|Title||Social networks and alcohol consumption among first generation Chinese and Korean immigrants in the Los Angeles metropolitan area|
|Publication Type||Journal Article|
|Year of Publication||2014|
|Authors||C. Hofstetter, R, Clapp, JD, Allem, J-P, Hughes, SC, Li, Y, Irvin, VL, Daly, AJ, Kang, S, Hovell, MF|
|Journal||The International Journal of Alcohol and Drug Research|
Aims: To test hypotheses involving mechanisms of reinforcement of alcohol behaviors operating in social networks.
Design: Telephone interviews conducted by professional interviewers in Mandarin or Korean or English with first generation Chinese (from Mainland or Taiwan) and Korean immigrants residing using a dual frame stratified sampling design. Combined probability and non-probability approaches for sampling due to the widespread use of cell phones. Interviews were conducted in language of preferences with over 95% of interviews in Korean or Mandarin.
Setting: Residents of three counties with the largest proportions of eligible residents (Los Angeles, Orange, and San Bernardino) were included.
Participants: Adult residents (21 and over) stratified by gender who could be reached by telephone constituted the sample.
Measures: Measures included frequency/amount alcohol consumption drawn from NIAAA standard, a “relax, socialize, have fun with” name generator was used to identify alters. Reinforcers within networks were measured by participant reports of amount of alter drinking, drunkenness, and encouragement to drink, acculturation, and demographic variables were measured by self report.
Findings: Using a random effects approach and controlling for other variables, including drinking in the network, acculturation, Korean/Chinese origin, and demographics, source of immigration, network context, as was and sampling frame, encouragement to drink in the network was related to drinking (P<.05).
Conclusions: Studies of social networks in relation to health behaviors should include measures of actions within networks, especially reinforcers of behaviors, in order to understand the functioning and consequences of networks.