 ± 8.99) years, and 5 155 (59.17%) of them were women. After 100?day intervention, all outcome variables decreased significantly. For every additional 1 000 steps per day, subjects would have extra decrease in BMI of 0.023 kg/m2 [β (95%CI ): -0.023 (-0.030, -0.017)], in waist circumference of 0.046 cm [β (95%CI ):-0.046 (-0.071, -0.020)], and the likelihood for becoming overweight or obesity was 0.97 times [OR (95%CI): 0.97 (0.95, 0.98)] that of before intervention. With additional 1 000 effective steps per day, the difference between baseline and endpoint increased by 0.028 kg/m2 [β (95%CI ): -0.028 (-0.035,-0.020)] in BMI and 0.062 cm [β (95%CI):-0.062 (-0.091,-0.033)] in waist circumference. The likelihood of progressing into overweight or obesity was 0.97 times [ OR (95%CI ): 0.97(0.95, 0.98)] that of before?intervention, and the likelihood of becoming central obesity was 0.98 times [OR (95%CI): 0.98(0.96, 0.99)] that of before?intervention. Compared to subjects with low level percent of fulfilling continuous walking per day, those with high level would have an extra decrease in BMI by 0.150 kg/m2 [β (95%CI):-0.150 (-0.22,-0.079)], in waist circumference by 0.340 cm [β (95%CI ):-0.340 (-0.620,-0.064)], and the likelihood of becoming overweight or obesity decreased to 0.74 times that of the low level group [ OR (95%CI ): 0.74(0.62, 0.89)] and the likelihood of becoming central obesity decreased to 0.78 times that of the low level group [ OR (95%CI ): 0.78 (0.68, 0.91)]. Conclusion Strengthening walking exercise in the short term has a positive effect on promoting working population to reduce BMI and waist circumference, and prevent overweight, obesity and central obesity.

OBJECTIVETo compare design-based and model-based methods in descriptive analysis of complex sample.

METHODSA total of 1 000 samples were selected and a multistage random sampling design was used in the analysis of the 2010 China chronic disease and risk factors surveillance. For each simulated sample, cases with probability proportional age were randomly deleted so that sample age structure was deviated systematically from that of the target population. Mean systolic blood pressure (SBP) and prevalence of raised blood pressure, as well as their 95% confidence intervals (95%CI) were determined using design-based and model-based methods (routine method and multi-level model). For estimators generated from those 3 methods, mean squared error(MSE) was computed to evaluate their validity. To compare performance of statistical inference of these methods, the probability of 95%CI covering the true parameter(mean SBP and raised blood pressure prevalence of the population) was used.

RESULTSMSE of mean estimator for routine method, design-based analysis and multilevel model was 6.41, 1.38, and 5.86, respectively; and the probability of 95%CI covering the true parameter was 24.7%, 97.5% and 84.3%, respectively. The routine method and multi-level model probably led to an increased probability of type I error in statistical inference. MSE of prevalence estimator was 4.80 for design-based method, which was far lower than those for routine method (20.9) and multilevel model (17.2). Probability of 95%CI covering the true prevalence for routine method was only 29.4%, and 86.4% for multilevel model, both of which were lower than that for design-based method (97.3%).

CONCLUSIONCompared to routine method and multi-level model, design-based method had the best performance both in point estimation and confidence interval construction. Design-based method should be the first choice when doing statistical description of complex samples with a systematically biased sample structure.

Objective To describe the prevalence on overweight and obesity among Chinese elderly aged 60 and above.Methods Data from China Chronic Disease Surveillance in 2010 was gathered and information on 19 882 subjects aged 60 and over was analyzed.Sample was weighted to represent the population of Chinese elderly.The mean and percentiles of BMI,prevalence of overweight and obesity grouped by sex,age,urban and rural areas,geographic location,education level and household income were analyzed.Results The mean BMI was (23.8 ± 3.6) kg/m2 among the Chinese elderly.The overall prevalence of overweight was 32.1％ among the Chinese elderly,with 31.0％ among males and 33.3％ among females (x2=15.23,P＜0.05),38.3％ in urban areas and 29.1％ in rural areas (x2=29.05,P＜0.05).The overall prevalence of obesity was 12.4％ among Chinese elderly,with 9.3％ among males and 15.3％ among females (x2=152.75,P＜0.05),16.5％ in urban areas and 10.3％ in rural areas(x2=20.67,P＜0.05).Compared with those with lower income or lower education level,the prevalence rates of both overweight and obesity were higher in elderly with higher household income or higher education level.According the WHO definitions on overweight and obesity,the prevalence rates of overweight and obesity among Chinese elderly were 29.3％ (25 kg/m2≤BMI＜30 kg/m2) and 5.3％ (BMI≥30 kg/m2),respectively.Conclusion Approximately,50％ of the Chinese elderly showed abnormal high body mass index.The profiles of body weight among Chinese elderly were characterized by the mean of BMI and the higher prevalence rates of overweight and obesity seen in women than in men,higher in urban than in rural areas,The prevalence rates of overweight and obesity decreased with age but increased with household income and education level.

Objective: To evaluate the provincial representativeness of China Non-communicable and Chronic Disease Risk Factor Surveillance System, 2013. Methods: The Sixth National Population Census data which was collected by National Bureau of Statistics of People's Republic of China was used to calculate proportion of population who aged 65 and above, mortality rate, the proportion of non-agriculture population, the illiteracy rate and urbanization rate in order to evaluate the surveillance system in each province. The Mann-Whitney U test was used to determine the statistically differences between the surveillance system and corresponding general population. Results: Among the 298 disease surveillance points (DSPs) in China Non-communicable and Chronic Disease Risk Factor Surveillance System, there were 111, 85, and 102 DSPs located in the east, middle, and west area of China, which covering 13.90%, 11.48%, and 12.28% of the total population, respectively. The surveillance system covered 169 million of the population of China, accounting for 12.70% of Chinese population. The number of DSPs by provinces ranges from 6 (Hainan, Qinghai, and Ningxia) to 14 (Shandong, Guangdong and Henan). It indicated that mortality rate (DSP: 0.238%; Province: 0.482%) and the illiteracy rate (DSP: 15.54%; Province: 26.22%) among DSPs in Tibet were significantly lower than the provincial level, on the other hand, the proportion of non-agriculture population among DSPs (40.6%) was significantly higher than the provincial level (18.8%). The urbanization rate among Jiangxi DSPs (43.4%) was significantly lower than the provincial level (59.9%). The proportion of non-agriculture population among Shandong DSPs (32.8%) was significantly higher than the provincial level (24.2%), however, the illiteracy rate among Shandong DSPs (3.86%) was significantly lower than the provincial level (5.25%). Other than the provinces mentioned above, there was no statistical differences (P>0.05) among proportions of population who aged 65 and above, mortality rates, the proportions of non-agriculture population, the illiteracy rates and urbanization rate between provincial surveillance system and corresponding area. Conclusion Other than 3 provinces, in general, China Non-communicable and Chronic Disease Risk Factor Surveillance System had provincial representativeness.

Objective: To assess the disease burden for low back pain in China in 2013 and analyzed the change of it between 1990 and 2013. Methods: Data was from the Global Burden of Disease Study 2013 (GBD 2013). The burden of low back pain (LBP) among age groups, gender groups, provinces (excluding Taiwan China) groups was assessed by years lived with disability (YLD), including YLD, YLD rate, proportion of YLD due to LBP. The change of the YLD for LBP was analyzed between 1990 and 2013 by age-standardized YLD rate using the world standard population of 2000-2025 WHO. Results: In 2013, The YLD for LBP was 16 347 thousand (the leading cause of YLD in China), and the proportion of YLD in age group 30-59 years old was 54.6% (8 929/16 347) . The age-standardized rate in China was 1 072.6/100 000, and the rates in Guangdong (1 742.2/100 000) , Shanghai (1 227.8/100 000) and Beijing (1 136.6/100 000) were higher than in other provinces. The proportion of YLD due to LBP was 11.8%. LBP was the leading cause of YLD in China. Compared with 1990, the growth rates of age-standardized rate, proportion of YLD and YLD, were 5.6%, 25.5% and 72.1%, desperately. Conclusion Low back pain was the leading cause of YLD in China in 2013. Compared with 1990, the disease burden for low back pain increased rapidly.

In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.

In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.