Alcohol Use Disorder and Its Association with Quality of Life and Mortality in Chinese Adult Males: A Population-Based Cohort Study | BMC Public Health

Study design and population

The China PEACE Million Persons Project is a government-funded public health project across China. The details of the project design have been described previously [12]. Briefly, from September 2014 to November 2019, 254 county-level regions in the 31 provinces of mainland China were selected as study sites to provide diversity in geographic distribution, population structure (ethnic distribution) and exposure to risk factors and disease patterns. Although study sites were not randomly selected, selection considered population size, population stability, and local capacity to support the project. Local residents between the ages of 35 and 75, who were currently registered in the community’s Hukou (a register officially identifying residents of the area), or who had lived in the community for at least 6 of the previous 12 months, were invited and recruited in this project. The overall response rate was approximately 30%. Enrolled participants with a serial project ID number ending in 1, 3, 5, or 7, who were chosen for a detailed lifestyle survey as a representative sample of the entire cohort of the project, were included in the analyzes of the study. We excluded female participants because the rate of alcohol consumption among them was very low (about 5.9%). The central ethics committee of the Chinese National Center for Cardiovascular Diseases has approved this project. All registered participants provided written informed consent.

Data collection and variables

For each participant, standardized face-to-face interviews were conducted by trained staff to collect information on socio-demographic status (education, annual household income, health insurance and marital status), lifestyle (smoking, alcohol, diet and physical activity), medical history and quality of life. Blood pressure, height and weight were measured using unified protocols and devices.

The presence of AUD was assessed by the AUDIT score (alcohol use disorder identification test) [13]. Each of the 10 AUDIT questions has an answer set, which has a score ranging from 0 to 4. The answer scores for all 10 questions were added together to get the total score for each participant. The presence of AUD was defined as the total AUDIT score equal to or greater than 8 according to the recommendation of the World Health Organization (WHO) [13]. Current drinker was defined on the basis of question 1, as having drunk at least once a month in the past 12 months [14]. The AUDIT includes three conceptual domains including hazardous drinking, presence of symptoms of dependence, and harmful drinking. A score of 1 or more on question 2 or question 3 indicates drinking at a dangerous level. Points scored above 0 in questions 4-6 (especially weekly or daily symptoms) imply the presence or onset of symptoms of alcohol dependence. The points scored in questions 7 to 10 indicate that harmful consumption of alcohol has already taken place. The AUDIT has been validated in the Chinese population, which has high validity (0.93-0.95) and high reliability (0.95-0.99) [15]. And it has high sensitivity (0.877-1.000) and specificity (0.881-0.900) to identify participants with AUD.

The EuroQol three-level five-dimensional instrument (EQ-5D-3L) was used to assess quality of life (QOL) [16]. For each participant, an index score of the EQ-5D-3L instrument was calculated based on the time trade-off method for the Chinese population [17]. The highest index score was 0.961 as optimal quality of life, indicating no reduction in health-related quality of life. A lower index score indicated a lower quality of life.

In addition, we verified the vital status and causes of death of each registered participant through the national mortality surveillance system and vital registration of the Chinese Center for Disease Prevention and Control, with annual active confirmation of local residential, medical, health insurance and administrative records. We used the International Classification of Diseases (ICD)-10 to code mortality records. All-cause mortality and mortality from cardiovascular disease (ICD-10: I00-I99), cancer (ICD-10: C00-C97) and injury (ICD-10: L55-L55.9, L56.3, L56 .8-L56.9, L58 -L58.9, U00-U03, V00-V86.9, V87.2-V87.3, V88.2-V88.3, ​​V90-V98.8, W00-W46 .2, W49-W62.9, W64 -W70.9, W73-W75.9, W77-W81.9, W83-W94.9, W97.9, W99-X06.9, X08-X39.9, X46 -X48.9, X50-X54.9 , X57-X58.9, X60-X64.9, X66-Y08.9, Y35-Y84.9, Y87.0-Y87.1, Y88-Y88.3, ​​​​Y89.0-Y89.1) were analyzed.

statistical analyzes

Patient characteristics were summarized using proportion for categorical variables and mean ± standard deviation or median (interquartile range) as appropriate for continuous variables. Continuous variables were compared using Student’s t test or Mann-Whitney U test depending on the data distribution, and categorical variables using the chi-square test. Standardized mean differences (SMDs) were calculated to compare patient characteristics between current drinkers and non-drinkers, and between drinkers with and without AUD. When the absolute value of the SMD was

We fitted multivariate mixed models with study site as random effects and a logit link function to assess associations of demographic, socioeconomic, and health-related factors with AUD in the study population. The four dependent variables were whether male drinkers had AUD, hazardous drinking, symptoms of dependence, and harmful drinking. The individual characteristics included in the model were age, urbanization, level of education, annual household income, marital status, smoking, obesity and cardiovascular disease, hypertension and diabetes. diagnosed.

We assessed the association of AUD with quality of life and mortality in all male drinkers and in subgroups stratified by age group and geographic region. Multivariate mixed models with study sites as random effects and a logit link function were fitted to assess associations of AUD with quality of life (optimal vs. non-optimal QOL) adjusted for age, geographic regions, level of education, annual household income, marital status, medical insurance, smoking status, history of hypertension, history of diabetes, and BMI groups. Cox proportional hazard models were used to calculate hazard ratios (HR) and 95% CIs for AUD with all-cause mortality. Competing risk models were used to calculate HRs and 95% CIs for AUD with cause-specific mortality. All models were adjusted for age, education, annual household income, current smoking, and BMI. Since mortality data is available through December 31, 2019, we censored follow-up on that date or date of death, whichever came first.


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