中国成年双生子饮酒行为的分布特征和遗传度

李渊宸; 高文静; 曹卫华; 吕筠; 余灿清; 王胜锋; 黄涛; 孙点剑一; 廖春晓; 庞元捷; 高汝钦; 俞敏; 周金意; 吴先萍; 董忠; 吴凡; 王德征; 许志华; 刘彧; 马艳霞; 尹洁; 尹胜利; 李立明

Abstract

李渊宸,高文静,曹卫华,吕筠,余灿清,王胜锋,黄涛,孙点剑一,廖春晓,庞元捷,高汝钦,俞敏,周金意,吴先萍,董忠,吴凡,王德征,许志华,刘彧,马艳霞,尹洁,尹胜利,李立明.中国成年双生子饮酒行为的分布特征和遗传度[J].Chinese journal of Epidemiology,2025,46(1):73-80

中国成年双生子饮酒行为的分布特征和遗传度

Distribution characteristics and heritability of alcohol consumption behavior in adult twins in China

Received:May 22, 2024

DOI：10.3760/cma.j.cn112338-20240522-00294

KeyWord: 饮酒行为双生子研究遗传因素描述性研究

English Key Word: Alcohol consumption Twin study Genetic factor Descriptive analysis

FundProject:国家自然科学基金（82173499，82373659，82073633）；公益性行业科研专项（201502006，201002007）

Author Name	Affiliation	E-mail
Li Yuanchen	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
Gao Wenjing	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China	pkuepigwj@126.com
Cao Weihua	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
Lyu Jun	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness &Response, Beijing 100191, China
Yu Canqing	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness &Response, Beijing 100191, China
Wang Shengfeng	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
Huang Tao	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
Sun Dianjianyi	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness &Response, Beijing 100191, China
Liao Chunxiao	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness &Response, Beijing 100191, China
Pang Yuanjie	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness &Response, Beijing 100191, China
Gao Ruqin	Qingdao Municipal Center for Disease Control and Prevention, Qingdao 266033, China
Yu Min	Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
Zhou Jinyi	Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210008, China
Wu Xianping	Sichuan Center for Disease Control and Prevention, Chengdu 610041, China
Dong Zhong	Beijing Center for Disease Control and Prevention, Beijing 100013, China
Wu Fan	Shanghai Medical College of Fudan University, Shanghai 200032, China
Wang Dezheng	Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
Xu Zhihua	Qinghai Center for Disease Prevention and Control, Xining 810007, China
Liu Yu	Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150090, China
Ma Yanxia	Handan Center for Disease Control and Prevention, Handan 056001, China
Yin Jie	Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
Yin Shengli	Dezhou Center for Disease Control and Prevention, Dezhou 253516, China
Li Liming	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness &Response, Beijing 100191, China

Hits: 658

Download times: 266

Abstract:

目的描述中国双生子登记系统（CNTR）中成年双生子饮酒行为的分布特征，并进一步探究遗传因素对饮酒行为的影响。方法研究对象为2010-2018年CNTR在全国11个项目地区登记的双生子，共纳入56 966名（28 483对）≥18岁且回答饮酒行为相关问题的双生子，使用随机效应模型描述饮酒行为的人群、地区分布特征。进行双生子对内分析，计算饮酒行为一致率和遗传度。结果研究对象年龄为（36.6±12.0）岁，全部研究对象中当前饮酒者占比为16.6%（9 461/56 966）。在男性、50~59岁组、北方、乡村、高中及以下文化程度、超重/肥胖人群中当前饮酒者占比较高。剔除有戒酒行为的468对双生子、21 764对不饮/轻度饮酒的双生子后，在4 929对同性别双生子中进行对内分析发现，同卵双生子饮酒一致率为64.0%（2 059/3 215），异卵双生子为52.6%（902/1 714），差异有统计学意义（P<0.001），饮酒行为遗传度为24.1%（95%CI：18.9%~29.3%）。进一步分层分析后发现，在南方男性中，遗传度在40~49岁人群中最高［36.1%（95%CI：21.6%~50.7%）］，而在北方男性中，遗传度在50~59岁人群中最高［34.2%（95%CI：18.1%~50.3%）］。结论在我国成年双生子中，饮酒行为的分布存在人群和地区差异，饮酒行为受到遗传因素的影响，性别、年龄和地区具有潜在的修饰作用。

English Abstract:

Objective To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins. Methods The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption. Results The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant (P<0.001), and the heritability of alcohol consumption was 24.1% (95%CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95%CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95%CI: 18.1%-50.3%). Conclusions In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

View Fulltext Html FullText View/Add Comment Download reader