National and Provincial Burden of Non-Communicable Diseases Attributable to High Alcohol Use — China, 1990–2023

Yang Yang¹; Teng Li¹; Zhenping Zhao¹; Maigeng Zhou^1#

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

^# Corresponding author: Maigeng Zhou, zhoumaigeng@ncncd.chinacdc.cn.

To address the lack of long-term national–provincial comparisons, we used Global Burden of Disease 2023 to assess high alcohol use attributable non-communicable diseases (NCDs) burden in 31 provincial-level administrative divisions (PLADs) and Hong Kong and Macao Special Administrative Regions (SARs) at national and provincial levels from 1990 to 2023. We summarized deaths and disability-adjusted life years (DALYs) for GBD Level 1 cause NCDs and alcohol-linked Level 2 causes based on GBD comparative risk assessment framework. Analyses were conducted according to cause composition, age, sex, and region. In 2023, age-standardized death and DALY rate declined markedly (−57.6%, −46.9%), while absolute numbers rose slightly (11.8%, 6.9%) compared with 1990. Neoplasms contributed to the largest DALYs, followed by substance use disorders; diabetes and kidney diseases are smaller but rising(160.22%，1990-2023). Peaks occurred at 40 to 64 years (digestive, neoplasms, substance use) and 65 and older (cardiovascular, diabetes and kidney); neurological disorders are most negative at ages 65 and older. The male age-standardized DALY rate was 10.64 times that of females, and marked spatial heterogeneity persisted, with distinct provincial clustering by disease category. Declining rates but persistent absolute high alcohol use attributable burden and heterogeneous profiles support cause, age, sex and region-specific strategies prioritizing substance use disorders and monitoring the rise in diabetes and kidney diseases while sustaining efforts to reduce the large neoplasm burden.

国家及省级归因于高酒精使用慢性非传染性疾病负担 — 中国，1990–2023年

杨洋¹；李腾¹；赵振平¹；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。

^# 通信作者: 周脉耕，zhoumaigeng@ncncd.chinacdc.cn。

为弥补长期全国省级比较的不足，本研究基于全球疾病负担研究（GBD）2023，评估1990—2023年中国和31个省级行政区及香港、澳门特别行政区归因于高酒精使用的慢性非传染性疾病（NCDs）负担。研究基于GBD比较风险评估框架，汇总归因于高饮酒水平的死亡数和伤残调整寿命年（DALYs），涵盖GBD一级死因中的NCDs及与饮酒相关的二级死因；并按病因、年龄、性别和地区进行分析。研究结果显示，相较于1990年，2023年的年龄标化死亡率和DALY率均下降(−57.6%, −46.9%)，但死亡数和DALY数均上升(11.8%, 6.9%)。肿瘤贡献的DALYs最大，其次为物质使用障碍；糖尿病及肾脏疾病负担相对较小但呈上升趋势(160.22%，1990-2023)。消化系统疾病、肿瘤和物质使用障碍的DALYs峰值出现在40–64岁；心血管疾病以及糖尿病及肾脏疾病峰值出现在65岁及以上。神经系统疾病归因DALYs在65岁及以上负值最大。男性年龄标化DALY率为女性的10.64倍，且不同病因类别仍呈现明显的省级聚集分布。分析显示尽管年龄标化率下降，但归因于高酒精使用的绝对疾病负担仍高且异质性明显，提示需制定针对病因、年龄、性别和地区的防控策略：优先干预物质使用障碍，监测糖尿病及肾脏疾病上升趋势，同时持续推进降低肿瘤负担的措施。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.005

Alcohol Use Prevalence Among Chinese People Aged 15 Years and Above — China, 2024

Ning Ji^1,&;  Youjiao Wang^2,&;  Yingchen Sang²;  Xinying Zeng²;  Ying Liu²;  Shiwei Liu^2,#

1. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China;

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

^& Joint first authors.

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

Alcohol use represents a major public health challenge worldwide. This survey provides nationally representative data on alcohol consumption patterns among China's population aged 15 years and above. In 2024, a population-based cross-sectional survey was conducted using a multi-stage stratified cluster random sampling design. Trained interviewers administered self-reported questionnaires to collect data on the prevalence of alcohol use in the past 30 days, past 12 months, and heavy episodic drinking (HED). Prevalence estimates with 95% confidence intervals (CIs) were calculated using weighted methods appropriate for the complex sampling design. Results showed that among Chinese individuals aged 15+ years, the prevalence of alcohol use was 20.3% in the past 30 days and 27.6% in the past 12 months. Males demonstrated significantly higher rates than females (past-month: 34.3% vs. 5.9%; past-year: 44.5% vs. 10.2%), with prevalence peaking in the 25–44 age group (past-month: 23.2%, past-year: 32.5%). Among current drinkers, the most common drinking frequency was <1 day/month (32.3%). Frequent drinking (≥5 days/week) was reported by 17.5% of current drinkers, with males (20.1%) exceeding females (5.7%). Additionally, 42.9% of current drinkers engaged in HED, with males (48.0%) substantially exceeding females (19.9%). The prevalence of alcohol use in China was lower than the global average. However, the proportion of HED among current drinkers was comparatively high. Pronounced gender disparities were observed, with males demonstrating substantially higher rates across all indicators. Targeted interventions addressing gender-specific drinking patterns and HED reduction among current drinkers are needed.

15岁及以上人群饮酒情况调查 — 中国，2024年

吉宁^1,&；王友娇^2,&；桑莹宸²；曾新颖²；刘影²；刘世炜^2,#

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. 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。

^& 共同第一作者。

^# 通信作者：刘世炜，liusw@chinacdc.cn。

饮酒是一个重大的公共卫生问题。本调查提供了中国15岁及以上人群饮酒情况的全国代表性数据。2024年，采用多阶段分层整群随机抽样设计，对15岁及以上居民开展了一项基于人群的横断面调查。经过培训的调查人员利用自填式问卷收集了以下饮酒情况的数据：过去30天、过去12个月内的饮酒情况以及重度间歇性饮酒情况（heavy episodic drinking，HED）。针对复杂抽样设计，采用加权方法计算了率的估计值及其95%置信区间。研究结果显示，2024年，在中国15岁及以上人群中，过去30天饮酒率为20.3%，过去12个月饮酒率为27.6%。男性饮酒率显著高于女性（过去30天：34.3% vs. 5.9%；过去12个月：44.5% vs. 10.2%），且饮酒率在25–44岁年龄组达到峰值（过去30天：23.2%，过去12个月：32.5%）。现在饮酒者中，饮酒频率以“<1天/月”最为常见（32.3%）。饮酒频率每周饮酒≥5天者占17.5%，其中男性（20.1%）高于女性（5.7%）。此外，42.9%的现在饮酒者有HED，男性（48.0%）显著高于女性（19.9%）。分析显示，中国饮酒率低于全球平均水平，但饮酒者中重度间歇性饮酒的比例相对较高，且存在显著的性别差异，男性各项指标均远高于女性。需据此制定针对性干预措施。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.006

A Norovirus and Rotavirus Co-Infection Outbreak Investigation in a Primary School — Pudong New Area, Shanghai Municipality, China, March 2025

Yanxin Xie¹, Lili Feng¹, Zhiying Zhao¹, Bing Zhao¹, Tanghu Xu², Yunxia Li², Siqi Fan³, Shaotan Xiao¹, Zhaorui Chang^4,#, Chuchu Ye^1,#

1. Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute), Shanghai, China;

2. Heqing Community Health Service Center, Shanghai, China;

3. Chuansha Community Health Service Center, Shanghai, China;

4. Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.

^# Corresponding author: Zhaorui Chang, changzr@chinacdc.cn; Chuchu Ye, ccye@pdcdc.sh.cn.

Gastrointestinal disease outbreaks pose significant public health challenges, particularly in high-density settings such as schools. This study presents a rare co-infection outbreak caused by two enteric viruses in a primary school. Active case searching was employed to identify all cases, and pathogens were identified using polymerase chain reaction (PCR) nucleic acid testing. The outbreak affected 14 cases in 1 class, yielding a 38.9% attack rate with mild symptoms. Among 8 anal swab samples, 3 cases tested positive for norovirus GI, 2 cases (including the index case) tested positive for rotavirus A, and 1 case tested positive for both norovirus GI and rotavirus A. Among 8 environmental samples, 4 samples tested positive for both norovirus GI and rotavirus A, 1 sample tested positive for norovirus GI only, and 3 samples tested positive for rotavirus A only. The outbreak was initiated by the index case vomiting in the classroom; individuals with atypical symptoms and environmental contamination subsequently contributed to the co-infection transmission. Case numbers peaked within 3 days before the outbreak was successfully controlled. Notably, family-based active case searching identified 1 asymptomatic carrier of norovirus GI. Dining facilities and water hygiene were confirmed safe, ruling out foodborne or waterborne transmission. Timely and proactive intervention strategies are crucial for outbreak control in high-density settings, particularly given that different pathogens possess varying transmission potentials and incubation periods.

某小学一起诺如病毒与轮状病毒共感染暴发疫情调查 — 浦东新区，上海市，中国，2025年3月

谢彦昕¹，冯莉莉¹，赵治英¹，赵冰¹，徐唐虎²，李云霞²，樊斯骑³，肖绍坦¹，常昭瑞^4,#，叶楚楚^1,#

1. 上海市浦东新区疾病预防控制中心（上海市浦东新区卫生健康监督所）, 上海，中国；

2. 合庆社区卫生服务中心, 上海，中国；

3. 川沙社区卫生服务中心, 上海，中国；

4. 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：常昭瑞，changzr@chinacdc.cn；叶楚楚，ccye@pdcdc.sh.cn。

在学校等人群高密度重点机构中，胃肠道疾病暴发疫情构成了重大公共卫生挑战。本研究介绍了一起发生于小学的由两种肠道病毒引起的共感染暴发疫情。采用主动病例搜索识别病例，通过PCR核酸检测明确感染病原体。本疫情发生在1个班级共14例病例，班级发病率为38.9%，所有病例均为轻症。共采集8份病例肛拭子，其中3份诺如病毒GI（+）；2份（包括指示病例）轮状病毒A（+）；1份诺如病毒GI（+）+轮状病毒A（+）。共采集8份环境样本，其中4份诺如病毒GI（+）+轮状病毒A（+）；3份轮状病毒A（+）；1份诺如病毒GI（+）。本疫情由指示病例在班级内呕吐引发，非典型症状个体和被污染的环境导致双病毒共感染，病例数在3天内达到高峰后被有效控制。同时，家庭主动病例搜索发现1例诺如病毒GI无症状携带者。本起疫情排除了食源性或水源性感染来源。不同病原体的传播能力及潜伏期不同，在人群密集重点机构中，有效的干预策略对共感染疫情防控至关重要。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.007

Large Language Model-Based Text Recognition and Structured Data Extraction for Dietary Surveys

Fangxu Guan^1,&, Ruixue Niu^2,&, Feifei Huang¹, Xiaofan Zhang¹, Yanli Wei¹, Jiguo Zhang¹, Xiaofang Jia¹, Yifei Ouyang¹, Jing Bai¹, Chang Su¹, Li Li¹, Wenwen Du^1,#, Honglei Liu^3,#, Huijun Wang¹

1. Key Laboratory of Public Nutrition and Health, National Health Commission of the People's Republic of China; National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China;

2. School of Software Engineering, Beijing Jiaotong University, Beijing, China;

3. School of Biomedical Engineering, Capital Medical University, Beijing, China.

^& Joint first authors.

^# Corresponding authors: Wenwen Du, duww@ninh.chinacdc.cn; Huijun Wang, wanghj@ninh.chinacdc.cn.

Traditional dietary surveys are time-consuming, and manual recording may lead to omissions. Improvement during data collection is essential to enhance accuracy of nutritional surveys. In recent years, large language models (LLM) have been rapidly developed, which can provide text processing functions and assist investigators in conducting dietary surveys. Thirty-eight participants from 15 families in the Huangpu and Jiading districts of Shanghai were selected. A standardized 24-hour dietary recall protocol was conducted using an intelligent recording pen that simultaneously captured audio data. There recordings were then transcribed into text. After preprocessing, we used GLM-4 for prompt engineering and chain-of-thought for collaborative reasoning, output structured data, and analyzed its integrity and consistency. Model performance was evaluated using precision and F1 scores. The overall integrity rate of the LLM-based structured data reached 92.5%, and the overall consistency rate compared with manual recording was 86%. The LLM can accurately and completely recognize the names of ingredients and dining and production locations during the transcription. The LLM achieved 94% precision and an F1 score of 89.7% for the full dataset. LLM-based text recognition and structured data extraction can serve as effective auxiliary tools to improve efficiency and accuracy in traditional dietary surveys. With the rapid advancement of artificial intelligence, more accurate and efficient auxiliary tools can be developed more precise and efficient data collection in nutrition research.

膳食调查中基于大语言模型的文本识别和结构化数据提取

关方旭^1,&，牛瑞雪^2,&，黄绯绯¹，张晓帆¹，魏艳丽¹，张继国¹，贾小芳¹，欧阳一非¹，白晶¹，苏畅¹，李丽¹，杜文雯^1,#，刘红蕾^3,#，王惠君¹

1. 公共营养与健康重点实验室，国家卫生健康委员会；营养与健康所，中国疾病预防控制中心（中国预防医学科学院），北京，中国；

2. 软件工程学院，北京交通大学，北京，中国；

3. 生物医学工程学院，首都医科大学，北京，中国。

^& 共同第一作者。

^# 通信作者：杜文雯，duww@ninh.chinacdc.cn；王惠君，wanghj@ninh.chinacdc.cn。

传统膳食调查耗时较长，且人工记录可能导致遗漏。在数据收集过程中进行改进对于提高营养调查的准确性至关重要。近年来，大型语言模型（LLM）得到快速发展，可提供文本处理功能并协助调查人员开展膳食调查。选取上海市黄浦区和嘉定区15个家庭的38名参与者，使用智能录音笔同步采集音频数据，进行标准化24小时膳食回顾调查。录音随后被转录为文本，预处理后采用GLM-4模型进行提示工程设计和链式推理，输出结构化数据并分析其完整性和一致性。通过精确率和F1分数评估模型性能。基于LLM的结构化数据总体完整率达92.5%，与人工记录的总体一致性率为86%。LLM在转录过程中能准确完整地识别食材名称、用餐地点及制作地点。在整体数据集上，模型精确率为94%，F1分数为89.7%。基于LLM的文本识别和结构化数据提取可作为有效的辅助工具，提高传统膳食调查的效率和准确性。随着人工智能的快速发展，有望开发出更精准高效的辅助工具，为营养研究提供更精确的数据收集支持。

For more information: https://weekly.chinacdc.cn/en/article/doi/10.46234/ccdcw2026.008