Skip to main content
PMC home page
Alcohol and Alcoholism (Oxford, Oxfordshire) logoLink to Alcohol and Alcoholism (Oxford, Oxfordshire)
. 2014 Dec 22;50(2):226–235. doi: 10.1093/alcalc/agu092

Drinking Patterns and Victimization among Male and Female Students in Mexico

Lee Strunin 1,*, L Rosa Díaz-Martínez 2, Alejandro Díaz-Martínez 3, Timothy Heeren 4, Michael Winter 5, Seth Kuranz 1, Carlos A Hernández–Ávila 6, Héctor Fernández-Varela 7, Cuauhtémoc Solís-Torres 7
PMCID: PMC4327343  PMID: 25534933

Abstract

Aims: The purpose of this study is to estimate the prevalence of alcohol use and alcohol-related consequences, identify drinking profiles using latent profile analysis (LPA), and investigate associations between profiles and violent victimization among young people in Mexico. Methods: LPA identified profiles of drinking behavior in a survey of entering first year university students. Multinomial and logistic regression examined associations between drinking patterns, socio-demographic variables and violent victimization. Results: The LPA identified five profiles of behaviors and consequences among the 22,224 current, former and never drinkers: Non/Infrequent-No Consequences, Occasional-Few Consequences, Regular-Some Consequences, Heavy-Many Consequences and Excessive-Many Consequences drinkers. The Occasional-Few Consequences profile comprised the largest, and the Excessive-Many Consequences profile the smallest, group of drinkers. Multinomial regression showed males and older students more likely to be Heavy or Excessive-Many Consequences drinkers. Living alone was associated with higher odds, and higher maternal education with lower odds, of being a Non/Infrequent-No Consequences drinker. Heavier drinking profiles were more likely to experience violent victimization adverse consequences. Logistic regression showed male and female Heavy and Excessive-Many Consequences drinkers had the highest odds, and Non/Infrequent drinkers the lowest odds, of experiencing any victimization. Conclusion: Findings suggest changes in male and female drinking behavior and a continuation of the established pattern of infrequent but high consumption among Mexican youths. Both male and female Heavy and Excessive-Many Consequences drinkers were at elevated risk for experiencing victimization. Identifying cultural gender norms about drinking including drinker expectations and drinking context that contribute to these patterns can inform prevention efforts.

INTRODUCTION

Studies of alcohol use among young people worldwide show heavy episodic drinking and increased alcohol use frequently associated with harmful consequences including a higher risk of accidents (Perkins, 2002), injuries (Hingson and Zha, 2009; Rehm et al., 2010), fights (Hingson et al., 2009; Cleveland et al., 2012), adverse sexual events (Connor et al., 2013) and problems with authorities (Reboussin et al., 2006). All these studies suggest the risk of these outcomes peaks at the age at which periodic or high-risk drinking is greatest (National Institute of Alcohol Abuse and Alcoholism, 2006).

In Mexico, men traditionally consumed alcohol more frequently and more heavily than women but since the 1990s this difference has become less prominent among young people. Over the 10-year period 1988–1998, the age of drinking onset decreased and heavier drinking increased among males aged 18–29 indicating that Mexican men experience their heaviest drinking at increasingly younger ages. Drinking among women and adolescent females has also increased significantly as have the proportions of females with abuse or dependence (Medina-Mora, 2007). A recent national household survey examining alcohol and drug use found fewer than 1% of the general population drank daily but over half (53.6%) of young adults aged 18–35 consumed 5+ drinks on a single occasion in the past year, and among 12–17 year olds 42.9% ever used alcohol with 31.8% of males and 28.1% of females drinking in the past year (Health Ministry, 2012). Although the frequency of drinking was 20% greater among adult men than adult women, this difference was only 6% between males and females aged 12–17 (Health Ministry, 2012) suggesting continued increase in use among female adolescents. Four cross-sectional surveys of entering first year university students in Mexico City conducted from 2005 to 2008 also show a pattern of heavy episodic drinking among youths with both consumption of large quantities in a single occasion and increasingly frequent use (Díaz-Martínez et al., 2008, 2012; Solís-Torres et al., 2012; Strunin et al., 2013a). In 2005 75% of male and 66% of female students reported past year drinking (Díaz-Martínez et al., 2008), in 2007 26.9% drank 4+ drinks on a single occasion (Solís-Torres et al., 2012) and in 2008 a majority (86.3%) were ever drinkers with more males (35.2%) than females (23.7%) drinking 2+ times per month and more males (31.1%) than females (20.4%) reporting hazardous and harmful (Alcohol Use Disorders Identification Test, AUDIT, score of 6+) levels of drinking (Strunin et al., 2013a). All these studies of alcohol use among young people from different socioeconomic backgrounds in Mexico suggest changes in traditional gender patterns of alcohol use. Identifying factors that contribute to gender differences can inform prevention and intervention efforts and, potentially, explain more universal risk and protective factors contributing to gender differences among Mexican American young people.

The present study is from a project investigating patterns of alcohol use including risk and protective factors among students entering first year university in Mexico City. The project used a mixed method approach in two phases. In Phase 1 ethnographic interviews exploring the influence of the Mexican drinking culture were conducted with students identified from an ongoing general health survey conducted prior to the start of the academic year (Strunin et al., 2013b). In Phase 2, an alcohol survey supplement to the general health survey was administered to incoming first year students to assess prevalence and correlates of alcohol use. This paper focuses on data from Phase 2. The purpose of this study is to: (a) estimate the prevalence of alcohol use and alcohol-related consequences by examining quantity, frequency, frequency of 5+ drinks and alcohol-related consequences, (b) use latent profile analysis (LPA) to identify ‘drinking profiles’ based on drinking behavior and alcohol-related consequences, and then to examine associations between socio-demographic characteristics and these drinking profiles, and (c) investigate the associations between the drinking profiles and violent victimization among a population of Mexican youths aged 17–20. Alcohol is the most widely used substance in Mexico and emergency room data show a strong association between episodic and frequently heavy patterns of drinking and violence related injury (Borges et al., 2005; Cherpitel et al., 2012). Violent crime rates in Mexico are among the highest in Latin America (ICESI, 2011). In a recent national survey of the general Mexican population, 55.3% of males and 44.7% of females aged 18–19 years reported violent victimization including being injured, robbed and sexual assault (ICESI, 2011). Studies in Mexico also indicate males and females experience different forms of assault. Males are more likely to be threatened with a weapon and physically assaulted, and females more likely to be sexually assaulted (Norris et al., 2003; ICESI, 2011). Males are also more likely to ever experience violence, be a victim of recurrent violence, or be a victim of violence during adolescence (Baker et al., 2005). We hypothesized that among drinking groups based on quantity and frequency of drinking and alcohol-related consequences: (a) groups with heavier drinking profiles are more likely to experience violent victimization, (b) males with heavier drinking profiles are more likely to experience physical assault and (c) females with heavier drinking profiles are more likely to experience sexual assault. This is the first study to examine drinking profiles among Mexican youths and their associations with violent victimization. Past studies of alcohol use among Mexican young people use single measures to assess alcohol use but other research suggests that individuals' multidimensional patterns of use can be identified using multivariate person-centered methods that study associations among characteristics of alcohol use (Auerbach and Collins, 2006; Reboussin et al., 2006; Cleveland et al., 2012; Varvil-Weld et al., 2013). LPA is one such person-centered method used to identify underlying subgroups from a set of observed variables (Varvil-Weld et al., 2013).

METHODS

Procedure

The study design is a cross-sectional survey of entering first year students at a large public university in Mexico City conducted during registration prior to the beginning of the school year. During the registration period the university Medical Services routinely administers a general health survey to all entering students. In 2012, an alcohol survey supplement to the general health survey was administered to collect more detailed information about alcohol use. The alcohol survey supplement questions were developed from the Phase 1 ethnographic interviews. The study was approved by the university IRB for the PI in the USA and the IRB in Mexico City.

Sample

In 2012, 29,677 (80.0%) of 37,077 students enrolled in nine campuses of the university in the Mexico City metropolitan area completed the surveys. Of those who completed the surveys 13% had missing data on age and 3.5% had missing or inconsistent data on drinking status.

Measures

The alcohol supplement survey included questions about frequency and quantity of alcohol use and alcohol-related consequences in the past year. The general health survey queried frequency of drinking 5+ in a single occasion, violent victimization and socio-demographics.

Alcohol consumption

Questions assessed alcohol consumption using frequency of drinking ‘once a month or less’, ‘two to four times a month’, ‘two to three times a week’, ‘four or more times a week’, ‘every day’, ‘I used to drink but I don't drink anymore’, ‘I never drink’; quantity on a typical drinking day in the past month: 0–29 drinks; and frequency of drinking 5+ drinks in a single occasion ‘never in the past year’, ‘at least once in the past year’, ‘once in the past month’, ‘two to three times in the past month’, ‘one or more times in the past week’. Students were shown a chart with picture equivalents for a single drink of different types of alcoholic beverages to assist with calculation of quantity of alcohol consumed; for example a 330 ml bottle or can of beer equaled one drink. Students were categorized as never drinkers if they never consumed alcoholic drinks and ever drinkers if they reported past or current drinking. Current drinkers drank once a month or less, 2–4 times a month, 2+ times a week, every day.

Alcohol-related consequences

Alcohol-related consequences were assessed asking which of the following problems happened in the past 12 months: ‘you got into trouble with your parents because you drank’, ‘you got into a sexual situation after drinking that you later regretted’, ‘you had problems with friends because of the way you drank’, ‘you got into a physical fight with a friend or stranger because you had drunk’.

Violent victimization

Outcome measures included ever being a victim of the following situations: ‘threatened with a weapon (knife, gun, sticks, ice pick, etc.)’, ‘hit, insulted, threatened or humiliated by someone in your family, a friend, or partner’, ‘injured in a fight or assault’, ‘forced to have sexual contact or sexual relations’.

Socio-demographic measures

Students provided information on age; sex; parental education of ‘secondary school or less’, ‘high school or technical degree’, ‘undergraduate degree or more’, and living situation with ‘mother’, ‘father’, ‘siblings or step siblings’, ‘other family’, ‘non family’, ‘alone’, ‘with a partner’.

Analysis

Sample characteristics and drinking behaviors were stratified by sex. In Mexico the legal drinking age is 18 and we assessed differences between underage 17 year olds and of age 18–20 year olds. Drinking behaviors were categorized and described through percentages and means. Chi-square tests and Wilcoxon rank sum tests were used to compare males and females on socio-demographic characteristics and drinking behaviors.

LPA was used to identify subgroups of individuals with similar patterns of drinking behaviors and consequences among the sample using seven variables: categorical variables for frequency of drinking and frequency of heavy drinking, a measurement variable for number of drinks consumed on a typical drinking day, and four indicator variables for alcohol-related consequences. LPA was conducted using Mplus 7.11 (Muthén and Muthén, 1998). Successive LPA models were fit to the data, starting with a model including only one profile and increasing up to six profiles. To determine the optimal number of profiles the fit of each model was examined through the Bayesian information criteria (BIC) (Schwartz, 1978), the sample-size adjusted Bayesian information criteria (SSABIC) (Sclove, 1987) and the Lo-Mendell-Rubin adjusted likelihood ratio test (LMR) (Lo et al., 2001). For both the BIC and SSABIC lower values indicate better fit; for the LMR a significant result indicates that the model is a better fit than the model with one fewer profile. Entropy values were also used to determine the model with the optimal LPA solution. Entropy values range from 0 to 1; values closer to 1 indicate better separation of the profiles (Ramaswamy et al., 1993). In addition to these measures of fit and quality, interpretability of the resulting latent profile structure was also considered in selecting the optimal number of profiles.

Multinomial regression examined socio-demographic characteristics as predictors of drinking profile. This analysis was conducted using the R3STEP method in Mplus which adjusts for the measurement error stemming from assigning individuals to the most likely latent profile (Asparouhov and Muthén, 2013).

The most likely latent profile was saved for further analysis of the association between drinking profile (as a predictor) and violent victimization outcomes. Four separate logistic regression models (one for each violent victimization outcome) were fit with drinking profile as the main independent variable. A concern of this approach is that it fails to account for misclassification (Lanza and Rhoades, 2013). To address this issue we conducted secondary analyses using multiple imputation to generate imputed profile membership based on each subject's probabilities of profile membership. These analyses were conducted via logistic regression and PROC MIANALYZE in SAS 9.3 (SAS Institute, Inc., Cary, NC, USA) and associations described by odds ratios and 95% confidence intervals.

The surveys were administered during orientation at 21 schools and departments at the nine university campuses. All analyses accounted for clustering by school or department. In MPlus this adjustment was accomplished through the Mixture Complex feature. In SAS, generalized estimating equations (GEE) logistic regression was used with an independence working correlation and empirical standard errors reported.

RESULTS

Socio-demographics

Of the sample 22,224 (74.9%) were aged 17–20 of whom 14,663 (66.0%) reported current drinking, 1727 (7.8%) reported being a former drinker and 5834 (26.3%) reported never drinking alcohol. Almost 60% (57.6%) of the sample were 18 years old and over half (55.6%) were female. More students (37.6%) had a father than mother (27.1%) with an undergraduate or higher degree. Over 95% of both males and females lived with one or both parents or other family members and twice as many males (1.6%) as females (0.6%) lived alone (Table 1).

Table 1.

Socio-demographics, alcohol use and alcohol-related consequences

Overall (N = 22,224)
 Male (N = 9860)
 Female (N = 12,364)
N % N % N % χ2 (df)
Socio-demographics
 Agea 178.70 (3)
  17 2698 (12.1) 1080 (11.0) 1618 (13.1)
  18 12,811 (57.6) 5389 (54.7) 7422 (60.0)
  19 4746 (21.4) 2298 (23.3) 2448 (19.8)
  20 1969 (8.9) 1093 (11.1) 876 (7.1)
 Living situationa 104.47 (3)
  One or both parent(s) 19,606 (92.1) 8451 (90.1) 11,155 (93.6)
  Other family (no parents) 1088 (5.1) 571 (6.1) 517 (4.3)
  Non-family/partner 384 (1.8) 213 (2.3) 171 (1.4)
  Alone 217 (1.0) 145 (1.6) 72 (0.6)
 Maternal educationa 47.32 (2)
  Secondary school or less 6795 (32.9) 2912 (32.1) 3883 (33.5)
  High school/technical degree 8267 (40.0) 3483 (38.4) 4784 (41.3)
  Undergraduate degree or more 5608 (27.1) 2678 (29.5) 2930 (25.3)
 Paternal educationa 54.39 (2)
  Secondary school or less 5886 (29.6) 2440 (27.9) 3446 (30.9)
  High school/technical degree 6545 (32.9) 2781 (31.8) 3764 (33.8)
  Undergraduate degree or more 7475 (37.6) 3535 (40.4) 3940 (35.3)
Alcohol use
 Frequency of usea
  Never drinkers 5834 (26.3) 2456 (24.9) 3378 (27.3) 33.8 (2)
  Former drinkers 1727 (7.8) 699 (7.1) 1028 (8.3)
  Current drinkers 14,663 (66.0) 6705 (68.0) 7958 (64.4)
 Frequency of any drinkinga 335.62 (4)
  I never drink 5834 (26.3) 2456 (24.9) 3378 (27.3)
  I used to drink but do not drink anymore 1727 (7.8) 699 (7.1) 1028 (8.3)
  Once a month or less 8922 (40.2) 3599 (36.5) 5323 (43.1)
  2–4 times a month 5201 (23.4) 2750 (27.9) 2451 (19.8)
  2+ times a week 540 (2.4) 356 (3.6) 187 (1.5)
Number of drinks on a typical drinking day in past montha
 Did not drink in the past monthc 9928 (44.7) 4044 (41.0) 5884 (47.6) 664.85 (7)
 1 2222 (10.0) 816 (8.3) 1406 (11.4)
 2 2588 (11.7) 1006 (10.2) 1582 (12.8)
 3 2057 (9.26) 881 (8.9) 1176 (9.5)
 4 1542 (6.9) 751 (7.6) 791 (6.4)
 5 1272 (5.7) 653 (6.6) 619 (5.0)
 6–10 1995 (9.0) 1253 (12.7) 742 (6.0)
 11+ 620 (2.8) 456 (4.6) 164 (1.3)
 Mean (SD)d,e 2.3 (3.4) 2.9 (4.0) 1.8 (2.7)
 Frequency of 5+ drinks in a single occasiona 517.67 (4)
  Never in past year 10,806 (48.8) 4117 (41.8) 6689 (54.3)
  At least once in past year 6420 (29.0) 2929 (29.8) 3491 (28.3)
  Once in past month 2951 (13.3) 1564 (15.9) 1387 (11.3)
  2–3 times in past month 1711 (7.7) 1045 (10.6) 666 (5.4)
  1+ times in past week 278 (1.3) 187 (1.9) 91 (0.7)
Alcohol-related consequences
 In the past 12 months, which of the following consequences happened to you? (responded ‘yes’)
  You got into trouble with your parents because you drankb 3440 (15.5) 1609 (16.3) 1831 (14.8) 9.55 (1)
  You got into a sexual situation you later regretted because you had been drinkinga 559 (2.5) 332 (3.4) 227 (1.8) 52.45 (1)
  You had problems with friends because of the way you drinka 577 (2.6) 344 (3.5) 233 (1.9) 55.83 (1)
  You got into a physical fight with a friend or stranger(s) because you had drunka 381 (1.7) 322 (3.3) 59 (0.5) 253.15 (1)
Open in a new tab

aDifferences between males and females significant at P < 0.0001.

bDifferences between males and females significant at P < 0.01

cStudents not drinking in past month were coded as 0.

dW = 117,966,177.5, Z = 18.55, P < 0.0001.

eMeans presented include students not drinking in past month coded as 0; among students who drank in the past month the mean number of drinks was 4.2 (SE 3.6); among males 5.0 (SE 4.1) and among females 3.5 (SE 2.9), W = 40148491.5, Z = 22.60, Differences between males and females significant at P < 0.0001.

Alcohol use and alcohol-related consequences

Of the sample 66.0% were current drinkers and 26.3% were never drinkers. Significantly more males than females were current drinkers (68.0 vs. 64.4%) and significantly more females than males were never drinkers (27.3 vs. 24.9%) (Table 1). An analysis of age and drinking status (ever and current) showed a steady increase in drinking with increase in age with 68% of 17 year olds, 72% of 18 year olds, 79% of 19 year olds and 81% of 20 year olds reporting being ever drinkers. There were no gender differences by age.

Males were significantly more likely than females to drink both frequently and heavily. Over twice as many males as females drank 2+ times per week and more males than females drank 5+ drinks in a single occasion at least once in the past year. Males were also significantly more likely than females to report problems with friends, a sexual situation they later regretted or having a physical fight with a friend or stranger because they drank. Both males and females reported trouble with parents because of drinking more than any other alcohol-related consequence (Table 1).

Latent drinking profiles

LPA identified five distinct profiles of alcohol use and alcohol-related consequences based on frequency of drinking, quantity on a typical drinking day, frequency of drinking 5+ drinks and alcohol-related consequences reported in the past 12 months. Our choice of the five profile solution was based on a significant improvement in fit of five vs. four profiles and better interpretability for the five vs. six profile solution (Table 2). Estimated probabilities of profile membership are estimated for the five profiles which we label Non/Infrequent-No Consequences, Occasional-Few Consequences, Regular-Some Consequences, Heavy-Many Consequences and Excessive-Many Consequences drinkers (Table 3). This approach may lead to different findings compared with studies that define drinking groups through absolute cutoffs on specific drinking variables because it identifies subgroups of students with similar profiles across a set of variables. For example, while all of those classified as Excessive-Many Consequences drinkers reported drinking 5+ in the past year, 23% reported drinking 5+ only once in the past month, and 10% only once in the past year. However, all of these students reported having at least 14 drinks on a typical drinking day, and 52% reported at least one alcohol-related consequence. Similarly, 55% of Regular-Some Consequences drinkers reported drinking 5+ at least once in the past month (compared with 85% of Heavy and 89% of Excessive-Many Consequences); but all these students reported seven or fewer drinks on a typical drinking day and low occurrence of alcohol-related consequences.

Table 2.

Fit indices for the latent profile analysis

Profiles Free parameters AICa BICb SSABICc LMR-Ad P-value Entropy
2 28 241329.161 241553.411 241464.428 24132.830 0.0008 0.842
3 42 227721.048 228057.423 227923.949 13539.488 0.0117 0.873
4 56 218688.328 219136.828 218958.862 8996.516 0.0017 0.917
5 70 211385.572 211946.197 211723.739 7278.811 0.0023 0.895
6 84 208052.890 208725.640 208458.691 3336.868 0.1896 0.904
Open in a new tab

aAkaike information criterion.

bBayesian information criterion.

cSample-size adjusted Bayesian information criterion.

dLo-Mendell-Rubin adjusted likelihood ratio test.

Table 3.

Frequency and quantity of alcohol use and related consequences by latent profile

Profile 1 (Non/Infrequent-No Consequences)
 Profile 2 (Occasional-Few Consequences)
 Profile 3 (Regular-Some Consequences)
 Profile 4 (Heavy-Many Consequences)
 Profile 5 (Excessive-Many Consequences)
Total, N (%) 6676 (30.0) 8913 (40.1) 4771 (21.5) 1448 (6.5) 420 (1.9)
Frequency of any drinking
Estimated probabilities (SE)
 I never drink 84.6 (2.2) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
 I used to drink but don't drink
anymore		 9.4 (0.6) 11.9 (0.6) 0.8 (0.2) 1.2 (0.3) 1.7 (0.8)
 Once a month or less 6.0 (2.0) 74.3 (1.1) 36.8 (1.8) 21.0 (1.5) 13.6 (1.3)
 2–4 times a month 0 (0.0) 13.5 (1.3) 57.3 (1.4) 66.1 (1.3) 63.5 (2.7)
 2+ times a week 0 (0.0) 0.3 (0.1) 5.1 (0.6) 11.8 (1.3) 21.2 (2.2)
Number of drinks on a typical drinking day in past month
Estimated mean (SE)		 0.03 (0.01) 1.14 (0.06) 4.22 (0.08) 9.27 (0.08) 17.67 (0.15)
Frequency of 5+ drinks in a single occasion
Estimated probabilities (SE)
 Never in past year 96.9 (0.3) 46.6 (1.2) 4.1 (1.0) 0 (0.0) 0 (0.0)
 At least once in past year 2.6 (0.2) 46.5 (1.5) 41.1 (1.5) 14.9 (1.5) 10.7 (1.1)
 Once in past month 0.4 (0.1) 5.9 (0.4) 36.3 (1.4) 36.8 (1.3) 23.3 (2.3)
 2–3 times in past month 0.1 (0.1) 1.0 (0.1) 16.6 (0.9) 40.6 (2.0) 49.8 (3.1)
 1+ times in past week 0 (0.0) 0 (0.0) 1.9 (0.3) 7.7 (0.8) 16.2 (1.8)
In the past 12 months, which of the following consequences happened to you? (responded ‘yes’)
Estimated probabilities (SE)
 You got into trouble with your
parents because you drank		 0 (0.0) 15.8 (1.2) 28.4 (1.4) 36.5 (1.3) 39.7 (2.4)
 You got into a sexual situation you later regretted because you had been drinking 0 (0.0) 1.9 (0.2) 4.5 (0.4) 9.3 (0.7) 9.3 (2.0)
 You had problems with friends because of the way you drink 0 (0.0) 3.1 (0.4) 4.0 (0.2) 6.1 (0.4) 6.7 (1.2)
 You got into a physical fight with a friend or stranger(s) because you had drunk 0 (0.0) 1.2 (0.2) 2.7 (0.3) 6.8 (0.4) 12.4 (1.2)
Open in a new tab

The majority of Profile 1, Non/Infrequent-No Consequences drinkers, never drank and did not report any alcohol-related consequences.

The largest group of drinkers, 40.1% of the total sample, was Profile 2, Occasional-Few Consequences drinkers. This group had a low prevalence of frequency, quantity and heavy drinking and reported trouble with their parents because of drinking more than any other alcohol-related consequence.

Profile 3, Regular-Some Consequences drinkers, were characterized by a pattern of drinking 2–4 times a month, averaging 4.2 drinks on a typical drinking day and over 33% drank 5+ drinks once in the past month. Although almost 30% of Regular-Some Consequences drinkers reported trouble with parents because of drinking they had low incidence of other alcohol-related consequences.

Profile 4, Heavy-Many Consequences drinkers, included 6.5% of the total sample, drank 2–4 times a month and had heavy consumption. Heavy-Many Consequences drinkers averaged 9.3 drinks on a typical drinking day and almost half drank 5+ drinks in a single occasion 2+ times in the past month. Heavy-Many Consequences drinkers reported higher incidence of alcohol-related consequences.

Profile 5, Excessive-Many Consequences drinkers, comprised the smallest group of drinkers (1.9%) but had the highest prevalence of frequency, quantity and heavy drinking. Most Excessive-Many Consequences drinkers drank 2–4 times per month, two-thirds drank 5+ drinks in a single occasion 2+ times in the past month and they averaged 17.7 drinks on a typical drinking day. Although Excessive-Many Consequences drinkers were as likely as Heavy drinkers to report alcohol-related consequences, they had almost twice as many physical fights because of drinking.

Associations between socio-demographic characteristics and drinking profiles

A multinomial regression model was used to examine associations between socio-demographic variables (independent variables) and drinking profile (dependent variable). This analysis treated Occasional-Few Consequences drinkers as the reference group and controlled for the other variables in Table 4. Factors associated with higher odds of being a Heavy or Excessive-Many Consequences drinker included being male and older. Living alone was associated with increased odds of being a Non/Infrequent-No Consequences drinker, and higher maternal education was associated with lower odds of being a Non/Infrequent-No Consequences drinker (Table 4).

Table 4.

Associations between socio-demographic variables and drinking profiles

Non/Infrequent-No Consequencesa
 Regular-Some Consequencesa
 Heavy-Many Consequencesa
 Excessive-Many Consequencesa
ORb 95% CI ORb 95% CI ORb 95% CI ORb 95% CI
Sex
 Female 1.00 1.00 1.00 1.00
 Male 1.17 (1.09, 1.25) 1.59 (1.49, 1.70) 3.36 (2.95, 3.82) 4.62 (3.49, 6.12)
Age
 17 1.17 (1.03, 1.34) 0.86 (0.75, 0.99) 0.97 (0.77, 1.22) 0.78 (0.54, 1.12)
 18 1.00 1.00 1.00 1.00
 19 0.21 (0.19, 0.23) 1.27 (1.17, 1.38) 1.52 (1.23, 1.89) 1.50 (1.21, 1.86)
 20 0.15 (0.13, 0.17) 1.47 (1.28, 1.68) 1.80 (1.46, 2.23) 2.38 (1.76, 3.22)
Living situation
 One or both parent(s) 1.00 1.00 1.00 1.00
 Other family (not parents) 1.10 (0.95, 1.28) 1.13 (0.94, 1.35) 0.84 (0.63, 1.12) 1.47 (0.88, 2.46)
 Non-family/partner 1.11 (0.82, 1.49) 0.96 (0.76, 1.20) 0.65 (0.35, 1.20) 0.27 (0.08, 0.97)
 Alone 2.01 (1.50, 2.69) 1.37 (0.90, 2.09) 1.17 (0.74, 1.85) 1.92 (0.78, 4.69)
Maternal education
 Secondary school or less 1.00 1.00 1.00 1.00
 High school/technical degree 0.84 (0.77, 0.91) 1.01 (0.88, 1.16) 0.96 (0.79, 1.17) 0.72 (0.54, 1.96)
 Undergraduate degree or more 0.81 (0.74, 0.89) 0.99 (0.86, 1.14) 0.85 (0.69, 1.04) 0.61 (0.40, 0.92)
Paternal education
 Secondary school or less 1.00 1.00 1.00 1.00
 High school/technical degree 0.93 (0.84, 1.03) 1.72 (1.51, 1.95) 1.06 (0.87, 1.30) 1.29 (1.01, 1.66)
 Undergraduate degree or more 0.94 (0.85, 1.03) 1.12 (0.99, 1.27) 1.01 (0.79, 1.28) 1.26 (0.83, 1.92)
Open in a new tab

OR, odds ratio; CI, confidence interval.

aOccasional/Few Consequences drinkers used as reference.

bAdjusted for all variables included in the table.

Associations between drinking profiles and violent victimization

Logistic regression models examined associations between drinking profile (independent variable) and violent victimization variables (dependent variables). These analyses treated Occasional-Few Consequences drinkers as the reference group controlling for age, sex, parental education and living situation (Table 5). Excessive-Many Consequences drinkers had the highest odds and Non/Infrequent-No Consequences drinkers the lowest odds of reporting any violent victimization. Female Heavy and Excessive-Many Consequences drinkers had higher odds than males of being hit, insulted, threatened or humiliated. Male and female Excessive-Many Consequences drinkers had three times the odds, and Heavy-Many Consequences drinkers twice the odds, of being injured in a fight or assault. Male and female Excessive-Many Consequences drinkers had over three times the odds, and females the highest odds, of being forced to have sexual contact or sexual relations.

Table 5.

Odds of experiencing violent victimization by latent profile membership

Profile Threatened with a weapon (yes vs. no)
 Hit, insulted, threatened or humiliated (yes vs. no)
 Injured in a fight/assault (yes vs. no)
 Forced to have sexual contact/sexual relations (yes vs. no)
OR (95% CI) χ2 (df) OR (95% CI) χ2 (df) OR (95% CI) χ2 (df) OR (95% CI) χ2 (df)
Overalla
 Non/Infrequent-No Consequences 0.80 (0.74, 0.87) 113.41 (4) 0.90 (0.81, 0.99) 135.53 (4) 0.72 (0.64, 0.81) 405.98 (4) 0.72 (0.59, 0.88) 72.48 (4)
 Occasional-Few Consequences 1.00 1.00 1.00 1.00
 Regular-Some Consequences 1.21 (1.09, 1.36) 1.12 (1.02, 1.23) 1.58 (1.44, 1.75) 1.06 (0.83, 1.37)
 Heavy-Many Consequences 1.50 (1.32, 1.71) 1.32 (1.16, 1.50) 2.18 (1.89, 2.52) 1.72 (1.15, 2.56)
 Excessive-Many Consequences 2.01 (1.49, 2.71) 1.80 (1.47, 2.22) 3.53 (2.95, 4.23) 3.30 (1.85, 5.91)
Maleb
 Non/Infrequent-No Consequences 0.85 (0.76, 0.95) 68.84 (4) 1.02 (0.92, 1.14) 19.95 (4) 0.73 (0.63, 0.86) 267.21 (4) 0.70 (0.36, 1.36) 16.77 (4)
 Occasional-Few Consequences 1.00 1.00 1.00 1.00
 Regular-Some Consequences 1.36 (1.14, 1.63) 0.98 (0.83, 1.16) 1.62 (1.44, 1.81) 0.96 (0.54, 1.70)
 Heavy-Many Consequences 1.57 (1.37, 1.80) 1.19 (1.00, 1.42) 2.16 (1.83, 2.56) 1.57 (0.86, 2.89)
 Excessive-Many Consequences 2.13 (1.49, 3.05) 1.58 (1.23, 2.04) 3.63 (2.94, 4.49) 3.18 (1.24, 8.16)
Femaleb
 Non/Infrequent-No Consequences 0.75 (0.69, 0.81) 83.96 (4) 0.79 (0.68, 0.92) 122.77 (4) 0.69 (0.57, 0.83) 237.81 (4) 0.72 (0.57, 0.92) 41.53 (4)
 Occasional-Few Consequences 1.00 1.00 1.00 1.00
 Regular-Some Consequences 1.07 (0.99, 1.17) 1.28 (1.14, 1.43) 1.52 (1.31, 1.77) 1.09 (0.82, 1.45)
 Heavy-Many Consequences 1.45 (1.16, 1.80) 1.60 (1.31, 1.96) 2.32 (1.84, 2.93) 1.81 (1.11, 2.96)
 Excessive-Many Consequences 1.89 (1.20, 2.97) 2.64 (1.82, 3.83) 3.23 (2.23, 4.67) 3.37 (1.64, 6.93)
Open in a new tab

OR, odds ratio; CI, confidence interval.

aAdjusted for age, sex, mother's education, father's education, living situation.

bAdjusted for age, mother's education, father's education, living situation.

DISCUSSION

This is the first study to examine profiles among Mexican young people that predict membership in drinking subgroups experiencing alcohol-related consequences and associations with violent victimization.

The study found five distinct drinking profiles of which Occasional-Few Consequences drinkers comprised the largest profile and Excessive-Many Consequences drinkers the smallest profile. Drinking profile was associated with socio-demographic variables of age, parental education and living situation. Older students were more likely to be Heavy or Excessive-Many Consequences drinkers. Students whose parents had higher education were less likely to be Non/Infrequent-No Consequences drinkers and, although almost all students lived with their parents, those living alone were significantly more likely to be Non/Infrequent-No Consequences drinkers. In our Phase 1 qualitative study, the few students not living at home initiated or increased drinking after beginning university. However, the interviews were conducted 6–9 months after the start of the school year and the survey may be administered too early in the academic year to show any change in drinking due to living situation (Strunin et al., 2014). Other research at the same university found higher parental education associated with harmful and hazardous drinking but only among female students (Díaz-Martínez et al., 2008) which differs from our findings. Studies in the USA indicate differences in drinking behavior and living situation among white, Hispanic/Latino and other students. Students living with parents during the first year of college drank less than students living on or off campus (Fromme et al., 2008), and although there was an association between living away from parents and heavy drinking among white students but not Hispanic or other racial/ethnic groups (Paschall et al., 2005), Latino college students living away from parents had higher peak and weekly drinking (Varvil-Weld et al., 2014).

Parental influences on alcohol use among young people in Mexico including whether parental restrictions/supervision play an important role in students' drinking behaviors, and whether students in families with higher parental education have different communication about alcohol (Elder et al., 2000), different family relations (Wilkinson et al., 2011), or drink for different reasons (Raffaelli et al., 2007) are questions for future study.

Our finding of a consumption pattern of infrequent alcohol use but occasional high intake among Occasional-Few Consequences drinkers is similar to other findings in Mexico which indicate that infrequent use with occasionally high intake is the most common drinking pattern in Mexico (Medina-Mora et al., 2000; Medina-Mora, 2007; Cherpitel et al., 2012; Health Ministry, 2012; Benjet et al., 2014). However, the Heavy and Excessive-Many Consequences profile drinkers in our study are clearly deviating from this pattern. Considering their weekly and monthly consumption, almost half of Heavy and almost two-thirds of Excessive-Many Consequences drinkers consumed 5+ drinks in a single occasion 2+ times a month. Our findings from the Phase 1 qualitative study show similarly that heavy and excessive drinkers were breaking with traditional norms of drinking (Strunin et al., 2013b). Other research also indicates heavy drinkers breaking with a cultural tradition of moderate drinking (Strunin et al., 2010). Although males in our study were significantly more likely than females to be Heavy and Excessive-Many Consequences drinkers, comparable proportions of males and females drank 5+ drinks on a single occasion confirming substantial increases in alcohol use among Mexican female youths. In our study Heavy and Excessive-Many Consequences drinkers appear to be challenging or breaking with cultural norms and whether other risk factors differ among these groups need further study. Research shows that compared with males, females drink less often (Rahav et al., 2006; Bond et al., 2010), less heavily (Rahav et al., 2006), and are more likely to abstain or stop drinking (Wilsnack et al., 2009); however, male drinking patterns influence gender differences even when male and female drinking (Roberts, 2012) and drunkenness (Kuntsche et al., 2011) are highly correlated. Future research about male and female youths and traditional patterns of alcohol use would fill an important gap in the literature about drinking among young people in Mexico.

As hypothesized, groups with heavier drinking profiles were more likely to experience adverse consequences of violent victimization. Our logistic regression models show an increased risk of violent victimization among Heavy and Excessive-Many Consequences drinkers and there were gender differences. Compared with Occasional-Few Consequences drinkers, both male and female Heavy and Excessive-Many Consequences drinkers had the highest odds, and Non/Infrequent-No Consequences drinkers the lowest odds, of experiencing any victimization. However, Regular-Some Consequences, Heavy and Excessive-Many Consequences female drinkers had higher odds than males of being hit, insulted, threatened or humiliated, and Heavy and Excessive-Many Consequences female drinkers had higher odds than males of being forced to have sexual contact or sexual relations. Although our findings concerning sexual victimization should be interpreted with caution because of the small number of these events, the reporting may be conservative and should not be minimized. Researchers have argued that self-administered surveys are the best method for collecting information on sexual violence among young people (Krebs, 2014), but it is likely underreported by young people because of general underreporting of traumatic and socially undesirable events (Callahan et al., 2003). A recent study of sexual abuse in Mexico recommends interventions designed from a gender perspective. The authors propose that youths underreport sexual abuse in surveys because of stigma, shame and fear which are related to the Mexican social construction of sex and sexuality (Frías and Erviti, 2014).

In addition to frequency, amount of alcohol consumed and drinker characteristics, the influences of drinker expectations (Martens et al., 2006), and the drinking context and situation (Forsyth and Lennox, 2010) have been found to be important in the drinking-violence connection and should be considered in future studies. The contributions of cultural factors are also unknown and research is needed about changes in cultural gender norms about drinking in order to inform prevention efforts.

This investigation of drinking patterns and victimization among young people in the Mexican context can help clarify key factors associated with alcohol use among Mexican young people, and also, potentially, inform future work among Mexican American young people. The Hispanic population is the largest ethnic minority population in the USA, with 39.1% under the age of 21 (U.S. Census Bureau, 2011) and projected to comprise over 25% of the US population by 2050 (U.S. Census Bureau, 2005). In 2010, over 10% of the US population and 65.1% of Hispanics identified as Mexican (Ennis et al., 2011). There are often contradictory findings in alcohol studies of youths in the USA which suggest different patterns of drinking among racial and ethnic subgroups. Some indicate Hispanic youths drink less than white youths and more than Black youths (Johnston et al., 2013; Substance Abuse and Mental Health Services Administration, 2013) while others that Hispanic youths have similar rates to White youths (Swendsen et al., 2012). Importantly when the data is not aggregated across Hispanic subgroups findings show different patterns and trends among youths from different ethnic subgroups indicating socio-cultural differences (Delva et al., 2005; Wahl and Eitle, 2010). The physical and mental health of the growing Mexican American population is of great importance to both the USA and Mexico (Cesarman-Maus, 2003; Borges et al., 2007) and researchers have recommended further investigation of cultural variables to inform prevention and intervention for different ethnic groups of Latino youths (Alegria et al., 2006; Zamboanga et al., 2006; Strunin et al., 2007).

There are a number of limitations to the study. The results are from a large, comprehensive sample of young people completing a survey as they transition into their first year of university with very high participation rates and analysis utilizes person centered latent variables modeling, but the alcohol use of these students may differ from students entering private universities or from young people not attending university. However, findings from a study of private and public university students (Mora-Ríos and Natera, 2001) and of non-university Mexican youths in the same age group as participants in this study (Medina-Mora et al., 2000; Latimer et al., 2004; Marsiglia et al., 2009) report similar prevalence of ever drinkers suggesting that our findings are similar to Mexican youths of the same age group. For the analysis of drinking profiles students were classified based on their most likely drinking profile and concern has been raised about potential misclassification with this statistical approach (Lanza and Rhoades, 2013). In this study the LPA had entropy of 0.90, and 94% of students had a 70% or higher probability of profile membership. In addition, to account for potential misclassification bias, we imputed five replicates of the data set with profile membership based on profile probabilities. Multiple imputation techniques averaged results across imputations. Findings of the multiple imputation analysis agreed closely with the analysis based on the most likely profile, with all statements of significance agreeing between the two approaches. Another limitation of the study are the narrow violent victimization measures and the lumping together of multiple types of victimization. We did not have the ability to examine specific types of physical assault or verbal aggression. However, all these issues had a very low rate of reporting in our population.

Identifying factors that contribute to cultural and gender differences can inform alcohol prevention and intervention efforts in this population and, potentially, elucidate more universal risk and protective factors contributing to differences among Mexican American young people. These factors can also help in the broader goal of developing the most effective programs and policies to reduce alcohol-related health and social problems in Mexico, the USA, and other countries.

Funding

This work was supported by the National Institute of Alcohol Abuse and Alcoholism of the National Institutes of Health [R01 AA018149]. The National Autonomous University of Mexico provided financial support for the conduct of the alcohol survey.

Conflict of interest statement

None declared.

Acknowledgements

The authors thank Carlos Camilo García Bernabé for assistance with the study. They thank Dr José Narro Robles, UNAM rector, for his support in the realization of this project.

REFERENCES

  1. Alegria M, Canino G, Stinson FS, et al. Nativity and DSM-IV psychiatric disorders among Puerto Ricans, Cuban Americans, and non-Latino Whites in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry. 2006;67:56–65. doi: 10.4088/jcp.v67n0109. [DOI] [PubMed] [Google Scholar]
  2. Asparouhov T, Muthén B. Auxiliary variables in mixture modeling: 3-step approaches using Mplus. 2013. Retrieved from http://www.statmodel.com/download/3stepOct28.pdf .
  3. Auerbach KJ, Collins LM. A multidimensional developmental model of alcohol use during emerging adulthood. J Stud Alcohol Drugs. 2006;67:917–25. doi: 10.15288/jsa.2006.67.917. [DOI] [PubMed] [Google Scholar]
  4. Baker CK, Norris FH, Diaz D, et al. Violence and PTSD in Mexico. Soc Psychiatry Psychiatr Epidemiol. 2005;40:519–28. doi: 10.1007/s00127-005-0921-2. [DOI] [PubMed] [Google Scholar]
  5. Benjet C, Borges G, Méndez E, et al. Adolescent alcohol use and alcohol use disorders in Mexico City. Drug Alcohol Depend. 2014;136:43–50. doi: 10.1016/j.drugalcdep.2013.12.006. [DOI] [PubMed] [Google Scholar]
  6. Bond JC, Roberts S, Greenfield TK, et al. Gender differences in public and private drinking contexts: a multi-level GENACIS analysis. Int J Environ Res Public Health. 2010;7:2136–60. doi: 10.3390/ijerph7052136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Borges G, Mondragon L, Medina-Mora ME, et al. A case-control study of alcohol and substance use disorders as risk factors for non-fatal injury. Alcohol Alcohol. 2005;40:257–62. doi: 10.1093/alcalc/agh160. [DOI] [PubMed] [Google Scholar]
  8. Borges G, Medina-Mora ME, Breslau J, et al. The effect of migration to the United States on substance use disorders among returned Mexican migrants and families of migrants. Am J Public Health. 2007;97:1847–51. doi: 10.2105/AJPH.2006.097915. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Callahan MR, Tolman RM, Saunders DG. Adolescent dating violence victimization and psychological well-being. J Adolesc Res. 2003;18:664–81. [Google Scholar]
  10. Cesarman-Maus G. The consular program for Mexican communities abroad: a source of outreach for health workers. J Transcult Nurs. 2003;14:272–5. doi: 10.1177/1043659603014003014. [DOI] [PubMed] [Google Scholar]
  11. Cherpitel CJ, Ye Y, Bond J, et al. Multi-level analysis of alcohol-related injury and drinking pattern: emergency department data from 19 countries. Addiction. 2012;107:1263–72. doi: 10.1111/j.1360-0443.2012.03793.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cleveland MJ, Mallett KA, White HR, et al. Patterns of alcohol use and related consequences in non-college-attending emerging adults. J Stud Alcohol Drugs. 2012;74:84–93. doi: 10.15288/jsad.2013.74.84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Connor J, Psutka R, Cousins K, et al. Risky drinking, risky sex: a national study of New Zealand university students. Alcohol Clin Exp Res. 2013;37:1971–8. doi: 10.1111/acer.12175. [DOI] [PubMed] [Google Scholar]
  14. Delva J, Wallace JM, O'Malley PM, et al. The epidemiology of alcohol, marijuana, and cocaine use among Mexican American, Puerto Rican, Cuban American, and other Latin American eighth-grade students in the United States: 1991–2002. Am J Public Health. 2005;95:696–702. doi: 10.2105/AJPH.2003.037051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Díaz-Martínez A, Díaz-Martínez LR, Hernández-Ávila CA, et al. Prevalencia del consumo riesgoso y dañino de alcohol y factores de riesgo en estudiantes universitarios de primer ingreso. Salud Ment. 2008;31:271–82. [Google Scholar]
  16. Díaz-Martínez LR, Díaz-Martínez A, Hernández-Ávila CA. La identificación del consumo de alcohol en los estudiantes de educación media-superior y superior. In: Díaz-Anzaldúa L, editor. Desarrollo de Nuevos Modelos Para La Prevención Y El Tratamiento de Conductas Adictivas. Mexico: Universidad Nacional Autónomas de México y Miguel Angerl Porrúa; 2012. pp. 29–38. [Google Scholar]
  17. Elder JP, Campbell NR, Litrownik AJ, et al. Predictors of cigarette and alcohol susceptibility and use among Hispanic migrant adolescents. Prev Med. 2000;31:115–23. doi: 10.1006/pmed.2000.0693. [DOI] [PubMed] [Google Scholar]
  18. Ennis SR, Rios-Vargas M, Albert NG. U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau; 2011. The Hispanic Population: 2010. [Google Scholar]
  19. Forsyth AJ, Lennox JC. Gender differences in the choreography of alcohol-related violence: an observational study of aggression within licensed premises. J Subst Use. 2010;15:75–88. [Google Scholar]
  20. Frías SM, Erviti J. Gendered experiences of sexual abuse of teenagers and children in Mexico. Child Abuse Negl. 2014;38:776–87. doi: 10.1016/j.chiabu.2013.12.001. [DOI] [PubMed] [Google Scholar]
  21. Fromme K, Corbin WR, Kruse MI. Behavioral risks during the transition from high school to college. Dev Psychol. 2008;44:1497–504. doi: 10.1037/a0012614. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Health Ministry. Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz; Instituto Nacional de Salud Pública; Secretaría de Salud; 2012. Encuesta Nacional de Adicciones 2011: Reporte de Alcohol. México, DF, México Retrieved from www.inprf.gob.mx . [Google Scholar]
  23. Hingson RW, Zha W. Age of drinking onset, alcohol use disorders, frequent heavy drinking, and unintentionally injuring oneself and others after drinking. Pediatrics. 2009;123:1477–84. doi: 10.1542/peds.2008-2176. [DOI] [PubMed] [Google Scholar]
  24. Hingson RW, Zha W, Weitzman ER. Magnitude of and trends in alcohol-related mortality and morbidity among U.S. college students ages 18–24, 1998–2005. J Stud Alcohol Drugs. 2009;16:12–20. doi: 10.15288/jsads.2009.s16.12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. ICESI. Encuesta Nacional sobre Inseguridad 2010. 2011. Instituto Ciudadano de Estudios sobre la Inseguridad, Mexico.
  26. Johnston LD, O'Malley PM, Bachman JG, et al. Monitoring the Future National Survey Results on Drug use, 1975–2012. Ann Arbor: Institute for Social Research, University of Michigan; 2013. Volume I: Secondary school students Retrieved Feb 12, 2014. [Google Scholar]
  27. Krebs C. Measuring sexual victimization: on what fronts is the jury still out and do we need it to come in? Trauma Violence Abuse. 2014;15:170–80. doi: 10.1177/1524838014521028. [DOI] [PubMed] [Google Scholar]
  28. Kuntsche E, Kuntsche S, Knibbe R, et al. Cultural and gender convergence in adolescent drunkenness: evidence from 23 European and North American countries. Arch Pediatr Adolesc Med. 2011;165:152–8. doi: 10.1001/archpediatrics.2010.191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lanza ST, Rhoades BL. Latent class analysis: an alternative perspective on subgroup analysis in prevention and treatment. Prev Sci. 2013;14:157–68. doi: 10.1007/s11121-011-0201-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Latimer W, Floyd LJ, Kariis T, et al. Peer and sibling substance use: predictors of substance use among adolescents in Mexico. Rev Panam Salud Publica. 2004;15:225–32. doi: 10.1590/s1020-49892004000400002. [DOI] [PubMed] [Google Scholar]
  31. Lo Y, Mendell NR, Rubin DB. Testing the number of components in a normal mixture. Biometrika. 2001;88:767–78. [Google Scholar]
  32. Marsiglia F, Kulis S, Rodriguez GM, et al. Culturally specific youth substance abuse resistance skills: applicability across the U.S.—Mexico border. Res Soc Work Pract. 2009;19:152–64. doi: 10.1177/1049731507303886. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Martens MP, Page JC, Mowry ES, et al. Differences between actual and perceived student norms: an examination of alcohol use, drug use, and sexual behavior. J Am Coll Health. 2006;54:295–300. doi: 10.3200/JACH.54.5.295-300. [DOI] [PubMed] [Google Scholar]
  34. Medina-Mora ME. Mexicans and alcohol: patterns, problems and policies. Addiction. 2007;102:1041–5. doi: 10.1111/j.1360-0443.2007.01857.x. [DOI] [PubMed] [Google Scholar]
  35. Medina-Mora ME, Borges G, Villatoro J. The measurement of drinking patterns and consequences in Mexico. J Subst Abuse. 2000;12:183–96. doi: 10.1016/s0899-3289(00)00048-1. [DOI] [PubMed] [Google Scholar]
  36. Mora-Ríos J, Natera G. Expectancies, alcohol drinking and associated problems in university students in Mexico City. Salud Pública Mex. 2001;43:89–96. [PubMed] [Google Scholar]
  37. Muthén LK, Muthén BO. Mplus User's Guide. 7th edn. Los Angeles: Muthén and Muthén; 1998. [Google Scholar]
  38. National Institute of Alcohol Abuse and Alcoholism. U.S. Department of Health and Human Services; 2006. Alcohol across the lifespan, Five year strategic plan, FY 08-13. [Google Scholar]
  39. Norris FH, Murphy AD, Baker CK, et al. Epidemiology of trauma and posttraumatic stress disorder in Mexico. J Abnorm Psychol. 2003;112:646–56. doi: 10.1037/0021-843X.112.4.646. [DOI] [PubMed] [Google Scholar]
  40. Paschall MJ, Bersamin M, Flewelling RL. Racial/ethnic differences in the association between college attendance and heavy alcohol use: a national study. J Stud Alcohol Drugs. 2005;66:266–74. doi: 10.15288/jsa.2005.66.266. [DOI] [PubMed] [Google Scholar]
  41. Perkins HW. Surveying the damage: a review of research on consequences of alcohol misuse in college populations. J Stud Alcohol Drugs. 2002;14:91–100. doi: 10.15288/jsas.2002.s14.91. [DOI] [PubMed] [Google Scholar]
  42. Raffaelli M, Torres-Stone RA, Iturbide MI, et al. Acculturation, gender, and alcohol use among Mexican American college students. Addict Behav. 2007;32:2187–99. doi: 10.1016/j.addbeh.2007.02.014. [DOI] [PubMed] [Google Scholar]
  43. Rahav G, Wilsnack R, Bloomfield K, et al. The influence of societal level factors on men's and women's alcohol consumption and alcohol problems. Alcohol Alcohol. 2006;41:i47–55. doi: 10.1093/alcalc/agl075. [DOI] [PubMed] [Google Scholar]
  44. Ramaswamy V, DeSarbo WS, Reibstein DJ, et al. An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Market Sci. 1993;12:103–24. [Google Scholar]
  45. Reboussin BA, Song EY, Shrestha A, et al. A latent class analysis of underage problem drinking: evidence from a community sample of 16–20 year olds. Drug Alcohol Depend. 2006;83:199–209. doi: 10.1016/j.drugalcdep.2005.11.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Rehm J, Baliunas D, Borges G, et al. The relation between different dimensions of alcohol consumption and burden of disease: an overview. Addiction. 2010;105:817–43. doi: 10.1111/j.1360-0443.2010.02899.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Roberts S. Whether men or women are responsible for the size of gender gap in alcohol consumption depends on alcohol measure: a study across the United States. Contemp Drug Probl. 2012;39:195–212. doi: 10.1177/009145091203900202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Schwartz G. Estimating the dimension of a model. Ann Stat. 1978;6:461–4. [Google Scholar]
  49. Sclove SL. Application of model-selection criteria to some problems in multivariate analysis. Psychometrika. 1987;52:333–43. [Google Scholar]
  50. Solís-Torres C, Gorab-Ramírez A, Fernández-Varela H. Consumo de Alcohol, Marihuana y Cocaína en Estudiantes de la zona Metropolitana de la Ciudad de México que ingresaron a licenciatura en el año 2007. In: María-Reydl L, editor. Desarrollo de Nuevos Modelos Para La Prevención Y El Tratamiento de Conductas Adictivas. Mexico: Universidad Nacional Autónomas de México y Miguel Angerl Porrúa; 2012. pp. 203–14. [Google Scholar]
  51. Strunin L, Edwards EM, Godette DC, et al. Country of origin, age of drinking onset, and drinking patterns among Mexican American young adults. Drug Alcohol Depend. 2007;91:134–40. doi: 10.1016/j.drugalcdep.2007.05.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Strunin L, Lindeman K, Tempesta E, et al. Familial drinking in Italy: harmful or protective factors? Addict Res Theory. 2010;18:344–58. [Google Scholar]
  53. Strunin L, Díaz-Martínez A, Díaz-Martínez LR, et al. Parental monitoring and alcohol use among Mexican students. Addict Behav. 2013a;38:2601–6. doi: 10.1016/j.addbeh.2013.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Strunin L, Díaz-Martínez A, Díaz-Martínez LR, et al. Alcohol use among Mexican youths: is familismo protective for moderate drinking? J Child Fam Stud. 2013b:1–8. doi: 10.1007/s10826-013-9837-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Strunin L, Díaz-Martínez A, Díaz-Martínez LR, et al. Changes in alcohol use among first year university students in Mexico. Subst Use Misuse. 2014;50:106–13. doi: 10.3109/10826084.2014.960591. [DOI] [PubMed] [Google Scholar]
  56. Substance Abuse and Mental Health Services Administration. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2013. Results from the 2012 National Survey on Drug Use and Health: Summary of National Findings (No. NSDUH Series H-46, HHS Publication No. (SMA) 13–4795) [Google Scholar]
  57. Swendsen J, Burstein M, Case B, et al. Use and abuse of alcohol and illicit drugs in U.S. adolescents. Arch Gen Psychiatry. 2012;69:390–8. doi: 10.1001/archgenpsychiatry.2011.1503. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. U.S. Census Bureau. Annual estimates of population by sex, race, and Hispanic or Latino origin for the United States: April 1, 2000 to July 1, 2004. 2005. Retrieved from http://www.census.gov/popest/data/historical/2000s/vintage_2005/index.html .
  59. U.S. Census Bureau. 2011 American Community Survey. 2011. Retrieved July 26, 2013, from http://www.census.gov/acs/www .
  60. Varvil-Weld L, Mallett KA, Turrisi R, et al. Are certain college students prone to experiencing excessive alcohol-related consequences? Predicting membership in a high-risk subgroup using pre-college profiles. J Stud Alcohol Drugs. 2013;74:542–51. doi: 10.15288/jsad.2013.74.542. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Varvil-Weld L, Turrisi R, Hospital MM, et al. Maternal and peer influences on drinking among Latino college students. Addict Behav. 2014;39:246–52. doi: 10.1016/j.addbeh.2013.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Wahl AM, Eitle TM. Gender, acculturation and alcohol use among Latina/o adolescents: a multi-ethnic comparison. J Immigr Minor Health. 2010;12:153–65. doi: 10.1007/s10903-008-9179-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Wilkinson AV, Shete S, Spitz MR, et al. Sensation seeking, risk behaviors and alcohol consumption among Mexican origin youth. J Adolesc Health. 2011;48:65–72. doi: 10.1016/j.jadohealth.2010.05.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Wilsnack RW, Wilsnack SC, Kristjanson AF, et al. Gender and alcohol consumption: patterns from the multinational GENACIS project. Addiction. 2009;104:1487–500. doi: 10.1111/j.1360-0443.2009.02696.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Zamboanga BL, Raffaelli M, Horton NJ. Acculturation status and heavy alcohol use among Mexican American college students: investigating the moderating role of gender. Addict Behav. 2006;31:2188–98. doi: 10.1016/j.addbeh.2006.02.018. [DOI] [PubMed] [Google Scholar]

Articles from Alcohol and Alcoholism (Oxford, Oxfordshire) are provided here courtesy of Oxford University Press

RESOURCES