RUNNING HEAD: Drinking trajectories and pregnant Inuit women
“Trajectories of Alcohol Use and Binge Drinking among Pregnant Inuit Women”
Marilyn Fortin, Ph.D.1,2,, Gina Muckle, Ph.D.1,2, Elhadji Anassour-Laouan-Sidi, M.Sc.2, Sandra W. Jacobson, Ph.D.3, Joseph L. Jacobson, Ph.D.3, Richard E. Bélanger, M.D.2,4
1Department of Psychology, Laval University, Québec (QC) Canada2Population Health and Optimal Health Practices Research Unit, CHU de Québec
Research Centre, Québec (QC), Canada.3Department of Psychiatry and Behavioral Neurosciences, Wayne State University
School of Medicine, Detroit, Michigan, USA4Department of Pediatrics, Centre mère-enfant Soleil, CHUQ, Laval University, Québec
(QC) Canada
Word count abstract: 250Word count text: 4,018Number of tables: 3Figures: 1
Declaration of interest
This study was supported by the National Institute of Environmental Health and
Sciences⁄National Institutes of Health (R01-ES07902); Indian and Northern Affairs
Canada (Northern Contaminants Program); Health Canada; Hydro-Québec
(Environmental Child Health Initiative); the Public Health Direction of the Nunavik
Regional Board of Health and Social Services; the Joseph Young, Sr. Fund from the State
of Michigan, USA; and by postdoctoral research awards from the Canadian Institutes of
Health Research (CIHR) (RN188397-299895) and the Nasivvik Centre for Inuit Health
and Changing Environments (to Marilyn Fortin). The authors declare no competing
financial interests.
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AbstractBackground: This study investigated trajectories of alcohol use and binge drinking
among Inuit women starting from a year before pregnancy until a year after delivery,
examined transition rates between time periods, and established whether specific factors
could be identified as predictors of changes in alcohol behaviors.
Methods: Drinking trajectories and movement among alcohol users and binge drinkers
(i.e., non-binging and binging) were explored by Markov modeling across time periods.
Two hundred and forty-eight Inuit women from Arctic Quebec were interviewed at
midpregnancy, and at 1 and 11 months postpartum to obtain descriptive data on alcohol
use during the year before pregnancy, the conception period, the pregnancy and the year
after delivery.
Results: The proportions of drinkers and bingers were 73% and 54% during the year
prior to pregnancy and 62% and 33% after delivery. Both alcohol use and binge drinking
trajectories demonstrated a significant drop in prevalence between the year before
conception to the conception period. We also noted high probabilities of becoming an
abstainer or not binging at this time. However, up to 60% of women continued to drink
alcohol during pregnancy. Women in couples and not consuming marijuana were more
likely to decrease their binge drinking at conception.
Conclusions: This study emphasizes the importance of including the period around
conception in the definition of drinking patterns during pregnancy. The importance of
considering alcohol consumption in a multidimensional way (personal, familial and
social determinants) is also addressed while trying to minimize problems both for the
fetus and the mother.
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Keywords: Trajectory, Alcohol, Binge drinking, Women, Pregnancy, Inuit, Markov
models, Marijuana
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Title: Trajectories of Alcohol Use and Binge Drinking among Pregnant Inuit Women
1. Introduction
In most countries and cultures, alcohol is strongly embedded in modern life
(Gusfield, 1996; Heath, 1986; World Health Organization (WHO), 2014). The WHO
estimated that in 2010 one-third of adults worldwide drank alcohol at least once in their
lives, and three-quarters of them drank alcohol in the previous year (WHO, 2014). In
North America, the vast majority of adults are considered active drinkers (Health Canada,
2011; Substance Abuse and Mental Health Services Association, 2012). Excessive
alcohol consumption is attributable to 5% of the worldwide global burden of disease
(WHO, 2014), healthcare costs of 12.8% in high-income countries (Rehm et al., 2009),
and a number of associated short and long-term health problems, such as violence, heart
disease, stroke, cancer, mental health and substance dependence (National Institute of
Alcohol Abuse and Alcoholism, 2008).
The Inuit – an Aboriginal population living in North America and Greenland –
have their own cultural and social history related to alcohol. Accordingly, their alcohol
consumption frequency is relatively low, and abstinence is high compared to their fellow
Canadian citizens (Muckle et al., 2007, cited in Muckle et al. 2011). However, the
amount of alcohol Inuit men and women consume per drinking day is much greater, and
episodes of binge drinking are three times more frequent (Korhonen, 2004; Muckle et al.,
2007).
Maternal alcohol drinking during pregnancy is of particular concern. As many
women continue to drink heavily or have binge-drinking episodes during pregnancy
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(Substance Abuse and Mental Health Services Administration, 2012), alcohol exposure in
utero may result in a constellation of growth, developmental and behavioral problems
falling under the umbrella of fetal alcohol spectrum disorders, including fetal alcohol
syndrome (FAS) and alcohol-related neurodevelopmental disorders (Hoyme et al., 2005).
Higher FAS rates have been reported among American and Canadian aboriginal groups
in comparison to the general population (Burd and Moffat, 1994; Carney and Chermak,
1991; Chudley et al., 2005; Werk et al., 2013). Alcohol use during pregnancy is also
associated with socioeconomic insecurity, poor social support, smoking and drug use and
abuse by mothers (Archibald, 2004; Fortin et al., 2015; Haynes et al., 2003; Horrigan et
al., 2000), which can also negatively impact child health.
Considerable intra-individual variability of alcohol drinking exists over time and
according to specific lifetime periods or stage of development, personal and familial
status, family and peer influences as well as lifestyle (Barnes et al., 2000; Bobo and
Greek, 2011; Curran et al., 1998; Fuzhong et al., 2001; Maggs and Schulenberg, 2004-
2005). In certain Occidental cultures, pregnancy is associated with decreased alcohol
consumption (Cameron et al., 2013; Denny et al., 2009; Walker et al., 2011). Women
from Russia (Balachova et al., 2012) and France (Malet et al., 2006) have been found to
report no significant difference in alcohol consumption before and during pregnancy.
Exceedingly heavy binge drinking before and during pregnancy has also been noted
among the Cape Colored (mixed ancestry) community in South Africa (Jacobson et al.,
2006; May et al., 2013), resulting in some of the highest prevalence of FAS in the world.
This trend has also been observed among older and single women of low socioeconomic
status who consume recreational drugs (Cameron et al., 2013).
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While some studies have established how much Inuit women drink during and
around the time of pregnancy (Godel et al., 1992, 2000; Muckle et al. 2011), none has
conducted time trends analyses of longitudinal data to follow the evolution of drinking
patterns in the context of pregnancy. To our knowledge, only few have examined the
question of time-specific variation in alcohol use across pregnancy and how such
variability could impact future drinking patterns among female western populations (Day
et al., 1989; Jacobson et al., 2002).
This study (1) investigated trajectories of alcohol consumption and binge drinking
among Inuit women beginning the year prior to pregnancy until the end of the first
postpartum year, and (2) assessed transitions between time periods. Since variations in
drinking patterns have been reported in many populations in relation to personal and
familial factors, (3) we examined whether these influences could be identified as
predictors of changes in alcohol behavior. Our study has the potential to contribute to the
development of prevention and intervention programs adapted for Inuit women.
2. Methods
2.1 Study procedures and sample
Pregnant Inuit women were invited to participate in a prospective mother-child
cohort in Northern Quebec, Nunavik, Canada (Muckle et al., 2001, 2011; Jacobson et al.,
2008). The Nunavik region is located north of the 55th parallel in the province of Quebec
(Canada). About 11,000 Inuit are scattered along a 2,000-km shoreline of Hudson Bay,
the Hudson Strait and Ungava Bay. They live in 14 villages, ranging from 160 to 2,055
inhabitants per village. From November 1995 to November 2000, a midwife or nurse in
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each of the 3 largest Inuit villages on the Hudson Bay coast provided us with the names
of pregnant women shortly after their first prenatal visit. A project research assistant
contacted potential participants by telephone and invited them to meet at the village’s
nursing station to learn more about the study’s objectives and procedures. Women
without telephones were reached by announcement on the village’s radio station.
Maternal interviews were conducted at the nursing station in mid-pregnancy and at 1 and
11 months postpartum by a research assistant with a master or doctoral degree in
psychology. Interviews were conducted in English, French or Inuktitut with the help of a
female Inuit interpreter. Detailed, informed consent was obtained from all participants
and the research procedures were approved by the Ethics Review Boards of Université
Laval (Canada) and Wayne State University (USA).
Four hundred and seventeen pregnancies were identified during the study period.
Fifty-nine potential participants were excluded for the following reasons: inclusion in the
cohort during a previous pregnancy, miscarriage during the first trimester of pregnancy,
or could not be contacted. Of the 417 pregnant women identified, 110 (26.4%) refused to
participate. Women who agreed to participate were interviewed during pregnancy (N =
248, 59.5% of all pregnancies during that period), then at 1 (N = 248) and 11 months
postnatally (N = 174). The main reasons for loss of participants after delivery were: infant
adopted (28%) or mother moved to a community not participating in the study (22%),
miscarriage and infant mortality (22%), and mother could not be found for subsequent
follow-up (18%). The refusal rate after enrollment was 6.7% at 11-month follow-up (for
more information, see Muckle et al., 2011).
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2.2 Measures
Alcohol use. During the prenatal interview, alcohol consumption was assessed for
3 time periods: the year prior to pregnancy (T1), the periconceptual period (which
corresponded to the 3-week period after the first day of the last menses) (T2), and the
period from conception to the prenatal interview (part of T3). The interview, conducted 1
month after delivery, documented alcohol consumption in the period from the initial
maternal interview to the end of pregnancy (part of T3). As a result, data from the
prenatal interview were considered together with those obtained from the 1-month
postnatal interview as alcohol use during the pregnancy period (T3). The interview at 11
months postpartum documented alcohol use from delivery until interview (T4).
Frequency and quantity of alcohol intake were assessed through semistructured
interviews designed to document number of drinking days, number of standard drinks
(beer, wine, or liquor) per drinking day, binge drinking episodes, and number of standard
drinks per binge drinking episode. Binge drinking was defined as the consumption of at
least 5 standard drinks of alcohol (beer, wine or liquor) during a single occasion. To
characterize alcohol consumption longitudinally, we focused on dichotomous indicators
of alcohol use (yes/no) and binge drinking (yes/no) from T1 to T4.
Predictors. Based on the literature (Fillmore et al., 1991; Fraser et al., 2012;
Muckle et al., 2011; Nunavik Inuit Health Survey, Qanuippitaa?, 2004; Wilsnack et al.,
2000, 2009), the following potential predictors of alcohol drinking trajectories,
documented during the prenatal interview, were considered in the analyses: maternal age,
marital status, socioeconomic status, total number of pregnancies (gravidity), smoking
and illicit drug use during pregnancy and during life. Maternal age was analyzed as
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median values of 24 years versus those above. Marital status (married, living with
someone, single, divorced or widower) was documented as couple versus single.
Socioeconomic status (SES) was assessed using the Hollingshead Index (Hollingshead,
2011), which is based on the level of educational attainment of mother and father as well
as each parent’s occupational status. The Hollingshead Index ranges from 0 to 66: 0-19 =
unskilled laborers, menial service workers; 20-29 = machine operators, semiskilled
workers; 30-39 = skilled craftsmen, clerical, sales workers; 40 and above = technical,
major or medium-size business or professional). Scores were recorded according to the
median value of 15: 0-15 = low SES (55%) versus over 15 = other (45%). Number of
previous pregnancies, including current pregnancy, was dichotomized according to the
median value of 3 pregnancies: 0-3 pregnancies = 48% versus >3 pregnancies. The
following illicit drugs were documented by yes⁄no questions for the lifetime and perinatal
periods: marijuana, cocaine (including crack and cocaine), solvent sniffing (mainly glue,
gas, and nail polish remover), heroin, mushrooms, PCP (phencyclidine), angel dust,
sedatives, and amphetamines. Marijuana, as the most prevalent drug consumed in the
context of pregnancy, was retained for further analysis, but other drugs were discarded
because of their low use (below 5.6%; see Muckle et al., 2011). To best evaluate possible
associations between marijuana and alcohol drinking trajectories, we selected the closest
indicator of active marijuana use available: at conception. We excluded measurements of
tobacco as 9 out of 10 women reported smoking cigarettes during pregnancy (Muckle et
al., 2011).
2.3 Statistical analyses
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Drinking patterns across the pregnancy period were explored by Markov
modeling. We applied a Markov model in which stages were based on a single measure
of alcohol use (yes/no) (first model) and a binge drinking measure only (yes/no) (second
model) with the assumption of no measurement error. This method provides a way of
describing and predicting trajectories and movement between stages (times) of use and
non-use. Markov models (Collins and Lanza, 2010; Collins and Wugalter, 1992; Collins
et al., 1994), sometimes referred to as “latent transition” models, are commonly tested in
alcohol research when drinking patterns are conceptualized as a multidimensional,
discrete variable in a developmental process (Bray et al., 2014; Guo et al., 2000; Jackson
et al., 2001; White et al., 2009).
The analytical strategy seeks to introduce drinking variables from T1 to T4 (first
model: yes/no question about alcohol use; second model: yes/no question about binge
drinking) to calculate prevalence over time. Prevalence rates correspond to the
proportions of individuals in each class at each time. To assess the stability of drinking
trajectories over time and to ascertain if there were changes in drinking behaviors over
time, we referred to transition rates. Transition rates represent the proportions of
individuals in different stages at time t + 1 conditional on drinking stage at time t, and
interpreted as probabilities of staying in the trajectory at this time. Models were
estimated by PROC LTA procedures for latent transition analysis with SAS version 9.3
(Lanza et al., 2013) and replicated with Mplus (Muthén and Muthén, 1998-2002).
Missing data on latent class indicators (alcohol and binge variables; 28.9% at T4) were
handled with the maximum likelihood technique and the expectation-maximization
algorithm, assuming that data were missing at random (Collins and Lanza, 2010).
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With Markov modeling, it is also possible to estimate associations of predictors
on baseline membership (T1) and between times via multivariate logistic regression.
However, analysis of predictors of drinking behaviors between times required
measurements of the predictors at each time point, which were not available in our study.
Moreover, in the context of alcohol research, it is particularly relevant to estimate the
effects of predictors on drinking behavior at a significant time. For these reasons, we
ascertained the probability of belonging to a specific alcohol drinking trajectory at T2 (at
conception) via traditional multivariate logistic regression assessing which predictors
may explain the significant change of drinking behavior from the conception period.
We identified which predictors were associated with changes: 1) from drinking
status to abstainer from T1 to T2, and 2) from binge drinker to abstainer from T1 to T2.
The third regression analysis was designed to identify predictors related to stability of
binge drinking status from T1 to T2. Because very few women continued to drink from
T1 to T2 (0.8%), we were unable to look at predictors of stable status. Multivariate
logistic regression was performed with SPSS 13.
3. Results
Table 1 summarizes sample characteristics. The majority (80%) were between 18
and 33 years, with only 24 (10%) below 18 and 5 (2%) above 38. More than half of the
women were part of a couple and were unskilled laborers or menial service workers
(mean for sample = 17.5). The average number of pregnancies was 3.9, with 38 women
who were primiparous (15%), and about a third of them used marijuana in early
pregnancy.
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____________________________________________________________________________________________________________
INSERT TABLE 1
3.1 Proportions and trajectories of alcohol use and binge drinking
Table 2 presents the proportions of alcohol use and binge drinking over study
periods T1 to T4. The proportion of drinkers declined from its peak during the year prior
to pregnancy to the conception period and then rose back in the pregnancy period and
during the year after pregnancy. Similarly, the proportion of binge drinking women
dropped between the year before pregnancy to the conception period, rose during the
pregnancy period and increased substantially by the year after pregnancy.
Figure 1a illustrates the proportions of alcohol use over time but, more
importantly, provides the transition rates of changing status from period to period. The
lowest probability of stay in drinking status was between the year before pregnancy and
the conception period (48%), indicating instability of drinking status at this time. During
the pregnancy period, the majority of drinkers had the probability of staying in the
drinking trajectory. In contrast, one-quarter of drinkers had the chance to move from
drinking to non-drinking behavior a year after delivery. The probability of transitioning
from non-drinking to drinking behavior over time was more stable. At all time periods,
less than 50% of non-drinkers had the probability of moving from non-drinking to
drinking status, and this probability was higher a year after delivery (43%). Transition
probabilities of binge drinking over time are presented in Figure 1b. Transition rates of
changing status from binge drinking to non-binge drinking (which included abstainers
and alcohol users who did not binge drink) were substantially higher over time than
transition rates of not binging to binge drinking status. The probability of staying in the
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binging trajectory was lowest between the year before pregnancy and the conception
period (19%) and was higher between the pregnancy period and a year after delivery
(62%). At all time periods, the probability of moving from non-binging to binging status
was less than 30% for non-bingers. For both alcohol and binge drinking trajectories, the
probability of transitioning from user to abstainer or non-binging status was higher from
the year before pregnancy to the conception period. Status change from non-binging to
binge drinking was greater from the pregnancy period to the postpartum year, while the
probability of moving from abstainer to alcohol user status was greater after conception
and was similar to that reported for the pregnancy period to the postpartum year.
____________________________________________________________________________________________________________
INSERT TABLE 2____________________________________________________________________________________________________________
INSERT FIGURE 1a and 1b 3
Prevalence and transition rates describe drinking trajectories and change over
time. However, they do not provide information about the proportions of participants who
remained non-drinkers or non-bingers over the course of the study. Among participants
who provided data on alcohol use for all four time periods (N = 174), 18.7% were alcohol
drinkers during all four periods, and 12.7% were abstainers. Only 1.6% reported binge
drinking throughout the course of the study. In comparison, 31.1% of women never
binged in all four time periods.
3.2 Variables related to changes in drinking status
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Table 3 presents the results of multivariate logistic regression analysis. Because
the total number of pregnancies was highly correlated with maternal age (rs = 0.772;
p<0.001), two regression models were tested with only one variable at each time period.
Among the potential predictors considered, being in a couple was related to
greater probability of moving from binge drinking status the year before conception to
abstainer status at conception. In contrast, women who reported marijuana use during
conception were less likely to move from binge drinking status the year before
conception to abstainer status at conception. Change from alcohol user to abstainer and
stability of binge drinking status were not related to socioeconomic status or marijuana
use. The results were similar when total number of pregnancies were included in the
regression models (data not shown).
____________________________________________________________________________________________________________
INSERT TABLE 3
4. Discussion
Our analysis of Inuit alcohol consumption is the first to present distinctive
trajectories covering the year before conception to the year after pregnancy. Our results
indicated that the proportions of alcohol use and binge drinking varied considerably
across specific periods related to pregnancy, and that probability of transitioning from
drinking to non-drinking behavior and vice versa changed considerably across these
periods. Yet, most notably, 60% of women did not change status and were alcohol
consumers during all four time periods, indicating that alcohol use in this specific
population is not well understood.
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Drinking trajectories have previously been reported across several years for the
general population (Jackson et al., 2000), specifically during the potentially more
tumultuous periods of adolescence and young adulthood (Berg et al., 2013; Brodbeck et
al., 2013), even among adolescent mothers (Oxford et al., 2003). To our knowledge, only
one other study examined trajectories in the perinatal period (Spears et al., 2010) and
focused on adolescent girls from the USA who were followed during pregnancy at 3 and
6 months and then at 12 months postpartum. The prevalence rate of drinking was lower
than in the Inuit and, as they did not include a measure of binge drinking in their work,
they failed to observe excessive alcohol use and abuse during pregnancy. Among the
Inuit, transition probabilities revealed great instability of drinking status during almost a
3-year period starting the year before pregnancy to the end of the first postpartum year.
Sources of drinking status variations at different time periods are well known to be
multifactorial and may be individual, social, familial and cultural (Arokiasamy, 1995;
Beck et al., 1995; Cooper et al., 1992; Cox and Klinger, 1988; Cutter and O’Farrell,
1984; Gire, 2002; Heath, 2000; Kuntsche et al., 2006), psychosocial (Harrison and
Sidebottom, 2009), or specific factors and situations (Gusfield, 1987; Harford, 1979).
Our findings support the view that both alcohol use and binge drinking status are
more likely to change to abstainer or non-binge drinker in the conception period. Such
changes in alcohol behavior may reflect general pregnancy-related lifestyles and life
habit changes, especially among women who planned the pregnancy (Kim et al., 2012;
Perham-Hester and Gessner, 1997). Alcohol awareness and prevention programs started
to get delivered to the Inuit population of Northern Quebec in the 1990s, (Korhonen,
2004). Changes in drinking behavior in early pregnancy may be the result of these
15
interventions, or prenatal care, which increase population knowledge about the harmful
effects of alcohol use during pregnancy (Badry and Felske, 2013; Nathoo et al., 2013).
Our findings also indicate that Inuit women are more likely to change from
abstainer to alcohol user after the conception period. This outcome is a particular public
health concern as the long-lasting effects of fetal exposure to alcohol are well-
documented. According to Kaskutas (2000) and Branco and Kaskutas (2001), in the
general population, “many women have a limited understanding of the health
consequences of drinking alcohol during pregnancy and a misperception regarding the
amount of alcohol they are consuming” (Montag et al., 2012, p. 441). It is not clear if
trajectories of drinking and binging reported here could be replicated nowadays since the
Inuit are better informed of the effects of maternal alcohol use during pregnancy on child
health and development. However, drinking remains a problem in Nunavik, and alcohol
use and abuse is still present among pregnant women. In contrast, according to our
results, a sub-group of women consistently remained abstainers or non-bingers
throughout pregnancy. Future studies dedicated to FAS prevention should focus on these
abstinent Inuit women, and a qualitative research approach may provide insights to
develop culturally-sensitive prevention and intervention programs based on their
experiences.
Regarding predictors of alcohol use and binge drinking, we reported that being in
a couple is related to a greater probability of moving from binge drinking status the year
before conception to abstainer status at conception. This finding corroborates numerous
studies showing that being married reduces heavy drinking among both men and women
(Cho and Crittenden, 2006; Gmel et al., 2000; Hajema and Knibbe, 1998; Kuntsche et al.,
16
2006; Neve et al., 1997). Similar results have been obtained for women in couples who
are not married (Ebrahim et al., 1998; Gladstone et al., 1997; Perham-Hester and
Gessner, 1997). Quality of and satisfaction with the relationship as well as marital
support are additional influential factors of adoption of drinking type, especially a low
drinking pattern (Holt-Lunstad et al., 2008; Kearns-Bodkin and Leonard, 2005; Leonard
and Eiden, 2007), although being in a couple is associated with greater probability of
moving from binge drinking status the year before conception to abstainer status at
conception.
Our study revealed that marijuana use decreases the likelihood of moving from
binge drinking status the year before conception to abstinence at conception. Gladstone et
al. (1997) and Harrison and Sidebottom (2009) demonstrated that curtailed alcohol use
during pregnancy is more frequent among irregular drinkers, non-smokers and drug non-
users. Concomitant use or abuse of other substances needs to be seen as a factor that may
help identify women at greater risk of being unable to decrease alcohol consumption in
pregnancy or among those wishing to have a child. Several studies have already pointed
out the efficiency of a multidimensional framework in alcohol research and public health
(Demers et al., 2002; Frohlich et al., 2008; Kairouz et al., 2002; Kairouz and Greenfield,
2007).
4.1 Limitations
One limitation of our study is the loss to follow-up after delivery (30%). The
statistical likelihood technique allowed latent transitional class analysis to counter this
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drawback. In addition, information about pregnancy planning was not documented.
Planning a pregnancy is likely to influence alcohol consumption around conception, and
our study could not take this into account in the interpretation of transitional rates from
the year before pregnancy to the conception period. Moreover, our study does not include
spouse drinking status and information about family violence and marital problems.
Women tends to drink more in the context of family problems or when men drink at
home (Health Canada, 2008; National Institute of Alcohol Abuse and Alcoholism, 2008).
Future research has to analyze the impact of these factors on the trend in alcohol use
among pregnant Inuit women. Our study may also present a recall bias (or response bias)
relative to self-reported alcohol use (Greenfield and Kerr, 2008; Grønbæk and Heitmann,
1996; Midanik, 1989; Rehm, 1998). However, our pregnancy alcohol ascertainment
approach has been validated in relation to child cognitive outcomes (Jacobson et al.,
2002). Finally, because data were collected from 1995 to 2000, it would be informative to
document whether proportions and the longitudinal transitioning portrait of drinkers have
changed for the Inuit in subsequent years in which programs tried to increase public
awareness and implement prevention programs.
5. Conclusion
Our results emphasize the importance of future studies on alcohol use around the
pregnancy period to document trajectories of consumption and to identify determinants of
specific drinking trajectory among the Inuit and other indigenous groups. Spotting
transitional periods where alcohol use and binge drinking status are most likely to change
adds to the typical description of prevalent alcohol use in a time period, and help to flag
18
sensitive periods for interventions. Research focusing on motives, contexts and beliefs
surrounding alcohol drinking during pregnancy may also contribute to the development
of culturally-sensitive prevention and intervention programs.
Acknowledgments
We are grateful to the Nunavik population and their organisations for participating
in this research. We thank R. Sun, G. Lebel, E. Lachance, C. Bouffard, K. Poitras, C.
Vézina, J. Gagnon, L. Chiodo, B. Tuttle and N. Dodge for their committed study
involvement, and N. Forget-Dubois for her support in data analysis. This manuscript was
edited by Ovid M. Da Silva.
19
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Table 1: Sample characteristics N Characteristics
Age (years) – mean (SD) 248 24.9 (5.8)
Marital status (In a couple) – % [95% CI] 248 68.1% [62.3-73.9]
SES – % [95% CI] 247
Unskilled laborers, menial service workers 55.5% [49.3-61.7]
Machine operators, semiskilled workers 23.9% [18.6-29.2]
Skilled craftsmen, clerical, sales workers 16.6% [12.0-21.2]
Technical, major or medium-size business or professional
4.0 [1.6-6.5]
Total pregnancies – mean (SD) 248 3.9 (2.3)
Marijuana use at conception (Yes) – % [95% CI] 248 35.1 [29.1-41.1]
CI: confidence interval; SD: standard deviation; SES: socioeconomic status based on the Hollingshead Index (Hollingshead, 2011).
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Table 2: Proportions of alcohol and binge drinking from the year before conception to the end of the postnatal year (N = 248)
Proportions
Alcohol use Drinking Non-drinking
Before conception (T1) .73 .27
At conception (T2) .36 .64
During pregnancy (T3) .60 .40
Postnatal year (T4) .62 .38
Binge drinking Binging Non-binging
Before conception (T1) .54 .46
At conception (T2) .10 .90
During pregnancy (T3) .19 .81
Postnatal year (T4) .33 .67
29
Table 3: Multivariate logistic regression of personal and SES variables on alcohol and binge drinking trajectories at conception
Covariates OR CI p-value
Decreasing alcohol use (N=93)
Age – 14-24 years. 1.33 0.78-2.25 0.29
Marital status – In a couple 0.99 0.56-1.74 0.96
SES – Low 1.13 0.67-1.90 0.65
Marijuana – Yes 0.64 0.37-1.09 0.10
Decreasing binge drinking (N=107)
Age – 14-24 years 0.80 0.47-1.35 0.40
Marital status – In a couple 1.74 0.99-3.07 0.05*
SES – Low 1.59 0.94-2.70 0.08
Marijuana – Yes 0.41 0.24-0.72 0.002*
Constant binge drinking (N=26)
Age – 14-24 years 2.12 0.90-5.00 0.09
Marital status – In a couple 1.91 0.81-4.47 0.14
SES – Low 1.13 0.50-2.59 0.80
Marijuana – Yes 0.81 0.35-1.89 0.63
OR: odds ratio; CI: confidence interval; SES: socioeconomic status
30
Figure 1a: Proportions and transition rates of alcohol drinking over time
Figure 1b: Proportions and transition rates of binge drinking over time
31
A year before conception At conception
During pregnancy
A year after delivery
Non-drinking
Drinking
27% 64% 40% 38%
73% 36% 60% 62%
97% 60% 57%
48% 98% 75%
40% 43%3%
52% 2% 25%
A year before conception At conception
During pregnancy
A year after delivery
Non-binging
Binging
46% 90% 81% 67%
54% 10% 19% 33%
100%% 84% 74%
19% 46% 62%
16% 26%0%
80% 54% 38%
27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%27%
62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%62%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%73%
38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%38%
60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%60%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%36%
40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%40%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%64%
46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%46%
33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%33%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%54%
67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%67%
19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%19%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%10%
81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%81%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%90%