8: Mauritian Joint Child Health Project: A Multigenerational Family Study Emerging from a Prospective Birth Cohort Study: Initial Alcohol-related Outcomes in the Offspring Generation

In their ‘Key Findings on Families, Family Policy and the Sustainable Development Goals: Synthesis Report’, UNICEF (2018, p 5) recognized the family unit as the ‘natural and elementary social unit of all modern society’ and a key to understanding social progress and development that the UN’s Sustainable Development Goals (SDG) seek to address. The family unit, while appreciated, often is not prioritized in development efforts. The UN Secretary General acknowledged that the contribution of families continues to be largely overlooked, and that ‘policy focusing on improving the well-being of families is certain to benefit development’ (United Nations, 2010). At the global level, there is a need for more research on the family, with the recognition that family policy requires adaptation to the different contexts and countries in which it will be implemented.

This study seeks to contribute to this research literature on family and its role in health behaviour by focusing on alcohol involvement in two generations of the Joint Child Health Project (JCHP), a longitudinal birth cohort study on the East African island nation of Mauritius. This research relates to SDG 3 on improving health and well-being, including via prevention and treatment of substance use (SDG 3.5) and harmful use of alcohol (SDG 3.5.2). The work serves to exemplify how a prospective child health study can be utilized to examine risk relationships within the family unit to better understand each child’s risky health behaviour.

Introduction

In their ‘Key Findings on Families, Family Policy and the Sustainable Development Goals: Synthesis Report’, UNICEF (2018, p 5) recognized the family unit as the ‘natural and elementary social unit of all modern society’ and a key to understanding social progress and development that the UN’s Sustainable Development Goals (SDG) seek to address. The family unit, while appreciated, often is not prioritized in development efforts. The UN Secretary General acknowledged that the contribution of families continues to be largely overlooked, and that ‘policy focusing on improving the well-being of families is certain to benefit development’ (United Nations, 2010). At the global level, there is a need for more research on the family, with the recognition that family policy requires adaptation to the different contexts and countries in which it will be implemented.

This study seeks to contribute to this research literature on family and its role in health behaviour by focusing on alcohol involvement in two generations of the Joint Child Health Project (JCHP), a longitudinal birth cohort study on the East African island nation of Mauritius. This research relates to SDG 3 on improving health and well-being, including via prevention and treatment of substance use (SDG 3.5) and harmful use of alcohol (SDG 3.5.2). The work serves to exemplify how a prospective child health study can be utilized to examine risk relationships within the family unit to better understand each child’s risky health behaviour. The unique combination of the JCHP study features, including the multigenerational longitudinal design, cultural setting and inclusion of families that largely remain intact, increases the potential for this study to contribute to our understanding of development of alcohol involvement (and mental health more broadly) within families. The goals are to report initial findings on rates of alcohol use and heavy use in the JCHP offspring (aged 13–24), and to examine how maternal and paternal alcohol-specific factors are linked to offspring alcohol use and heavy use, which may be gender-specific.

To provide appropriate background and context for this study, first the literature on social development models, transmission of alcohol behaviours within families and gender-specific transmission within families is reviewed, noting that most of this research has been conducted in Western societies. An overview of the JCHP is then provided and some of the prospective findings from the original birth cohort are highlighted, ending with JCHP research focused on alcohol outcomes. This background is used to guide predictions for relationships among parental (mother and father) alcohol-specific risk and protective factors and offspring (daughters and sons) alcohol use.

Family and alcohol involvement

A first-degree family history of alcohol problems is a strong and well-established predictor of developing alcohol problems (Cotton, 1979; Merikangas, 1990; Sher, 1991). The underlying mechanisms for family transmission and how these mechanisms are modified by gender and culture, however, remain unclear. Alcohol involvement may be transmitted (1) directly via inherited genetic risk (such as alcohol use disorders, AUDs), (2) directly via alcohol-related environments (such as modelling), and (3) indirectly through environmental effects associated with parental alcohol use (for example, parental monitoring; see D’Onofrio et al, 2007). Behavioural genetics studies indicate that environmental factors are more strongly implicated in early drinking behaviour, whereas genetic factors are more strongly associated with the development of problems including AUDs (Agrawal and Lynskey, 2008; Fowler et al, 2007; Pagan et al, 2006; Prescott and Kendler, 1999). It is recognized that a family study like the JCHP cannot separate genetic and environmental causes of transmission, but it can model risk factors across generations, strength of transmission, and gender as a moderator of this transmission.

The current study is guided by the social development model, which combines key features of social control and social learning theory (see Catalano et al, 1996). This model proposes that children observe various patterns of behaviour and learn normative guidelines for appropriate behaviour from proximal socializing agents, including their families as well as broader groups to which they belong (for example, religious groups). Cialdini and colleagues’ (1990) norm-focus theory distinguishes between two types of norms, descriptive and injunctive norms. Descriptive norms are standard behaviour generally guided by what people actually do (Elek et al, 2006). In relation to alcohol, adolescent alcohol behaviours would be triggered by social processes such as modelling and imitation of parental alcohol consumption (see Sieving et al, 2000). Injunctive norms refer to what people ‘ought’ to do, as imposed by external factors such as parents or the larger society (Elek et al, 2006). Perceived injunctive norms related to alcohol-specific behaviours among adolescents involve the perception of how much parents approve or disapprove of the adolescent’s alcohol use.

Research consistently has found perceived parental descriptive alcohol norms are associated with adolescents’ alcohol use (for example, Mrug and McCay, 2013; Duncan et al, 2006; Elek et al, 2006), with children who are exposed to parental drinking being more likely to model parental drinking behaviours and to consider it a socially acceptable behaviour, even when parental drinking includes intoxication (Duncan et al, 2006; Rossow and Kuntsche, 2013; Ryan et al, 2010; Chassin et al, 1993, 2016). Perceived parental injunctive norms have also been associated with adolescent alcohol consumption. For example, perceived strict parental rules were associated with lower alcohol consumption in children (Van Den Eijnden et al, 2011). Yu (1998) found that perceived parental attitudes towards alcohol consumption had a greater impact on children deciding to start using alcohol, but once offspring started drinking then parental attitudes were less strongly related to child behaviour. However, in youth aged 11–17, Mrug and McCay (2013) found the relationship between parental disapproval of alcohol use and youth consumption was maintained throughout adolescence, with little decline with age. How child-perceived and parent-rated disapproval of child drinking, along with parental drinking behaviours, combine to relate to child behaviours warrants continued investigation.

Gender, family and alcohol involvement

Although there are clear gender differences in alcohol involvement, the basis for these differences is not clear. Societal norms for alcohol use often differ by gender, and across cultures rates of alcohol use and problems are consistently lower in women than men, regardless of total overall use (Wilsnack et al, 2009). Poor parental monitoring and inconsistent rules have been shown to be greater predictors of alcohol use for males than females (see Nargiso et al, 2013). For alcohol-specific parenting, however, Mrug and McCay (2013) found daughters perceived greater disapproval of alcohol use from parents than did sons. Additionally, Yu and Perrine (1997) found a gender-specific relationship between fathers’ and mothers’ alcohol use and drinking behaviour by children, with drinking more likely to occur in the same gender children as the drinking parent. In line with these findings, Burk and colleagues (2011) showed that greater parental alcohol consumption increased adolescents’ drinking behaviour for both daughters and sons, but with daughters showing stronger effects. There also is some genetic evidence for specificity of alcohol transmission within genders and for greater risk being transmitted from female- than from male-affected relatives (Prescott et al, 2001). McGue and colleagues (2001) tested associations of early drinking and found only early drinking in mothers, not fathers, was predictive of early use in both daughters and sons. Thus, it is possible that parental risk and protective factors differ across mothers and fathers for their daughters and sons in terms of both absolute levels and strengths of association. Examining familial relationships in a novel cultural setting will provide a unique test of these parent–child risk factors for youth drinking.

The Mauritian Joint Child Health Project (JCHP): a prospective birth cohort family study

Background

The JCHP is conducted on Mauritius, a small upper- to middle-income island nation located in the Indian Ocean. Following an invitation by the World Health Organization(WHO), the JCHP began in the late 1960s as a collaborative effort among American and European researchers Doctors Sarnoff Mednick, Fini Schulsinger and Peter Venables and the Mauritian Ministry of Health. In 1972, the first data were collected from 1,795 participants who comprised almost the entire population of three-year-olds born in a one-year period (based on immunization records) in two adjacent towns (see Venables, 1978, for details). The ethnic breakdown of the JCHP sample was representative of the island and included 69% Indian, 26% Creole, 2% Chinese and 4% other; 48% of the sample was female. Multiple biological, social and psychological measures have been collected on the birth cohort participants at various data collection phases in childhood and adulthood, including major waves at ages 3, 11, 17, 23, late thirties and mid-forties (see Raine et al, 2010). Data also have been obtained on offspring that matched the timeframes (3–5 years old or 8–13 years old) and assessment domains (behaviour, cognition, psychophysiology) obtained from the original cohort in childhood.

The initial goal of the JCHP was to understand the causes of schizophrenia, but over the years outcomes have been expanded to include additional aspects of mental health including psychopathy, psychosocial well-being and, most recently, substance use. The majority of JCHP publications have focused on malnutrition, temperament, cognitive ability (IQ), behaviour and psychophysiology as childhood risk factors. Here a brief review is given of JCHP findings showing that early childhood malnutrition, a modifiable risk factor, is related to cognitive ability and behavioural problems in childhood, which in turn are risk factors for schizotypy personality, antisocial behaviour and alcohol problems in adulthood. Multiple indicators of malnutrition were obtained on the JCHP birth cohort when they were three years old. A direct path was found between chronic malnutrition (stunting and anaemia) at age 3 and IQ at age 11, and an indirect path was found between acute malnutrition (wasting) to verbal IQ via behavioural inhibition (Venables and Raine, 2015). Clinical indicators of nutrition (protein, riboflavin and iron) deficiency at age 3 also predicted low verbal IQ at age 11 as well as externalizing behaviour (aggression, attention deficit and hyperactivity) at ages 8, 11 and 17 (Liu et al, 2004). The effects of malnutrition on IQ were graded, with even mild malnutrition showing some association with IQ, and were independent of a measure of psychosocial adversity. Low performance IQ at age 11 was associated with features of schizotypal personality by age 23, with the relationship between chronic malnutrition at age 3 and schizotypy at age 23 mediated by performance IQ at age 11 (Venables and Raine, 2012). Low verbal IQ at age 11 was also predictive of alcohol problems by adulthood (mid-thirties) after co-varying for psychosocial adversity and religion, with this relationship being stronger in females than males (Luczak et al, 2015). Finally, a select sample of 100 of the JCHP birth cohort who were assigned to an enriched pre-school showed reduced schizotypal personality and antisocial behaviour at age 17 compared with controls, with the greatest benefits in those who had signs of malnutrition at age 3 (Raine et al, 2003). These findings highlight how both direct and indirect roles of childhood risk factors, including those that are modifiable, on mental health outcomes in adulthood can be discerned through longitudinal studies.

In addition to shedding light on developmental trajectories for health outcomes, JCHP publications also have examined the nature of psychological constructs in this cultural context (for example, Reynolds et al, 2000; Venables, 1990; Yarnell et al, 2014), including alcohol constructs and their covariates (Luczak et al, 2001, 2014, 2017). Testing the consistency (that is, invariance) of alcohol problem constructs at age 23, consistency was found in how Creole and Hindu males viewed alcohol problems, but differences in Muslim males (Luczak et al, 2001). In adulthood (mid-thirties), we also found variation in lifetime alcohol use and AUDs based on religion and religious commitment that were consistent across gender, despite women in all religious groups having lower rates of alcohol use and AUDs (Luczak et al, 2014). Further, the typology of alcohol problems within male drinkers were examined and four latent classes were found, including a distinct hazardous drinking class that had unique demographic correlates and was thought to represent a cluster of problems more bound by cultural factors, as well as problem classes on a severity continuum from none to moderate to severe problems (Luczak et al, 2017). These studies highlight how examining subgroup and person-level factors in different cultural settings can improve our understanding of the commonality and uniqueness of alcohol problem outcomes and correlates across societies.

Current study

The original birth cohort have now been followed into their mid-forties and concurrent assessment of spouses and children has been added. Thus delineation of familial risk and protective factors for alcohol involvement in the next generation of the JCHP can begin. Several features of the JCHP are beneficial for examining early stages of drinking within the context of the family. First, the original birth cohort was obtained from two adjacent towns, such that many macro-level factors (for example, media, healthcare, primary schools, neighbourhood) have low variability, which affords the opportunity to study young adult behaviour more at the levels of individual- and familial-level factors. Second, the JCHP biological families remain largely intact, with most biological mothers and fathers raising their offspring over the duration of childhood. This makes is possible to examine maternal and paternal direct influences on family environment, in addition to family history, for most of the offspring generation. Third, family remains an important aspect of social control and monitoring into early adulthood in Mauritius, with most offspring living with their parents until they are married (regardless of whether they attend university or enter the work force after secondary school), and then often still living with either their or their spouse’s family once married. Finally, national-level surveys show drinking in Mauritian females is on the rise (CDC, 2007; CDC et al, 2013; Ministry of Health and Quality of Life, 2016), which means that examining gender differences in risk factors for Mauritian youth drinking is relevant and timely.

Study hypotheses

The study seeks to extend current knowledge by testing aspects of the social development model in a non-Western setting. It hypothesizes that alcohol consumption in offspring will be predicted by (1) perceived parental descriptive norms (modelling), (2) perceived parental injunctive norms (perceived disapproval), (3) parental attitudes (parent-rated disapproval), and (4) lifetime parental alcohol involvement (family history, regardless of offspring awareness). As in some genetically informative studies, it is possible that (a) mother–daughter and father–son relationships will be strongest, (b) parental injunctive norms will be stronger predictors in sons, and (c) parent alcohol involvement will be stronger predictors for daughters, particularly for binge drinking.

Method

Participants

The study utilizes data collected when the JCHP birth cohort members were in their mid-forties (M = 43.7 years, range 41–47, SD = 1.37). All available original cohort members (n = 1,161, representing 63% of the 1,795 individuals in the original birth cohort in 1972; 48% female), their current or former spouses/co-parents (n = 876) and children (n = 1,911) were assessed in person on demographic variables and personal and familial alcohol use, norms and problems as part of a larger battery. In the original cohort, this included 72% who were in their first marriage, 8% who were separated or divorced, 2% widowed, 9% remarried or living as married and 9% who were never married (single).

The analytic sample included the 1,147 biological offspring of the original JCHP birth cohort who were aged 13–24 at the time of interview. Sample characteristics are presented in Table 8.1 are stratified by offspring age group and gender. Of these children, 986 (86%) were from intact parenting units where both biological parents were still living together in the same household. Based on their relationship to these offspring, fathers reported on 958 (84%) and mothers reported on 1,083 (94%) of these offspring, including 910 (79%) offspring where both mother and father reported on the child (termed ‘Intact’ families).

Procedure

All interviews and questionnaires were translated by bilingual JCHP staff into Kreol (the common spoken language of Mauritius), with back translation to provide evidence of semantic and cultural equivalence. Trained research staff conducted structured interviews with each family member separately in private rooms. This research was approved by the University of Southern California Institutional Review Board and received ethical clearance from the Mauritian Ministry of Health and Quality of Life (MOHQL). Written informed consent/assent was obtained for all participants.

Variables

Demographics

Gender, age and religion

All offspring were classified as either male or female, which was termed Gender. Four age groups (13–15, 16–17, 18–20, 21–24 years) were created to disaggregate offspring into age ranges expected to have different prevalence of drinking, with the legal age of drinking being 18 years. Religion was coded into Hindu, Tamil, Muslim, Catholic and other/none, with Tamil kept separate from Hindu due prior findings in the original cohort participants of different associations with alcohol use (Luczak et al, 2014).

Parental predictors

Child-perceived parental injunctive norms

Offspring rated their perception of each parent’s approval or disapproval of drinking with (a) family and (b) friends on a five-point scale from ‘strongly disapprove’ to ‘strongly approve’. Each variable was dichotomized into 1 = strongly disapprove, 0 = do not strongly disapprove, with 0 including all response choices other than ‘strongly disapprove’.

Child-perceived parental descriptive norms

Using a family tree (Mann et al, 1985), offspring rated each parent as a lifetime ‘non-drinker’, ‘social drinker’, ‘possible problem drinker’ and ‘definite problem drinker’. Being a drinker was dichotomized into 0 = non-drinker or 1 = drinker as indicated by all values other than ‘non-drinker’. Being a problem drinker was indicated by 1 = ‘possible problem drinker’ or ‘definite problem drinker’ versus 0 = ‘non-drinker’ or ‘social drinker’.

Parent-reported attitudes towards child’s drinking

Using the same items as rated by each child, parents reported on disapproval of child’s drinking with (a) family and (b) friends.

Parent-reported lifetime drinking behaviour

Trained interviewers conducted a structured interview that ascertained lifetime alcohol use and alcohol-related problems using a battery that was adapted for use in multiple countries including developing nations (‘Gender, Alcohol, and Culture: An International Study’, GENACIS; Wilsnack et al, 2009), plus integrated additional items from other surveys and interviews (Babor et al, 2001; Bucholz et al, 1994; Spitzer et al, 1997). As in prior JCHP waves (Luczak et al, 2014), we defined lifetime drinker as having consumed a full drink, or less than a full drink multiple times. We also created a problem drinker variable based on having one or more self-reported lifetime DSM-V AUD symptoms (APA, 2013; tally sheets rated by first two authors), or informants reporting possible or definite problem drinking with supporting detail (for example, ratings from seven, or 1%, of original birth cohort and spouse interviews were replaced by informant data when self-report was deemed to be of questionable accuracy).

Offspring outcomes

Current drinker

Offspring reported on their frequency of alcohol use over the past 12 months using a nine-point graduated frequency scale (from ‘never’ to ‘daily/almost daily use’). This drinker variable was dichotomized into 1 = current drinker, 0 = current non-drinker, with non-drinker being ‘never’ in the past year.

Current binge drinker

Offspring reported on their frequency of consuming 4+ drinks for females and 5+ drinks for males in a drinking episode (Wechsler et al, 1997) over the past 12 months using the same nine-point scale. This binge drinker variable was dichotomized into 1 = current binge drinker, 0 = currently not a binge drinker (‘never’ during the past year).

Analyses

Analyses were conducted in SPSS version 24 (IBM Corp, 2016). Cross-tabulations and likelihood ratio chi-square (LR χ2) tests of significance were used to examine categorical outcome variables by age group and gender. Logistic regressions were conducted to obtain odd ratios (ORs) with 95% confidence intervals (CIs) and adjusted Nagelkerke pseudo R2 change (∆R2; Homer and Lemeshow, 2000) for the two dichotomous outcome variables.

The datafile was structured as a wide file organized by offspring and including parental variables based on the relation of each parent to the child (mother, father). It was not assumed that parental data were missing at random, and thus missing values were not imputed; analyses were conducted for mother variables and father variables in separate models to examine their unique effects. Demographic variables (religion, age group) were included as covariates in all models and gender differences via interactions were tested for. In addition to running these models co-varying for religion and age group, these models were also run removing Muslims, removing the oldest age group (21–24 years) from the alcohol use analyses and the youngest age group (13–15 years) from the binge drinking analyses, and removing both Muslim and age groups. Results with the restricted samples were largely consistent with the models co-varying for religion and age, so results from the analyses conducted with the full sample are presented.

Two separate series of logistic regression analyses were conducted to examine the two offspring current drinking outcomes: (1) drinker and (2) binge drinker. We began with single block predictor models. In four separate analyses, each of the four sets of mother and father predictor variables (two variables in each block) were entered as a block, followed by gender as a block, and then the interaction terms with gender in a final block (p-value set at 0.10 for the interaction step). Based on the results of these analyses, the sample was split by gender and these single-predictor block analyses were repeated.

Parental predictors that were significant in the single-block models were entered into hierarchical multiple block analyses to show relationships among variable blocks for son–mother, daughter–mother, son–father and daughter–father pairs. Child-perceived variables were entered first in a block followed by parent-reported variables in a block to determine if parent-rated variables remained significant predictors (as indicated by the step χ2 value) after accounting for child-perceived variables.

Results

Descriptive statistics

The top rows of Table 8.1 display offspring demographics for total sample (first column) and stratified by age group and gender. In the two older age groups, participants were more likely to report their religion as other/none and less likely to report as Tamil, which is consistent with Tamil Mauritians often identifying with two religions (that is, ‘baptized Tamils’). The middle rows of Table 8.1 display child-perceived parental norms and parent-rated attitudes and behaviours. Perceived descriptive norms were consistent across gender and age groups, indicating that daughters and sons of different ages rated parents similarly. Both mothers and fathers were more likely to strongly disapprove of offspring drinking prior to age 18, with greater differences between son and daughter disapproval for the older age groups. Parents also were more likely to disapprove of offspring drinking with friends than drinking with family.

The bottom rows of Table 8.1 and Figure 8.1 display rates of current drinking and binge drinking in the offspring. Rates of drinking were similar for boys and girls in the younger age groups, but were more divergent in the older age groups where drinking rates for daughters remained close to half, but drinking rates for sons were about two thirds of 18–20-year-olds and three quarters of 21–24-year-olds. In all age groups, approximately twice as many sons as daughters engaged in binge drinking. Rates of binge drinking were low in 13–15-year-olds, but in 16–17-year-olds about one third of male drinkers and one sixth of female drinkers engaged in binge drinking, and once of legal drinking age, binge drinking was common among drinkers, including about 80% of male drinkers and about 40% of female drinkers.

Figure 8.1:
Figure 8.1:

Past-year drinking and binge drinking in Joint Child Health Project offspring stratified by gender and age group

Source: Author’s own
Table 8.1:

Demographic characteristics and alcohol involvement percentages stratified by gender and age of offspring (13–24 years old)

* p< .05, ** p< .01, *** p< .001

Total

13–15 years old

16–17 years old

18–20 years old

21–24 years old

Significant differences

Male

Female

Male

Female

Male

Female

Male

Female

n = 1,147

n = 184

n = 206

n = 99

n = 99

n = 156

n = 157

n = 111

n = 135

Demographics

Religion (4-level, n = 1,147)

Hindu

35

36

37

37

32

35

39

27

34

Tamil

7

10

8

10

6

3

7

4

5

Age 18 split*

Catholic

26

25

22

19

30

27

24

29

31

Muslim

24

25

29

25

23

21

22

26

23

Other/none

8

5

4

3

8

14

8

14

7

Age 18 split*

Current status

Student (n = 1,147)

67

98

99

87

90

41

57

22

25

Age***; gender in 18–20**

Single (n = 1,144)

93

100

100

100

99

98

90

87

62

Age***; gender in 18–20*, 21–24***

Family

Living with family of origin (n = 1,147)

90

100

98

98

97

90

88

85

62

Age***; gender in 21–24***

Intact (biological parents together; n = 1,144)

86

90

91

86

86

86

87

78

81

Age in males*

Raised by biological (N = 1,146)

Mother (pre-school: 0–5 years)

98

97

100

97

99

99

95

97

97

Age in females*; gender 13–15*, 18–20*

Mother (1° school: 6–11 years)

95

97

98

98

98

97

96

92

96

Mother (2° school: 12–18 years)

97

95

98

97

98

95

93

92

93

Father (pre-school: 0–5 years)

91

95

96

96

94

96

94

94

93

Father (1° school: 6–11 years)

95

92

92

95

89

93

91

94

85

Father (2° school: 12–18 years)

88

90

89

92

83

86

90

88

80

Age in females*; gender in 18–20*

Offspring-rated parental norms

Descriptive norms

Mother lifetime drinker (n = 1,137)

60

60

58

63

60

64

58

56

66

Mother lifetime problem drinker (n = 1,137)

2

2

1

3

3

2

3

4

4

Father lifetime drinker (n = 1,129)

71

72

70

67

71

75

71

70

73

Father lifetime problem drinker (n = 1,129)

18

13

17

10

23

19

21

16

23

Gender in 16–17*

Perceived injunctive norms

Mother strongly disagrees with child drinking with family (n = 1,135)

51

71

59

65

47

45

39

36

37

Age***;gender in 13–15*, 16–17**

Mother strongly disagrees with child drinking with friends (n = 1,136)

76

90

89

85

81

60

73

52

67

Age***; gender in 18–20*, 21–24*

Father strongly disagrees with child drinking with family (n = 1,104)

54

70

63

63

58

44

45

36

44

Age***

Father strongly disagrees with child drinking with friends (n = 1,104)

79

89

93

82

85

58

79

52

75

Age***; gender in 18–20***, 21–24***

Parent-reported

Parental behaviour

Mother lifetime drinker (n = 1,087)

71

70

67

69

65

72

72

68

73

Mother lifetime problem drinker (n = 1,087)

69

7

4

4

2

9

5

7

12

Age in females*

Father lifetime drinker

(n = 956)

84

85

85

78

84

86

91

83

87

Father lifetime problem drinker (n = 956)

36

31

36

28

36

45

34

38

37

Age in males*

Parental attitudes

Mother strongly disagrees with child drinking with family (n = 1,083)

70

89

87

75

78

52

64

41

61

Age***; gender in 18–20*, 21–24**

Mother strongly disagrees with child drinking with friends (n = 1,083)

89

97

99

94

95

77

91

71

85

Age***; gender in 18–20**, 21–24**

Father strongly disagrees with child drinking with family (n = 958)

75

86

91

83

84

57

66

51

66

Age***; gender in 21–24*

Father strongly disagrees with child drinking with friends (n = 958)

90

94

100

94

100

76

89

74

90

Age***; gender in 13–15**,16–17*,18–20**, 21–24**

Offspring alcohol use (self-report)

Past year drinker (n = 1,146)

52

33

31

51

56

68

56

76

63

Age***; gender in 18–20*, 21–24*

Past year binge drinker (n = 1,146)

21

4

2

19

9

56

24

58

24

Age***; gender in 16–17*, 18–20***, 21–24***

Alcohol use

Single predictor block models

Table 8.2 shows the single-block results of each predictor set for offspring current drinking. Interactions with gender were significant for all but three blocks, indicating that most of the parental predictors operated differently for daughters and sons. Thus, the models for the total offspring sample are presented, and split by offspring gender.

For daughters, each of the parental variable blocks were predictive of alcohol use (based on step χ2 significance), with the sole exception of the intact family block. Within blocks, almost all variables predicted drinking status (based on OR significance). Strong parental disapproval of drinking with family and strong mother disapproval of drinking with friends (both perceived and parent-rated) were associated with a four- to five-fold reduced risk of being a drinker. Three sets of perceived and parent-rated alcohol behaviour variables were also significant: mother being a drinker increased risk by 2.6-fold, father being a drinker increased risk by 4.6–5.6-fold, and father being a problem drinker increased risk by about two-fold (ORs = 1.9–2.1). Mother lifetime alcohol problems had a low prevalence (2% perceived by offspring, 6% lifetime self-report) and although the perceived risk was high (OR = 4.3), it did not reach significance (p = 0.17).

For sons, all variable blocks were predictive of alcohol use except parent-reported lifetime drinking behaviours. Within blocks, all child-perceived parental variables predicted use except mother and father problem drinking; for parent-rated variables, only mother (OR = 0.39) and father (OR = 0.31) strongly disapproving of drinking with family predicted use. Perceived parental strong disapproval of drinking with family and friends, however, was associated with two- to three-fold reduced risk of being a drinker. Mother being a drinker (perceived and self-reported) increased risk by 1.7–1.8-fold, and perceiving father as a drinker increased risk by 3.2-fold. Finally, sons whose parents were not intact were over twice as likely to drink as those from intact families.

Comparing ORs by offspring gender, all parental predictor ORs were higher for daughters compared with sons, except for perceived parental strong disapproval of drinking with friends.

Table 8.2:

Univariate predictors of current (past year) offspring alcohol use in total sample and stratified by gender

Total sample (n = 1147)

Female (n = 597)

Male (n = 550)

Interaction

Variables in step (block)

n

df

OR (95% CI) p

Step χ2 (p)

∆R2

OR (95% CI) p

Step χ2 (p)

∆R2

OR (95% CI) p

Step χ2 (p)

∆R2

Gender X step

Step χ2 (p)

Family not intact

1,143

1

1.75 (1.13–2.69) 0.011

6.62 (0.010)

0.006

1.37 (0.76–2.46) 0.30

1.09 (0.30)

0.001

2.23 (1.17–4.24) 0.015

6.26 (0.012)

0.012

ns (0.28)

Child-perceived norms

Mother SD drink with family

with friends

1,134

2

0.33 (0.24–0.47) 0.000

0.35 (0.23–0.54) 0.000

113.04 (0.000)

0.094

0.18 (0.11–0.29) .000

0.40 (0.22–0.73) 0.003

91.83 (0.000)

0.140

0.55 (0.33–0.91) 0.019

0.32 (0.17–0.60) 0.000

33.35 (0.000)

0.059

12.05 (0.002)

Mother drinker

problem drinker

1,136

2

2.16 (1.52–3.08) 0.000

0.90 (0.36-2.30) 0.83

18.17 (0.000)

0.015

2.66 (1.64–4.31) 0.000

4.34 (0.53–35.65) 0.17

19.67 (0.000)

0.032

1.77 (1.03–3.03) 0.039

0.34 (0.10–1.18) 0.09

6.44 (0.040)

0.011

11.29 (0.004)

Father SD drink with family

with friends

1,103

2

0.32 (0.23–0.45) 0.000

0.40 (0.25–0.64) 0.000

104.05 (0.000)

0.089

0.22 (0.14–0.35) 0.000

0.56 (0.28–1.12) 0.098

65.49 (0.000)

0.105

0.48 (0.29–0.81) 0.006

0.32 (0.16–0.61) .001

40.15 (0.000)

0.072

6.81 (0.033)

Father drinker

problem drinker

1,128

2

3.77 (2.37–6.00) 0.000

1.76 (1.19–2.60) 0.005

48.72 (.000)

.042

4.57 (2.35–8.90) 0.000

2.08 (1.253.47) 0.005

36.65 (0.000)

0.059

3.24 (1.65–6.34) 0.001

1.43 (0.77–2.65) 0.26

14.95 (0.001)

0.027

5.20 (0.074)

Mother reported

Mother SD drink with Family

with Friends

1,082

2

0.31 (0.21–0.45) .000

0.41 (0.20–0.83) .013

66.66 (0.000)

0.060

0.25 (0.15–0.42) 0.000

0.23 (0.06–0.86) 0.029

46.33 (0.000)

0.078

0.39 (0.22–0.69) 0.001

0.54 (0.23–1.28) 0.16

20.33 (0.000)

0.039

ns (0.19)

Mother drinker

problem drinker

1,087

2

2.05 (1.32–3.17) 0.001

1.30 (0.70–2.41) 0.40

11.27 (0.004)

0.010

2.62 (1.40–4.88) 0.003

1.02 (0.43–2.43) 0.96

9.18 (0.010)

0.016

1.72 (0.91–3.27) .095

1.77 (0.72–4.34) 0.22

4.73 (0.09)

0.009

5.41 (0.067)

Father reported

Father SD drink with family

with friends

957

2

0.29 (0.18–0.45) 0.000

0.79 (0.39–1.61) 0.522

41.85 (0.000)

0.042

0.27 (0.14–0.50) 0.000

0.61 (0.17–2.21) 0.46

23.19 (0.000)

0.044

0.31 (0.16–0.62) 0.001

0.89 (0.36–2.21) 0.80

17.22 (0.000)

0.035

ns (0.31)

Father drinker

problem drinker

956

2

1.39 (0.74–2.62) 0.31

1.72 (1.24–2.40) 0.001

12.85 (0.002)

0.013

3.57 (1.12–11.39) 0.031

1.88 (1.19–2.96) ..006

15.07 (0.001)

0.028

0.91 (0.38–2.27) 0.84

1.50 (0.92–2.44) 0.11

2.63 (0.27)

0.006

7.66 (0.022)

Note: Results co-varied for religious group and age group

Hierarchical predictor block models

In these models, two blocks were entered stepwise to determine whether parental attitudes and self-reported lifetime behaviours accounted for additional variance beyond that accounted for by child perception of these parental alcohol norms (see Table 8.3). Within daughters in the mother model, both perceived (OR = 0.21) and mother-rated (OR = 0.41) strong disapproval of drinking with family remained significant in the final step, but mother-reported strong disapproval of drinking with friends and lifetime drinking were no longer significant when entered after child-perceived ratings of drinking with friends (OR = 0.39) and perceived mother drinker (OR = 2.0). This pattern was similar in the father model, where both perceived (OR = 0.22) and father-reported (OR = 0.34) disapproval of drinking with family were significant in the final step, along with perceived father lifetime drinker (OR = 2.6).

Among sons in the mother model, perceived strong disapproval of drinking with friends (OR = 0.33) and mother-rated strong disapproval of drinking with family (OR = 0.49) remained significant in the final step. In the father model, both perceived (OR = 0.32) and father-rated (OR = 0.37) strong disapproval of drinking with friends remained significant in the final step.

Table 8.3:

Parental predictors of current drinking stratified by offspring gender

Daughters

Sons

+ p < .10, *p < .05, **p < .01, ***p < .001

Note. SD = strongly disagree

Mother

OR

(95% CI)

Father

OR

(95% CI)

Mother

OR

(95% CI)

Father

OR

(95% CI)

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Child rated

Perceived norms

Mother SD drink with family

0.18***

(0.11–0.29)

0.21***

(0.13–0.35)

0.56*

(0.33–0.94)

0.68

(0.39–1.17)

Mother SD drink with friends

0.34***

(0.18–0.65)

0.39**

(0.20–0.75)

0.32***

(0.16–0.62)

0.32**

(0.16–0.64)

Father SD drink with family

0.21***

(0.13–0.34)

0.22***

(0.13–0.37)

0.50*

(0.28–0.89)

0.56+

(0.31–1.01)

Father SD drink with friends

0.30***

(0.15–0.61)

0.32**

(0.15–0.66)

Descriptive norms

Mother lifetime drinker

2.22**

(1.28–3.4)

2.01*

(1.09–3.70)

1.46

(0.83–2.56)

1.34

(0.76–2.37)

Father lifetime drinker

3.55**

(1.63–7.71)

2.58*

(1.16–5.77)

1.72

(0.77–3.83)

1.77

(0.78–4.01)

Father problem drinker

1.85+

(1.00–3.43)

1.55

(0.78–3.07)

Parent rated

Attitude

Mother SD drink with family

0.41**

(0.23–0.74)

0.49*

(0.28–0.87)

Mother SD drink with friends

0.34

(0.09–1.25)

Father SD drink with family

0.34**

(0.18–0.66)

0.37**

(0.19–0.69)

Father SD drink with friends

Behaviour

Mother lifetime drinker

1.03

(0.47–2.23)

Father lifetime drinker

2.74

(0.75–10.00)

Father problem drinker

1.58

(0.90–2.77)

Step χ2

107.50***

16.58**

67.00***

15.69**

34.84***

6.02*

40.38***

9.95**

∆R2

0.017

0.024

0.125

0.027

0.066

0.011

0.084

0.019

Binge drinking

Single predictor block models

Table 8.4 shows the single-block results for predictors of offspring current binge drinking for the total sample and split by offspring gender. Interactions with gender in the total sample models were significant at the 0.10 level only for perceived father injunctive norms and father-reported behaviour, and were at 0.20 for the other three perceived parental norms and for intact family. In the total sample, all four parent-rated disapproval variables predicted binge drinking, with mother-rated strong disapproval of drinking with family associated with decreasing likelihood of binge drinking by three-fold (OR = 0.35) and the other three indicators of parental disapproval reducing the likelihood by about two-fold (OR = 0.52–0.57).

Among daughters, all parental variable blocks except mother-reported behaviour were predictive of binge drinking. Daughters who perceived their mothers were drinkers were 2.8 times more likely to binge drink and daughters who perceived their mothers were problem drinkers were 3.4 times more likely to binge drink, although this relationship did not reach significance (p = 0.07). Daughters who perceived their fathers as drinkers were over 10 times more likely to binge drink, and in the father-reported model almost all (98%) daughters who binged had a father who reported being a lifetime drinker (note the OR is out of range because it is almost constant, but LR χ2 = 65.73, 1df, p < 0.001). In addition, perceived and mother-rated strong disapproval of drinking with family and friends were related to a two- to three-fold decrease in binge drinking, and perceived and father-rated strong disagreement with daughters drinking with family (but not friends) was associated with a two-fold reduction of risk for binge drinking. Finally, daughters whose parents were not intact were three times more likely to binge drink.

Among sons, fewer parental variables were significantly associated with binge drinking. Perceived mother (OR = 0.38) and father (OR = 0.28) strong disapproval of drinking with friends were protective against binge drinking, and mother-rated strong disapproval of drinking with family was associated with a two-fold reduction in risk for binge drinking. The only parent alcohol behaviour variable that was predictive of binge drinking in sons was father-reported lifetime problems, which was associated with a 2.2-fold increase in risk.

Comparing the ORs by offspring gender, parental strong disapproval of drinking with family (both perceived and self-reported) was stronger in daughters, whereas perceived father strong disapproval of drinking with friends was stronger in sons.

Table 8.4:

Univariate predictors of current (past year) offspring binge use in total sample and stratified by gender

Total sample (n = 1,147)

Female (n = 597)

Male (n = 550)

Interaction

Variables in step (block)

n

df

OR (95% CI) p

Step χ2 (p)

∆R2

OR (95% CI) p

Step χ2 (p)

∆R2

OR (95% CI) p

Step χ2 (p)

∆R2

Gender X Step

Step χ2 (p)

Family not intact

1,143

1

1.93 (1.25–2.97) 0.003

8.71 (0.003)

0.009

2.99 (1.57–5.72) 0.001

10.68 (0.001)

0.028

1.38 (0.73–2.62) 0.32

0.98 (0.32)

0.002

ns (0.14)

Child-perceived norms

Mother SD drink with family

with friends

1,134

2

0.82 (0.52–1.29) 0.38

0.29 (0.19–0.43) 0.000

54.60 (0.000)

0.057

0.32 (0.13–0.76) 0.010

0.29 (0.16–0.53) 0.000

36.34 (0.000)

0.009

0.91 (0.49–1.68) 0.76

0.38 (0.21–0.68) 0.001

15.56 (0.000)

0.028

ns (0.20)

Mother drinker

problem drinker

1,136

2

1.45 (0.93–2.26) 0.10

1.38 (0.56–3.39) 0.48

3.52 (0.17)

0.004

2.84 (1.24–6.46) 0.013

3.40 (0.91–12.68) 0.07

11.25 (0.004)

0.029

0.98 (0.53–1.81) 0.96

0.85 (0.22–3.54) 0.85

0.04 (0.98)

0.000

ns (0.15)

Father SD drink with family

with friends

1,103

2

0.76 (0.48–1.19) 0.23

0.36 (0.24–0.54) 0.000

40.09 (0.000)

0.043

0.40 (0.20–0.81) 0.011

0.85 (0.44–1.62) 0.61

9.90 (0.007)

0.025

1.13 (0.59–2.18) 0.71

0.28 (0.15–0.52) 0.000

21.78 (0.000)

0.039

6.05 (0.049)

Father drinker

problem drinker

1,128

2

2.32 (1.24–4.35) 0.009

1.43 (0.96–2.13) 0.08

12.78 (0.002)

0.014

10.79 (2.54–45.83) 0.001

1.81 (0.101–3.24) 0.046

22.50 (0.000)

0.057

1.16 (0.51–2.62) 0.72

1.73 (0.92–3.23) 0.09

3.33 (0.19)

0.006

ns (0.14)

Mother reported

Mother SD drink with family

with friends

1,082

2

0.35 (0.23–0.53) 0.000

0.57 (0.35–0.93) 0.024

45.48 (0.000)

0.051

0.27 (0.14–0.53) 0.000

0.53 (0.23–1.23) 0.14

24.55 (0.000)

0.070

0.52 (0.28–0.94) 0.031

0.76 (0.38–1.50) 0.42

8.25 (0.016)

0.016

ns (0.38)

Mother drinker

problem drinker

1,010

2

1.23 (0.68–2.23) 0.48

0.71 (0.38–1.342) 0.29

1.53 (0.47)

.001

2.84 (0.85–9.56) 0.09

0.98 (0.38–2.55) 0.97

3.22 (0.20)

0.009

0.94 (0.44–2.03) 0.88

0.58 (0.24–1.44) 0.24

1.45 (0.48)

0.002

ns (0.62)

Father reported

Father SD drink with family

with friends

957

2

0.52 (0.33–0.80) 0.003

0.52 (0.30–0.91) 0.021

22.97 (0.000)

0.029

0.46 (0.24–0.89) 0.022

0.77 (0.29–2.06) 0.60

6.84 (0.033)

0.021

0.59 (0.31–1.13) 0.11

0.62 (0.29–1.30) 0.20

7.63 (0.022)

0.019

ns (0.91)

Father drinker

problem drinker

906

2

1.00 (0.38–2.65) 0.99

1.56 (1.06–2.31) 0.025

5.08 (0.079)

0.007

#

1.13 (0.62–2.06) 0.68

7.51 (0.023)

0.023

0.29 (0.07–1.17) 0.082

2.21 (1.25–3.90) 0.006

9.37 (0.009)

0.016

6.46 (0.040)

Note: Results co-varied for religious group and age group.

# = Not estimated in range. Almost all female drinkers (98%) have a father who was a lifetime drinker. L-R chi-square 65.73, 1df, p=.000.

Hierarchical predictor block models

Among daughters in the mother model (see Table 8.5), perceived mother strong disapproval of drinking with friends (OR = 0.29) remained significant in the final step, but perceived mother strong disapproval of drinking with family was no longer significant, with mother-rated strong disapproval of drinking with family (OR = 0.41) included in the model. In the father model, perceived father drinker (OR = 4.8), father-rated strong disapproval of drinking with family (OR = 0.45) and father-reported lifetime drinking (endorsed in 98% of fathers with daughter who binged) remained significant in the final step.

Among sons in the mother model, perceived strong disapproval of drinking with friends (OR = 0.41) remained significant in the final step. In the father model, father-reported lifetime problem drinking (OR = 1.7) did not reach significance (p = 0.06) when added to the model in the final step.

Table 8.5:

Parental predictors of current binge drinking stratified by offspring gender

Daughters

Sons

+ p < .10, *p < .05, **p < .01,

***p < .001

Note. SD = strongly disagree

Mother

OR

(95% CI)

Father

OR

(95% CI)

Mother

OR

(95% CI)

Father

OR

(95% CI)

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Child rated

Perceived norms

Mother SD drink with family

0.33*

(0.12–0.46)

0.36+

(0.13–1.01)

Mother SD drink with friends

0.24***

(0.12–0.46)

0.28***

(0.14–0.56)

0.36***

(0.22–0.62)

0.41***

(0.24–0.70)

Father SD drink with family

0.54

(0.25–1.15)

0.60

(0.27–1.30)

Father SD drink with friends

0.31***

(0.17–0.53)

0.33***

(0.19–0.58)

Descriptive norms

Mother lifetime drinker

1.93

(0.74–4.99)

1.50

(0.57–3.97)

Father lifetime drinker

7.64*

(1.62–36.01)

4.83*

(1.09–21.46)

Father problem drinker

1.89+

(0.91–3.90)

1.86+

(0.89–3.90)

Parent-reported

attitudes

Mother SD drink with family

0.35*

(0.18–0.71)

0.60+

(0.34–1.07)

Mother SD drink with friends

Father SD drink with family

0.45*

(0.23–0.89)

Father SD drink with friends

Behaviour

Mother lifetime drinker

Father lifetime drinker

#

Father problem drinker

1.72+

(0.98–3.02)

Step χ2

42.92***

8.75**

18.16***

8.85*

13.96**

2.94+

17.32***

3.49+

∆R2

0.120

0.024

0.058

0.027

0.027

0.005

0.040

0.008

Note: = Out of range, with 98% of fathers whose daughters binge drink being lifetime drinkers

Discussion

Rates of alcohol use and heavy use in Mauritian youth

This study found similar drinking rates for male and female JCHP youth under age 18, but higher rates for male compared with female JCHP young adults (aged 18+). Binge drinking was consistently about twice as high in males versus females in all age groups, with almost a quarter of the young adult females and half of the young adult males engaging in binge drinking over the past year. The finding that about a third of 13–15-year-old JCHP offspring were drinking over the past year is higher than the 2011 Global School-Based Health Survey (GSHS) past-month rates for Mauritian schoolchildren (26% of boys, 22% of girls; CDC, 2011). Similarly, the finding that half or more of 16–20-year-olds were drinking, with 80% of these male drinkers and 40% of these female drinkers binging, was also higher than WHO (2018) past-month rates in 15–19-year-old Mauritians, which found that 28% of males drank in the past month and 14% (or 48% of male drinkers) engaged in heavy episodic (binge) drinking, and 11% of females drank in the past month and 2% (or 17% of female drinkers) binged. Drinking behaviour was assessed over an annual cycle because many of the JCHP offspring were interviewed during school holidays, which could bias past-month rates. Thus, the numbers are not directly comparable to these national-level surveys, but trends across gender within each age group are similar to the broader population of youth on Mauritius in these national surveys that show increasing rates in recent years (for example, in the 2006 GSHS rates were only 19% for boys and 17% for girls; CDC, 2007). It is also possible that the lifelong participation of the JCHP families, the established relationships and rapport with JCHP staff, and the detailed assessment battery in this JCHP wave may have yielded higher reported levels of use than in national surveys. These numbers indicate that drinking among Mauritian youth is common and should be considered a potential public health concern, particularly binge drinking, which is often linked to negative consequences in adolescence and young adulthood (for example, Wechsler et al, 1997, 1998).

Parental risk and protective factors

The findings within families show consistency in how children view their parents’ drinking behaviours across offspring age groups and gender. It is common for Mauritians to socialize with their families, and the findings show that children are able to perceive parental consumption and problems in ways that are consistent across age groups and gender. It is also shown, however, that offspring have received different messaging regarding the appropriate use of alcohol based on their age and gender. Most Mauritian parents are providing clear messages of disapproval to their children regarding the use of alcohol, and these perceived injunctive norms are associated with their children’s drinking behaviours. By parsing parental injunctive norms by context (drinking with family versus drinking with friends), it can be seen that parents may be guiding their children to consume alcohol under their supervision and thus drink with family in situations that do not include heavy drinking. Norms that relate to binge drinking were more focused on drinking with friends, which likely is a context in which more extreme consumption occurs. It is also possible, however, that parental influence is working in reverse, with those children who are drinking heavily doing so with friends, which parents then strongly oppose. The findings also highlight that not only what parents say, but also what parents do makes a difference in offspring drinking behaviour – parental drinking behaviour modelled to offspring played an important role in offspring early drinking behaviour, and to some extent to offspring early heavy drinking. Continuing to follow the JCHP offspring over their early drinking years and assessing drinking behaviours at multiple time points will enable the progression of offspring drinking to be observed and the directional influence of familial factors on early drinking trajectories to be determined.

Gender-specific parental risk and protective factors

Daughters

It was predicted that daughter alcohol use would be influenced by maternal alcohol norms and attitudes and this was the case, but it was also true that paternal alcohol use behaviours were strong predictors of daughter alcohol use. Thus, it was not that gender-specific modelling was the critical factor for daughter drinking and heavy drinking, but rather that daughters were broadly influenced by parental alcohol-specific risk and protective factors. Alcohol use in females is now more common in this younger generation of Mauritians than it was for females in the older generation, so it is possible that daughters are taking their drinking cues from their fathers more than their mothers. Understanding what constitutes acceptable behaviour now for females in this changing society warrants further attention. In addition, better knowledge of how binge drinking is linked to negative consequences in Mauritius, and if these relationships are consistent with youth from other societies (for example, Brown et al, 2008; Wechsler et al, 1997, 1998), will be important for understanding its impact on health in this society.

Sons

Among sons, there was indication of modelling of drinking behaviour, with perceiving parents to be drinkers linked to increased likelihood of being a drinker, regardless of actual lifetime parent self-reported drinking. For parental monitoring, the role of mothers operated via expressed disapproval of drinking, and a protective role of paternal disapproval of sons drinking with friends (but not family) as also found. Questions about parental alcohol-specific attitudes were split to distinguish between drinking with family, which is common among non-Muslim Mauritians, who often socialize within family units (including across generations), and drinking with friends, which is more common among Mauritian youth than Mauritian adults and may be influenced by factors specific to developmental stage (see Maggs et al, 2008).

That only a few parental drinking variables were predictive of a son’s binge drinking was not expected (even though stronger relationships were hypothesized for daughters than for sons), but suggests this common behaviour among young Mauritian males may be more influenced by non-familial factors such as peers or availability, or perhaps by more nuanced familial factors than were captured in this study. The only father alcohol behaviour that significantly predicted a son’s binge drinking was father-reported lifetime problem drinking, indicating that the risk from father’s drinking history is contained within variance not captured by what the son observes of the father; this is suggestive of a stronger genetic influence than environmental influence, although no definitive conclusions can be drawn regarding genetic versus environmental contributions in this family study of primarily intact families. Among sons, being from a parental unit that was not intact also doubled the risk for binge drinking, however, indicating that reduced parental presence may also indirectly play a role in binge drinking (for example, perhaps father drinking contributed to the parental unit split and indirectly to son binge drinking). Additional examination of parental alcohol use and problems while raising children during different child developmental periods (pre-school, primary school, secondary school) may yield further insight into how fathers’ lifecourse alcohol involvement predicts the future alcohol consumption trajectories of their sons.

Summary

Taken together, the findings show important mother–daughter and father–son relationships, supporting the hypothesis that modelling within genders is critical for use, but also indicate that daughters may utilize descriptive norms from fathers as well as mothers to guide their alcohol use and heavy use. Based on prior behaviour genetics studies, it was explored whether these descriptive relationships would be stronger in daughters than in sons, which was supported in relation to drinking and partially supported in relation to binge drinking, where for son’s binge drinking evidence was only found of self-reported father lifetime problems being a significant parental behaviour predictor. Regarding injunctive norms, parent-rated disapproval adds protection for drinking and binge drinking beyond child-perceived parental injunctive norms, indicating that parental disapproval of drinking may be indicative of more than just what the child perceives as disapproval and perhaps represents a broader range of parental controls that operate both directly and indirectly on offspring behaviour. Injunctive norms were expected to be stronger in sons than daughters, but what consistent relationships were found across parents that varied by offspring gender (that is, strong parental disapproval of drinking with family related to daughter alcohol involvement, strong parental disapproval of drinking with friends related to son alcohol involvement). Finally, we see context-specific variations in injunctive norms that are consistently reported across generations but differentially related to alcohol use versus heavy use. This variation in norms–behaviour associations is similar to the earlier findings in the original birth cohort that religious abstinence norms were protective against being a drinker, but did not afford additional protection for AUDs (Luczak et al, 2014), supporting the specificity of the impact of norms on different alcohol behaviours.

Study strengths and limitations

Findings from a birth cohort study like the JCHP have the advantage of not being a biased sample due to selection criteria, and thus results found with these Mauritian families may generalize to broader populations. It is possible these findings would be relevant to other middle-income nations where relative financial security provides for youth spending on alcohol, or in nations where alcohol use among females is growing in similar ways as in Mauritius. It is also possible, however, that the results are not applicable within nations where rates of intact families are much lower than in Mauritius. Interpreting research findings within the contextual constraints of the sample and society will help lead to a more complete picture of unique and common risk factors for youth drinking across nations as well as within dynamic cultures where the norms for drinking may be changing to support more female drinking and heavier drinking in youth overall.

It is also recognized that reporting biases in alcohol research differ by assessment format, rater, demographic groups and contexts. Having multiple assessment waves on the original cohort and multiple informants within the family, however, made it possible to remove several self-reports that were deemed inconsistent, highlighting an important benefit of conducting research over time within families. In this example of work conducted with the JCHP sample, the first wave of data collection on offspring drinking is presented, and thus it is recognized that these initial finding do not highlight all benefits of a longitudinal study. The best way to look at family influences is through multiple-rater studies that track behaviour over time, and at key developmental periods. Over the last several decades, the JCHP has made contributions to understanding how early childhood health affects mental health outcomes into early and mid-adulthood within the original birth cohort. The JCHP is now in the process of expanding into a multigenerational family study, including collecting many of the same constructs on the offspring as were obtained on the original cohort. The study presented here represents initial efforts to understand how gender and parental alcohol risk and protective factors relate to drinking and heavy drinking in Mauritian youth. The findings point to the notion that parental lifetime alcohol behaviours relate to current offspring drinking in multiple ways through modelling, monitoring, family constellation and family history, and provides avenues to investigate next in multi-informant prospective designs. Gathering additional waves of data on the offspring will make it possible to examine how risk and protective factors obtained from multiple generations affect early drinking trajectories in this next generation, thus, building upon the longitudinal findings, the JCHP can contribute to understanding the lifecourse development of mental health.

Acknowledgments

This research was supported by US National Institutes of Health grants K08AA14265 and R01AA18179 and the Mauritian Ministry of Health and Quality of Life. We gratefully acknowledge the contributions of founding investigators of the JCHP Sarnoff A. Mednick, Peter H. Venables, Fini Schulsinger, Abdul C. Raman, Cyril Dalais, current Co-International Director of the JCHP Adrian Raine and researchers who have published JCHP findings over the decades, Joint Child Health Project staff including Naajiyah Seesurun, Luczak USC Laboratory staff including Emily B. Saldich, and the JCHP birth cohort and their families for their lifelong participation in this study.

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  • Figure 8.1:

    Past-year drinking and binge drinking in Joint Child Health Project offspring stratified by gender and age group

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