The relationship between depression and alcohol use among the Wa ethnic minority in China

doi:10.21203/rs.3.rs-4891111/v1

Background

Alcohol use and depression often co-occur; however, little is known about this association with specific ethnic groups. This study aimed to explore the relationship between alcohol use and depression in the Wa ethnic group in China.

Methods

A stage sampling method was utilized to survey respondents from the Wa ethnic group, who have transitioned rapidly from traditional slash-and-burn cultivation to modern societies. The Alcohol Use Disorder Identification Test (AUDIT) and the Patient Health Questionnaire-9 (PHQ-9) to assess their alcohol use and depressive symptoms, respectively. Data were analyzed using generalized additive models and a two-segment logistic regression.

Results

Among the 668 participants, 48.98% (337/668) were current drinkers. Low-risk, high-risk, and probable alcohol-dependence drinkers accounted for 21.4%, 25.4%, and 2.7% of the sample, respectively. Generalized additive models revealed a non-linear association between AUDIT scores and depressive symptoms, with a statistically significant non-linearity (P < 0.001). A-segment logistic regression identified a critical point at an AUDIT of 15. this threshold, each increase in AUDIT score led to a notable 43% increase in the likelihood of experiencing depressive symptoms (OR = 143, 95 CI: 119,1.72, < 0.). while, on the lower end of the threshold, there was no significant association between the AUDIT score and depressive symptoms observed (OR 0.98 95% CI 0.90, 1.05, P = 0.53).

Conclusion

A non-linear relationship between alcohol use and depression was identified in the Wa ethnic group, suggesting a threshold effect. Screening for alcohol use could help identify individuals at risk of depression in ethnic populations.

depression

alcohol use

alcohol use disorders

ethnic minority

Alcohol use is known to co-occur with poor mental health, [1]. loads of studies have consistently found that alcohol abuse and dependence are often co-morbidities with affective disorders[1, 2]. Further, individuals with mental health problems, such as depression, are more likely to misuse alcohol[3]. Prospective cohort studies have reported that participants exhibiting depressive symptoms, anxiety[4], or psychosis[5] at baseline had an increased risk of reporting alcohol problems, alcohol dependence, or alcohol use disorders at follow-up, indicating that alcohol use increases with worsening mental health status. Moreover, some literature suggests a causal connection between alcohol use disorders and major depression, indicating that greater alcohol consumption heightens the likelihood of depression [6].

The association between level of alcohol use and depression is complex. Some research has indicated a “J” shaped [7], or “U” shaped relationship [8], with moderate alcohol consumption related to a lower risk of depression; and harmful effects related to no or heavy consumption [6]. However, whether moderate alcohol consumption has a protective effect on depressive symptoms remains a subject of debate. The samples in these studies may include confounding factors, such as non-drinkers who have abstained due to existing health conditions. Additionally, the measurement of depression varies across studies, with some using a clinical diagnosis of major depression [9] and others using recent depressive symptoms [8]. Notably, their relationship has rarely been examined in.

Current evidence suggests that drinkers among are at increased risk of alcohol-related harms (including social and health harms), especially co-occurring alcohol use and mental health problems [10, 11]. For example, Baker et al. reported that the prevalence of co-occurring depression and alcohol use is highest among black populations in the UK (23%) and lowest among other white populations (14%) [12]. Importantly, rarely accepted formal treatment for mental disorders and instead use alcohol as a means of coping with or numbing their mental health symptoms [13], thus exacerbating the challenges associated with co-occurring alcohol and mental health issues. However, few studies have explored the association between alcohol and mental health, with small sample sizes in some ethnic groups [10, 11]. It is a priority to conduct research with large samples of participants from minority ethnic groups to support sufficient analyses [12], to clarify the link between alcohol use and mental health to explore effective treatment for ethnic groups[1].

Some research suggests that cultural and ethnic differences in beliefs and behaviors towards alcohol among ethnic or racial minorities may contribute to differences in the incidence of depression [14, 15]. In China, there are fifty-five ethnic groups with disparities in the culture and behaviors. The alcohol culture of ethnic minorities is very popular, and alcohol consumption is deeply rooted in the traditions and festivals of many ethnic minorities, with a more tolerant attitude towards drinking [16]. Furthermore, there are no specific laws regulating the minimum legal drinking age, and the younger age of drinkers is also a prominent feature in ethnic groups, potentially contributing to hazardous drinking [17]. Few studies published in Chinese journals have reported co-occurring depressive symptoms and alcohol use were common among certain ethnic groups, including Uygur, Miao,Tujia,Bai,ect. [18, 19]. Nonetheless, it should be noted that existing studies have limitations such as small samples and lack of reporting of comorbidity rates, necessitating further validation of their findings. Significantly, out of the fifty-five in China, nine are referred to as "advancing directly " groups, including the Dulong, Wa, Lisu, Jipo, etc. They maintained their traditional slash-and-burn farming lifestyles and were relatively isolated until the 1950s. Since 1994, the Chinese government has implemented poverty alleviation programs aimed at helping poor ethnic groups break out of the poverty cycle and improve their underdeveloped economic conditions. No studies on alcohol use and depression in “advancing directly advancing” are currently available. To help fill this evidentiary gap, we surveyed one of the “advancing directly advancing” ethnic groups, the Wa. The aim of the current study mainly focuses on the following: (1) examine the prevalence of current drinking incidence in the Wa (2) evaluate the risk factors associated with depression within this population, and (3) explore the relationship between depression and alcohol use.

2.1. Ethics approval and consent to participate

The study received approval from the Institutional Review Board (IRB) of the Institute of Psychology, Chinese Academy of Sciences (No.H18031), and was conducted by the Declaration of Helsinki. Before data collection, written informed consent was obtained.

2.2 Procedure and Participants

The cross-sectional study was conducted in Cangyuan County in Yunnan Province of China, bordering Myanmar, and adopted a multi-stage cluster sampling method in collecting the data between December 2022 and February 2023. The Wa had kept a primitive society and their language until 1964 and is one of the “advancing directly advancing” ethnic groups. In this study, the collection of samples followed the principles of the China Health Literacy Survey (CHLS) in four stages. Firstly, eight administrative villages were randomly selected from a total of ninety villages in Cangyuan County. Secondly, two natural villages were chosen from each administrative village, a total of 16 natural villages. Thirdly, a systematic sampling method was employed to select between 25 to 50 households from each natural village. Finally, one participant from each household was chosen utilizing the Kish Grid sampling.

The calculation of the sample size was performed using the formula: N=Z²P(1-P)/E². Here, Z represents the significance level value (α = 0.05), P denotes the percentage of probable alcohol dependence, and E indicates, the maximum allowable error. According to the literature on alcohol consumption in Yunnan Province, the incidence of alcohol dependence in the Dulong ethnic minority was 19.08%[20], and the proportion of high-risk drinking in the general population was 13.4%[21]; on this basis, P was set at 19%, and a 95% confidence threshold was established, with a maximum relative error rate of 30%, and set at 3%. Using the formula, the minimum sample size was 656.

Participants aged between 15 to 69 years had resided in Cangyuan County for at least 12 months. A total of 700 individuals were interviewed, with 688 individuals responding. 20 individuals were excluded due to unfinished interviews and conflicting information. The questionnaire's validity rate was 95%. Therefore, the subject number is large enough to meet the sample size requirements.

2.3 Measures

During the visit, standardized questionnaire was used to collect sociodemographic characteristics and general data from respondents, including gender, age, marital status, education, ethnicity, annual household income, current smoking, and the frequency of alcohol consumption. The frequency of alcohol use was grouped into five categories: never drinking, drinking less than once a month, drinking 2-4 times a month, drinking 2-3 times a week, and drinking more than 4 times a week. Smoking was categorized as current smoking or current non-smoking, encompassing both past smoking and never smoking. Standard anthropometric measurements of height in meters (m) and weight in kilograms (kg) were taken for all participants to calculate their Body Mass Index（BMI）.

The Alcohol Use Disorder Identification Test (AUDIT) is a 10-item scale to screen for high-risk alcohol use problems and has been validated for DSM-IV alcohol use disorders[22]. The AUDIT score range is from 0 to 40, and a higher score signifies a greater degree of alcohol dependence. The classification was used to categorize individuals into different levels of risky drinking: non-drinkers (score = 0 or answering “no” to drinking alcohol) and low-risk alcohol use (scores = 1–7), high-risk alcohol use (scores= 8 to 19), or probable alcohol dependence (score ≥ 20) [23].

The Patient Health Questionnaire (PHQ-9) scale was used to assess depressive symptoms and its score scores are defined as the presence (scores of 5 or higher) or absence (scores below 5) of depressive symptoms[24]. The PHQ-9 suicide item was employed as an effective tool for evaluating suicidal ideation. This item examines passive thoughts of death and the desire for self-harm within the past two weeks among respondents.

The Generalized Anxiety Disorder 7-item scale (GAD-7) scale was utilized to evaluate anxious symptoms, comprising a comprehensive set of seven anxiety-related questions. The GAD-7 scale ascertained a total score, ranging from 0 to 21, as an indicator of the overall severity of anxiety symptoms[25]. In this study, a GAD-7 score of 5 or higher indicated at least mild comorbid anxiety symptoms.

To accommodate some respondents with limited education or were illiterate, trained interviewers conducted face-to-face interviews after intensive training. Repeated assessments were conducted utilizing standardized scales to ensure consistency and reliability in data collection. The inter-observer reliability of these evaluations was consistently maintained, with a correlation coefficient exceeding 0.8.

2.4. Statistical analysis

Continuous variables were presented as the mean values accompanied by their respective standard deviations (SD), while categorical variables were reported in terms of frequencies and percentages. To assess differences among various AUDIT groups, we employed one-way ANOVA tests or chi-squared tests for categorical variables. To investigate the linear relationship between AUDIT scores and depressive symptoms, logistic regression models were utilized. The AUDIT score was analyzed in both its continuous and categorical forms, categorized according to different levels of risky drinking in distinct models. The results of the regression models were displayed in terms of unadjusted and adjusted odds ratios (ORs) along with 95% confidence intervals (CIs). To assess the potential concern of multicollinearity, the variance inflation factor (VIF) was computed for the independent variables. Variables exhibiting a VIF value exceeding 5 were deemed to indicate the presence of multicollinearity and were excluded from the final model. Confounding variables were included in the final multivariable model if they fulfilled the criteria of either having a p-value below 0.10 in univariable analysis or causing a change in the estimates of the AUDIT score on depressive symptoms by more than 10%[26]. Three different logistic regression models were developed to investigate the relationships between AUDIT scores and depressive symptoms: an unadjusted model, Model I adjusted for gender and age, and Model II adjusted for gender, age, current smoking status, frequency of alcohol consumption, annual household income, suicidal ideation, and anxiety symptoms. In case a non-linear relationship between AUDIT scores and depressive symptoms was detected, a two-segment linear regression model utilizing the Generalized Estimating Equation (GEE) was established to estimate the threshold effect, with a smoothing plot serving as a reference.

The statistical analyses were conducted utilizing two software packages: R (version 4.3.0, The R Foundation) and Empower Stats (version 4.1, X&Y Solution, Inc., Boston, Massachusetts, USA).Statistical significance was defined as P < 0.05 for a two-tailed test.

This study enrolled a total of 668 individuals from the Wa. The mean age of the participants was (42.19 ± 12.76) years; 52.84% (353/668) were male and 47.16% (315/668) were female. Among the participants, 208 (31.14%) had depressive symptoms, of which 25% (167/668) had mild depressive symptoms, 4.5% (30/668) had moderate depressive symptoms, and 1.6% (11/668) had moderate or severe depressive symptoms. 51.02% (351/668) were non-drinkers, and 48.98% (337/668) were current drinkers. According to the AUDIT score, low-risk, high-risk, and probable alcohol-dependence drinkers accounted for 21.4% (143/668), 25.4% (170/668), and 2.7% (18/668), respectively. Among participants with probable alcohol dependence, 61.1% (11/18) had depressive symptoms. Further, Table 1 compares the participants' characteristics between the three groups (non-drinker, low-risk, high-risk, and probable alcohol-dependence drinkers). Significant correlations between AUDIT scores and gender, marital status, current smoking, the frequency of drinking alcohol, suicidal ideation, and depressive symptoms (all P < 0.05), were found.

Findings through the univariate analysis are presented in Table 2, showing the associations between various factors and depressive symptoms. Specifically, suicidal ideation (odds ratio [OR] = 9.87, 95% confidence interval [CI]: 3.97, 24.54) and with anxiety symptoms (OR = 12.69, 95% CI: 8.12, 19.84) were positive correlations with depressive symptoms (all P < 0.05). Conversely, a decreased likelihood of depressive symptoms was observed for individuals who consumed alcohol at a frequency of >= 4 times every week (OR = 0.48, 95% CI: 0.25, 0.92 vs. non-drinker; P < 0.05).

The fully adjusted data in Table 3 revealed a significant association between a higher AUDIT score and an increased risk of depressive symptoms (OR = 1.07, 95% CI: 1.01, 1.13; P = 0.031). Notably, participants falling into the AUDIT score category (20-40) exhibited a significantly greater likelihood of developing depressive symptoms after accounting for various variables (OR = 7.62, 95% CI: 1.79, 32.49, P = 0.006) compared to those in the lower category (0-7). Figure 1 shows the non-linear association between the AUDIT score and depressive symptoms, with a statistically significant non-linearity (P for non-linearity < 0.001) by utilizing generalized additive model. Employing a two-segment logistic regression analysis, an inflection point at an AUDIT score value of 15 was identified. Beyond this inflection point, for each unit increase in AUDIT score, the likelihood of experiencing depressive symptoms increased substantially by 43% (OR = 1.43, 95% CI: 1.19, 1.72, P < 0.001). However, no significant relationship between the AUDIT score and depressive symptoms was observed on the left side of the inflection point (OR = 0.98, 95% CI: 0.90, 1.05, P = 0.53), as indicated in Table 4. The calculation of 95% confidence intervals (CIs) around the AUDIT score's inflection point, which ranged from 11 to 17, was performed using bootstrap techniques. The study included 52 participants with an AUDIT score greater than or equal to 15, while 616 participants had an AUDIT score below 15.

To our knowledge, this study is the first investigation of the relationship between depression and alcohol consumption among the Wa. The primary findings can be summarized as follows: (1) a high prevalence of current drinking was observed, (2) higher depressive symptoms associated with lower frequency of drinking and higher suicide ideation and anxious symptoms, and (3) a non-linear relationship was identified between depression and AUDIT scores, with an inflection point observed at 15.

Significant differences existed in alcohol consumption, alcohol-related problems, and access to alcohol treatment among various ethnic groups [11] [27]. For instance, in England, the General Household Survey from 2001 to 2005 indicates that out of the 66% of adults in Great Britain who reported drinking in the past week, 8% belonged to an ethnic minority background [28] [29-31]. In the USA, based on NESARC and NSDUH epidemiology data, there were three groups with the highest frequency of drinking and the highest amount, namely Whites (3.0%-4.6%), Blacks (1.4%- 3.2%), and Hispanics (2.5%- 3.9%)[32]. In China, based on the limited literature, there is no difference in the rate of current drinking between the major groups (Han) and ethnic groups, except for that prohibit alcohol, such as Islam. However, the prevalence of current drinking in “advancing directly advancing” ethnic groups is still unclear. In the present study, we conducted the Wa with 48.98% in prevalence of current drinking was 48.98%, which was similar to another “advancing directly advancing” ethnic minority, the Dulong, with 43.64%[20]. Compared to “non-advancing directly advancing”, our participants tended to report a higher rate of drinking. For example, the prevalence rates of drinkers of 15-35 years old in the Han majority group, Yi ethnic groups, and Lisu in China were 33.4%, 32.1%, and 34.5%, respectively [21]. Notably, alcohol use among “advancing directly advancing” ethnic groups of China may be challenging. On the one hand, “advancing directly advancing” ethnic groups, usually living in rural areas, maintain traditional culture and customs very well. Drinking is an essential part of festive occasions, religious celebrations, and social gatherings in their daily lives[17]. Also, they have their alcohol production and consumption rituals, which are more likely to increase alcohol and alcohol-related harm, such as illegal or unrecorded manufacture and sale[17], and high-risk drinking behavior [33]. On the other hand, over the past 20 years, the Chinese Government to implemented policies to promote the economic development of “advancing directly advancing”, their economies have been overgrown, and personal consumption, such as tobacco, alcohol, and daily necessities, has been constantly increasing. Regrettably, limited information concerning alcohol use on health-related problems among "advancing directly advancing" has been reported. To address this gap, future studies should endeavor to provide a comprehensive understanding of this area.

Currently, studies have reported the association between alcohol use and depression, with the most famous being the “u” or “J” shaped relationship [34]. Heavy drinkers are more likely to be at an increased risk of depression, while light to moderate drinking may reduce the risk of depression compared with no drinking. However, our results approximated “J” shaped non-linear relationships. The dose-response relationship between alcohol use and depressive symptoms reveals an inflection point, with a score of 15 on the AUDIT. These outcomes imply that alcohol use elevates the risk of depression when it reaches high-risk drinking or possible alcohol dependence. There are explanations for our findings. First, our sample was the Wa, and the incidence of severe depressive symptoms was relatively low, with 1.6% (11/668). Some studies found a J-shaped relationship only among ex-drinkers who met the criteria for major depression [34]. Second, it is difficult to distinguish light, moderate, and heavy drinking based on the existing criteria among our drinkers. Some studies define light to moderate drinkers as 14 drinks/week, and heavy drinkers as ≥14 drinks/week[35]; the other was classified as light (0-84 g/week), moderate (85-168 g/week), and heavy drinking (>168 g/week or >48 g/day at least weekly)[34]. Mostf our drinkers drank alcohol made by themselves and rarely drank beer and wine, which makes it difficult to assess the grams of alcohol.

More importantly, among, more consideration is given to the impact of sociocultural factors on drinking behavior. Social drinking motives, bonding with others, or improving social gatherings[36], or social rewards[37], also contribute to alcohol consumption. Drinking’s social motivation is common among in China [21, 17]. Alcohol use among ethnic populations in China has extended beyond religious activities and celebrations [16], which is more of an important means to enhance interpersonal relationships [38]. Meantime, increased acculturation within ethnic groups exposes individuals to friends from different cultures who may influence their drinking behaviors, potentially leading to a positive relationship with risky drinking patterns [39, 40]. Social motivation appears to have a weaker association with heavy or problematic drinking [41, 42]. It is therefore reasonable to speculate that a subset of our sample were social drinkers whose AUDIT scores were not significantly associated with depression, while another participants with severe or underlying alcohol dependence had a positive association between their alcohol use and depression.

Furthermore, the Chinese alcohol culture likely plays a pivotal role in shaping drinking patterns and coping strategies. The old Chinese proverb says “Drown your sorrow with drinking”, which highlights drinking alcohol as a remedy for emotional problems. Actually, the “self-medication” hypothesis has been widely suggested as an explanatory mechanism for the comorbidity of mood and anxiety disorders with substance use disorders[43, 1]. This hypothesis posits that individual’s resort to alcohol or drugs as a means of coping with distressing symptoms [44]. Approximately 8%-40% of the general population with affective symptoms self-reported the use of alcohol or drugs to help cope with them [45, 7]. To some extent, our findings corroborate the self-medication hypothesis. The proportion of severe depressive symptoms in our respondents with probable alcohol dependence was high at 61.6%. Participants classified as high-risk and potentially alcohol-dependent exhibit approximately eight times higher risk of experiencing depression and suicidal ideation compared to others. Our study is the initial exploration of the association between alcohol use and depression among ethnic minorities and contributes preliminary evidence. Further studies utilizing diverse methodologies that support causal relationships are needed.

Ethnic groups showed increasing elevated rates of common psychiatric disorders, including depression, anxiety, and suicide [46, 1].However, Ethnic groups are less likely to initiate and receive adequate mental health care compared to other populations [47], often resorting to unhealthy coping strategies like alcohol consumption and binge drinking [13].Meantime, the link between alcohol use and mental health among Ethnic groups may be exacerbated due to the stigmatization of mental health[48], potentially leading to delayed help-seeking [46].Taken together, this link among Ethnic groups should be emphasized, because they are vulnerable to being exposed to social stressors, such as racial discrimination, and have fewer resources to cope with stress [49]. Given that preventing depression is a priority in public health hinges on accurately identifying and addressing modifiable risk factors for the condition[13], exploring the relationship between alcohol use and depression as a modifiable factor warrants further investigation. Particularly, updated genetic studies have begun to unravel a shared genetic susceptibility between depression and alcoholism. For instance, Muench et al. found that the MDD risk allele rs10514299 can predict the reward mechanism of alcohol dependence[50]. Although the current understanding is limited, alcohol use should be one candidate worthy of further study for the prevention depression [51, 52]. Therefore, examining the drinking, drunkenness, and other drinking patterns of Ethnic groups will be beneficial for the initial screening of depression in this group and guiding targeted interventions. This approach holds significant potential as a feasible public health intervention within the community medical service system.

Our findings suggest two main clinical implications. First, healthcare professionals in community primary healthcare settings consider utilizing AUDIT scores as a preliminary screening tool for identifying depression among ethnic minority populations. Second, addressing AUD holds promise as a more effective approach for both preventing and treating depression among Ethnic groups. These communities may more readily embrace this approach, as it helps reduce the stigma associated with mental diseases. Nonetheless, there are also limitations. First, the scales used in our study should be validated in the Wa, as there may be cultural diversity in the way depression and alcohol use are experienced and reported among Ethnic groups. Second, we collected data through face-to-face interviews. Interviews with elderly individuals relied on translation as they only spoke their language, which could lead to recall bias and errors.

In conclusion, this study represents the first investigation into the relationship between alcohol use and depression among the Wa. Our findings indicate a noteworthy correlation between current drinking behaviors and both depression and suicidal ideation. Specifically, our results highlight that it is not the frequency of drinking that increases the risk of depression, but hazardous drinking behavior. Particularly, when AUDIT scores are higher than 15, the risk of depression increases dramatically. These findings suggest that utilizing AUDIT scores to identify those at risk of depression in risky drinkers could be a promising approach in ethnic groups.

Author Contribution

Wanqiu Yang, Allan Young, Jess Kerr-Gaffney, Sameer Jauhar, and Xiangyang Zhang were responsible for manuscript preparation and review. Wanqiu Yang and Junjun Liu were responsible for statistical analysis. Dan Leng, Chaoxiao Li, Kunjie Liu, Yongjie Pu, Borui Yang, and Yanqing Wang, were responsible for recruiting the participants, performing the screening, and collecting the data. All authors reviewed the manuscript.

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Table 1. Comparison of participant characteristics among non-drinkers, low-risk, high-risk, and probable alcohol-dependent drinkers

Variables	Total	non-and low-risk drinkers (AUDIT: 0-7)	high-risk drinkers (AUDIT: 8-19)	probable alcohol dependence (AUDIT: 20-40)	P-value
N	668	480	170	18
Age (years)	42.19 ± 12.76	42.49 ± 12.36	41.09 ± 13.74	44.60 ± 13.68	0.337
Annual household income (yuan)	47144.74 ± 40123.16	46024.27 ± 37491.60	51824.03 ± 47764.79	32830.44 ± 20157.91	0.083
BMI (kg/m²)	24.13 ± 3.76	24.12 ± 3.82	24.00 ± 3.64	25.46 ± 2.89	0.296
Gender					<0.001
Male	353 (52.84%)	232 (48.33%)	112 (65.88%)	9 (50.00%)
Female	315 (47.16%)	248 (51.67%)	58 (34.12%)	9 (50.00%)
Education					0.288
Junior high school and below	586 (87.72%)	425 (88.54%)	144 (84.71%)	17 (94.44%)
Senior high school and above	82 (12.28%)	55 (11.46%)	26 (15.29%)	1 (5.56%)
Ethnic group					0.381
Han	11 (1.65%)	8 (1.67%)	2 (1.18%)	1 (5.56%)
Wa	657 (98.35%)	472 (98.33%)	168 (98.82%)	17 (94.44%)
Marital status					0.002
Single	140 (20.96%)	84 (17.50%)	52 (30.59%)	4 (22.22%)
Married	528 (79.04%)	396 (82.50%)	118 (69.41%)	14 (77.78%)
Currently smoking					0.016
No	369 (55.24%)	250 (52.08%)	110 (64.71%)	9 (50.00%)
Yes	299 (44.76%)	230 (47.92%)	60 (35.29%)	9 (50.00%)
The frequency of drinking alcohol					<0.001
Never	351 (52.54%)	347 (72.29%)	4 (2.35%)	0
<= 1 time/month	111 (16.62%)	79 (16.46%)	32 (18.82%)	0
2-4 times/month	72 (10.78%)	29 (6.04%)	39 (22.94%)	4 (22.22%)
2-3 times/week	65 (9.73%)	17 (3.54%)	46 (27.06%)	2 (11.11%)
>= 4 times/week	69 (10.33%)	8 (1.67%)	49 (28.82%)	12 (66.67%)
Suicidal ideation					0.009
No	638 (95.51%)	453 (94.38%)	169 (99.41%)	16 (88.89%)
Yes	30 (4.49%)	27 (5.62%)	1 (0.59%)	2 (11.11%)
PHQ-9 Total Score					0.004
<5	460 (68.86%)	325 (67.71%)	128 (75.29%)	7 (38.89%)
>=5	208 (31.14%)	155 (32.29%)	42 (24.71%)	11 (61.11%)
GAD-7 Total Score					0.139
<5	532 (79.64%)	384 (80.00%)	137 (80.59%)	11 (61.11%)
>=5	136 (20.36%)	96 (20.00%)	33 (19.41%)	7 (38.89%)

Note: AUDIT: the alcohol use disorder identification test; PHQ-9: the nine-item Patient Health Questionnaire; GAD-7: the seven-item Generalized Anxiety Disorder questionnaire.

Table 2. Univariate analysis for depressive symptoms

Covariate	OR	95% CI	P-value
N	668
Age (years)	1.00	0.99, 1.01	0.869
Annual household income (yuan)	1.00	1.00, 1.00	0.065
BMI (kg/m²)	1.03	0.98, 1.07	0.211
Gender
Male	1.0 (Reference)
Female	0.75	0.54, 1.05	0.092
Education
Junior high school and below	1.0 (Reference)
Senior high school and above	0.79	0.47, 1.32	0.369
Ethnic group
Han	1.0 (Reference)
Wa	1.21	0.32, 4.61	0.780
Marital status
Single	1.0 (Reference)
Married	1.07	0.71, 1.61	0.744
Currently smoking
No	1.0 (Reference)
Yes	0.79	0.57, 1.11	0.174
The frequency of drinking alcohol
Never	1.0 (Reference)
<= 1 time/month	0.84	0.53, 1.34	0.471
2-4 times/month	1.04	0.61, 1.78	0.888
2-3 times/week	1.30	0.75, 2.25	0.348
>= 4 times/week	0.48	0.25, 0.92	0.026
Suicidal ideation
No	1.0 (reference)
Yes	9.87	3.97, 24.54	<0.001
GAD-7 Total Score
<5	1.0 (Reference)
>=5	12.69	8.12, 19.84	<0.001

Note: PHQ-9: the nine-item Patient Health Questionnaire; GAD-7: the seven-item Generalized Anxiety Disorder questionnaire.

Table 3 Relationship between alcohol dependence score and depressive symptoms in different models

Variable		Unadjusted Model		Model Ⅰ		Model Ⅱ
Variable	N	OR (95%CI)	P-value	OR (95%CI)	P-value	OR (95%CI)	P-value
AUDIT score	668	1.01 (0.98, 1.04)	0.532	1.01 (0.98, 1.03)	0.712	1.07 (1.01, 1.13)	0.031
AUDIT score categorical
AUDIT: 0-7	480	1.0 (Reference)		1.0 (Reference)		1.0 (Reference)
AUDIT: 8-19	170	0.69 (0.46, 1.02)	0.065	0.64 (0.43, 0.96)	0.032	0.73 (0.39, 1.38)	0.331
AUDIT: 20-40	18	3.29 (1.25, 8.66)	0.016	3.32 (1.26, 8.78)	0.015	7.62 (1.79, 32.49)	0.006
P for trend		0.982		0.813		0.412

Abbreviations: AUDIT, the alcohol use disorder identification test; OR, odds ratio; CI, confidence interval;

Unadjusted Model adjusted for none;

Model Ⅰ adjusted for age, sex;

Model Ⅱ adjusted for age, sex, current smoking, frequency of drinking alcohol, annual household income, suicidal ideation, and anxiety symptoms.

Table 4 The results of the two-piecewise Logistic regression model

Inflection point of AUDIT score	OR	95%CI	P-value
Inflection point	15
< 15 slope 1 (n=616)	0.98	0.90 to 1.05	0.53
≥ 15 slope 2 (n=52)	1.43	1.19 to 1.72	<0.001
slope 2 – slope 1	1.47	1.17 to 1.84	<0.001
predicted at 15	-1.23	-1.69 to -0.78
Log likelihood ratio test			<0.001

Effect: Depressive symptoms; Cause: AUDIT score; adjusted for age, sex, current smoking, the frequency of drinking alcohol, annual household income, suicidal ideation, and anxiety symptoms.

Slope 1 and slope 2 are the slope coefficients for the segment before and after the inflection point.

No competing interests reported.

The relationship between depression and alcohol use among the Wa ethnic minority in China

Status:

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Abstract

Figures

1. Introduction

2. Methods

3. Results

4. Discussion

Conclusion

Declarations

Author Contribution

References

Tables

Additional Declarations

Status:

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