Abstract
Objective
To describe changes in alcohol drinking behaviour, estimate the incidence rate of alcohol drinking and explore its risk factors in the Chinese community population.
Design
A community population prospective cohort study.
Setting
A total of 48 townships of 12 counties or districts in Guizhou province, China.
Participants
With the multistage proportional stratified cluster sampling method, a total of 7343 adult residents were enrolled into this study and eligible to be analysed.
Primary and secondary outcome measures
The incidence rate and its risk factor (adjusted HR (aHR) and 95% CIs) as well as the prevalence of alcohol drinking.
Results
There was a little increase trend in the overall prevalence of alcohol drinking among 7343 subjects over an average of 7.22-year follow-up, and the prevalence in women increased by 2.5% statistically (p=0.001). Among 5005 non-drinkers in 7343 subjects at baseline, 1107 incident drinkers were identified, and the incidence rate of alcohol drinking was estimated at 30.63/1000 person-years with significant sex difference (57.46 vs 17.99 per 1000 person-years for men and women, respectively, p<0.001). The incidence rate decreased gradually with age, peaking in men aged 18–29 years old and women aged 30–39 years old at baseline. After the adjustment for covariates, being male (aHR=3.46, 95% CI: 3.02 to 3.96), being non-Han Chinese (aHR=1.65, 95% CI: 1.44 to 1.88), living in urban areas (aHR=3.50, 95% CI: 3.01 to 4.08), being employed (aHR=1.33, 95% CI: 1.16 to 1.52), smoking (aHR=1.17, 95% CI: 1.00 to 1.38) and having no history of chronic diseases (aHR=1.19, 95% CI: 1.04 to 1.35) were independent risk factors for incident drinkers.
Conclusion
The number of women increased in the prevalence of alcohol drinking significantly although there was no significant overall change for the cohort population in Southwest China. Also, there was a high risk of developing alcohol drinking among the study population, especially for those non-drinkers who were younger men, non-Han Chinese, living in urban areas, employed, current smokers or without any chronic diseases. Interventions to prevent and manage alcohol consumption should be designed and implemented in Chinese communities as soon as possible.
Keywords: PUBLIC HEALTH, EPIDEMIOLOGY, Nutrition
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This is the first study in China on the risk of developing alcohol drinking among the Chinese community population and prospectively identified its risk factors.
This study has relatively high follow-up rate (86.6%) during follow-up.
There is a possibility of report bias in the collection of alcohol drinking information with the questionnaire in this study.
With only one follow-up, the average time of the onset of incident drinking may bias the incidence rate of alcohol drinking in this cohort.
Introduction
Cigarette smoking, alcohol drinking and physical activity (PA) are all linked to the occurrence of chronic diseases such as cancer and cardiovascular disease, and premature death.1 Alcohol use is a major contributor to the global burden of disease. According to the estimate by WHO, alcohol use is responsible for approximately 3.3 million deaths worldwide each year.2 In China, drinking alcohol was a widely accepted cultural tradition, especially during rituals, festivals, social gatherings, commercial occasions and special activities.3 In 2016, the alcohol drinking prevalence of Chinese men and women was 48% and 16%, respectively, and China had the highest number of deaths attributed to alcohol (650 000 for men and 59 000 for women) worldwide.4
Most researches on alcohol consumption were focused on the aetiology of adults, mainly in the physiological and clinical analysis, or the alcohol-related health harms.4 Most studies on changes in alcohol drinking behaviour used official statistics such as tax and sales data of alcohol consumption, or estimates based on self-reported alcohol consumption data from the population with a small sample size.5 6 The quantity and frequency of personal alcohol use and its risk were determined by a variety of influencing factors including social factors such as historical time, social culture and geopolitical context; individual-level factors such as family history and effects of prenatal alcohol exposure; psychological factors and sociodemographic features (eg, gender, age, race, ethnicity, culture, religious affiliation and socioeconomic status).7–14 Most of them were cross-sectional or multistage cross-sectional studies to describe the changes in alcohol drinking behaviour and the factors influencing these changes.7 15 16 However, as one of the most important health-related behaviours, there was no prospective study reported on the trend of alcohol drinking behaviour based on a same community cohort population so far.
Also, only few cohort studies focused on incident alcohol drinking (or initial alcohol drinking) among adolescents.17 18 One previous study in the USA found that among early adolescent new drinkers (drinking onset at age 11–14 years), incident drinking girls progressed to heavy drinking episode more quickly than boys at or after age 15 years.17 Another study in the USA showed that there were rising age-specific drinking incidence rates across adolescence to plateau at age 16–18 years, dipping at age 19–20 years, peaking at age 21 years and sharply reducing incidence thereafter.18 Over the past decades, health-related lifestyles including alcohol drinking have changed dramatically worldwide.5 6 So far, the incidence rate and risk factors of alcohol drinking among the adult community population are unclear. This study aimed to describe changes in alcohol drinking behaviour, estimate the incidence rate of alcohol drinking and explore its risk factors in the adult Chinese population.
Material and methods
Study design and population
The Guizhou Population Health Cohort Study is a prospective community-based cohort in Guizhou province, China.19 Based on the multistage proportional stratified cluster sampling method, a total of 9268 adult residents from 48 townships of 12 counties or districts in Guizhou province were recruited into this study from 2010 to 2012. The inclusion criteria were met as follows: (1) those who were 18 years or older; (2) those who lived in the study region and having no plans of moving; (3) those who completed a survey questionnaire with full alcohol drinking data at baseline and follow-up; (4) those who signed the written informed consent form.
Trained health professionals used a structured questionnaire through a face-to-face interview to collect the information on demographic variables (sex, age, ethnicity, education, marriage status and occupation), lifestyle (smoking status, alcohol usage and PA) and history of chronic diseases. All participants were followed up for lifestyle factors, major chronic diseases and vital status through a repeated investigation during 2016–2020, and 1117 (12.04%) were lost to follow-up. All deaths were confirmed through the Death Registration Information System and Basic Public Health Service System. We excluded 17 people who had missing alcohol drinking data at baseline and 791 people who had missing alcohol drinking data at follow-up, respectively. The remaining 7343 participants were analysed for the changes in alcohol drinking behaviour. Furthermore, we excluded 2338 people who drank at baseline, and finally, 5005 non-drinkers were eligible for the analysis of incident alcohol drinking (online supplemental figure 1).
bmjopen-2022-060914supp001.pdf (13.9KB, pdf)
Anthropometric and laboratory measurements
The anthropometric measurements, including height, body weight, waist circumference (WC) and blood pressure, were measured by trained local health professionals. Standing height was recorded to the nearest 0.1 cm by a portable stadiometer. Weight was numbered to the nearest 0.1 kg using a digital weighing scale. WC was measured to the nearest 0.1 cm at the midpoint between the lowest rib margin and the iliac crest. Body mass index (BMI) was calculated as body weight in kilograms divided by square height in metres (kg/m2) and divided into four categories following the Chinese BMI classification standard (low normal weight <22.0; high normal weight 22.0–23.9; overweight 24.0–27.9 and obese ≥28.0 kg/m2).20
Definitions
All definitions related to alcohol consumption are followed from the Dietary Guidelines for Chinese Residents (2016).21 Drinkers were defined as those who consumed alcohol in the last 12 months.2 Incident drinkers were those who drank alcohol first at any time during the follow-up. The consumption of concentrated liquor, low-concentrated liquor, beer, yellow rice wine, rice wine, wine and barley wine (alcohol degree was 52%, 38%, 4%, 18%, 18%, 10%, 3%) was recorded. Average daily alcohol intake (g) was calculated by average daily drinking weight multiplied by alcohol degree (recorded by weight) or calculated by average daily drinking volume multiplied by alcohol degree multiplied by ethanol density (0.789 g/mL) (recorded by volume). Excessive drinking was defined as pure alcohol intake >25 g/day for male and >15 g/day for female.21 The changes in alcohol drinking behaviour were assessed by the prevalence of alcohol drinking and excessive drinking among the study population, and average daily alcohol intake among alcohol drinkers. Chronic diseases were one of the diseases diagnosed with diabetes, hypertension or dyslipidaemia at baseline.19–21 Those subjects who smoked in the previous 12 months were considered as current smokers. Annual household income was the income shared by people living in the same household in the last year. PA included all kinds of PA in the past 12 months (farm work, work, housework, transportation-related PA, leisure exercise or sports, etc).
Patient and public involvement
Patients and members of the public were not directly involved in this study. The study population was limited to the anonymised records of individuals in this study.
Statistics analysis
The Χ2 test was used for categorical variables to compare the differences between incident drinkers and non-drinkers. The Student’s t-test was applied for continuous variables. The person-years (PYs) of follow-up were calculated from the date of enrolling the cohort to the date of follow-up or death, whichever came first. We define crude incidence rate of alcohol drinking as:
Cox proportional hazards regression model was used to determine the association between baseline factors and incident alcohol drinking. Covariates including age, sex, ethnicity, residence, education level, occupation, marriage status, smoking and history of chronic diseases were adjusted in Cox regression model. The Schoenfeld residuals were used to test the assumption of hazard proportionality in Cox regression models and no evidence of non-proportionality was found. All statistical tests were two sided and p<0.05 was considered statistically significant. All analyses were performed in R software (major packages: ‘ezcox’, ‘survival’, and ‘survminer’) (V.4.1.0; R Foundation for Statistical Computing, Vienna, Austria).
Results
Characteristics of subjects at baseline
The general characteristics of 7343 eligible subjects at baseline were shown in table 1. Nearly half of all subjects were male, with an average age of 44.4±15.0 years old, and 31.8% were alcohol drinkers at baseline. Alcohol drinkers were more likely to live in rural areas and to be non-Han Chinese than non-drinkers. Also, male, subjects aged 40–49 years old comprised the higher proportion of alcohol drinkers. In addition, participants who were farmers, having a lower education level and a lower annual household income, current smokers, having PA or without any history of chronic diseases comprised the higher proportion of alcohol drinkers (table 1).
Table 1.
General characteristics of this study population at baseline in Southwest China (%)
| Characteristics | Overall | Non-drinker | Drinker | P value |
| n=7343 | n=5005 | n=2338 | ||
| Male | 3422 (46.6) | 1590 (31.8) | 1832 (78.4) | <0.001 |
| Age, years (mean±SD) | 44.4±15.0 | 44.3±15.3 | 44.6±14.3 | 0.529 |
| 18–29 | 1416 (19.3) | 1005 (20.2) | 411 (17.6) | <0.001 |
| 30–39 | 1573 (21.4) | 1078 (21.5) | 495 (21.2) | |
| 40–49 | 1853 (25.3) | 1233 (24.6) | 620 (26.5) | |
| 50–59 | 1294 (17.6) | 827 (16.5) | 467 (20.0) | |
| ≥60 | 1207 (16.4) | 862 (17.2) | 345 (14.7) | |
| Urban | 2359 (32.1) | 1655 (33.1) | 704 (30.1) | 0.012 |
| Non-Han Chinese | 3080 (41.9) | 1988 (39.7) | 1092 (46.7) | <0.001 |
| Unmarried | 1417 (19.3) | 959 (19.2) | 458 (19.6) | 0.688 |
| Farmer | 4237 (57.7) | 2902 (58.0) | 1335 (57.1) | <0.492 |
| Education (≤9 years) | 6351 (86.5) | 4442 (88.8) | 1909 (81.7) | <0.001 |
| Annual household income (<¥200 000 CNY)* | 4147 (56.5) | 2659 (53.1) | 1488 (63.6) | <0.001 |
| Current smokers | 2057 (28.0) | 687 (13.7) | 1370 (58.6) | <0.001 |
| Physical activity | 6425 (87.5) | 4287 (85.7) | 2138 (91.4) | <0.001 |
| BMI, kg/m2 (mean±SD)* | 22.93±3.37 | 22.92±3.35 | 22.95±3.41 | 0.663 |
| <22.0 | 3214 (43.8) | 2201 (44.1) | 1013 (43.3) | 0.267 |
| 22.0–23.9 | 1729 (23.6) | 1170 (23.4) | 559 (23.9) | |
| 24.0–27.9 | 1857 (25.3) | 1244 (24.9) | 613 (26.3) | |
| ≥28.0 | 530 (7.3) | 378 (7.6) | 152 (6.5) | |
| History of chronic diseases† | 4944 (67.3) | 3256 (65.1) | 1688 (72.2) | <0.001 |
*Missing value.
†Chronic diseases include diabetes mellitus, hypertension and dyslipidaemia at baseline.
BMI, body mass index; CNY, Chinese Yuan.
Changes in alcohol drinking behaviour between baseline and follow-up
Among 7343 subjects, there was a little increasing trend in the overall prevalence of alcohol drinking during the follow-up, although it was not significant (table 2). However, such prevalence for female subjects increased by 2.5% significantly. Also, the prevalence of excessive drinking decreased by 3.2%, and there was greater reduction of 4.2% in male subjects statistically, but increased in female subjects (3.0%). In addition, daily alcohol intake showed similar change to those prevalences.
Table 2.
Changes of alcohol drinking behaviour between the baseline and follow-up
| Phase | Alcohol drinking | Excessive alcohol drinking | ADAI, g/day (mean±SD) | ||||||
| Male n (%) | Female n (%) | All n (%) | Male n (%) | Female n (%) | All n (%) | Male | Female | All | |
| Baseline | 1832 (53.5) | 506 (12.9) | 2338 (31.8) | 650 (36.2) | 71 (14.5) | 721 (31.6) | 28.2±39.8 | 7.6±15.7 | 23.8±37.1 |
| Follow-up | 1776 (51.9) | 604 (15.4) | 2380 (32.4) | 547 (32.0) | 98 (17.5) | 645 (28.4) | 28.0±68.5 | 9.1±21.7 | 23.2±60.9 |
| Change | −1.6 | 2.5 | 0.6 | −4.2 | 3.0 | −3.2 | −0.2 | 1.5 | −0.6 |
| χ2 or t value | 1.838 | 10.079 | 0.551 | 6.946 | 1.787 | 5.301 | 0.143 | −1.342 | 0.414 |
| P value | 0.175 | 0.001 | 0.458 | 0.008 | 0.181 | 0.021 | 0.886 | 0.186 | 0.679 |
ADAI, average daily alcohol intake.
Associations between potential risk factors at baseline and incident alcohol drinking
A total of 5005 non-drinkers at baseline was eligible for this analysis, and their general characteristics at baseline were presented in table 3. Of them, there was a mean age of 44.3±15.3 years old, and 31.8% were male. Compared with subjects who remained free of alcohol, incident drinkers were more likely to live in urban areas, be non-Han Chinese, be male, be unmarried, be employed, have lower education level, have higher annual household income, be current smokers, have less PA, be not obese or have no history of chronic diseases.
Table 3.
Population baseline characteristics among non-drinkers at baseline over incident alcohol drinking status (%)
| Characteristics | Overall | Non-drinker | Incident alcohol drinker | P value |
| n=5005 | n=3898 | n=1107 | ||
| Male | 1590 (31.8) | 925 (23.7) | 665 (60.1) | <0.001 |
| Age, years (mean±SD) | 44.3±15.3 | 45.1±15.3 | 41.9±14.8 | <0.001 |
| 18–29 | 1005 (20.2) | 732 (18.8) | 273 (24.7) | <0.001 |
| 30–39 | 1078 (21.5) | 811 (20.8) | 267 (24.1) | |
| 40–49 | 1233 (24.6) | 971 (24.9) | 262 (23.7) | |
| 50–59 | 827 (16.5) | 660 (16.9) | 167 (15.1) | |
| ≥60 | 862 (17.2) | 724 (18.6) | 138 (12.4) | |
| Urban | 1655 (33.1) | 1251 (32.1) | 404 (36.5) | 0.007 |
| Non-Han Chinese | 1988 (39.7) | 1519 (39.0) | 469 (42.4) | 0.045 |
| Unmarried | 959 (19.2) | 708 (18.2) | 251 (22.7) | <0.001 |
| Employed | 4118 (82.3) | 3170 (81.3) | 948 (85.6) | 0.001 |
| Education (≤9 years) | 4442 (88.8) | 3486 (89.4) | 956 (86.4) | 0.005 |
| Annual household income (<¥200 000 CNY)* | 2659 (53.1) | 2122 (54.4) | 537 (48.5) | <0.001 |
| Current smokers | 687 (13.7) | 433 (11.1) | 254 (22.9) | <0.001 |
| Physical activity | 4287 (85.7) | 3384 (86.8) | 903 (81.6) | <0.001 |
| Obesity* | 4627 (92.4) | 3580 (91.8) | 1047 (94.6) | 0.006 |
| History of chronic diseases† | 3256 (65.1) | 2570 (65.9) | 686 (62.0) | 0.016 |
*Missing value.
†Chronic diseases include diabetes mellitus, hypertension and dyslipidaemia at baseline.
CNY, Chinese Yuan.
During the mean (SD) follow-up of 7.22 (1.17) PYs that ranged from 5.05 years to 9.53 years, the crude incidence rate of incident alcohol drinking was 30.63 per 1000 PYs, and was significantly higher among men than that of women (57.46 vs 17.99 per 1000 PYs). The incidence decreased gradually with age, with a peak in 18–29 years old for men and 30–39 years old for women at baseline (figure 1). Univariate Cox regression showed that subjects who were male, living in urban areas, non-Han Chinese, had more than 9 education years, employed, current smokers or without any history of chronic diseases had higher risk of incident alcohol drinking. After the adjustment for covariates, it was discovered that subjects who were male, non-Han Chinese, living in urban areas, employed, current smokers and without any history of chronic diseases still had significantly higher risk of developing alcohol drinking (table 4).
Figure 1.
Data shown are incidence rates of alcohol drinking over age group and gender.
Table 4.
Cox regression on associations between risk factors and incident drinking
| Potential factors | Case of incident drinking | Person-year (PY) of observation | IR (1000 PYs) | HR (95% CI)* | aHR (95% CI)† |
| Total | 1107 | 36 137.23 | 30.63 | ||
| Gender | |||||
| Female | 442 | 24 564.26 | 17.99 | 1.00 | 1.00 |
| Male | 665 | 11 572.97 | 57.46 | 3.10 (2.75 to 3.50) | 3.46 (3.02 to 3.96) |
| Age, years | |||||
| 18–29 | 273 | 7396.68 | 36.91 | 1.00 | 1.00 |
| 30–39 | 267 | 7862.44 | 33.96 | 0.98 (0.83 to 1.16) | 1.01 (0.84 to 1.20) |
| 40–49 | 262 | 8860.09 | 29.57 | 0.92 (0.77 to 1.09) | 1.04 (0.86 to 1.25) |
| 50–59 | 167 | 5851.17 | 28.54 | 0.94 (0.78 to 1.14) | 1.00 (0.82 to 1.23) |
| ≥60 | 138 | 6166.85 | 22.38 | 0.71 (0.58 to 0.87) | 0.72 (0.58 to 0.90) |
| Urban | |||||
| No | 703 | 24 932.37 | 28.20 | 1.00 | 1.00 |
| Yes | 404 | 11 204.86 | 36.06 | 2.30 (2.10 to 2.70) | 3.50 (3.01 to 4.08) |
| Han Chinese | |||||
| Yes | 638 | 21 887.41 | 29.15 | 1.00 | 1.00 |
| No | 469 | 14 249.82 | 32.91 | 1.20 (1.10 to 1.40) | 1.65 (1.44 to 1.88) |
| Education | |||||
| >9 years | 151 | 4082.76 | 36.98 | 1.00 | 1.00 |
| ≤9 years | 956 | 32 054.47 | 29.82 | 0.82 (0.69 to 0.98) | 1.14 (0.94 to 1.37) |
| Employed | |||||
| No | 159 | 6457.90 | 24.62 | 1.00 | 1.00 |
| Yes | 948 | 29 679.33 | 31.94 | 1.30 (1.10 to 1.50) | 1.33 (1.16 to 1.52) |
| Married | |||||
| Yes | 856 | 29 149.81 | 29.37 | 1.00 | 1.00 |
| No | 251 | 6987.42 | 35.92 | 1.15 (1.01 to 1.33) | 1.06 (0.91 to 1.24) |
| Current smokers | |||||
| No | 853 | 31 167.35 | 27.37 | 1.00 | 1.00 |
| Yes | 254 | 4969.88 | 51.11 | 1.80 (1.60 to 2.10) | 1.17 (1.00 to 1.38) |
| History of chronic diseases‡ | |||||
| Yes | 686 | 23 647.71 | 29.01 | 1.00 | 1.00 |
| No | 421 | 12 489.52 | 33.71 | 1.31 (1.16 to 1.48) | 1.19 (1.04 to 1.35) |
*Univariate Cox regression.
†Multivariate Cox regression adjusted by all covariates excluding itself.
‡Chronic diseases include diabetes mellitus, hypertension and dyslipidaemia at baseline.
aHR, adjusted HR; IR, incidence rate.
Discussion
Over the past 10 years, the pattern of alcohol drinking behaviour was relatively stable in this study population. The overall prevalence of alcohol drinking increased a little during the follow-up without statistical significance, but increased significantly among women, which was consistent with previous studies.22 23 Also, the prevalence of excessive alcohol drinking statistically decreased overall, and there was greater reduction in men, which was confirmed by a longitudinal study in China.24 Although the prevalence of both alcohol drinking and excessive alcohol drinking was higher in men than in women, as reported in some previous studies,6 25–27 it was noted that both increased among women. This may be due to recent changes in economic and social status in terms of developing stronger independent consciousness, increasing levels of employment, and increasing social activities and communication opportunities in women.12 28 29 Those findings suggested that women should be a priority population for reducing alcohol consumption, particularly unhealthy alcohol drinking.
Another finding from this study was that the incidence of alcohol drinking was 30.63 per 1000 PYs among non-drinkers at baseline and decreased gradually with age, with a peak in 18–29 years old for men and 30–39 years old for women at baseline. Previous studies in China and Switzerland reported that people with high emerging adulthood were more likely to have moderate or excessive alcohol drinking behaviours.30 31 One of the possible reasons that women reached their peak later than men may be marriage and childbirth, which reduced the chance to drink for younger women. Another reason was that women may get career promotion later than men,32 which called for further researches to confirm that. Anyway, those findings implied that alcohol drinking intervention in earlier adulthood may be important.
Furthermore, even after adjustment for covariates, being male, being non-Han Chinese, living in urban areas, being employed, smoking and having no history of chronic diseases were still significantly associated with incident drinking. Results from China Kadoorie Biobank and some cross-sectional studies indicated that urban residents had a higher prevalence of current drinking.11 33 Urban residents with higher risk of developing alcohol drinking may be related to their higher income, prevalent consumption patterns and business demands. Non-Han Chinese had higher risk of becoming incident alcohol drinkers partly due to their different culture and tradition on alcohol drinking. In addition, employed subjects often had higher socioeconomic status, which was one of the important factors influencing alcohol use.34–36 Subjects with a history of chronic diseases at baseline were more likely to know possible unhealthy impacts of alcohol drinking and further reduce or avoid such behaviour.
To our limited knowledge, this study was the first on the risk of incident alcohol drinking among the Chinese community population in China. One of the strengths of this study was its high follow-up rate (86.6%) during 10 years of follow-up. Another strength of this prospective study was identifying risk factors for incident alcohol drinking among the Chinese community population. However, this study had some notable limitations. First, there may be report bias in the acquisition of alcohol drinking information with the questionnaire in this study. Second, residual confounding may not be controlled well although major potential confounding factors had been adjusted in this analysis. Third, because of only one follow-up that ranged from 5.05 to 9.53 years and no data on initiation time, the incidence rate of alcohol drinking may be underestimated in this cohort. The incidence rate slightly increased from 30.63/1000 PYs to 34.42/1000 PYs, if the midpoint between baseline and follow-up was used as the time of drinking initiation. However, the Cox regression results remained similar. In future, more follow-up should be done and more details in the initiation time should be collected.
In conclusion, alcohol drinking behaviour remained relatively stable overall in Chinese community population, but the prevalence of excessive alcohol drinking significantly increased among women. Also, there was a high incidence of alcohol drinking in this study population, and adults who were male, non-Han Chinese, living in urban areas, employed, smoking or without a history of chronic diseases should be targeted as the population at risk. Therefore, the interventions for the prevention and control of alcohol consumption should be urgently developed and implemented in the Chinese communities, especially in the youth.
Supplementary Material
Acknowledgments
We would like to thank all participants enrolled in this cohort study and all the health workers of the Guizhou Province Center for Disease Control and Prevention for contributing to this study.
Footnotes
BZ and JZ contributed equally.
Contributors: BZ—conceptualisation, methodology, software, formal analysis, data curation, writing (original draft), visualisation. JZ—investigation, writing (review and editing), supervision. YC—software, data curation. KX—supervision. YWu—investigation. YWang—investigation. NW—supervision. TL—investigation, resources, data curation, supervision, project administration, funding acquisition. CF—conceptualisation, methodology, validation, writing (review and editing), supervision, project administration. All authors have read and agreed to the published version of the manuscript. The scientific guarantors of this publication are TL and CF.
Funding: This work was supported by Guizhou Province Science and Technology Support Program (Qiankehe (2018)2819).
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request.
Ethics statements
Patient consent for publication
Not required.
Ethics approval
This study involves human participants and was approved by the Institutional Review Board of Guizhou Province Center for Disease Control and Prevention (No. S2017-02). At the time of enrolment, all subjects provided written informed consent.
References
- 1.Fau VS, Alvaro A, Fau AA. Heart disease and stroke Statistics-2020 update: a report from the American heart association. Circulation:1524–4539. 10.1161/CIR.0000000000000757 [DOI] [PubMed] [Google Scholar]
- 2.Organization World Health . Global status report on alcohol and health 2018 [M]. World Health Organization, 2019. [Google Scholar]
- 3.Wang S, Newman IM, Shell DF. Cultural orientation and its associations with alcohol use by university students in China. PLoS One 2016;11:e0165858. 10.1371/journal.pone.0165858 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Cochrane J, Chen H, Conigrave KM, et al. Alcohol use in China. Alcohol Alcohol 2003;38:537–42. 10.1093/alcalc/agg111 [DOI] [PubMed] [Google Scholar]
- 5.Griswold Max G, Nancy F, Caitlin H. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet 2018;392:4–1996. 10.1016/S0140-6736(18)31310-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Organization World Health . Global status report on alcohol 2018, 2018. [Google Scholar]
- 7.Hilton ME. Trends in U.S. drinking patterns: further evidence from the past 20 years. Br J Addict 1988;83:269–78. 10.1111/j.1360-0443.1988.tb00468.x [DOI] [PubMed] [Google Scholar]
- 8.Shaw BA, Krause N, Liang J, et al. Age differences in long-term patterns of change in alcohol consumption among aging adults. J Aging Health 2011;23:207–27. 10.1177/0898264310381276 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kim S, Choi S, Kim J, et al. Trends in health behaviors over 20 years: findings from the 1998-2018 Korea National health and nutrition examination survey. Epidemiol Health 2021;43:e2021026. 10.4178/epih.e2021026 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Son H-G, Jeong K-H, Cho HJ, et al. Changes in types of drinking behavior in Korean adults: differences in demographics, depression, and suicidal thoughts. Int J Environ Res Public Health 2021;18:7514. 10.3390/ijerph18147514 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Lyu J, Guo Y, Bian Z. Regional differences in patterns of alcohol consumption: findings from the China Kadoorie Biobank study on half a million people from 10 regions. Chinese Journal of Epidemiology:0254–6450. [PubMed] [Google Scholar]
- 12.Bratberg GH, C Wilsnack S, Wilsnack R, et al. Gender differences and gender convergence in alcohol use over the past three decades (1984-2008), the HUNT study, Norway. BMC Public Health 2016;16:723. 10.1186/s12889-016-3384-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Davies EL, Puljevic C, Connolly D. The world’s favorite drug: What we have learned about alcohol from over 500,000 respondents to the Global Drug Survey. In: The Handbook of alcohol use, 2021: 17–47. [Google Scholar]
- 14.Charles J. Library Journal. In: Drink: a cultural history of alcohol, 2008. [Google Scholar]
- 15.Windle M, Windle RC. A prospective study of alcohol use among middle-aged adults and marital partner influences on drinking. J Stud Alcohol Drugs 2014;75:546–56. 10.15288/jsad.2014.75.546 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Wilsnack SC, Wilsnack RW. Epidemiology of women's drinking. J Subst Abuse 1991;3:133–57. 10.1016/S0899-3289(05)80033-1 [DOI] [PubMed] [Google Scholar]
- 17.Cheng HG, Anthony JC. Male-Female differences in the onset of heavy drinking episode soon after first full drink in contemporary United States: from early adolescence to young adulthood. Drug Alcohol Depend 2018;190:159–65. 10.1016/j.drugalcdep.2017.12.035 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Cheng HG, Cantave MD, Anthony JC. Alcohol experiences viewed Mutoscopically: newly incident drinking of Twelve- to Twenty-Five-Year-Olds in the United States, 2002-2013. J Stud Alcohol Drugs 2016;77:405–12. 10.15288/jsad.2016.77.405 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Yu Y, Chen Y, Wang Y, et al. Is the efficiency score an indicator for incident hypertension in the community population of Western China? Int J Environ Res Public Health 2021;18. 10.3390/ijerph181910132. [Epub ahead of print: 27 09 2021]. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Wang Z-wu, Wu Y-feng, Zhao L-cheng, et al. [Trends in prevalence, awareness, treatment and control of hypertension in middle-aged Chinese population]. Zhonghua Liu Xing Bing Xue Za Zhi 2004;25:407–11. [PubMed] [Google Scholar]
- 21.Wang S-S, Lay S, Yu H-N, et al. Dietary guidelines for Chinese residents (2016): comments and comparisons. J Zhejiang Univ Sci B 2016;17:649–56. 10.1631/jzus.B1600341 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.White A, Castle I-JP, Chen CM, Aaron W, Chen Chiung M, et al. Converging patterns of alcohol use and related outcomes among females and males in the United States, 2002 to 2012. Alcohol Clin Exp Res 2015;39:1712–26. 10.1111/acer.12815 [DOI] [PubMed] [Google Scholar]
- 23.Slade T, Chapman C, Swift W, et al. Birth cohort trends in the global epidemiology of alcohol use and alcohol-related harms in men and women: systematic review and metaregression. BMJ Open 2016;6:e011827. 10.1136/bmjopen-2016-011827 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lee K, Salomon J, Goldhaber-Fiebert J. Patterns of heavy drinking behaviour over age and birth cohorts among Chinese men: a Markov model. BMJ Open 2021;11:e043261. 10.1136/bmjopen-2020-043261 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wilsnack RW, Wilsnack SC, Kristjanson AF, et al. Gender and alcohol consumption: patterns from the multinational GENACIS project. Addiction 2009;104:1487–500. 10.1111/j.1360-0443.2009.02696.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Wilsnack RW, Vogeltanz ND, Wilsnack SC, et al. Gender differences in alcohol consumption and adverse drinking consequences: cross-cultural patterns. 2000;95:251–65. 10.1046/j.1360-0443.2000.95225112.x [DOI] [PubMed] [Google Scholar]
- 27.Li Y, Jiang Y, Zhang M, et al. Drinking behaviour among men and women in China: the 2007 China chronic disease and risk factor surveillance. Addiction 2011;106:1946–56. 10.1111/j.1360-0443.2011.03514.x [DOI] [PubMed] [Google Scholar]
- 28.Erol A, Karpyak VM. Sex and gender-related differences in alcohol use and its consequences: contemporary knowledge and future research considerations. Drug Alcohol Depend 2015;156:1–13. 10.1016/j.drugalcdep.2015.08.023 [DOI] [PubMed] [Google Scholar]
- 29.Keyes KM, Grant BF, Hasin DS. Evidence for a closing gender gap in alcohol use, abuse, and dependence in the United States population. Drug Alcohol Depend 2008;93:21–9. 10.1016/j.drugalcdep.2007.08.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Lu W, Xu J, Taylor AW, et al. Analysis of the alcohol drinking behavior and influencing factors among emerging adults and young adults: a cross-sectional study in Wuhan, China. BMC Public Health 2019;19:458. 10.1186/s12889-019-6831-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Rehm J, Arminger G, Jurgen R. Alcohol consumption in Switzerland 1987-93: adjusting for differential effect of assessment techniques on the analysis of trends. Addiction 1996;91:1335–44. 10.1111/j.1360-0443.1996.tb03619.x [DOI] [PubMed] [Google Scholar]
- 32.Lewis GB, Lewis Gregory B. Gender and promotions: promotion chances of white men and women in federal White-Collar employment. J Hum Resour 1986;21:406–19. 10.2307/145971 [DOI] [Google Scholar]
- 33.Im PK, Millwood IY, Guo Y, et al. Patterns and trends of alcohol consumption in rural and urban areas of China: findings from the China Kadoorie Biobank. BMC Public Health 2019;19:217. 10.1186/s12889-019-6502-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Collins SE. Associations between socioeconomic factors and alcohol outcomes. Alcohol Res 2016;38:83–94. [PMC free article] [PubMed] [Google Scholar]
- 35.Wiles NJ, Lingford-Hughes A, Daniel J, et al. Socio-Economic status in childhood and later alcohol use: a systematic review. Addiction 2007;102:1546–63. 10.1111/j.1360-0443.2007.01930.x [DOI] [PubMed] [Google Scholar]
- 36.Patrick ME, Wightman P, Schoeni RF, et al. Socioeconomic status and substance use among young adults: a comparison across constructs and drugs. J Stud Alcohol Drugs 2012;73:772–82. 10.15288/jsad.2012.73.772 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2022-060914supp001.pdf (13.9KB, pdf)
Data Availability Statement
Data are available upon reasonable request.