Steele, _Migrant Alcohol Use_ (2013)

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INTRODUCTION

Alcohol consumption in China has increased steadily since the cultural

revolution of the 1970s and the opening of China to the West (Casswell, 2009;

Cochrane, Chen, Conigrave, & Hao, 2003; Hao, Chen, & Su, 2005; Newman, 2002). With

the increase in alcohol use, higher numbers of alcohol-related disorders, both chronic

and acute, have become apparent throughout Chinese society. Government response,

both through policy and laws, is lagging behind these increased rates of use and abuse

(Casswell & Thamarangsi, 2009; Hao et al., 2004). Alcohol consumption in China has

been increasing steadily with a rise of beer consumption from 10.21 million tons in

1990 to 22.89 millions tons in 2001 (Chinese National Bureau of Statistics, 2010). In

2007, (two years after the data for this paper were collected), Li et al., (2011) found

that 35.7% of the general population in China consumed alcohol, and over 50% of men

binged on alcohol when they drank (Y. Li et al., 2011).

Much research has been done on the effects of employment-related stress on

alcohol consumption, abuse, and disorders, but there have been inconsistent findings

and very few of these studies were done outside of Western countries. Some research

has shown that employment-related stress (from the inability to find stable

employment, lack of control at current job, or other stress-inducing factors) causes

increases in both problem drinking and alcohol dependence and lowered wages or

economic opportunities (Bobak, McKee, Rose, & Marmot, 1999; Crawford, Plant,

Krettman, & Latcham, 1987; Janlert & Hammarstrom, 1992; San Jose, Van Oers, Van De

Mheen, Garretsen, & Mackenbach, 2000). Other scholars do not find these results, and

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rather find that moderate drinking increases earning potential for employed people

(Hammer, 1992; Sutton & Godfrey, 1995). Socio-economic status, age, and gender

effects on drinking habits also have been explored with varying results.

China’s National Bureau of Statistics estimated that there were approximately

140 million internal migrant workers in 2008 - about 10% of the workforce of China

(Chinese National Bureau of Statistics, 2010). This rural‐to‐urban movement is not a

new phenomenon, having gained momentum after the founding of the People’s

Republic of China in 1949 and the move away from an agriculturally‐based economy.

Because of the growing internal migrant population, there has been increased

interest in issues that affect this population in particular. The varying findings in

alcohol research in non-Chinese populations, and the lack of research within this

particular population make it unclear whether they are at heightened risk for alcohol-

related health issues in the future. Though the Chinese government has recently

implemented specific laws and regulations related to alcohol abuse (Cochrane, Chen,

Conigrave, & Hao, 2003; Hao et al., 2004; Newman, 2002), there are few rehabilitation

or treatment centers for alcohol-related illnesses. Migrant populations without access

to state-run healthcare (hukou), which is determined by place of birth not current

residence, may be unable to access the few resources that are available (Biao, ; H.

French, 2006; Gao, Tang, Tolhurst, & Rao, 2001; L. Lee, 2004; Solinger, 1999). It is

important to understand the drinking behaviors of this large population in order to

formulate the most successful city- and nation-wide policies targeted at alcohol-use

reduction and treatment.

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Current studies on drinking behaviors in China are few and far between. Those

that have been published vary in respect to their measures. Some count drinking even

one alcohol beverage in the past 12 months as “current drinking” (Hao, Derson, Xiao,

Linjiang, & Zhang, 1999; Jiafang, Casswell, & Cai, 2008; Y. Li et al., 2011; Zhou et al.,

2002), likely skewing the percentage of current drinkers in the population upwards.

Others ask respondents to measure their own drinking behavior by asking, “how often

have you been intoxicated” (X. Chen et al., 2009; Lin et al., 2005). This question could

be misleading because it does not define “intoxicated”. It also may be hard for

someone to know the exact number of times they have been intoxicated in the past

three-, six-, or 12-months. Heavy drinkers, problem drinkers, and binge drinking are

defined a number of ways in these studies (Y. Li et al., 2011). Some offer definitions

similar to the international standards, while others do not, making it hard to interpret

and compare statistics.

This paper explores the effects of socio-economic status (SES) and employment

variables on the risky drinking habits of internal migrants in the city of Chengdu using a

standard 30-day drinking history inventory. The paper further explores the differences

between rural-to-urban migrants and their urban-to-urban migrant counterparts, to

explore any differences that may arise due to the environment where a migrant was

raised, rather than the environment where he or she now lives. This is the first

research on this particular population with standard 30-day drinking measurements,

looking into the drinking habits of this growing population, and factors that contribute

or protect against problem drinking in the internal migrant community.

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Drinking Behaviors of Chinese Migrant Workers

Alcohol consumption in general has increased since the opening of China, and is

becoming more accepted as each generation becomes more “Westernized” (Cochrane,

Chen, Conigrave, & Hao, 2003; Hao, Chen, & Su, 2005). According to Hao, Chen, and Su,

2005, the per capita amount of ethanol (pure alcohol) consumed per year went from

1.03 liters in 1970 to approximately 7.1 liters in 2003. A study of the general population

of China found that in 2007, 35.7% of the population drank alcohol (55.6% of males,

35.7% of females). Of those who drank, 57.3% of men and 26.6% of women binged

when consuming alcohol. The level of binge drinking increased with the frequency of

consumption (Y. Li et al., 2011). The level of alcohol consumption is even higher in

young adults (18-29) (Y. Li et al., 2011; K. Zhang, Li, Li, & Beck, 1999). This increase in

consumption and problem drinking could be due to the way the younger Chinese view

alcohol consumption.

Culturally, alcohol is thought of as a “food” item, rather than a drug, and is

accepted as a socially acceptable way to conduct both business and pleasure activities.

It is also used as a traditional medicine (Hao et al., 2004; Jiafang, Jiachun, Yunxia,

Xiaocia, & Ya, 2004; Newman, 2002). Studies have found that the rural and urban

populations tend to use alcohol in different ways. Rural populations use alcohol

medicinally to ease pain, as a sleep aid, or for the treatment of chronic disorders, while

urban populations use alcohol as a social tool (ibid).

The behaviors and health outcomes of migrants in China, as well as migrants in

other countries, have been studied in numerous works, though studies comparing the

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differences in urban and rural migrant workers within China are lacking. Most studies

focus on the higher proclivity for risky behaviors in general (Biao, ; X. Chen et al.,

2004; He et al., 2005; Hong et al., 2006; Lin et al., 2005; Scheineson, 2009; X. Yang &

Xia, 2006), or the effect of the lack of access to the Chinese healthcare system has on

their overall health (H. French, 2006; Gao, Tang, Tolhurst, & Rao, 2001; Tang et al.,

2008; Xu, Wang, Collins, & Tang, 2007). Research within China has established that

migrants are at a higher risk to develop both behavior‐related illnesses and

chronic health issues than non-migrants (He et al., 2005; Scheineson, 2009; X. Yang

& Xia, 2006). A 2005 study of rural-to-urban migrants in Beijing and Nanjing showed

that 1/3 of participants reported drinking to the point of intoxication in the past

month – higher than the general public (Lin et al., 2005). This study did not, however,

compare the drinking and intoxication levels of rural-to-urban migrants with their

urban-to-urban migrant counterparts.

One study that compared rural migrants to urban migrants found that rural

migrants tend become intoxicated less than or equal to their urban peers (53% in the

past 6 months versus 62.8%, respectively), though this was more dependent on

income level and socio-economic status than migratory origin (X. Chen et al., 2009; B.

Wu, Mao, Rockett, & Yue, 2008). The findings of Chen et al.’s study were at odds with

previous studies that stated rural migrants workers were more likely to participate in

risky behaviors such as alcohol abuse than urban workers (Hao et al., 2004; X. Li et al.,

2007). None of these studies looked at the effects of socio-economic or employment-

related variables within each urbanized migrant cohort.

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Very few studies on alcohol use in China share measures, making results diverge

greatly across the literature. Hao et al.’s 1999 study of five provinces around China

reported a drinking rate of 84.1% of respondents, but the study used a measure that

rated even one alcoholic beverage per year as a “current drinker” (Hao, Derson, Xiao,

Linjiang, & Zhang, 1999). Li et al.’s 2011 study used this same measure but only found

that 35.7% of respondents were “current drinkers” (Y. Li et al., 2011). These variances

are reflected in much of the literature, making it hard to compare across populations

and to trust the statistics being reported.

Employment, Socio-Economic Status, and Drinking

There is a considerable amount of research on the effects of employment,

unemployment, socio-economic status, and work-related stress on alcohol

consumption, with varying findings. Studies differ in scope, looking at binge-drinking

(usually >4 drinks per hour for women and >5 drinks per hour for men) or alcohol

dependence (American Psychiatric Association, 2000; Wechsler, Dowdall, Davenport,

& Rimm, American Journal of Public Health). Most of these studies focus on Western

populations.

Many studies find that binge-drinking rates are higher for unemployed

individuals than employed individuals (Bobak, McKee, Rose, & Marmot, 1999;

Crawford, Plant, Krettman, & Latcham, 1987; Janlert & Hammarstrom, 1992; San Jose,

Van Oers, Van De Mheen, Garretsen, & Mackenbach, 2000), but this is not consistent

in all studies (Hammer, 1992; Sutton & Godfrey, 1995). Reasons for the discrepancy

vary from “the unemployed have more time on their hands to drink heavily” to “the

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employed have more free income to spend on alcohol than the unemployed” (Caswell,

Pledger, & Hooper, 2003).

Socio-economic status seems to have varying effects on drinking behavior. Less

educated respondents tend to report heavier drinking (Dawson, Grant, Chou, &

Pickering, 1995; Droomers, Schrijvers, Stronks, Van De Mheen, & Mackenbach, 1999; J.

Van Oers, Bongers, Van De Goor, & Garretsen, 1999), but researchers suggest the

direction of causation is unclear (Cook & Moore, 1993; Mullahy & Sindelar, 1989).

Alcohol dependence levels seem to be higher in lower SES groups (Delva & Kameoka,

1999; Droomers, Schrijvers, Stronks, Van De Mheen, & Mackenbach, 1999; Grant,

1997; Hasin, Stinson, Ogburn, & Grant, 2007; J. Van Oers, Bongers, Van De Goor, &

Garretsen, 1999) but binge-drinking levels seem to be lower for lower SES groups

(Slutske, 2005). Others find no correlation (Keyes & Hasin, 2008).

Among employed individuals, studies have found that both occupational status

(blue-collar versus white-collar) and stress-level at work affect consumption levels

with manual-laborers and workers without decision-freedom drinking more than their

non-manual-labor counterparts (Crum, Muntaner, Eaton, & Anthony, 1995; Grunberg,

Moore, & Greenberg, 1998; Hemmington, Lundberg, Diderichsen, & Allebeck, 1998).

Others disagree with these findings showing that neither labor status nor stress level

directly affects drinking levels (Cooper, Russel, & Frone, 1990; Finch, Catalano,

Novaco, & Vega, 2003; Mensch & Kandel, 1996; M. Seemen & Anderson, 1983; M.

Seemen, Seemen, & Budros, 1988). These studies show that coping style is the

moderator in consumption level, rather than stress level or job type.

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Job insecurity and loss seems to cause an increase in binge drinking, but

enduring unemployment does not (Brown, 1983; Catalano, Dooley, Wilson, & Hough,

1993; Cooper, Russel, & Frone, 1990; Crawford, Plant, Krettman, & Latcham, 1987).

High unemployment rates in an area seems to cause a decrease in binge-drinking rates

in employed individuals, as people fight to keep the jobs that they have (Catalano,

Rook, & Dooley, 1986; Ettner, 1997).

Moderate alcohol use (falling below the binge-drinking and dependence

thresholds) seems to be related to higher wages in some studies (Berger & Leigh,

1988; M. French & Zarkin, 1995; V. Hamilton & Hamilton, 1977; Heien, 1996;

McDonald & Shields, 2001). Other studies dispute this, citing the negative indirect

effects of alcohol use on long term earning potential (Mullahy & Sindelar, 1989;

Mullahy & Sindelar, 1993).

METHODS

The findings in this article are the result of a cross-sectional survey of job-seeking

migrants (lacking Chengdu hukou) that was carried out in 2005 in the city of Chengdu,

the capital of Sichuan Province and the economic and technological hub of

Southwestern China. The focus of the dataset was to provide a comparison of the

impact of socioeconomic status and employment conditions on the psychological

outcomes of rural-to-urban and urban-to-urban job-seeking Chinese migrants. The

research team consisted of researchers from the Claremont Graduate University School

of Community and Global Health, the University of Southern California Institute for

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Prevention Research and the Chengdu (China) Center for Disease Control and Prevention

(CCDCP). According to the city census the number of rural-to-urban migrants in this city

of 9.9 million was approximately one million, with unofficial estimates putting the

number closer to two million. While most studies of migrants in China have focused on

unskilled and low skilled workers, the objective of this study was to investigate the

impact of rural-to-urban migration on the health of a diverse sample of migrants, taking

into account different educational, job skills and employment experiences. All consent

procedures and survey instruments were approved by both the U.S. universities’ and

CCDCP’s institutional review boards.

[For an in depth explanation of the methods, sampling, data collection, and survey

development procedures, please see Palmer, “X”, 2012…]

Measures

The questionnaire consisted of 165 pilot-tested items, however for this article,

the focus is on the demographic, socioeconomic, and alcohol-consumption variables.

General socioeconomic status

General socioeconomic status was explored using items about education, family

and individual monthly income, subjective appraisal of income of self versus others and

affordability of food and medical care. Educational attainment was measured

categorically with increments ranging from no formal schooling to a graduate degree or

higher. These responses were then collapsed into four categories: elementary school or

below, middle school, high school/vocational school, and college/university or higher.

Family and individual monthly income questions included: “What is your average total

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monthly family income from all sources including bonuses, salary, money earned from

second job, etc,”, “How much of this income do you personally earn monthly in

Chengdu?” Response options ranged from <100 Yuan/month (<$12 USD/month) to

>10,000 Yuan/month (>$1200 USD/month). The midpoint value was used to convert the

categorical responses to two continuous variables (family and individual monthly

income). Income levels were collapsed into tertiles for analysis. Affordability of food and

medical care was assessed by: “In the past year, were you able to afford to buy the kind

of food you wanted?” and “the kind of medical care you needed?” (yes or no).

Employment experiences

Job experiences were evaluated by ten employment status, work conditions and job

security questions. Items include: 1. Ease in finding a job: “In your opinion, is it easy to

find employment in Chengdu?” (yes, definitely to no, definitely not); 2. Number of jobs

in the past year: “How many different employers did you have in the past 12 months?”

(0 to 2 or more); 3. Current employment status (unemployed or employed); 4. Number

of workdays in the past month (0 days, 1-7 days, 8-14 days, 15-21days, and 22-30 days);

5. Number of working hours per week (none, 1-10 hours to more than 50 hours); 6. Time

pressure at work (“I don’t experience substantial time pressure at work. It is only

important that I finish my work tasks within a reasonable amount of time” (coded as 0),

“Sometimes I face time pressure at work” (coded as 1), “I have an extremely tight

schedule, but with maximal effort I can usually finish my tasks on time” (coded as 2), “I

have an extremely tight schedule, and despite my bet efforts, I sometimes or often

cannot finish my task on time” (coded as 3)); 7. On-time payment from employers: “How

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often do your employers pay you on time?” (always to never); 8. Receive compensation

for work: “How often do your employers not pay you for your work?” (always to never);

9. Receive amount of payment for work as promised: “How often do your employers pay

you substantially less than he/she promised?” (always to never), and 10. Job security:

“Do you feel confident that you will be able to find regular work and remain employed?”

(definitely yes to definitely no).

Alcohol consumption

Alcohol consumption was measured with three questions. The first question

asked respondents, “During the past 30 days, on how many days did you have at least

one drink of alcohol?” (0 days, 1 or 2 days, 3 to 5 days, 6 to 9 days, 10 to 19 days, 20 to

29 days, all 30 days). Responses were combined to make three categories: 0 days, 1-9

days, and 10+ days. Binge-drinking was measured with two separate questions to cover

the different accepted binge-drinking level (American Psychiatric Association, 2000;

Wechsler, Dowdall, Davenport, & Rimm, American Journal of Public Health). The

question was asked in the same way, but with two different drinking amounts: “During

the past 30 days, on how many days did you have 4 (5) or more drinking of alcohol in a

row, that is, within a couple of hours?” (0 days, 1 day, 2 days, 3 to 5 days, 6 to 9 days, 10

to 19 days, 20 or more days). This paper uses the 4+ drinking rate question as the

definition of binge drinking because far fewer respondents answered the 5+ drinking

rate question, therefore skewing the results. We find this to be acceptable because of

the lower levels of alcohol tolerance in the wider Chinese population, leading to

drunkenness and “binges” at lower levels of consumption than in European and

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American populations (Hao, Chen, & Su, 2005; J. Lee, 1987; Teng, 1981).Because any

episode of binge-drinking was considered important, the responses were combined into

two categories: 0 days or 1+ days. This 30-day drinking inventory is not common in other

studies of alcohol use in China, but is a recognized measure in international drinking

literature (American Psychiatric Association, 2000; Wechsler, Dowdall, Davenport, &

Rimm, American Journal of Public Health).

Other covariates

Other covariates included age, gender, length of stay in Chengdu, marital status,

and “migration type” (urban-to-urban or rural-to-urban).

Statistical Analysis

The sample included 1,005 participants from Chengdu. 95 participants were

excluded due to claiming Chengdu hukou. Descriptive statistics (mean, standard

deviation and percentage) were calculated to show norm demographic variables,

socioeconomic status and employment experiences of the sample. Independent t-test

and chi-square tests were used to compare characteristics of demographic variables,

socioeconomic status and employment experiences between urban-to-urban migrants

and rural-to-urban migrants. Odds ratios, calculated with SAS 2011 statistical software,

were used to look at the differences in binge-drinking between the urban-to-urban

cohort and the rural-to-urban cohort. The analysis was expanded to compare the effects

of a variety of socio-economic status and employment-related questions on the drinking

habits of urban-to-urban and rural-to-urban respondents, adjusting for marriage,

education level, gender, age, and employment.

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RESULTS

Detailed descriptions of general socio-demographic characteristics of the sample

are summarized in Table 1. Of the 1,005 respondents, 504 were female (50.2%) and 501

were male (49.9%). Close to 50% of migrant workers were aged 18 to 25 years (47.4%)

and received below high school of education (47.1%). The majority of them were not

married (63.3%) and had stayed in Chengdu over one year (67.9%). The average monthly

family income was 1,580.5 Yuan (equivalent to 231 USD), and individual income was

885.3 Yuan (equivalent to 130 USD). Distributions of these general socio-demographic

characteristics were significantly different between urban-to-rural migrants and rural-to-

urban migrants. Compared to the rural-to-urban group, the urban-to-urban migrant

group was younger (18.7% were 31-40 years versus 34.2%; p<0.0001), more highly

educated (43.5% completed college versus 14.2%; p<0.001), and had higher family and

individual incomes (34.2% versus 19.8% and 37% versus 22% for the third tertile;

p<0.0001).

Tables 2a and 2b show the general drinking characteristics of the population,

and the comparison between the urban-to-urban respondents and the rural-to-urban

respondents. In the past 30 days, 35.5% of respondents reported having had at least one

drink of alcohol; 25.1% on one to nine days and 10.5% on ten days or more, though this

was not statistically significant (P = 0.356). There was no significant difference between

urban-to-urban migrants and rural-to-urban migrants (35.6% and 35.57% drank at least

once in the past thirty days, respectively). In terms of binge-drinking (4 or more drinks

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within one to two hours), in the combined population, 81.3% of respondents had not

had any binge-drinking incidences within the past 30 days (80.7% for urban-to-urban

migrants; 81.6% for rural-to-urban migrants) (p<0.01). Similar to the overall drinking

rate, the binge drinking rates were similar between urban and rural migrants (19.3% and

18.4%, respectively).

The gender breakdown of drinking follows the same pattern as found in other

alcohol literature in China. Far more male respondents could be considered current

drinkers (55.7% versus 15.49 for female respondents) (p<0.01). 29.5% of male

respondents binged at least once in the past month while only 7.95% of females did

(p<0.01). Urban males and rural males were current drinkers at around the same levels

(57.6% and 55%), but rural males answered to drinking more days per month than urban

males (18.4% versus 15.8% for drinking 10+ days per month). This difference was not

statistically significant. Urban males binged slightly more than rural-to-urban males

(32.9% and 28.1%, respectively) but this was also not statistically significant. Urban

migrant females were more likely to be current drinkers than rural migrant females

(18.6% versus 13.3%), and slightly more likely to binge drink as well (8.8% versus 7.36%),

but these findings were not statistically significant. These findings should be accepted

with caution, as very few female respondents answered drinking-related questions.

Table 3 summarizes the characteristics of socioeconomic status and employment

difficulty. The majority of migrant workers were able to afford food (84.1%) and medical

care (69.4%), and in the past year had one to three jobs (86.2%). Most respondents did

not (41.7%) or only sometimes (29.3%) experience time pressure at work, were

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completely (65.4%) or partially (27.2%) able to control the speed of work, and were

always (61.9%) or usually (20.6%) paid on-time. A little less than half of respondents

were sometimes paid less than originally promised (38.1%). Approximately one-third

(38.8% total, 9% definitely yes and 29.8% maybe yes) of participants reported it was

easy to find a job and 69.8% of participants felt confident in their ability to eventually

find and maintain employment (35% definitely yes and 34.8% probably yes). Compared

to their urban-to-urban counterparts, relatively more rural-to-urban migrants reported

ease in finding a job (p=0.01), having 4 or more different jobs in the past year (p=0.04),

working longer than 50 hours per week (p<0.0001), or being unconfident in job security

(p<0.01).

There were significant differences between urban-to-urban respondents and

rural-to-urban respondents, so groups were split to show the differences in their

economic and alcohol use patterns. Table 4a and 4b show the relationship between

employment and socio-economic variables and binge drinking, separated by urban-to-

urban and rural-to-urban respondents (adjusted for marriage, education, gender, age,

income, and employment).

For urban-to-urban migrants (table 4a), an increase in education level (OR: 1.52,

p<0.01) and an increase in monthly income level (OR: 1.63, p<0.01) were highly

positively correlated with an increased likelihood of being a current drinker. Increased

time pressure at work was positively correlated with monthly history of alcohol

consumption, but at a less significant level (OR: 1.40, p=0.02). Respondents with higher

education level (OR: 1.75), higher monthly income level (OR: 1.71), and more time

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pressure at work (OR: 1.68) were all more likely to binge-drink over 4 drinks within a few

hours (p<0.01).

Correlations were slightly different for rural-to-rural migrants (table 4b).

Increased individual income (OR: 1.42, p=0.01) was the only variable correlated

positively with an increased monthly history of alcohol consumption. As the variable

was reverse-coded, increased affordability of medical care was the only variable

negatively correlated with binge-drinking over 4 drinks per hour (OR: 0.48, p=0.02).

The interaction between gender, place of origin, socioeconomics, and drinking

showed fewer significant results, but did have a few interesting findings. In the entire

population of respondents, the interaction between male gender and days worked in

the past month was positively correlated with increased drinking in the past thirty days

(OR: 4.84, p=0.0281). Less payment from employer interacted with male gender was

positively correlated with increased binge drinking (OR: 4.17, p=0.0415). In the urban-

to-urban migrant cohort, interactions between being male and current employment

status (OR: 4.35, p=0.0378), number of days worked in the past month (OR: 6.22,

p=0.0131), and number of hours worked in the past week (OR: 5.84, p=0.0162) were all

positively correlated with increased drinking alcohol in the past thirty days. The

interaction between male gender and income was positively correlated with increased

binge drinking (OR: 4.35, p=0.0378). The rural-to-urban migrant cohort did not have any

significant interactions, nor did being female.

DISCUSSION

This study looked at the effects of employment and socio-economic factors on

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the drinking behaviors of rural-to-urban and urban-to-urban migrants in the city of

Chengdu, China using a standardized 30-day drinking history inventory.

Though drinking behaviors in China have changed in the past thirty years,

alcohol use is still less prevalent in Chinese society than in Western countries (Biao, ;

Cochrane, Chen, Conigrave, & Hao, 2003). The results of this study agree with this, as

the majority of respondents did not drink at all. 35.5 % of the respondents to this

study reported drinking at least once in the past 30 days, an increase from the early

days of China’s relationship with the west. These findings agree with Li (2011) and are

a more reliable measure of the current drinking rate than studies that use 3-month or

12-month drinking inventories.

Of those who did drink, binge-drinking rates (4+ drinks within an hour) were at a

comparable rate to binge drinking rates in the United States, which according to the

CDC Binge Drinking Fact Sheet 2010, was around 17% (up from 14.3% in 2001), though

these studies used 5+ drinks for men and 4+ drinks for women as the definition of

binge drinking (Centers for Disease Control, 2012; Naimi et al., 2003). In a country with

little focus on the prevention, education, or treatment, these rates could spell disaster

for the Chinese health system.

The variance between drinking rates for urban-to-urban migrants did not vary

significantly from the drinking rates for rural-to-urban migrants, though binge-drinking

rates were slightly higher for urban-to-urban respondents, which is consistent with the

findings of Chen et al., 2005. This could possibly be explained by the different ways

that urban and rural Chinese approach alcohol use. According to Newman (2002), rural

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Chinese see alcohol as “medicinal”, while urban populations tend to have a

Westernized, social view of alcohol use (Newman, 2002).

For urban-to-urban migrants, increases in education, monthly income, and level

of time pressure at work led to a 1.5+ times greater chance of regular use of alcohol

and binge-drinking. This could be due to the use of alcohol as a tool for social and

business mobility (Hao et al., 2004; Newman, 2002) and as a stress-escape tool

(Cooper, Russel, & Frone, 1990; Dawson, Grant, & Ruan, 2005; Grunberg, Moore, &

Greenberg, 1998; San Jose, Van Oers, Van De Mheen, Garretsen, & Mackenbach,

2000). Increased income could also be related to the ability to afford alcohol

(Catalano, Rook, & Dooley, 1986; Ettner, 1997; M. French & Zarkin, 1995). The

relationship between on-time payment from employers and increased alcohol use may

have to do with stress and escapist uses of alcohol, as this was only correlated with

binge drinking. In the modern Chinese urban culture, alcohol is an acceptable and

expected social lubricant for business deals (Hao et al., 2004; Newman, 2002), and this

could be the reason for these particular correlations.

In the rural-to-rural cohort, increasing income led to a 1.4 times higher

likelihood of current alcohol consumption and binge-drinking, but at a less significant

level. Affordability of medical care had an inverse relationship with drinking level: as

medical care became more affordable, respondents drank less. This makes sense when

looking at the cultural history of alcohol use in rural areas where alcohol is commonly

used as a form of medicine (Newman, 2002).

The level of drinking in female respondents is far lower than those reported in

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other studies (Hao, Derson, Xiao, Linjiang, & Zhang, 1999; Hao et al., 2004; Jiafang,

Jiachun, Yunxia, Xiaocia, & Ya, 2004). This seems likely to be due to the 30-day

inventory rather than the 12-month inventory which captured women who drank only

once in the year as “current drinkers”. Urban women binged at a slightly hire rate than

their rural counterparts, which may be due to the level of acceptance of female

drinking in the urban environments versus the rural environments.(X. Chen et al.,

2009; Cochrane, Chen, Conigrave, & Hao, 2003; Newman, 2002). Though the results

must be seen through the limitation of low female respondents, this offers an

interesting view on the rural and urban differences in drinking patterns within each

gender. Gender is explored in other alcohol studies, but there is a lack of consistent

and significant findings in these studies as well (Dawson, Grant, Chou, & Pickering,

1995; Klassen & Wilsnack, 1986; Knupfer, 1984; Nolen-Hoeksema, 2004; Perkins,

Meilman, Leichliter, Cashin, & Presley, 1999; S. Wilsnack & Wilsnack, 1991). This would

be an interesting topic to explore further, due to the implications of alcohol abuse on

all segments of Chinese society.

Interactions showed results that confirm the findings offered above. Being male

is more likely to be correlated with both current drinking and binge drinking, and is

connected by income, working days per month, and working hours per week, as is

being from an urban-to-urban migrant cohort. This bolsters the findings of this paper

in terms of gender, origin location, and drinking patterns.

There are several limitations to this study. As this research took place in

southwestern China, the findings may not be generalizable to migrants in other

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regions of the country, particularly in the large cities in Eastern China or even the

majority of migrants throughout Chengdu. Despite the attempt to provide an

appropriate and confidential environment for participant interviews, some

participants, may have not been completely honest in all of their responses,

particularly those questions regarding alcohol use and abuse. In the case of female

respondents, many of the alcohol-related questions were left blank. Despite these

limitations, this study utilized a reliable sampling strategy that was inclusive of the full

range of migrants.

Another limitation is the inability to compare these findings with other scholarly

research due to the lack of measure standardization (Knupfer, 1984). Some studies

measure alcohol intake in liters of pure ethanol or grams of alcohol consumed (Hao,

Derson, Xiao, Linjiang, & Zhang, 1999; Y. Li et al., 2011), while others, like this study,

use number of drinks. Still others asked respondents to rate whether they have been

intoxicated in the past X amount of days or months (X. Chen et al., 2009). This lack of

clarity makes it hard to interpret results across multiple studies.

Future directions for this research should include comparing this particular

group of data with the alcohol use rates of the general population to explore any risk

proclivities or protective factors that one group may have compared to the Chinese

population as a whole. These standardized, easy to interpret measures should be used

in other areas of China to make for easily comparable and internationally valid

datasets.

Rural-to-urban and urban-to-urban migrants seem to have different reasons for

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their alcohol consumption. Though alcohol consumption is increasing in China, it is

important to explore these differences to best inform policy for both prevention and

treatment. Laws concerning social drinking may not be effective for migrants who are

using alcohol as a form of medicine, and social drinking may have different

consequences than escapist drinking. It is important for policy makers to recognize

these differences. Importantly, this research advances our knowledge about the

impact of the migration experience on the alcohol use patterns of rural-to-urban and

urban-to-urban migrants and, notably, brings to the forefront the importance of

differentiating migrant place-of-origin in future studies of migrant alcohol use.