Recently, latent class analysis (LCA) and its variants have been proposed to identify subgroups of individuals who follow similar sequential patterns of latent class membership for longitudinal study. A primary assumption underlying the family of LCA is that individual observations are independent. In many applications, however, particularly in research on adolescent substance use, individuals are often dependent because of multilevel data structure, where the unit of observation (e.g., students) is nested in higher level units (e.g., schools). In this study, we propose multilevel latent class profile analysis (MLCPA), which will allow us to analyze the longitudinal data with a multilevel structure under the framework of LCA. We apply an MLCPA using data from the COMPASS study, a 9-year study funded by the Canadian Institutes of Health Research and Health Canada, in order to identify representative sequential drinking patterns of Canadian youth and investigate whether these sequential patterns vary across schools. The MLCPA identified three common student-level drinking behaviors: non-drinker, ever lifetime, and binge drinker. The sequence of drinking behaviors can be classified into one of three longitudinal sequential patterns: non-drinking stayer, light drinking advancer, and heavy drinking advancer. In addition, MLCPA uncovered two latent clusters (low-use school and high-use school) out of 64 schools in Ontario and Alberta based on the prevalences of sequential drinking patterns.
AkaikeH. (1981). Likelihood of a model and information criteria. Journal of Econometrics, 16(1), 3–14.
2.
ÅslundC.NilssonK. W. (2013). Social capital in relation to alcohol consumption, smoking, and illicit drug use among adolescents: A cross-sectional study in Sweden. International Journal for Equity in Health, 12(1), 33.
3.
AuerbachK. J.CollinsL. M. (2006). A multidimensional developmental model of alcohol use during emerging adulthood. Journal of Studies on Alcohol, 67(6), 917–925.
4.
Bandeen-RocheK.MigliorettiD. L.ZegerS. L.RathouzP. J. (1997). Latent variable regression for multiple discrete outcomes. Journal of the American Statistical Association, 92, 1375–1386.
5.
BaumL. E.PetrieT.SoulesG.WeissN. (1970). A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. The Annals of Mathematical Statistics, 41(1), 164–171.
6.
BennerA. D.GrahamS. (2007). Navigating the transition to multi-ethnic urban high schools: Changing ethnic congruence and adolescents’ school-related affect. Journal of Research on Adolescence, 17(1), 207–220.
7.
BrennerA. B.BauermeisterJ. A.ZimmermanM. A. (2011). Neighborhood variation in adolescent alcohol use: Examination of socioecological and social disorganization theories. Journal of Studies on Alcohol and Drugs, 72(4), 651–659.
8.
BrièreF. N.RohdeP.SeeleyJ. R.KleinD.LewinsohnP. M. (2014). Comorbidity between major depression and alcohol use disorder from adolescence to adulthood. Comprehensive Psychiatry, 55(3), 526–533.
9.
Brooks-RussellA.Simons-MortonB.HaynieD.FarhatT.WangJ. (2014). Longitudinal relationship between drinking with peers, descriptive norms, and adolescent alcohol use. Prevention Science, 15(4), 497–505.
10.
BrubacherJ. R.ChanH.MartzW.SchreiberW.AsbridgeM.EpplerJ.PurssellR. (2016). Prevalence of alcohol and drug use in injured British Columbia drivers. BMJ Open, 6(3), 3009278.
11.
CambronC.KostermanR.CatalanoR. F.GuttmannovaK.HawkinsJ. D. (2018). Neighborhood, family, and peer factors associated with early adolescent smoking and alcohol use. Journal of Youth and Adolescence, 47(2), 369–382.
12.
ChanG. C.LeungJ.ConnorJ.HallW.KellyA. B. (2017). Parental supply of alcohol and adolescent drinking: A multilevel analysis of nationally representative data. BMC Public Health, 17(1), 560.
13.
ChungH.AnthonyJ. C. (2013). A Bayesian approach to a multiple-group latent class-profile analysis: The timing of drinking onset and subsequent drinking behaviors among US adolescents. Structural Equation Modeling: A Multidisciplinary Journal, 20, 658–680.
14.
ChungH.AnthonyJ. C.SchaferJ. L. (2011). Latent class profile analysis: An application to stage sequential processes in early onset drinking behaviours. Journal of the Royal Statistical Society: Series A (Statistics in Society), 174(3), 689–712.
15.
ChungH.ParkY.LanzaS. T. (2005). Latent transition analysis with covariates: Pubertal timing and substance use behaviors in adolescent females. Statistics in Medicine, 24(18), 2895–2910.
16.
CloggC. C.GoodmanL. A. (1984). Latent structure analysis of a set of multidimensional contingency tables. Journal of the American Statistical Association, 79, 762–771.
17.
CollinsL. M.LanzaS. T. (2010). Latent class and latent transition analysis with applications in the social, behavioral, and health sciences. John Wiley & Sons.
18.
CollinsL. M.WugalterS. E. (1992). Latent class models for stage-sequential dynamic latent variables. Multivariate Behavioral Research, 27(1), 131–157.
19.
DempsterA. P.LairdN. M.RubinD. B. (1977). Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1), 1–22.
20.
DuncanS. C.DuncanT. E.StryckerL. A. (2002). A multilevel analysis of neighborhood context and youth alcohol and drug problems. Prevention Science, 3(2), 152–153.
21.
EllicksonP. L.TuckerJ. S.KleinD. J. (2003). Ten-year prospective study of public health problems associated with early drinking. Pediatrics, 111(5), 949–955.
22.
EspelandM. A.HandelmanS. L. (1989). Using latent class models to characterize and assess relative error in discrete measurements. Biometrics, 45, 587–599.
23.
GilmoreW.ChikritzhsT.StockwellT.JerniganD.NaimiT.GilmoreI. (2016). Alcohol: Taking a population perspective. Nature Reviews Gastroenterology & Hepatology, 13, 426–434.
24.
GohariM. R.CookR. J.DubinJ. A.LeatherdaleS. T. (2020). Identifying patterns of alcohol use among secondary school students in Canada: A multilevel latent class analysis. Addictive Behaviors, 100, 106120.
25.
GoodmanL. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61, 215–231.
26.
HingsonR.HeerenT.WinterM.WechslerH. (2005). Magnitude of alcohol-related mortality and morbidity among us college students ages 18–24: Changes from 1998 to 2001. Annual Review of Public Health, 26, 259–279.
27.
IpB. A. R. E. H.WolfsonM. (2008). Locally dependent latent class models with covariates: An application to under-age drinking in the USA. Journal of Royal Statistical Society, Series A (Statistics in Society), 17. 877–897.
28.
JacksonK. M.SchulenbergJ. E. (2013). Alcohol use during the transition from middle school to high school: National panel data on prevalence and moderators49(11), 2147. Developmental psychology, 49(11), 2147–2158.
29.
JuangB. H.RabinerL. R. (1991). Hidden Markov models for speech recognition. Technometrics, 33, 251–272.
30.
KandelD. B. (Ed.). (2002). Stages and pathways of drug involvement: Examining the gateway hypothesis. Cambridge University Press.
31.
KandelD.YamaguchiK. (1993). From beer to crack: Developmental patterns of drug involvement. American Journal of Public Health, 83(6), 851–855.
32.
KeelingR. P. (2000). The political, social, and public health problems of binge drinking in college. Journal of American College Health, 48(5), 195–198.
33.
LandbergJ. (2009). Per capita alcohol consumption and suicide rates in the US, 1950–2002. Suicide and Life-threatening Behavior, 39(4), 452–460.
34.
LarsenK.ToT.IrvingH. M.BoakA.HamiltonH. A.MannR. E.FaulknerG. E. (2017). Smoking and binge-drinking among adolescents, Ontario, Canada: Does the school neighbourhood matter?Health & Place, 47, 108–114.
35.
LeatherdaleS. T.BrownK. S.CarsonV.ChildsR. A.DubinJ. A.ElliottS. J.FaulknerG.HammondD.ManskeS.SabistonC. M.LaxerR. E.BredinC.Thompson-HaileA. (2014). The compass study: A longitudinal hierarchical research platform for evaluating natural experiments related to changes in school-level programs, policies and built environment resources. BMC Public Health, 14(1), 331.
36.
LeeC.CorteC.SteinK. F. (2018). Drinker identity: Key risk factor for adolescent alcohol use. Journal of School Health, 88(3), 253–260.
37.
LeungA.LawJ.CookeM.LeatherdaleS. (2019). Exploring and visualizing the small-area-level socioeconomic factors, alcohol availability and built environment influences of alcohol expenditure for the City of Toronto: A spatial analysis approach. Health Promotion and Chronic Disease Prevention, 39(1), 15–24.
38.
LeventhalT.Brooks-GunnJ. (2000). The neighborhoods they live in: The effects of neighborhood residence on child and adolescent outcomes. Psychological Bulletin, 126(2), 309–337.
39.
LiangW.ChikritzhsT. (2015, February). Age at first use of alcohol predicts the risk of heavy alcohol use in early adulthood: A longitudinal study in the United States. International Journal of Drug Policy, 26(2), 131–134.
40.
Maldonado-MolinaM. M.LanzaS. T. (2010). A framework to examine gateway relations in drug use: An application of latent transition analysis. Journal of Drug Issues, 40(4), 901–924.
41.
McBrideO.AdamsonG.ChengH. G.SladeT. (2014). Changes in drinking patterns in the first years after onset: A latent transition analysis of national epidemiologic survey on alcohol and related conditions (NESARC) data. Psychology of Addictive Behaviors, 28(3), 696–709.
42.
McHughR. B. (1956). Efficient estimation and local identification in latent class analysis. Psychometrika, 21, 331–347.
43.
NaimiT. S.BrewerR. D.MokdadA.DennyC.SerdulaM. K.MarksJ. S. (2003). Binge drinking among us adults. The Journal of the American Medical Association, 289(1), 70–75.
44.
PatteK. A.QianW.LeatherdaleS. T. (2017). Is binge drinking onset timing related to academic performance, engagement, and aspirations among youth in the COMPASS study?Substance Use & Misuse, 52(13), 1795–1800.
45.
PetersonS. J.DavisH. A.SmithG. T. (2018). Personality and learning predictors of adolescent alcohol consumption trajectories. Journal of Abnormal Psychology, 127(5), 482–495.
RansomeY.LuanH.ShiX.DuncanD. T.SubramanianS. (2018). Alcohol outlet density and area-level heavy drinking are independent risk factors for higher alcohol-related complaints. Journal of Urban Health, 96, 889–901.
48.
RowlandB.ToumbourouJ. W.LivingstonM. (2015). The association of alcohol outlet density with illegal underage adolescent purchasing of alcohol. Journal of Adolescent Health, 56(2), 146–152.
49.
SchlenbergJ. E.MaggsJ. L. (2002). A developmental perspective on alcohol use and heavy drinking during adolescence and the transition to young adulthood. Journal of Studies on Alcohol, 14, S54–S70.
50.
SchwarzG. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464.
51.
SoloskiK. L.MonkJ. K.DurtschiJ. A. (2016). Trajectories of early binge drinking: A function of family cohesion and peer use. Journal of Marital and Family Therapy, 42(1), 76–90.
52.
SwahnM. H.SimonT. R.HammigB. J.GuerreroJ. L. (2004). Alcohol-consumption behaviors and risk for physical fighting and injuries among adolescent drinkers. Addictive Behaviors, 29(5), 959–963.
53.
VermuntJ. (2003). Multilevel latent class models. Sociological Methodology, 33(1), 213–239.
54.
WagenaarA. C.HolderH. D. (1995). Changes in alcohol consumption resulting from the elimination of retail wine monopolies: Results from five U.S. states. Journal of Studies on Alcohol, 56(5), 566–572.
55.
WhiteH. R.LoeberR.Stouthamer-LoeberM.FarringtonD. P. (1999). Developmental associations between substance use and violence. Development and Psychopathology, 11(4), 785–803.
56.
WodtkeG. T.ElwertD. J. H. F. (2011). Neighborhood effects in temporal perspective: The impact of long-term exposure to concentrated disadvantage on high school graduation. American Sociological Review, 76(5), 713–736.
57.
YangI. S.BeckerM. P. (1997). Latent variable modeling of diagnostic accuracy. Biometrics, 53, 948–958.
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