Disability-Free Life Expectancy and Its Drivers Among Adults Aged 60 and Above — China, 2018 and 2023

Yuqing Feng^1,2,&, Zhiwen Miao^3,&, Yue Cai³; Chengdong Xu^1,2; Shiyong Wu^3,#; Jinfeng Wang^1,2,#

1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.

2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.

3. Center for Health Statistics and Information, National Health Commission, Beijing, China.

^& Joint first authors.

^# Corresponding author: Shiyong Wu, wusy99@126.com; Jinfeng Wang, wangjf@lreis.ac.cn.

Disability-free life expectancy (DFLE) is a key metric of healthy aging. While prior studies have explored its trends and provincial-level patterns, sub-provincial variations and urban-rural disparities in China are underexplored. DFLE across prefectures was estimated using the Sullivan method, based on mortality data from the death registration system and disability data from the National Health Service Survey. A geodetector was used to assess the explanatory power of the socioeconomic, healthcare, environmental, and demographic factors. DFLE increased in all regions between 2018 and 2023, with a narrowing urban-rural gap. The largest gains occurred in the western region, but urban–rural inequality showed the least improvement. DFLE exhibited notable stratified spatial heterogeneity, predominantly driven by socioeconomic factors, whose influence weakened with advancing age, whereas environmental and demographic factors became more prominent. All the factors had stronger explanatory power in rural areas. Although DFLE improved nationwide, inequalities persisted. Targeted public health strategies are needed to reduce disparities, with priority placed on healthcare access, social security, and climate-adaptive infrastructure in rural areas, particularly in western China.

老年人健康预期寿命的城乡差异及影响因素研究 — 中国，2018和2023年

封雨晴^1,2,&，缪之文^3,&，蔡玥³，徐成东^1,2，吴士勇^3,#，王劲峰^1,2,#

1. 资源与环境信息系统，国家重点实验室，地理科学与资源研究所，中国科学院，北京，中国；

2. 资源与环境学院，中国科学院大学，北京，中国；

3. 统计信息中心，国家卫生健康委，北京，中国。

^& 共同第一作者。

^# 通讯作者：吴士勇，wusy99@126.com，王劲峰，wangjf@lreis.ac.cn。

健康预期寿命是衡量健康老龄化的关键指标。既往研究多关注其整体趋势与省级差异，而对省以下尺度和城乡差异的认识不足。本研究旨在估算2018年与2023年中国60岁及以上老年人群的无残疾预期寿命(Disability-Free Life Expectancy, DFLE)，分析其时空变化特征，并识别城乡差异的影响因素。本研究基于死亡登记系统的死亡数据及国家卫生服务调查的失能数据，采用Sullivan方法测算了2018年与2023年中国老年人的DFLE，并运用地理探测器模型评估社会经济、医疗卫生、环境与人群特征四类因素对城乡DFLE差异的解释力。2023年全国所有地区DFLE较2018年均有提升，城乡差距总体缩小。西部地区DFLE增幅最大，但城乡差异改善程度最低。DFLE呈现显著的分层空间异质性，主要驱动因素为社会经济发展水平，其影响随年龄增长逐渐减弱，而环境与人口因素的作用则逐渐凸显。所有影响因素在农村的解释力均更强。我国老年人健康预期寿命整体提高，但区域差异仍然存在。应制定更具针对性的公共卫生策略，以推动健康老龄化的公平实现。重点关注农村，特别是西部地区，强化其医疗卫生服务体系、社会保障和气候适应型基础设施的建设。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.271

Prevalence of Depression and Anxiety Symptoms and the Influencing Factors Among Older Adults Aged 60 Years and Over — 7 PLADs, China, 2024

Xin Gao^1,2; Yingchen Sang¹; Youjiao Wang¹; Xinying Zeng¹; Jinglei Wang²; Xiang Si²; Ying Liu¹; Shiwei Liu^1,#

1. Tobacco Control Office, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China;

2. Office of NCD and Ageing Health Management, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.

^# Corresponding author: Shiwei Liu, liusw@chinacdc.cn.

The increasing prevalence of depression and anxiety among older adults poses a significant public health challenge, necessitating a comprehensive understanding of the factors associated with these disorders. This study aimed to elucidate these correlates through a cross-sectional survey conducted across seven provincial-level administrative divisions (PLADs) in China in 2024. Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to evaluate symptoms of depression and anxiety among 20,113 participants aged ≥60 years. The findings indicated a prevalence of anxiety symptoms was 13.8% [95% confidence interval (CI): 12.1%, 15.5%] for depression symptoms and 8.0% (95% CI: 7.0%, 9.0%) for anxiety symptoms. Notably, the analysis revealed that older age, female sex, presence of comorbid chronic diseases, lower educational attainment, insufficient physical activity, and poor sleep quality were significantly correlated with a higher prevalence of these mental health issues. Specifically, participants with poor sleep quality exhibited an odds ratio (OR) of 7.88 (95% CI: 6.33, 9.79) for depression and 6.42 (95% CI: 5.02, 8.22) for anxiety compared to those with good sleep quality. In conclusion, this study underscores the critical role of modifiable factors such as chronic disease and sleep quality in addressing depression and anxiety among older adults. Future interventions should focus on chronic disease management and lifestyle modifications to improve the mental health of vulnerable populations.

60岁及以上老年人抑郁症状和焦虑症状的流行及其影响因素研究 — 7省份，中国，2024年

高欣^1,2，桑莹宸¹，王友娇¹，曾新颖¹，王静雷²，司向²，刘影¹，刘世炜^1,#

1. 控烟办公室，中国疾病预防控制中心 （中国预防医学科学院），北京，中国；

2. 慢病和老龄健康管理处，中国疾病预防控制中心 （中国预防医学科学院），北京，中国。

^# 通信作者：刘世炜，liusw@chinacdc.cn。

老年人群的抑郁和焦虑问题日益普遍，给公共卫生带来巨大挑战，亟需全面了解这些心理健康问题现状及其相关影响因素。本研究旨在通过对2024年在中国七个省级行政区 (PLADs)进行的横断面调查数据分析，阐明老年人焦虑和抑郁流行状况及其影响因素。本研究纳入20,113名60岁及以上老年人，通过患者健康问卷 (PHQ-9)和广泛性焦虑量表 (GAD-7)评估其抑郁和焦虑症状。研究结果显示，抑郁症状的检出率为13.8% (95% CI: 12.1%, 15.5%)，焦虑症状的检出率为8.0% (95% CI: 7.0%, 9.0%)。分析显示，年龄较大、女性、合并慢性疾病、教育程度较低、体力活动不足和睡眠质量差与抑郁、焦虑的检出率显著相关。与睡眠质量好的老年人相比，睡眠质量差的老年人更容易出现抑郁症状(OR=7.88，95% CI: 6.33, 9.79)和焦虑症状(OR=6.42, 95% CI: 5.02, 8.22)。本研究强调了可改变因素 (如慢病管理和睡眠质量)在预防老年人抑郁和焦虑中的关键作用。未来的干预措施应侧重于促进健康生活方式和加强慢病管理，以提升这一脆弱人群的心理健康水平。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.272

The Evolution of Patterns of Mortality and Disability Burden Among Older Adults — China, 1990–2023

Ainan Jia^1,&, Yuchang Zhou^2,&, Xiaohui Xu^1,3, Xinlei Gao¹, Yuyan Liu¹, Xiang Li¹, Yamin Bai^1,#, Xue Yu^4,#, Maigeng Zhou¹

1. National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.

2. Beijing Institute of Geriatrics, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

3. Department for Chronic and Non-communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Shandong City, Shandong Province, China.

4. Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

^& Joint first authors.

^# Corresponding authors: Yamin Bai, baiyamin@ncncd.chinacdc.cn；Xue Yu, yuxue2652@bjhmoh.cn.

China is confronting profound public health challenges owing to its rapidly aging population. However, current research often overlooks heterogeneity among older age subgroups, limiting the effectiveness of targeted policy interventions. To address these gaps and support evidence-based health strategies, this study used Global Burden of Disease Study 2023 data to analyze age-specific mortality rates (MR) and years lived with disability (YLDs) among older adults in China from 1990 to 2023. Estimates were further stratified into three subgroups (60–74, 75–89, and 90 years and above). Temporal trends were assessed using the average annual percent change (AAPC). Between 1990 and 2023, all-cause mortality declined substantially, whereas YLDs remained stable. Stroke, ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) remained the leading mortality causes, with MR per 100,000 at 619.53 (95% Uncertainty interval (UI): 478.17, 773.06), 605.01 (468.76, 748.25), and 324.76 (230.53, 495.15) in 2023, respectively. Alzheimer's disease and other dementias (ADOD) showed a rapid increase in MR with an AAPC of 1.76 [95% confidence interval (CI): 1.63, 1.87]. Age-related hearing loss and falls dominated in YLDs, with rates of 2833.58 (1960.10, 3896.06) and 2245.49 (1615.92, 3094.28) per 100,000 in 2023. Significant age disparities were also observed. IHD accounted for 26.20% of deaths in the 90+ age group, whereas ADOD accounted for 13.24%. China's aging population requires stratified, evidence-based policies integrating prevention and disability management to optimize healthy aging under "Healthy China 2030.".

老年人群死亡和伤残负担模式的演变特征研究 — 中国，1990–2023年

贾艾楠^1,&；周宇畅^2,&；徐晓慧^1,3；高鑫磊¹；刘玉燕¹；李想¹；白雅敏^1,#；于雪^4,#；周脉耕¹

1. 慢性非传染性疾病预防控制中心，中国疾病预防控制中心（中国预防医学科学院），北京，中国；

2. 北京市老年医学研究所，国家老年医学中心，老年医学研究院，中国医学科学院，北京，中国；

3. 慢性非传染性疾病预防控制所，山东省疾病预防控制中心，济南市，山东省，中国；

4. 北京医院心内科，国家老年医学中心，老年医学研究院，中国医学科学院，北京，中国。

^& 共同第一作者。

^# 通信作者：白雅敏，baiyamin@ncncd.chinacdc.cn；于雪，yuxue2652@bjhmoh.cn。

中国正面临人口快速老龄化所带来的深刻公共卫生挑战。然而，现有研究往往未能充分考虑老年人群内部的异质性，从而限制了针对性政策干预措施的有效性。为弥补这一研究空白并为循证卫生策略提供依据，本研究利用2023年全球疾病负担研究数据，系统分析了1990年至2023年中国老年人分年龄别死亡率及伤残生存年（YLDs）的变化趋势。研究进一步将人群划分为三个亚组（60–74岁、75–89岁、90岁及以上）进行分析，并采用平均年度变化百分比（AAPC）评估时间趋势。研究结果显示，1990年至2023年间，全死因死亡率显著下降，而YLDs保持稳定。卒中、缺血性心脏病和慢性阻塞性肺疾病仍是主要致死原因，2023年死亡率分别为每10万人619.53（95% UI: 478.17–773.06）、605.01（468.76–748.25）和324.76（230.53–495.15）。阿尔茨海默病及其他痴呆症的死亡率增长最为迅速，AAPC达1.76 (95% CI: 1.63–1.87)。在伤残负担方面，年龄相关性听力损失和跌倒为主要致残原因，2023年每10万人YLDs率分别为2833.58（1960.10–3896.06）与2245.49（1615.92–3094.28）。分析显示显著的年龄层差异：在90岁及以上高龄群体中，缺血性心脏病导致的死亡占26.20%，阿尔茨海默病及其他痴呆相关死亡占13.24%。为实现"健康中国2030"战略目标下的健康老龄化，我国亟需制定分层的、基于证据的公共卫生政策，统筹推进疾病预防与伤残管理。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.274

Burden and Risk Factors of Gout, Low Back Pain, Osteoarthritis, and Rheumatoid Arthritis — China, 1990–2023

Kun Xu¹; Feng Pan¹; Kunzhi Zhu¹; Yuan Gao¹; Jun Zhang^1,#

1. Joint Surgery, Beijing Jishuitan Hospital Guizhou Hospital, Guiyang City, Guizhou Province, China.

^# Corresponding author: Jun Zhang, zhangjun@stu.jnu.edu.cn.

Musculoskeletal diseases including gout, low back pain (LBP), osteoarthritis (OA), and rheumatoid arthritis (RA) impose a substantial health burden in China. This study analyzes disease trends from 1990 to 2023 and projects trends over the next 20 years to inform evidence-based prevention and management strategies. We utilized Global Burden of Disease (GBD) 2023 data to assess the burden of gout, LBP, OA, and RA. Temporal trends were evaluated using annual percentage change (APC) and estimated annual percentage change (EAPC), with systematic stratification by gender, age, and risk factors. The Autoregressive Integrated Moving Average (ARIMA) model was employed to forecast future disease rates. In 2023, China's prevalence cases for gout, LBP, OA, and RA were 17.67, 95.32, 161.74, and 4.99 million, respectively. From 1990 to 2023, the burden of gout, OA, and RA increased substantially, while LBP declined. Gout burden was higher in males, whereas LBP, OA, and RA were higher in females, with disease concentration in the 40–80 age group. Disability-adjusted life years (DALYs) attributable to high body mass index (BMI) increased for gout, OA, and LBP. ARIMA projections indicate continued increases for gout, OA, and RA, but improvement for LBP. The burden of gout, OA, and RA in China increased from 1990 to 2023, while LBP demonstrated improvement. Significant variations exist across gender and age groups. Strengthening health education and implementing comprehensive risk factor prevention strategies are crucial to reduce the future burden of these diseases.

痛风、腰背痛、骨关节炎及类风湿关节炎的疾病负担与危险因素：基于2023年全球疾病负担研究 — 中国，1990–2023年

徐坤¹；潘沨¹；朱坤智¹；高原¹；张骏^1,#

1. 关节外科，北京积水潭医院贵州医院，贵阳市，贵州省，中国。

^# 通讯作者: 张骏，zhangjun@stu.jnu.edu.cn。

痛风、腰背痛（LBP）、骨关节炎（OA）和类风湿关节炎（RA）等肌肉骨骼疾病给中国带来了沉重的健康负担。本研究分析了1990年至2023年间的疾病变化趋势，并对未来20年的趋势进行了预测，旨在为制定有效的防控策略提供科学依据。利用2023年全球疾病负担（GBD 2023）研究数据，评估痛风、LBP、OA及RA的疾病负担。采用年度变化百分比（APC）和估算年度变化百分比（EAPC）评估时间趋势，并按性别、年龄和危险因素进行了系统分析。同时，采用自回归移动平均（ARIMA）模型预测未来的发病趋势。2023年，中国痛风、LBP、OA和RA的患病人数分别为1767万、9532万、1.6174亿和499万。1990年至2023年间，痛风、OA和RA的疾病负担呈上升趋势，而LBP有所下降。痛风的疾病负担在男性中较高，而LBP、OA和RA在女性中较高，且主要集中在40-80岁年龄段。与高体重指数（BMI）相关的伤残调整寿命年（DALYs）（涉及痛风、OA和LBP）呈上升趋势。ARIMA模型预测显示，未来痛风、OA和RA的负担将持续增加，而LBP的情况将有所改善。1990年至2023年，中国痛风、OA和RA的疾病负担呈加重，而LBP的负担有所减轻。同时疾病负担在不同性别和年龄间存在显著差异。因此，加强健康教育和危险因素防控对于降低这些疾病未来的负担至关重要。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2025.273