Objective: To evaluate the suitability of the existing hemolysis rate standards for locally processed red blood cell components by retrospectively analyzing 5-year hemolysis rate data at the end of storage. Methods: A total of 720 blood samples of three types of red blood cell components from our blood station from January 2019 to December 2023 were collected. Parameters included hemoglobin concentration (Hb), hematocrit (Hct), and free hemoglobin concentration (fHb). Hemolysis rate were taken as the control standard of 0.8% in accordance with the national standard. The hemolysis rates were compared against the national standard threshold of 0.8% (GB18469-2012), and annual trends of the detection parameters were observed. Results: The hemolysis rates (x-+s,%) of leukocyte-depleted whole blood at the end of storage were (0.038±0.023 8) in 2019, (0.049±0.039 5) in 2020, (0.043±0.040 7) in 2021, (0.049±0.030 7) in 2022, and (0.058±0.054 8) in 2023, respectively; The hemolysis rates (x-+s" />,%) of leukocyte-depleted suspended red blood cells at the end of storage were (0.093±0.050 2) in 2019, (0.086±0.049 5) in 2020, (0.123±0.072 3) in 2021, (0.122±0.052 1) in 2022, and (0.106±0.058 6) in 2023, respectively; The hemolysis rates (x-+s,%) of washed red blood cells at the end of storage were (0.127±0.038 2) in 2019, (0.150±0.066 5) in 2020, (0.121±0.052 2) in 2021, (0.124±0.038 9) in 2022, and (0.128±0.044 3) in 2023, respectively. Conclusion: Hemolysis rates at the end of blood storage of three red blood cell components were significantly lower than the limits specified in Quality Requirements for Whole Blood and Components (GB18469-2012), as well as standards from the EU, AABB and the United States. The results demonstrate excellent product quality control. A regional internal control standard of <0.2% is proposed for hemolysis rates at the end of storage.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

Objective:To investigate the annual growth rate of obesity prevalence of residents aged 18 and above in China and prevention keypoints for target populations from 2013 to 2018.Methods:This was a cross-sectional study. Subjects from China Chronic Disease and Risk Factor Surveillance project in 2013 and 2018 were included. The prevalence of obesity and growth rate in 31 provinces (autonomous regions and municipalities) in China were collected through survey questionnaires and on-site measurements. Other demographic data such as the proportion of obesity control measures, diet, exercise and drug use was also analyzed. Obesity among adults was defined as body mass index≥28.0 kg/m2.Results:A total of 174 736 residents, aged (51.5±14.2) years, which included 74 704 (42.8%) males were recruited in 2013, and 179 125 residents, aged (55.1±13.8) years, which included 79 337 (44.3%) males were included in 2018. The average annual increase rate of adult obesity prevalence in China from 2013 to 2018 was 3.2% (uncertainty interval ( UI) 2.7%-3.6%), and the average increase rate of obesity prevalence among men (5.2% ( UI 4.6%-5.9%)) was higher than that of women (0.9% ( UI 0.5%-1.3%)). For subgroups analysis, the average increase rate of obesity prevalence among residents aged 18 to 29 (7.4% ( UI 6.9%-7.9%)), education level beyond college degree (6.3% ( UI 5.5%-7.1%)), and unmarried population (11.2% ( UI 10.2%-12.1%)) were higher than that of other subgroups between 2013 and 2018. The residents in Hainan province showed the highest average annual growth rate of obesity. With the exception of Shanxi, Hunan, Gansu and Ningxia province, the annual growth rate of obesity prevalence among adults increased in all other provinces (autonomous regions and municipalities) from 2013 to 2018. For the obese population, the proportion of people who took weight control measures increased from 22.6% in 2013 to 32.7% in 2018. Conclusions:The prevalence of obesity growth characteristics in subpopulations and regions in China are obviously different. Accordingly the focus points of obesity prevention and control in different regions should have their own emphasis.

Objective:To investigate the association between hyperuricemia and the risk for stroke occurrence, as well as the mediating effect of hypertension on this association.Methods:In this study, the China Chronic Diseases and Nutrition Surveillance system in 2015 was used as baseline data. We identified hospital admissions for stroke using the electronic homepage of inpatient medical records from 2013-2020, and death data were obtained from the 2015-2020 National Mortality Surveillance System. A retrospective cohort was established after matching and linking the database. The Cox proportional hazard regression model was used to analyze the relationship between hyperuricemia and the risk of stroke and its subtypes. Restricted cubic spline analysis was conducted to examine the dose-response relationship between serum uric acid levels and the risk for stroke. Mediation analysis was performed to investigate the mediating effect of hypertension on the association between hyperuricemia and the risk for stroke and its subtypes. Subgroup analyses were conducted based on gender and age groups.Results:A total of 124 352 study subjects were included, with an accumulative follow-up time of 612 911.36 person-years. During the follow-up period, 4 638 cases of stroke were found, including 3 919 cases of ischemic stroke and 689 cases of hemorrhagic stroke. The incidence density of stroke was 756.72 per 100 000 person-years, 641.37 per 100 000 person-years for ischemic stroke, and 114.60 per 100 000 person-years for hemorrhagic stroke. Multivariable Cox proportional hazards regression models showed that after adjusting for covariates, compared to those without hyperuricemia, individuals with hyperuricemia had a 16% higher risk for stroke [hazard ratio ( HR)=1.16, 95% CI: 1.06-1.27], a 12% higher risk of ischemic stroke ( HR=1.12, 95% CI: 1.01-1.24), and a 39% higher risk of hemorrhagic stroke ( HR=1.39, 95% CI: 1.11-1.75). Mediation analysis showed that hypertension partially mediated the associations between hyperuricemia and the risk for stroke, ischemic stroke, and hemorrhagic stroke, with mediation proportions of 36.07%, 39.98%, and 25.34%, respectively. The mediating effect is pronounced in the male population and individuals below 65. Conclusion:Hyperuricemia is a risk factor for stroke, and hypertension partially mediates the effect of hyperuricemia on stroke.

Objective:To study the prevalence and association factors of depressive and anxiety disorders in the hypertensive population.Methods:Using the database obtained from the 2013 China Chronic Disease and Risk Factor Surveillance and the 2013-2015 China Mental Health Survey,4 861 hypertensive residents were used as study subjects.And using the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ)as diagnostic criterion for depressive and anxiety disorders,the 12-month prevalence was calculated.Multifactorial lo-gistic regression models were used to explore the association factors of hypertension comorbid depressive and anxie-ty disorders.Results:The 12-month prevalence rates of depressive disorders and anxiety disorders were 4.1％and 5.0％in 4 861 hypertensive residents.Chinese Han[OR(95％CI):2.00(1.01-3.93)],lack of sleep[OR(95％CI):1.82(1.34-2.48)],having myocardial infarction[OR(95％CI):2.35(1.18～4.67)]and stroke in the past year[OR(95％CI):2.10(1.19-3.72)],and chronic obstructive pulmonary disease[OR(95％CI):2.11(1.11-4.05)]were risk factors of hypertension comorbid depressive disorder.Hypertensive people with controlled blood pressure[OR(95％CI):2.01(1.30-3.13)]had a higher risk of co-morbid depressive disorder than those with blood pressure above the normal range on this measurement.Chinese Han[OR(95％CI):2.51(1.32-4.80)],Southwest China[OR(95％CI):1.64(1.02-2.63)],and lack of sleep[OR(95％CI):1.45(1.09-1.93)]were risk factors of hypertension comorbid anxiety disorder.Former but current non-smoking[OR(95％CI):0.48(0.23-0.99)]was a protective factor of hypertension comorbid anxiety disorder.Conclusion:The 12-month prevalence of anxiety disorder was higher than that of depressive disorder in this hypertensive population.Both Han and sleep deprived hypertensive people had a higher risk of comorbid depressive and anxiety disorders.

Objective:To analyze the comorbidity status and influencing factors of hypertension, diabetes, and dyslipidemia among middle-aged and elderly Chinese adults and to provide support for the "co-management of three diseases".Methods:Using the relevant information collected from the National Chronic Disease and Risk Factor Surveillance in China in 2018, 134 950 permanent residents aged ≥45 years were selected as the research objects. After being weighed, the prevalence and comorbidity of hypertension, diabetes, and dyslipidemia in residents with different groups were compared; a multivariate logistic regression model was used to explore the influencing factors of comorbidity of the "three diseases".Results:The prevalence of hypertension, diabetes, and dyslipidemia among middle-aged and elderly Chinese adults were 46.0% (95% CI:45.1%-47.0%), 19.5% (95% CI:18.7%-20.2%), 43.3% (95% CI:42.3%-44.4%), respectively. The comorbidity rates of hypertension and diabetes, hypertension and dyslipidemia, and diabetes and dyslipidemia were 12.3% (95% CI:11.7%-12.8%), 22.8% (95% CI:22.1%-23.4%),11.6% (95% CI:11.1%-12.0%), respectively; the comorbidity rate of hypertension, diabetes, and dyslipidemia was 7.6% (95% CI: 7.2%-8.0%). These comorbidity rates increased with age and BMI, which was more significant in the urban areas than rural areas and more outstanding in North and Northeast China ( P<0.05). The comorbidity rate of hypertension, diabetes, and higher cholesterol was 1.9% (95% CI:1.7%-2.1%). The comorbidity rate of hypertension, diabetes, and higher low-density lipoprotein was 1.6% (95% CI:1.4%-1.7%), which was higher in women than in men ( P<0.05). Multivariate logistic regression results showed that male, age, city, overweight/obesity, excessive drinking, physical inactivity, daily sedentary behavior time ≥5 hours, and sleep duration <7 hours were risk factors for the comorbidity of the "three diseases". Conclusions:The comorbidity of hypertension, diabetes, and dyslipidemia, is common among middle-aged and elderly adults in China; comprehensive prevention and control of risk factors and "co-management of three diseases" are critical measures for health promotion in middle-aged and elderly populations.

Objective:To understand the regular leisure-time physical activity status of residents aged ≥60 years in China and to explore the potential influencing factors.Methods:National Chronic Disease and Risk Factor Surveillance were conducted in 298 counties (districts) in China in 2018, which covered 31 provinces (autonomous regions, municipalities), using a multi-stage stratified cluster random sampling method to select 194 779 permanent residents aged ≥18 years, using a questionnaire containing the Global Physical Activity Questionnaire. A face-to-face survey to obtain demographic information about the survey respondents, the frequency of moderate and vigorous-intensity leisure-time physical activity in their spare time and time, and other information related to chronic diseases and risk factors. Daily temperatures of 298 monitored counties (districts) in 2018 were obtained by inversion of satellite remote sensing data information such as MODIS, OMI, and AIRS, and the number of parks in 2017 was obtained by me. In this study, 68 379 residents aged ≥60 years who completed the survey and had complete information on leisure-time physical activity-related variables, temperature, and parks were used as survey respondents, and the prevalence of regular leisure-time physical activity and average weekly exercise time was calculated by gender in groups of age, urban and rural areas, education level, and geography. Multi-factor logistic regression models were used to analyze the individual and environmental influences on the regular exercise rate. All the results were weighted according to a complex sampling scheme.Results:The prevalence of regular leisure-time physical activity of residents aged ≥60 years in China in 2018 was 13.1% (95% CI: 12.1%-14.0%). The figures were slightly higher for men [13.6% (95% CI: 12.6%-14.7%)] than for women [12.5% (95% CI: 11.5%-13.5%)]; urban [17.5% (95% CI: 15.9%-19.1%)] were significantly higher than those in rural areas [9.6% (95% CI: 8.8%-10.4%)]; the prevalence of regular leisure-time physical activity in East China [15.1% (95% CI: 13.3%-16.9%)] was higher than those in other regions; older residents in counties (districts) with ≥28 parks [17.3% (95% CI: 15.3%-19.2%)] the highest. The average weekly exercise time of elderly residents in China was 68.3 (95% CI: 63.5-73.2) minutes; among them, men [74.3 (95% CI: 68.1-80.5) minutes] was higher than women [62.5 (95% CI: 57.8-67.2) minutes]; urban [89.8 (95% CI: 82.0-97.7) minutes] were higher than rural [51.4 (95% CI: 46.8-56.1) minutes]. The results of the multi-factorial logistic analysis showed that factors such as: living in rural areas, lower annual household income for literacy, poorer self-rated health status, and lack of parks in the area of residence were associated with a lower prevalence of regular leisure-time physical activity among elderly residents. Conclusions:The prevalence of regular leisure-time physical activity among elderly residents in China is still at a low level, and exercise time needs to be improved. We should increase the publicity of "national fitness", pay attention to the disadvantaged elderly groups and provide more suitable activity places to encourage more elderly residents to participate in leisure-time physical activity.

Objective:To improve the longevity genetic research study design by applying self-organizing maps to select a control group for longevity study.Methods:This study included the Han population aged 90 years and above or less than 80 years who have died (control group) from the natural population-based cohort formed by the fusion of the Chinese Chronic Diseases and Risk Factors Surveillance in 2013 and the China Death Surveillance System. The subjects who died of injury, infectious diseases, parasitic diseases, and malignant tumors were excluded. The self-organizing maps method, with multiple iterations and self-organizing clustering, was used to select similar factors among the population aged 90 years and above and the control group, including demographic characteristics, diseases, living habits, social behaviors, and mental and psychological factors. The study used PLINK 1.9 software to evaluate the quality of whole genome sequencing and to conduct logistic regression of single nucleotide polymorphisms (SNPs) and longevity on autosomes. Q-Q plots were used to visualize the P value associated with SNPs and longevity. Results:There were 1 019 samples selected from the baseline of 177 099 survey participants for genome sequencing, including 517 in the longevity group and 502 in the control group. The longevity and the control groups are generally similar in smoking, drinking, diet, sleep duration, blood lipid level, and self-assessment oral health status but differ significantly in socio-economic status, physical activity time, BMI, and self-assessment health status. The whole genome sequencing results were controlled, and 4 618 216 SNPs were involved in association analysis. The Q-Q plot of longevity-related SNPs analysis results showed that the enrichment of P value 1e-4 was significantly lower than the expected P value, and significant signals were also detected among P<1e-7 regions. Conclusions:The self-organizing maps can comprehensively consider the influence of socioeconomic and behavioral risk factors and select longevity control samples among samples with actual age and cause of death in a large-scale natural population cohort to improve the efficiency of longevity genome association analysis. This study provides a methodological reference for nested case-control study sample selection from the large-scale natural population cohort.

Objective:To understand the prevalence of insufficient physical activity among adults aged ≥18 years in China and to explore the influencing factors.Methods:The China Chronic Disease and Risk Factor Surveillance was conducted in 298 counties/districts in China in 2018, covering 31 provinces (autonomous regions, municipalities). A multi-stage stratified cluster random sampling method was used to select permanent residents aged ≥18 years. A questionnaire including Global Physical Activity Questionnaire was used to collect information about the participants' demographic characteristics and physical activity through face-to-face interview. A total of 183 769 participants completed the survey. After complex data weighting, the prevalence of insufficient physical activity, occupation, transportation, and leisure-time physical activity time was analyzed. Multivariate logistic regression models were used to analyze the influencing factors related to insufficient physical activity.Results:The prevalence of insufficient physical activity among adults aged ≥18 years was 22.3% (95% CI: 20.9%-23.7%) in China in 2018, with males [24.4% (95% CI: 23.0%-25.8%)] significantly higher than females [20.2% (95% CI: 18.6%-21.8%)]. Adults aged 70 years and above [28.4% (95% CI: 26.9%-29.9%)] were significantly higher than adults in other age groups, followed by adults aged 18-29 years [26.4% (95% CI: 24.4%- 28.3%)] and 30-39 years [23.4% (95% CI: 21.5%-25.3%)], and tended to increase with increasing education and total sedentary behavior time ( P<0.001). The weekly occupation, transportation, and leisure-time physical activity time appeared 958.6 (95% CI: 911.4-1 005.8) minutes, 234.5 (95% CI: 224.7- 244.2) minutes, and 88.6 (95% CI: 83.5-93.7) minutes, respectively. Multivariate logistic regression analysis showed that males, adults living in rural areas or northern China, ≥70 years, with junior high school education, an annual household income per capita <6 000 yuan and institutional/clerical/ technical occupation and longer total sedentary behavior time were related to a higher prevalence of insufficient physical activity. Conclusions:In China, over one-fifth of the adults had lower physical activity levels. Adults who are male, young adults, more educated, institutional/clerical/technical occupation, and with more extended total sedentary behavior are the populations that need to be focused on to promote physical activity-related health.