Cohort Profile: The Triple B Pregnancy Cohort Study: A longitudinal study of the relationship between alcohol, tobacco and other substance use during pregnancy and the health and well-being of Australian children and families

Cohort Profile: The Triple B Pregnancy Cohort Study: A longitudinal study of the relationship... Summary The Triple B Pregnancy Cohort Study investigates the effects of parental alcohol, tobacco and other substance use on infant development and family functioning. The study (also known as: Bumps, Babies and Beyond), recruited two sub-samples: (i) a general antenatal clinic sample of pregnant women and their partners (n = 1534 women; 842 of their partners); and (ii) a smaller sample of pregnant women with diagnosed substance use disorders (SUD; n = 89 women only). Participants were recruited through public antenatal clinics attached to major hospitals and area health services in New South Wales (NSW) and Western Australia (WA). Of 4068 eligible women from the general antenatal clinics, 37.7% participated, with equivalent numbers for the SUD clinics being 198, 44.9%. There were 1453 and 65 live births from the two groups, respectively, with a total of 1414 and 65 mothers in the two groups, respectively. Data were also collected on 1264 (86.9%) of 1455 eligible partners of women recruited through the general antenatal clinics. The study collected repeated measures across pregnancy (trimesters 1, 2 and 3), and at 8 weeks and 12 months postnatally; retention at 12 months was 84.0% and 73.8% for mothers in the general antenatal and specialist SUD clinics, respectively. The data collected include demographic, parental, familial and infant factors, with a focus on parental substance use and mental health, parenting practices, familial functioning and infant development. Following pregnancy awareness, 42% of women consumed alcohol, 12% smoked tobacco and 4% used illicit drugs at some stage in pregnancy. Comprehensive assessments have been conducted with infants at 12 months to test numerous developmental domains, including cognitive, motor and language skills, along with measures of social and emotional functioning. Data access enquiries can be made to the principal investigator [delyse.hutchinson@deakin.edu.au]. Why was the cohort set up? In 2010, the Australian National Medical Health Research Council (NHMRC) funded this longitudinal pregnancy cohort study to address limitations in knowledge of the effects of parental substance use on infants and families. The Triple B Pregnancy Cohort Study (known as: Bumps, Babies and Beyond), includes two sub-samples: (i) a public antenatal clinic sample of pregnant women and their partners, and (ii) a smaller sample of pregnant women with diagnosed substance use disorders. Participants were recruited though public antenatal clinics at major hospitals and health services in New South Wales (NSW) and Western Australia (WA). The study aims to examine: the effects of parental substance use in pregnancy on infant development (e.g. cognitive, motor, language and socio-emotional development) and family functioning; the extent to which substance use is interrelated among couples; and the influence substance use may have on parents’ respective substance use patterns. The study aims to contribute to improved public health services. The study represents a significant investment in longitudinal research, which builds on a history of quality Australasian longitudinal research. The Developmental Origins of Health and Disease (DOHaD)1 framework posits that early life environmental exposures induce critical changes in development which have long-term impacts on health and disease risk. Consistent with this framework, clinical studies of high-risk samples of parents diagnosed with substance use disorders suggest that parental substance use has significant adverse impacts on infant and child development.2,3 For example, substance-dependent pregnant women and their infants have an increased risk of obstetric, fetal and neonatal complications. These include miscarriage, prematurity, low birthweight for gestational age, fetal alcohol spectrum disorders (FASD), neonatal abstinence syndrome (NAS) and longer-term deficits in children’s physical, cognitive, behavioural and emotional development.4–7 The primary limitation of clinical studies is that the data are often derived from small-scale cross-sectional surveys, so that the effects over time are not known and the findings are not generalizable to the population. Longitudinal studies provide insights into potential causes of health problems, as well as factors capable of preventing or moderating problems. Emerging evidence from general population-based longitudinal studies suggests that the effect of parental substance use can vary considerably as a function of parent gender, pattern and type of substance use, and the presence of associated socioeconomic, physical health and psychosocial risk factors.2,3,8–11 Parental substance misuse may impact adversely on children and families via direct and indirect pathways. For example, parental substance use can impact negatively on the quality of the marital/intimate partner relationship and the parent-child relationship by reducing family cohesion and increasing conflict and violence.12,13 However, there is a dearth of data on parental substance use in the prenatal period, particularly defined by timing of exposure during pregnancy (i.e. pre-pregnancy awareness and at each trimester following awareness), with most research focusing solely on maternal consumption and neonatal outcomes. Furthermore, many studies use poor measures of parental substance use (e.g. retrospective reports of use). Notably, few assess partner substance use and its impacts. As a result, there are major gaps in current knowledge about the extent to which perinatal (pre- and postnatal) parental substance use impacts on early child development and family functioning, and the mechanisms by which these influences occur, particularly for low/moderate levels of use which are the most frequent levels of substance use among Australian parents.14 This cohort protocol aims to: (i) describe the Triple B Cohort samples and study methodology; and (ii) provide key summary data on perinatal substance use patterns, along with findings from three recent publications. The Triple B Cohort Study is led by the National Drug and Alcohol Research Centre (NDARC) at the University of New South Wales (UNSW) Australia and the National Drug Research Institute (NDRI) at Curtin University, in collaboration with Deakin University, Sydney University, the University of Queensland, the Murdoch Childrens Research Institute and the University of Melbourne. The study has been supported by the NHMRC (2010–14), Australian Rotary Health (ARH; 2012–13) and the Foundation for Alcohol Research and Education (FARE; 2010–11). Additionally, PhD candidates on the project have been funded through ARH; the NDARC Education Trust (NET), Macquarie University and both the Australian Centre for Perinatal Science (ACPS) and NDARC at UNSW. Ethics approval was granted by relevant university, hospital and health services human research ethics committees. Who is in the cohort? The study used a prospective cohort design. Pregnant women were recruited through general antenatal clinics (N = 1534: NSW = 1246; WA = 288) and specialist drug and alcohol antenatal clinics (N = 89; NSW = 59; WA = 30) in public hospitals and health services in NSW and WA between 2009 and 2013. Participating hospitals in NSW were the Royal Prince Alfred Hospital, Camperdown; the Royal Women’s Hospital, Randwick; and Liverpool Hospital, Liverpool. Participants in Western Australia were recruited through the King Edward Memorial Hospital, Subiaco. Pregnant women were invited to participate in the study by research officers who attended antenatal clinics at each hospital, across all days and months of the year, to represent (proportionally) all clinics operating at each recruitment site. A standardized script was used to describe the study to women. Eligibility criteria included: being pregnant; being over 15 years of age; having no major medical complications (mother or fetus); intention of mother or both parents to be the primary caregiver/s; being mentally able to complete assessments; possessing sufficient literacy in English; and informed consent. As outlined in Figures 1 and 2, 6597 pregnant women [255 from the specialist substance use disorder (SUD) cohort] were approached and informed about the study; 4266 (198 from the specialist SUD cohort) of these met eligibility criteria and were invited to participate. A total of 1534 (37.7%) and 89 (44.9%) women from the general and specialist cohorts, respectively, provided consent and completed at least one study measure. The participation rates of eligible women for individual hospitals ranged from 22.2% to 55.0%, with an overall participation rate of 44.0% for NSW and 25.0% for WA. Figure 1 View largeDownload slide Triple B Pregnancy Cohort Study: study flow diagram of mother, partner and infant participation rates (N = 1534 families) for the general antenatal sample. *The 8-week follow-up interview for partners was introduced after the pilot study. As such, 8-week data were unavailable for 60 participating partners, as it was not offered. **In some families, only infants were assessed at 12 months. Figure 1 View largeDownload slide Triple B Pregnancy Cohort Study: study flow diagram of mother, partner and infant participation rates (N = 1534 families) for the general antenatal sample. *The 8-week follow-up interview for partners was introduced after the pilot study. As such, 8-week data were unavailable for 60 participating partners, as it was not offered. **In some families, only infants were assessed at 12 months. Figure 2 View largeDownload slide Triple B Pregnancy Cohort Study. Study flow diagram of mother and infant participation rates (N = 88) for the specialist substance use disorder (SUD) antenatal sample. **In some families, only infants were assessed at 12 months; in total, 50 families remained in the cohort. Figure 2 View largeDownload slide Triple B Pregnancy Cohort Study. Study flow diagram of mother and infant participation rates (N = 88) for the specialist substance use disorder (SUD) antenatal sample. **In some families, only infants were assessed at 12 months; in total, 50 families remained in the cohort. Participation rates Figures 1 and 2 present study flow diagrams of mother and infant participation rates, and of partners, separated by non-exposed and substance use-exposed groups, respectively. Of those who participated, 79 withdrew (six from the specialist SUD cohort), and a further 65 (18 from the specialist cohort) were lost to follow-up before giving birth (attrition rate: 7.8% and 31.5% for general and specialist SUD cohorts, respectively). The remaining 1414 mothers in the general cohort gave birth to a total of 1453 offspring which included 37 twin pairs and one set of triplets. In the specialist SUD cohort, 65 singletons were born. Parents of twins and triplets were asked to complete a separate survey about each child. Data were collected on 1264 (86.87%) of eligible partners from the general cohort, either directly (n = 842), or indirectly (n = 422) via maternal report. Cohort characteristics The characteristics of participating mothers and infants are presented in Table 1. Partner characteristics are presented in Table 2. Maternal and partner data were collected in trimester 3; data on the infant were collected at the 8-weeks postnatal follow-up and were derived from infant Blue Books completed at birth by hospital staff. Compared with the Australian population, the Triple B general antenatal cohort is similar to the Australian population on rates of employment (z = 1.40; P = 0.08), and the proportion of participants of Aboriginal or Torres Strait Islander origin (z = −0.53; P = 0.23). The sex distribution of infants was also similar to Australian population figures (z = −0.46; P = 0.32), although other infant characteristics differed from the general population, with longer gestation at birth (z = 13.8; P < 0.001; Somers’ d = 0.000; 95% CI −0.066, 0.068), higher birthweight (z = 3.82; P = 0.001; Somers’ d = 0.07; 95% CI −0.01, 0.13) and a higher proportion of twins/multiple births (z = 4.55; P < 0.001; Cohen's h = 0.12; 95% CI 0.042, 0.186). Mothers in the cohort were also older (z = 12.86; P < 0.001, Somers’ d = 0.11; 95% CI 0.05, 0.17), more socioeconomically advantaged (SEIFA; t1577 = 31.56; P < 0.001; Cohen’s d = 0.47; 95% CI 0.42, 0.52), and better educated than the general population (university educated, z = 18.84; P < 0.001; Cohen’s h = 0.49; 95% CI 0.44, 0.55). In addition, binomial tests showed that there were more women born overseas (z = 15.03; P < 0.001; Cohen’s h = 0.36; 95% CI 0.31, 0.41), a higher proportion of nulliparous women (z = 10.70; P < 0.001; Cohen’s h = 0.28; 95% CI 0.22, 0.33) and fewer living in single-parent households (z = −11.45; P < 0.001; Cohen’s h = 0.36; 95% CI 0.31, 0.41) compared with general population figures. Table 1 Mother and infant cohort characteristics and comparison with Australian population data Mothers’ characteristics  General cohort at trimester 3 (n = 1498)a  Specialist SUD cohort at trimester 3 (n = 81)a  Australian population  Mean age (years)  32.5 (SD = 5.1) Range: 17–52 Median: 33.0  28.8 (SD = 5.6) Range: 17–42 Median: 28.0  In 2013, the median age of Australian women giving birth was 30.8 years29  Mean Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)  1047.2 (SD = 57.8) Range: 790–1164  1028.7 (SD = 60.8) Range: 853–1,122  IRSAD is standardized to a distribution with a mean score of 1000, and a standard deviation of 100.30  Education  n (%)  n (%)   Year 10 or below  92 (6.1)  47 (58.0)  In 2014, 63.6% of females aged 20–64 had a post-high school qualification; 31.0% had a university degree. Corresponding figures for 30–34 year-old females show that 74.1% had a post-school qualification; 43.3% had a university degree31   Year 12  170 (11.4)  9 (11.1)   Diploma, trade qualification  223 (14.9)  19 (23.4)   University/college degree  1008 (67.3)  6 (7.4)  Employment       Employed (full or part time)  1001 (66.8)  12 (14.8)  In 2012–13, 65.1% of females aged 20–74 were employed32  Country of birth       Australia  832 (55.5)  72 (88.9)  In 2011, 27% of people living in Australia were born overseas33 and 15.7% of the population were born in non main English-speaking countries34   Other English-speaking  279 (18.6)  6 (7.4)   Non main English-speaking  382 (25.5)  3 (3.7)  Single-parent household  90 (6.0)  44 (54.3)  In 2012, 17.2% of families with children under 15 were single-mother families35  Aboriginal/Torres Strait Islander  34 (2.3)  12 (14.8)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  Parity         0  841 (56.1)  28 (34.6)  In 2012, 42.4% of mothers had no previous pregnancies; 33.2% had one; 14.1% had two; 8.5% had three or more19   1  439 (29.3)  29 (35.8)   2  150 (10.0)  10 (12.4)   3 or more  68 (4.1)  12 (14.8)    Infants’ characteristics  General cohort at trimester 3 (n = 1453)a  Specialist SUD cohort at trimester 3 (n = 65)a  Australian population      n (%)  n (%)    Female  696 (47.9)  28 (43.1)  In 2012, 48.5% of live births were females19  Twins/triplets  77 (5.3)  0 (0.0)  In 2012, 3.0% of births were twins or other multiple births19  Mean gestation in weeks  39.2 (SD = 1.82)  Range: 27–43  38.3 (SD = 2.6) Range: 30–42  In 2012, the mean gestational age for all babies was 38.7 weeks19  Mean birthweight in kilograms  3.42 (SD = 0.55) Range: 0.98–5.70  3.13 (SD = 0.67) Range: 1.33–5.24  In 2011, the mean birthweight of liveborn babies was 3.37kg37  Mothers’ characteristics  General cohort at trimester 3 (n = 1498)a  Specialist SUD cohort at trimester 3 (n = 81)a  Australian population  Mean age (years)  32.5 (SD = 5.1) Range: 17–52 Median: 33.0  28.8 (SD = 5.6) Range: 17–42 Median: 28.0  In 2013, the median age of Australian women giving birth was 30.8 years29  Mean Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)  1047.2 (SD = 57.8) Range: 790–1164  1028.7 (SD = 60.8) Range: 853–1,122  IRSAD is standardized to a distribution with a mean score of 1000, and a standard deviation of 100.30  Education  n (%)  n (%)   Year 10 or below  92 (6.1)  47 (58.0)  In 2014, 63.6% of females aged 20–64 had a post-high school qualification; 31.0% had a university degree. Corresponding figures for 30–34 year-old females show that 74.1% had a post-school qualification; 43.3% had a university degree31   Year 12  170 (11.4)  9 (11.1)   Diploma, trade qualification  223 (14.9)  19 (23.4)   University/college degree  1008 (67.3)  6 (7.4)  Employment       Employed (full or part time)  1001 (66.8)  12 (14.8)  In 2012–13, 65.1% of females aged 20–74 were employed32  Country of birth       Australia  832 (55.5)  72 (88.9)  In 2011, 27% of people living in Australia were born overseas33 and 15.7% of the population were born in non main English-speaking countries34   Other English-speaking  279 (18.6)  6 (7.4)   Non main English-speaking  382 (25.5)  3 (3.7)  Single-parent household  90 (6.0)  44 (54.3)  In 2012, 17.2% of families with children under 15 were single-mother families35  Aboriginal/Torres Strait Islander  34 (2.3)  12 (14.8)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  Parity         0  841 (56.1)  28 (34.6)  In 2012, 42.4% of mothers had no previous pregnancies; 33.2% had one; 14.1% had two; 8.5% had three or more19   1  439 (29.3)  29 (35.8)   2  150 (10.0)  10 (12.4)   3 or more  68 (4.1)  12 (14.8)    Infants’ characteristics  General cohort at trimester 3 (n = 1453)a  Specialist SUD cohort at trimester 3 (n = 65)a  Australian population      n (%)  n (%)    Female  696 (47.9)  28 (43.1)  In 2012, 48.5% of live births were females19  Twins/triplets  77 (5.3)  0 (0.0)  In 2012, 3.0% of births were twins or other multiple births19  Mean gestation in weeks  39.2 (SD = 1.82)  Range: 27–43  38.3 (SD = 2.6) Range: 30–42  In 2012, the mean gestational age for all babies was 38.7 weeks19  Mean birthweight in kilograms  3.42 (SD = 0.55) Range: 0.98–5.70  3.13 (SD = 0.67) Range: 1.33–5.24  In 2011, the mean birthweight of liveborn babies was 3.37kg37  aIndividual sample sizes for each characteristic vary slightly due to missing data. Table 2 Partner cohort characteristics and comparison with Australian population data Partner characteristics  General antenatal cohort at trimester 3 (n = 1245)a,b  Australian population  Age in years  35.0 (SD = 5.9)   Range: 17–59  Median: 35.0  The median age of fathers for births registered in 2013 was 33.0 years29    n (%)    Same-sex (female)  15 (1.2)  In 2011, 0.7% of Australian couples were same-sex couples38  Education     Year 10 or below  111 (8.9)  In 2014, 65.6% of males aged 20–64 had a post-high school qualification, with 26.0% having a university degree31   Year 12  154 (12.4)   Diploma, trade qualification  260 (20.9)   University/college degree  692 (55.6)  Employment    In 2012–13, 78.8% of males aged 20–74 were employed32   Employed (full or part time)  1145 (91.9)  Country of birth    In 2011, 27% of people living in Australia were born overseas, and 15.7% of the population were born in non main English-speaking countries34,39   Australia  651 (52.3)   Other English-speaking  284 (22.8)   Non main English-speaking  284 (22.8)  Aboriginal/Torres Strait Islander  19 (1.5)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  Partner characteristics  General antenatal cohort at trimester 3 (n = 1245)a,b  Australian population  Age in years  35.0 (SD = 5.9)   Range: 17–59  Median: 35.0  The median age of fathers for births registered in 2013 was 33.0 years29    n (%)    Same-sex (female)  15 (1.2)  In 2011, 0.7% of Australian couples were same-sex couples38  Education     Year 10 or below  111 (8.9)  In 2014, 65.6% of males aged 20–64 had a post-high school qualification, with 26.0% having a university degree31   Year 12  154 (12.4)   Diploma, trade qualification  260 (20.9)   University/college degree  692 (55.6)  Employment    In 2012–13, 78.8% of males aged 20–74 were employed32   Employed (full or part time)  1145 (91.9)  Country of birth    In 2011, 27% of people living in Australia were born overseas, and 15.7% of the population were born in non main English-speaking countries34,39   Australia  651 (52.3)   Other English-speaking  284 (22.8)   Non main English-speaking  284 (22.8)  Aboriginal/Torres Strait Islander  19 (1.5)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  a Individual sample sizes for each characteristic vary slightly due to missing data. bIncludes participating and non-participating partners, where data are available. By contrast, the Triple B specialist SUD cohort reported higher levels of unemployment (z = −9.50; P < 0.001; Cohen’s h = 1.09; 95% CI 0.889, 1.34), higher proportions of Aboriginal or Torres Strait Islander participants (z = 7.10; P < 0.001; Cohen’s h = 0.47; 95% CI 0.22, 0.56), higher proportions of Australian-born mothers (z = −0.32; P = 0.001; Cohen’s h = 0.41; 95% CI 0.22, 0.68) and lower birthweights (z = −2.80; P = 0.005; Somers’ d = −0.41; 95% CI −0.75, −0.07) when compared with the Australian population. Mothers were also younger (z = −2.89; P = 0.004; Somers’ d = 0.11; 95% CI 0.05, 0.17), less educated (university educated; z = −0.65; P < 0.001; Cohen’s h = 0.90; 95% CI 0.69, 1.18), with more living in single-parent households (z = 8.85; P < 0.001; Cohen’s h = 0.80; 95% CI 0.58,1.03) compared with the Australian population. There were no differences in parity (z = −1.43; P = 0.08), the number of multiple births (z = −1.41; P = 0.08), infant gestational age (z = −0.26; P = 0.80) and infant sex distribution (z = −0.76; P = 0.22), between the specialist SUD cohort and the Australian population, although mothers in the specialist cohort were somewhat more socioeconomically advantaged (t = 4.25; P < 0.001; Cohen’s d = 0.29; 95% CI 0.07, 0.50). Demographic data were provided by 824 (97.9%) of the 842 participating partners for mothers in the general antenatal cohort. In addition, mothers in this group reported partner demographic characteristics for 418 (68.1%) of the 614 eligible partners who refused to participate. Comparisons with Australian population data suggest that the proportion of partners of Aboriginal or Torres Strait Islander origin was less than in the general population (z = −2.10; P = 0.02). However, like mothers, partners in the cohort appear to be slightly older (z = 10.55; P < 0.001; Somers’ d = 0.27; 95% CI 0.20, 0.34), more highly educated (university education; z = 24.54; P < 0.001; Cohen’s h = 0.64; 95% CI 0.58, 0.70), and more likely to be born overseas compared with the general population (z = 15.41; P < 0.001; Cohen’s h = 0.41; 95% CI 0.35, 0.47). In addition, the rate of employment was higher among partners in the cohort (z = 13.17; P < 0.001; Cohen’s h = 0.47; 95% CI 0.42, 0.53) and there was a higher proportion of same-sex partners in comparison with the general population (z = 2.20; P = 0.014; Cohen’s h = 0.05; 95% CI 0.01, 0.11). Comparisons were also conducted on the demographic characteristics of partners from the general cohort as a function of whether data were obtained via self-report, or indirectly via maternal report. These comparisons showed that the two partner groups did not differ on employment status (93.7% versus 95.2% in full- or part-time employment; χ2(1, N = 1215) = 1.06; P = 0.30), same-sex partner relationships [1.5% versus 0.7% female for partners who self-reported and those who were reported on indirectly, respectively [χ2(1, N = 1224) = 1.41; P = 0.24]; or Aboriginal or Torres Strait Islander origin [1.5% versus 1.7%; χ2(1, N = 1217) = 0.05; P = 0.83). Nevertheless, participating partners were slightly younger than refusers (mean age 34.7 versus 35.5 years; t1215 = −2.35; P = 0.01; Cohen’s d = 0.14; 95% CI 0.02, 0.26), and reported higher educational attainment [60.4% versus 50.1% completed university/college; χ2(1, N = 1245) = 11.75; P = 0.001; ϕ = 0.09; 95% CI 0.02, 0.19] . How often have they been followed up? Five assessment points are shown in Table 3. These include: trimester 1 (conception to 12 weeks), trimester 2 (13 weeks to 27 weeks), trimester 3 (28 weeks to birth) and an 8-week follow-up (8 weeks postnatal). A comprehensive developmental follow-up occurred at infant age 12 months. Mothers were assessed at all time points; partners at trimester 3, 8 weeks postnatal and the 12-month follow-up; and infants at the 8-week and 12-month follow-up. Survey response rates for eligible mothers and infants are presented in Figure 1. Table 3 Assessment schedule and methods of the Triple B Pregnancy Cohort Study Subject  Pregnancy trimester 1  Pregnancy trimester 2  Pregnancy trimester 3  Postnatal 8 weeks  Postnatal 12 months  Mother  Interview Questionnaire  Interview Questionnaire  Interview Questionnaire Urine sample  Interview Questionnaire Blue Book Buccal swab  Interview Questionnaire Observational assessment  Partner  –  –  Interview Questionnaire  Interview Questionnaire Buccal swab  Interview Questionnaire Observational assessment  Infant offspring  –  –  –  Blue Book Developmental assessment Buccal swab  Developmental / observational assessments Buccal swab  Subject  Pregnancy trimester 1  Pregnancy trimester 2  Pregnancy trimester 3  Postnatal 8 weeks  Postnatal 12 months  Mother  Interview Questionnaire  Interview Questionnaire  Interview Questionnaire Urine sample  Interview Questionnaire Blue Book Buccal swab  Interview Questionnaire Observational assessment  Partner  –  –  Interview Questionnaire  Interview Questionnaire Buccal swab  Interview Questionnaire Observational assessment  Infant offspring  –  –  –  Blue Book Developmental assessment Buccal swab  Developmental / observational assessments Buccal swab  In instances where women commenced participation after trimester 1 or 2, pregnancy assessments were completed for earlier waves retrospectively. What is attrition like? Attrition across the five waves of data collection for the general antenatal cohort has been low (Figure 1). Of the 1399 mothers remaining in the cohort following delivery, 118 (8.4%) withdrew or were lost to further follow-up, such that the total attrition rate at 12 months from the original cohort of 1534 was 16.0% (i.e. 84.0% retention). Of the 1436 infants included in the study, developmental data were collected from 1310 (91.2%) at the 12-month follow-up. Of the 842 general antenatal cohort partners who participated directly in the study, 57 (6.8%) withdrew or were lost to follow-up at 8 weeks, and a further 74 (8.8%) at 12 months (resulting in a total retention rate of 84.4%). Attrition rates for mothers from the specialist SUD drug and alcohol antenatal clinics were higher than for the general antenatal population [Figure 2; 46.1% versus 16.0%; χ2(1, N = 1623) = 52.5; P < 0.001; ϕ = 0.18; 95% CI 0.10, 0.26]. After infant delivery, 61 (68.5%) mothers remained in the study and, by 12 months, another 15 (24.6%) participants had withdrawn or were lost to follow-up, leaving a final retention rate of 53.9% from the original cohort. Mothers in the both cohorts who withdrew or were lost to follow-up by 12 months were younger than those who continued (general cohort mean age 30.8 versus 33.1 years; t289.8 = −5.47; P < 0.001; Cohen’s d = 0.44; 95% CI 0.30, 0.58; specialist cohort mean age 28.2 versus 30.2 years; t77.3 = −1.69; Cohen’s d = 0.37; 95% CI −0.06, 0.80) and had higher rates of unemployment [51.8% versus 30.0%; χ2(1, N = 1623) = 44.32; P < 0.001; ϕ = 0.17; 95% CI 0.10, 0.24]. In addition, participants in the general cohort who withdrew or were lost to follow-up at 12 months reported lower socioeconomic backgrounds through their Socio-Economic Indexes for Areas (SEIFA) scores (1027.7 versus 1050.5; t314.4 = −5.14; P < 0.001; Cohen’s d = 0.40; 95% CI 0.26, 0.54) and were more likely to be from WA than from NSW (31.3% versus 12.4%; χ2[1, N = 1534] = 72.74; P < 0.001; ϕ = 0.20; 95% CI 0.12, 0.28). Comparison of available infant data for both the general and the specialist SUD antenatal cohort who did complete the 12-month development assessment with those who did not, showed no differences in sex [general, 55.0% versus 51.8% male; χ2(1, N = 1453) = 0.49; P = 0.48; specialist, 58.8% versus 56.3% male; χ2(1, N = 55) = 0.03; P = 0.85], birthweight (general, 3.41 kg versus 3.42 kg; t1424 = −1.55; P = 0.44; specialist, 2.97 kg versus 3.18 kg; t56 = −1.07; P = 0.14), 5-min Apgar scores (general, 8.90 versus 8.93; t86.38 = −0.38; P = 0.35; specialist, 8.70 versus 8.80; t38 = −0.30; P = 0.38) and weeks’ gestation at birth (general, 38.88 versus 39.23; t140.25 = −1.59; p = 0.06; specialist, 35.13 versus 38.33; t58 = −0.27; p = 0.40). What has been measured? Table 4 provides a detailed overview of the measures included at each wave. Table 4 Mother, partner and infant measures at each assessment Parent measures  Trimester 1  Trimester 2  Trimester 3  8 weeks postnatal  12 months postnatal  Parent and household demographics             Birth date, gender, country of birth, Family composition, education, SEIFA40  –  –  ✓  –  –   Employment, income  ✓  ✓  ✓  ✓  ✓   Religiosity  –  –  ✓  –  ✓  Maternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  ✓  ✓  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  ✓  ✓  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43,44  ✓  ✓  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment  ✓  ✓  ✓  ✓  ✓  Paternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  –  –  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  –  –  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43  –  –  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment      ✓  ✓  ✓  Pre-conception             Alcohol, tobacco, illicit substance use, maternal – Q/F  –  –  ✓  –  –   Alcohol, tobacco, illicit substance use, paternal – Q/F  –  –  ✓  –  –   Pregnancy planning  –  –  ✓  –  –  Parent relationship functioning             Relationship adjustment/satisfaction, maternal45  –  –  ✓  –  ✓   Relationship adjustment/satisfaction, paternal45  –  –  ✓  –  ✓   Spousal abuse, maternal46  –  –  ✓  –  ✓   Spousal abuse, paternal46  –  –  ✓  –  ✓  Maternal general health             Diet (24-h food diary)/vitamin/supplement use  –  –  ✓  ✓  ✓   Physical health  –  –  ✓  ✓  ✓   Physical activity  –  –  ✓  –  ✓   Sexual health  –  –  ✓  ✓  ✓   Medical treatment  –  –  ✓  ✓  ✓   Pregnancy complications  –  –  ✓  ✓  –   Sleep  –  –  –  ✓  ✓  Paternal general health             Diet (2-h food diary)  –  –  ✓  –  ✓   Physical health  –  –  ✓  –  ✓   Physical activity  –  –  ✓  –  ✓   Medical treatment  –  –  ✓  –  ✓   Sleep  –  –  –  ✓  ✓  Parent measures  Trimester 1  Trimester 2  Trimester 3  8 weeks postnatal  12 months postnatal  Parent and household demographics             Birth date, gender, country of birth, Family composition, education, SEIFA40  –  –  ✓  –  –   Employment, income  ✓  ✓  ✓  ✓  ✓   Religiosity  –  –  ✓  –  ✓  Maternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  ✓  ✓  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  ✓  ✓  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43,44  ✓  ✓  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment  ✓  ✓  ✓  ✓  ✓  Paternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  –  –  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  –  –  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43  –  –  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment      ✓  ✓  ✓  Pre-conception             Alcohol, tobacco, illicit substance use, maternal – Q/F  –  –  ✓  –  –   Alcohol, tobacco, illicit substance use, paternal – Q/F  –  –  ✓  –  –   Pregnancy planning  –  –  ✓  –  –  Parent relationship functioning             Relationship adjustment/satisfaction, maternal45  –  –  ✓  –  ✓   Relationship adjustment/satisfaction, paternal45  –  –  ✓  –  ✓   Spousal abuse, maternal46  –  –  ✓  –  ✓   Spousal abuse, paternal46  –  –  ✓  –  ✓  Maternal general health             Diet (24-h food diary)/vitamin/supplement use  –  –  ✓  ✓  ✓   Physical health  –  –  ✓  ✓  ✓   Physical activity  –  –  ✓  –  ✓   Sexual health  –  –  ✓  ✓  ✓   Medical treatment  –  –  ✓  ✓  ✓   Pregnancy complications  –  –  ✓  ✓  –   Sleep  –  –  –  ✓  ✓  Paternal general health             Diet (2-h food diary)  –  –  ✓  –  ✓   Physical health  –  –  ✓  –  ✓   Physical activity  –  –  ✓  –  ✓   Medical treatment  –  –  ✓  –  ✓   Sleep  –  –  –  ✓  ✓  What has it found? Data on alcohol and substance use in pregnancy and the postnatal period are presented in Table 5. Rates of alcohol, tobacco and illicit substance use during pregnancy were highest in the period preceding pregnancy awareness, and decreased considerably after pregnancy awareness in the general cohort [trimester 1 before versus afternawareness [χ2(1, N = 1302) = 548.48; P < 0.00; OR = 0.03; 95% CI OR 0.01, 0.04; χ2(1, N = 1300) = 108.04, P < 0.001; OR = 0.01; 95% CI OR 0.00, 0.05; χ2(1, N = 1301) = 36.36, P < 0.001; OR = 0.05; 95% CI OR 0.01, 0.18, respectively]. For women in the specialist cohort, decreases in alcohol and illicit substance use following pregnancy awareness were also highest in trimester 1 [χ2(1, N = 70) = 20.17; P < 0.001; OR = 0.04; 95% CI OR 0.00, 0.27; χ2(1, N = 70) = 14.00; P < 0.001; OR = 0.00; 95% CI OR 0.00, 0.30]. Tobacco use, however, remained unchanged [χ2(1, N = 70) = 0.67; P = 0.414 before and after pregnancy awareness in trimester 1]. Table 5 Alcohol and other substance use in the Triple B Cohort during pregnancy and following delivery   Trimester 1 pre-awareness N = 1389an (%)   Trimester 1 post-awareness N = 1599bn (%)   Trimester 2 N = 1554 n (%)   Trimester 3 N = 1447 n (%)   8 weeks postnatal N = 1449 n (%)   Alcohol  General  Specialist  General  Specialist  General  Specialist  General  Specialist  General  Specialist  Typical frequency of consumption                       Never  503 (38.3)  36 (46.8)  1229 (80.9)  62 (78.5)  1038 (70.6)  69 (82.1)  977 (70.4)  50 (83.3)  530 (38.1)  35 (59.3)   Less than once per month  158 (12.0)  7 (9.1%)  100 (6.6)  6 (7.5)  129 (8.8)  4 (4.8)  104 (7.5)  5 (8.3)  225 (16.2)  14 (23.7)   Once per month  35 (2.7)  6 (7.8%)  34 (2.2)  2 (2.5)  72 (4.9)  5 (6.0)  52 (3.8)  1 (1.7)  82 (5.9)  3 (5.1)   2–3 times per month  74 (5.6)  –  55 (3.6)  1 (1.3)  87 (5.9)  1 (1.2)  86 (6.2)  –  105 (7.6)  1 (1.7)   1–2 times per week  308 (23.5)  13 (16.9)  84 (5.5)  6 (7.6)  121 (8.2)  3 (3.6)  134 (9.7)  4 (6.7)  273 (19.6)  5 (8.5)   3–4 times per week  133 (10.1)  9 (11.7)  11 (0.7)  2 (2.5)  18 (1.22)  1 (1.2)  22 (1.6)  –  118 (8.5)  –   5–6 times per week  40 (3.1)  3 (3.9)  1 (0.1)  –  1 (0.1)  1 (1.2)  4 (0.3)  –  29 (2.1)  1 (1.7)   Daily  61 (4.7)  3 (3.9)  6 (0.4)  –  4 (0.3)  –  8 (0.6)  –  28 (2.0)  –  Drinkers:  809  41  291  17  432  15  410  10  860  24  Median number of standard drinks consumed per typical occasion  3.0 (IQR = 3.0)  4.5 (IQR = 6.0)  1.5 (IQR = 0.4)  3.0 (IQR = 3.0  1.5 (IQR = 0.5)  2.0 (IQR = 1.5)  1.5 (IQR = 0.3)  2.3 (IQR = 3.0)  1.5 (IQR = 0.5)  2.7 (IQR = 4.1)  Binge drinking during period  >4 drinks on one occasion)  416 (51.4)  30 (73.2)  26 (8.9)  7 (41.2)  17 (3.9)  4 (26.7)  14 (3.4)  4 (40.0)  158 (18.4)  10 (41.7)  Median quantity per week (standard drinks)  4.5 (IQR = 9.4)  6.8 (IQR = 24.8)  0.6 (IQR = 2.1)  2.3 (IQR = 4.1)  0.5 (IQR = 2.1)  0.8 (IQR = 6.4)  0.9 (IQR = 2.1)  1.5 (IQR = 2.1)  1.9 (IQR = 4.1)  0.5 (IQR = 4.0)  Tobacco                       Any smoking during period  185 (14.1)  67 (87.0)  86 (5.7)  67 (84)  62 (4.2)  63 (74.1)  50 (3.6)  44 (73.3)  88 (6.3)  49 (83.1)   Median number of cigarettes per week (among smokers)  35.0 (IQR = 75.5)  82.5 (IQR = 84.0)  28.0 (IQR = 49.0)  70.0 (IQR = 77.5)  28.0 (IQR = 66.5)  49.0 (IQR = 49.0)  21.0 (IQR = 67.0)  42.0 (IQR = 42.0)  17.5 (IQR = 52.8)  56.0 (IQR = 56.0)  Illicit drug use                       Used cannabis during period  40 (3.1)  38 (49.4)  14 (0.9)  30 (38.0)  14 (1.0)  26 (30.6)  5 (0.4)  12 (20.0)  13 (0.9)  9 (15.3)   Used other illicit drugs  21 (1.6)  26 (34.2)  0 (0.0)  11 (13.9)  1 (0.1)  8 (9.4)  –  2 (3.3)  4 (0.3)  –    Trimester 1 pre-awareness N = 1389an (%)   Trimester 1 post-awareness N = 1599bn (%)   Trimester 2 N = 1554 n (%)   Trimester 3 N = 1447 n (%)   8 weeks postnatal N = 1449 n (%)   Alcohol  General  Specialist  General  Specialist  General  Specialist  General  Specialist  General  Specialist  Typical frequency of consumption                       Never  503 (38.3)  36 (46.8)  1229 (80.9)  62 (78.5)  1038 (70.6)  69 (82.1)  977 (70.4)  50 (83.3)  530 (38.1)  35 (59.3)   Less than once per month  158 (12.0)  7 (9.1%)  100 (6.6)  6 (7.5)  129 (8.8)  4 (4.8)  104 (7.5)  5 (8.3)  225 (16.2)  14 (23.7)   Once per month  35 (2.7)  6 (7.8%)  34 (2.2)  2 (2.5)  72 (4.9)  5 (6.0)  52 (3.8)  1 (1.7)  82 (5.9)  3 (5.1)   2–3 times per month  74 (5.6)  –  55 (3.6)  1 (1.3)  87 (5.9)  1 (1.2)  86 (6.2)  –  105 (7.6)  1 (1.7)   1–2 times per week  308 (23.5)  13 (16.9)  84 (5.5)  6 (7.6)  121 (8.2)  3 (3.6)  134 (9.7)  4 (6.7)  273 (19.6)  5 (8.5)   3–4 times per week  133 (10.1)  9 (11.7)  11 (0.7)  2 (2.5)  18 (1.22)  1 (1.2)  22 (1.6)  –  118 (8.5)  –   5–6 times per week  40 (3.1)  3 (3.9)  1 (0.1)  –  1 (0.1)  1 (1.2)  4 (0.3)  –  29 (2.1)  1 (1.7)   Daily  61 (4.7)  3 (3.9)  6 (0.4)  –  4 (0.3)  –  8 (0.6)  –  28 (2.0)  –  Drinkers:  809  41  291  17  432  15  410  10  860  24  Median number of standard drinks consumed per typical occasion  3.0 (IQR = 3.0)  4.5 (IQR = 6.0)  1.5 (IQR = 0.4)  3.0 (IQR = 3.0  1.5 (IQR = 0.5)  2.0 (IQR = 1.5)  1.5 (IQR = 0.3)  2.3 (IQR = 3.0)  1.5 (IQR = 0.5)  2.7 (IQR = 4.1)  Binge drinking during period  >4 drinks on one occasion)  416 (51.4)  30 (73.2)  26 (8.9)  7 (41.2)  17 (3.9)  4 (26.7)  14 (3.4)  4 (40.0)  158 (18.4)  10 (41.7)  Median quantity per week (standard drinks)  4.5 (IQR = 9.4)  6.8 (IQR = 24.8)  0.6 (IQR = 2.1)  2.3 (IQR = 4.1)  0.5 (IQR = 2.1)  0.8 (IQR = 6.4)  0.9 (IQR = 2.1)  1.5 (IQR = 2.1)  1.9 (IQR = 4.1)  0.5 (IQR = 4.0)  Tobacco                       Any smoking during period  185 (14.1)  67 (87.0)  86 (5.7)  67 (84)  62 (4.2)  63 (74.1)  50 (3.6)  44 (73.3)  88 (6.3)  49 (83.1)   Median number of cigarettes per week (among smokers)  35.0 (IQR = 75.5)  82.5 (IQR = 84.0)  28.0 (IQR = 49.0)  70.0 (IQR = 77.5)  28.0 (IQR = 66.5)  49.0 (IQR = 49.0)  21.0 (IQR = 67.0)  42.0 (IQR = 42.0)  17.5 (IQR = 52.8)  56.0 (IQR = 56.0)  Illicit drug use                       Used cannabis during period  40 (3.1)  38 (49.4)  14 (0.9)  30 (38.0)  14 (1.0)  26 (30.6)  5 (0.4)  12 (20.0)  13 (0.9)  9 (15.3)   Used other illicit drugs  21 (1.6)  26 (34.2)  0 (0.0)  11 (13.9)  1 (0.1)  8 (9.4)  –  2 (3.3)  4 (0.3)  –  aSample size is reduced as questions regarding pre- and post-awareness were introduced after the study had commenced (questions not included for n = 221). Also excludes 8 women who had no pre-awareness data as they were reportedly aware of their pregnancy immediately. bPost-awareness data were not available for 18 women who did not know they were pregnant in trimester 1. Overall, following pregnancy awareness and during the course of pregnancy, 36.94% and 30.26% of women consumed any alcohol, 6.02% and 86.84% smoked cigarettes and 1.37% and 52.63% consumed illicit drugs in the general and specialist groups, respectively. The quantity of alcohol consumption in the sample was generally low, averaging around two standard drinks per occasion in the specialist cohort and less than one in the generalist cohort. Alcohol use16–18 was comparable with that of the general population for the two subgroups, whereas tobacco smoking,1,20 and illicit drug use20 were lower in the general cohort subgroup but higher for the specialist subgroup, compared with the general population during pregnancy. A number of articles have been published on the Triple B Cohort.21–28 McCormack et al.21 examined the patterns and predictors of alcohol consumption by women before awareness of pregnancy, and change in alcohol use following pregnancy recognition. Binge and heavy drinking were common in the early weeks of pregnancy, before pregnancy recognition (15.5% and 19.3%, respectively). Importantly, the rate of alcohol-exposed pregnancies was shown to be considerably higher than previous estimates when the period preceding pregnancy recognition is taken into account. Factors associated with changes in women’s alcohol use following pregnancy recognition included level of alcohol use preceding pregnancy recognition, older maternal age, pregnancy planning and illicit substance use. Heavy drinkers were more likely to cease drinking than low or moderate drinkers were. Women drinking at low or moderate levels were more likely to continue drinking at the same level than they were to cease completely, relative to heavy drinkers. The results have important relevance to health policy and preventive measures to minimize alcohol-related harms to mothers and their offspring. In regard to the SU group, there is a dearth of prospective data on women affected by substance use disorders during the perinatal period, often due to challenges with recruitment and retention. Yet understanding the experiences of these women at this time is critical to informing perinatal services to promote maternal well-being and infant development. A, prospective study on the SUD group found that these women experience psychosocial disadvantage, poorer bonding to their developing fetus in utero and elevated levels of perinatal distress and postnatal parenting stress.22 Findings highlight the critical importance of psychological and parenting support for these high-risk pregnant women and their offspring. What are the main strengths and weaknesses? The study provides five areas of innovation. First, it provides the most comprehensive longitudinal assessment of substance use in the perinatal period to date in Australia. Comprehensive assessment during this period will improve knowledge of the impact of substance use on infant development, and help identify critical risk thresholds and periods. Importantly, the study takes into account substance use behaviour both before and after pregnancy awareness; a distinction often overlooked in previous research. Second, this is the first study comparing pregnant women recruited from a general antenatal clinic and a substance dependence treatment clinic, allowing for substance use to be examined across a wide spectrum from low/moderate, to harmful/dependent use. This will improve understanding of the psychosocial and physical risk factors from varying levels of substance use. Third, the study is the first to comprehensively assess the impact of the partner’s substance use and mental health, both pre- and postnatally, on child health and family function. It also assesses the influence partners have on each other’s substance use. Fourth, collection of buccal cells from infants (at 8 weeks and 12 months) and parents (at infant age 12 months) will provide a basis for epigenetic research into factors conferring individual differences in risk for substance use in parents, and adverse effects of parental substance use on children23 (although we also note that cord blood samples were not obtained, limiting the potential of epigenetic studies related to developmental origins and the effect of pregnancy exposure to these substances). Finally, there is potential for data synthesis with intergenerational cohort studies. For example, major components of the Triple B Cohort assessments have been aligned with the Australian Temperament Project Generation Three Study (ATPG3) and the Victorian Intergenerational Health Cohort Study (VIHCS). This alignment has the potential to develop an integrated network of intergenerational cohorts, each focusing on specific prenatal and preconception periods. Specifically, the Triple B Cohort will provide rare and detailed data on exposures in pregnancy. The ATPG3 and VIHCS have a single antenatal assessment in trimester 3 but rich preconception data across three and two generations, respectively. The Triple B Study also captures key patterns of substance use for which there are major public health, prevention or treatment implications. Namely, it captures heavy/dependent substance use, addressed through oversampling pregnant women in treatment for substance use problems, and low to moderate (and binge) alcohol and tobacco use, which are adequately captured in the antenatal clinic sample (based on power analyses). Given the low prevalence of illicit substance use (other than cannabis) in pregnancy, it is unlikely that Triple B, or any other single study, unless very large scale, will be able to examine the impacts of low to moderate stimulant or opioid use on children. We also note that the sample is underpowered for genetic (but not epigenetic) research. Although the Triple B Study is a multi-site study conducted in two states, it was conducted in public urban hospitals and therefore is not representative of rural areas of Australia, nor of families that use private hospitals. The planned cross-comparison and harmonization of data with other major national and international cohorts may allow for increased pooled data and the potential capacity to examine outcomes of lower prevalence in smaller subgroups. A further potential limitation of the study relates to the generalizability and validity of inferences drawn from the study, given that the general antenatal cohort differs in a number of ways from the general population, and there was evidence to suggest that attrition was higher among women in less privileged socioeconomic circumstances. Nevertheless, the cohort includes participants from a range of demographic backgrounds and with varying substance use patterns, and overall attrition was low. In addition, as noted above, substance use in the general antenatal cohort during pregnancy was consistent with Australian population data. A major focus of the study was on comprehensive (prospective) data capture in the antenatal period; as such, there is a longer gap between the 8-week an 12-month assessments. This limits the capacity to understand how early postnatal exposures may affect growth and development. We do note, however, that information on some key developmental indicators (breastfeeding and sleep, for example), was assessed in the intervening period via recent retrospective reports. We also note that response rates for the study ranged from 38% to 45%. Whereas these rates are consistent with some recent longitudinal cohorts with hospital-based recruitment in Australia,15 the limitation is that risk estimates may reflect underestimation of the true estimates because the extreme end of the distribution is less likely to be captured. Finally, much of the information collected, including substance use data, was via self-report and is thus subject to potential biases. In order to address this limitation, 85 participants were randomly selected for urine analysis during their third trimester of pregnancy, to confirm self-reported illicit substance use. Agreement between self-reported substance use and urine analysis was 97%, indicating that the information provided was reliable. Despite these limitations, the study will improve understanding of the effects of parental substance use on infants and families, which can direct health policy. The results can inform development of public health prevention and early intervention campaigns to allow parents to make informed choices about substance use during the prenatal period. The results will also identify the health and obstetric needs of pregnant women characterized by harmful and/or risky patterns of substance use. Improvements in these areas may subsequently reduce developmental problems in infant and family functioning problems in the community. The results of this study can also inform national guidelines on use of alcohol and other substances before conception, in pregnancy and while breastfeeding, which may guide public health education and policy on substance use. Can I get hold of the data? Where can I find out more? Further information can be obtained through the National Drug and Alcohol Research Centre, University of New South Wales [https://ndarc.med.unsw.edu.au/project/triple-b-bumps-babies-and-beyond]. Enquires can be directed to Dr Hutchinson (corresponding author). Data access is governed by the investigators. Research proposals must be consistent with ethical approval and participant consent, confidentiality and data management. The study protocol for collaborative research requires ratification by the respective ethics committee affiliated with the research. Profile in a nutshell The Triple B Pregnancy Cohort Study is a longitudinal pregnancy cohort focused on understanding the impacts of parental alcohol and other drug use in pregnancy and postnatally on infant development and family functioning. The study recruited two sub-samples: (i) a general antenatal clinic sample of pregnant women and their partners (n = 1534 women; 841 of their partners); and (ii) a smaller sample of pregnant women with diagnosed substance use disorders (n = 89 women). Participants were recruited in 2009–13 at antenatal clinics in Sydney, NSW, and Perth, WA, Australia. The sample has been extensively examined through the gestational period with assessments in trimesters 1, 2 and 3 and at 8 weeks and 12 months postnatally; retention at 12 months was 84.0% and 73.8% for mothers in the general antenatal and substance use disorder clinics, respectively. The data collected include demographic, parental, familial and infant factors, with a focus on parental substance use and mental health, parenting practices, familial functioning and infant development. For information on collaboration with the Triple B Cohort dataset see [https://ndarc.med.unsw.edu.au/project/triple-b-bumps-babies-and-beyond]. Funding The research was funded by an Australian National Health and Medical Research Council (NHMRC) Project Grant #GNT630517 for $2,196,179 to R.P.M., D.H., S.A., J.N., E.E., L.B., S.J., C.O. and A.B., and was financially supported by the National Drug and Alcohol Research Centre (NDARC), University of New South Wales (UNSW). NDARC and the National Drug Research Institute (NDRI), Curtin University, are funded by the Australian Government under the Substance Misuse Prevention and Service Improvements Grants Fund. We also acknowledge financial support from Australian Rotary Health, the Foundation for Alcohol Research and Education, and the Financial Markets Foundation for Children (Australia). R.P.M. is financially supported by an NHMRC Principal Research Fellowship Award from the NHMRC, and D.H. is financially supported by an Australian Unity Industry Partner Senior Research Fellowship. C.O. is supported by an Australian Research Council Senior Research Fellowship (DORA: DP 130101459). E.E. is supported by an NHMRC Practitioner Fellowship #1021480. Acknowledgements We gratefully acknowledge the NDARC and NDRI research staff and students who assisted with collection of the data, the hospitals and antenatal clinics for their assistance with recruitment, and the study participants and their families. We wish to acknowledge Rosa Alati, Brandi Baylock, Lauren Bell, Elissa Bowey Annie Bleeker, Apo Demirkol, Genevive Eckstein, David Fergusson, Thea Gumbert, Helen Gunn, Jeannie Minnis, Colleen O’Leary, Vaughan Palmer, Jemma Pope, Jarrod Proudfoot, Candice Rainsford, Joanne Ross, Fiona Shand, Lisa Sin, Matthew Sunderland, Wendy Swift, Scarlet Wilcock and Jesse Young. We also wish to acknowledge the Cannabis Cohorts Research Consortium (NHMRC Project Grants: AAP1009381, AAP1064893). The Triple B Research Consortium includes the primary investigators already listed and: Joanne Cassar, Aurora Popescu, Gabrielle Campbell, Lee Taylor, Maria Gomez, Emma Black, Danya Braunstein, Laura Dewberry, Erin Kelly, Alex Aiken, Sarah Brann, Sara Clews, Sharon Dawe, Adrienne Gordon, Paul Haber, Dale Hamilton, Andrew Lewis, Nyanda McBride, Elizabeth Moore, Raewyn Mutch, Julee Oei, George Patton, Ronald Rapee, Tim Slade, Marian Shanahan, Christine Stephens, Samantha Teague and Meredith Ward. Conflict of interest: None declared. Reference 1 Gluckman P, Hanson M. Developmental Origins of Health and Disease . Cambridge. UK: Cambridge University Press, 2006. Google Scholar CrossRef Search ADS   2 Mitchell P, Spooner C, Copelan J, et al.   The Role of Families in the Development, Identification, Prevention and Treatment of Illicit Drug Problems . NHMRC Report. Canberra: Commonwealth of Australia, 2001. 3 Hutchinson D, Mattick RP, Braunstein D, et al.   The impact of alcohol use disorders on family life: A review of the empirical literature. (Technical report). National Drug and Alcohol Research Centre, University of New South Wales, 2014. 4 Elliott E, Payne J, Haan E, Bower C. Diagnosis of foetal alcohol syndrome and alcohol use in pregnancy: A survey of paediatricians' knowledge, attitudes and practice. J Paediatr Child Health  2006; 42: 698– 703. Google Scholar CrossRef Search ADS PubMed  5 Stromland K, Mattson S, Adnams C., Autti-Ramo I, Riley E, Warren K. Fetal alcohol spectrum disorders: An international perspective. Alcohol Clin Exp Res  2005; 29: 1121– 26. Google Scholar CrossRef Search ADS   6 Bandstra ES, Morrow CE, Mansoor E, Accomero VH. Prenatal drug exposure: Infant and toddler outcomes. J Addict Dis  2010; 29: 245– 58. Google Scholar CrossRef Search ADS PubMed  7 NSW Department of Health. National Clinical Guidelines for the Management of Drug Use During Pregnancy, Birth and the Early Development Years of the Newborn . Sydney, NSW: NSW Department of Health, 2006. 8 Alati R, Davey Smith G, Lewis S, et al.   Effect of prenatal alcohol exposure on childhood academic outcomes: Contrasting maternal and paternal associations in the ALSPAC Study. PLoS One  2013; 8: e74844. Google Scholar CrossRef Search ADS PubMed  9 Alati R, Macleod J, Hickman M, et al.   Intrauterine exposure to alcohol and tobacco use and childhood IQ: findings from a parental-offspring comparison within the Avon Longitudinal Study of Parents and Children. Pediatr Res  2008; 64: 659– 66. Google Scholar CrossRef Search ADS PubMed  10 O'Callaghan FV, O'Callaghan M, Najman JM, et al.   Prenatal alcohol exposure and attention, learning and intellectual ability at 14 years: A prospective longitudinal study. Early Hum Dev  2007; 83: 115– 23. Google Scholar CrossRef Search ADS PubMed  11 Streissguth A. Offspring effects of prenatal alcohol exposure from birth to 25 years: The Seattle Prospective Longitudinal Study. J Clin Psychol Med Settingso  2007; 14: 81– 101. Google Scholar CrossRef Search ADS   12 Grekin ER, Brennan PA, Hammen C. Parental alcohol use disorders and child delinquency: the mediating effects of executive functioning and chronic family stress. J Stud Alcohol  2005; 66: 14– 22. Google Scholar CrossRef Search ADS PubMed  13 Goodwin RD, Fergusson DM, Horwood LJ. Childhood abuse and familial violence and the risk of panic attacks and panic disorder in young adults. Psychol Med  2005; 35: 881– 90. Google Scholar CrossRef Search ADS PubMed  14 Dawe S, Frye S, Best D, et al.   Drug Use in the Family: Impacts and Implications for Children . Canberra: Australian National Council on Drugs, 2006. 15 Vuillermin P, Saffery R, Allen K, et al.   Cohort profile: The Barwon infant study. Int J Epidemiol  2015; 44: 1148– 60. Google Scholar CrossRef Search ADS PubMed  16 Hutchinson D, Moore EA, Breen C, et al.   Alcohol use in pregnancy: Prevalence and predictors in the Longitudinal Study of Australian Children. Drug Alcohol Rev  2013; 32: 475– 82. Google Scholar PubMed  17 O'Keeffe L, Kearney P, McCarthy F, et al.   Prevalence and predictors of alcohol use during pregnancy: Findings from international multicentre cohort studies. BMJ  2015; 5: e006323. Google Scholar CrossRef Search ADS   18 Australian Institute of Health and Welfare. National Drug Strategy Household Survey . Canberra: AIHW, 2014. 19 Hilder L, Zhichao Z, Parker M, Jahan S, Chambers GM. Australia’s Mothers and Babies 2012 . Canberra: Australian Institute of Health and Welfare, 2014. 20 Australian Institute of Health and Welfare. Drugs in Australia 2010: Tobacco, Alcohol and Other Drugs . Canberra: AIHW, 2011. 21 McCormack C, Hutchinson D, Burns L, et al.   Prenatal alcohol consumption between conception and recognition of pregnancy. Alcohol Clin Exp Res  2017; 41: 369– 78. Google Scholar CrossRef Search ADS PubMed  22 Hutchinson D, Taylor L, Rapee R, et al.   Mental health, maternal bonding and parenting stress in women attending a specialist perinatal drug health service. Drug Dependence: Avid Science Publications. Accepted December 2016. http://www.avidscience.com/wp-content/uploads/2017/09/mental-health-maternal-bonding-and-parenting-stress-in-women-attending-a-specialist-perinatal-drug-health-service.pdf (4 October 2017, date last accessed). 23 Fransquet P, Hutchinson D, Olsson CA, et al.   Perinatal maternal alcohol consumption and methylation of the dopamine receptor DRD4 in the offspring: The Triple B Study. Environ Epigenet  2016; 4: 1– 9. 24 Rossen L, Hutchinson D, Wilson J, et al.   Maternal bonding through pregnancy and postnatal: Findings from an Australian longitudinal study. Am J Perinatol  2017; 34: 808– 17. Google Scholar CrossRef Search ADS PubMed  25 McPhie S, Skouteris H, Mattick RP, et al.   Weight in the first year of life: Associations with maternal prepregnancy body mass index and gestational weight gain: Findings from a longitudinal pregnancy cohort. Am J Perinatol  2017; 34: 774– 79. Google Scholar CrossRef Search ADS PubMed  26 Tay R, Wilson J, McCormack C. Alcohol consumption by breastfeeding mothers: Frequency, correlates and infant outcomes. Drug Alcohol Rev  2017, Mar 13. doi: 10.1111/dar.12473. 27 Rossen L, Hutchinson D, Wilson J. Predictors of postnatal mother-infant bonding: The role of antenatal bonding, maternal substance use and mental health. Arch Women Ment Health  2016; 19: 609– 22. Google Scholar CrossRef Search ADS   28 Burns L, Conroy E, Maloney E, et al.   Psychosocial characteristics and obstetric health of women attending a specialist substance use antenatal clinical in a large metropolitan hospital. Int J Pediatr  2011; 2011: 1– 7. Google Scholar CrossRef Search ADS   29 Australian Bureau of Statistics. Births, Australia, 2013 . Canberra: Australian Bureau of Statistics, 2014. 30 Pink B. Socio-Economic Indexes for Areas (SEIFA) . Canberra: Australian Bureau of Statistics, 2008. 31 Australian Bureau of Statistics. Education and Work, Australia . Canberra: Australian Bureau of Statistics, 2014. 32 Australian Bureau of Statistics. Gender Indicators, Australia . Canberra: Australian Bureau of Statistics, 2015. 33 Australian Bureau of Statistics (ABS). Cultural diversity in Australia – Reflecting a Nation: Stories from the 2011 Census, 2012–2013 . Canberra: Australian Bureau of Statistics, 2012. 34 Australian Bureau of Statistics (ABS). 2012. http://www.adelaide.edu.au/phidu/help-info/about-our-data/indicators-notes/sha-aust/demography-ses/nes-countries.html (22 November 2015, date last accessed). 35 Australian Bureau of Statistics (ABS). Labour Force, Australia: Labour Force Status and Other Characteristics of Families . Canberra: Australian Bureau of Statistics, 2013. 36 Australian Bureau of Statistics (ABS). Census of Population and Housing – Counts of Aboriginal and Torres Strait Islander Australians, 2011 . Canberra: Australian Bureau of Statistics, 2012. 37 Li Z, Zeki R, Hilder L, Sullivan EA. Australia’s Mothers and Babies 2011 . Canberra: AIHW National Perinatal Epidemiology and Statistics Unit, 2013. 38 Australian Bureau of Statistics (ABS). Same-sex Couple Families – Reflecting a Nation: Stories from the 2011 Census . Canberra: Australian Bureau of Statistics, 2012. 39 Australian Bureau of Statistics (ABS). Cultural Diversity in Australia – Reflecting a Nation: Stories from the 2011 Census . Canberra: Australian Bureau of Statistics, 2012. 40 SEIFA: Mean Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) Score (SD). 41 World Health Organization. Composite International Diagnostic Interview (CIDI) Core Version 2.1 . Geneva: World Health Organization, 1997. 42 Cottler LB, Robins lN, Grant BF, et al.   The CICI-core substance abuse and dependence questions: Cross-cultural and nosological issues. The WHO/ADAMHA Field Trial. Br J Psychiatry  1991; 159: 653– 58. Google Scholar CrossRef Search ADS PubMed  43 Lovibond SH, Lovibond PF. Manual for the Depression Anxiety Stress Scales . Sydney, NSW: Psychology Foundation, 1995. 44 Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression: Development of the 10-item Edinburgh postnatal depression Scale (EPDS). Br J Psychiatry  1987; 150: 782– 86. Google Scholar CrossRef Search ADS PubMed  45 Busby DM, Christensen C, Crane RD, et al.   A revision of the dyadic adjustment scale for use with distressed and nondistressed couples: Construct hierarchy and multidimensional scales. J Marital Fam Ther  1995; 21: 289– 308. Google Scholar CrossRef Search ADS   46 Hudson WW, McIntosh SR. The assessment of spouse abuse: Two quantifiable dimensions. J Marriage Fam  1981; 43: 873– 85. Google Scholar CrossRef Search ADS   47 Condon JT, Corkindale CJ, Boyce P. Assessment of postnatal paternal-infant attachment: Development of a questionnaire instrument. J Reprod Infant Psychol  2008; 26: 195– 210. Google Scholar CrossRef Search ADS   48 Biringen Z, Robinson JL, Emde RN. The emotional availability scales. 3rd edn Unpublished manuscript. University of Colorado Health Sciences Center, 1999. 49 Abidin RA. Parenting Stress Index . 3rd edn. Lutz, FL: PAR Inc., 2005. 50 Squires J, Bricker D, Potter L. Revision of a parent-completed developmental screening tool: Ages and Stages Questionnaires. J Pediatr Psychol  1997; 22: 313– 28. Google Scholar CrossRef Search ADS PubMed  51 Bayley N. Bayley Scales of Infant and Toddler Development . 3rd edn (Bayley–III). London: Pearson (Harcourt) Assessment, 2005. © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Epidemiology Oxford University Press

Cohort Profile: The Triple B Pregnancy Cohort Study: A longitudinal study of the relationship between alcohol, tobacco and other substance use during pregnancy and the health and well-being of Australian children and families

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Oxford University Press
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© The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association
ISSN
0300-5771
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1464-3685
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10.1093/ije/dyx126
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Abstract

Summary The Triple B Pregnancy Cohort Study investigates the effects of parental alcohol, tobacco and other substance use on infant development and family functioning. The study (also known as: Bumps, Babies and Beyond), recruited two sub-samples: (i) a general antenatal clinic sample of pregnant women and their partners (n = 1534 women; 842 of their partners); and (ii) a smaller sample of pregnant women with diagnosed substance use disorders (SUD; n = 89 women only). Participants were recruited through public antenatal clinics attached to major hospitals and area health services in New South Wales (NSW) and Western Australia (WA). Of 4068 eligible women from the general antenatal clinics, 37.7% participated, with equivalent numbers for the SUD clinics being 198, 44.9%. There were 1453 and 65 live births from the two groups, respectively, with a total of 1414 and 65 mothers in the two groups, respectively. Data were also collected on 1264 (86.9%) of 1455 eligible partners of women recruited through the general antenatal clinics. The study collected repeated measures across pregnancy (trimesters 1, 2 and 3), and at 8 weeks and 12 months postnatally; retention at 12 months was 84.0% and 73.8% for mothers in the general antenatal and specialist SUD clinics, respectively. The data collected include demographic, parental, familial and infant factors, with a focus on parental substance use and mental health, parenting practices, familial functioning and infant development. Following pregnancy awareness, 42% of women consumed alcohol, 12% smoked tobacco and 4% used illicit drugs at some stage in pregnancy. Comprehensive assessments have been conducted with infants at 12 months to test numerous developmental domains, including cognitive, motor and language skills, along with measures of social and emotional functioning. Data access enquiries can be made to the principal investigator [delyse.hutchinson@deakin.edu.au]. Why was the cohort set up? In 2010, the Australian National Medical Health Research Council (NHMRC) funded this longitudinal pregnancy cohort study to address limitations in knowledge of the effects of parental substance use on infants and families. The Triple B Pregnancy Cohort Study (known as: Bumps, Babies and Beyond), includes two sub-samples: (i) a public antenatal clinic sample of pregnant women and their partners, and (ii) a smaller sample of pregnant women with diagnosed substance use disorders. Participants were recruited though public antenatal clinics at major hospitals and health services in New South Wales (NSW) and Western Australia (WA). The study aims to examine: the effects of parental substance use in pregnancy on infant development (e.g. cognitive, motor, language and socio-emotional development) and family functioning; the extent to which substance use is interrelated among couples; and the influence substance use may have on parents’ respective substance use patterns. The study aims to contribute to improved public health services. The study represents a significant investment in longitudinal research, which builds on a history of quality Australasian longitudinal research. The Developmental Origins of Health and Disease (DOHaD)1 framework posits that early life environmental exposures induce critical changes in development which have long-term impacts on health and disease risk. Consistent with this framework, clinical studies of high-risk samples of parents diagnosed with substance use disorders suggest that parental substance use has significant adverse impacts on infant and child development.2,3 For example, substance-dependent pregnant women and their infants have an increased risk of obstetric, fetal and neonatal complications. These include miscarriage, prematurity, low birthweight for gestational age, fetal alcohol spectrum disorders (FASD), neonatal abstinence syndrome (NAS) and longer-term deficits in children’s physical, cognitive, behavioural and emotional development.4–7 The primary limitation of clinical studies is that the data are often derived from small-scale cross-sectional surveys, so that the effects over time are not known and the findings are not generalizable to the population. Longitudinal studies provide insights into potential causes of health problems, as well as factors capable of preventing or moderating problems. Emerging evidence from general population-based longitudinal studies suggests that the effect of parental substance use can vary considerably as a function of parent gender, pattern and type of substance use, and the presence of associated socioeconomic, physical health and psychosocial risk factors.2,3,8–11 Parental substance misuse may impact adversely on children and families via direct and indirect pathways. For example, parental substance use can impact negatively on the quality of the marital/intimate partner relationship and the parent-child relationship by reducing family cohesion and increasing conflict and violence.12,13 However, there is a dearth of data on parental substance use in the prenatal period, particularly defined by timing of exposure during pregnancy (i.e. pre-pregnancy awareness and at each trimester following awareness), with most research focusing solely on maternal consumption and neonatal outcomes. Furthermore, many studies use poor measures of parental substance use (e.g. retrospective reports of use). Notably, few assess partner substance use and its impacts. As a result, there are major gaps in current knowledge about the extent to which perinatal (pre- and postnatal) parental substance use impacts on early child development and family functioning, and the mechanisms by which these influences occur, particularly for low/moderate levels of use which are the most frequent levels of substance use among Australian parents.14 This cohort protocol aims to: (i) describe the Triple B Cohort samples and study methodology; and (ii) provide key summary data on perinatal substance use patterns, along with findings from three recent publications. The Triple B Cohort Study is led by the National Drug and Alcohol Research Centre (NDARC) at the University of New South Wales (UNSW) Australia and the National Drug Research Institute (NDRI) at Curtin University, in collaboration with Deakin University, Sydney University, the University of Queensland, the Murdoch Childrens Research Institute and the University of Melbourne. The study has been supported by the NHMRC (2010–14), Australian Rotary Health (ARH; 2012–13) and the Foundation for Alcohol Research and Education (FARE; 2010–11). Additionally, PhD candidates on the project have been funded through ARH; the NDARC Education Trust (NET), Macquarie University and both the Australian Centre for Perinatal Science (ACPS) and NDARC at UNSW. Ethics approval was granted by relevant university, hospital and health services human research ethics committees. Who is in the cohort? The study used a prospective cohort design. Pregnant women were recruited through general antenatal clinics (N = 1534: NSW = 1246; WA = 288) and specialist drug and alcohol antenatal clinics (N = 89; NSW = 59; WA = 30) in public hospitals and health services in NSW and WA between 2009 and 2013. Participating hospitals in NSW were the Royal Prince Alfred Hospital, Camperdown; the Royal Women’s Hospital, Randwick; and Liverpool Hospital, Liverpool. Participants in Western Australia were recruited through the King Edward Memorial Hospital, Subiaco. Pregnant women were invited to participate in the study by research officers who attended antenatal clinics at each hospital, across all days and months of the year, to represent (proportionally) all clinics operating at each recruitment site. A standardized script was used to describe the study to women. Eligibility criteria included: being pregnant; being over 15 years of age; having no major medical complications (mother or fetus); intention of mother or both parents to be the primary caregiver/s; being mentally able to complete assessments; possessing sufficient literacy in English; and informed consent. As outlined in Figures 1 and 2, 6597 pregnant women [255 from the specialist substance use disorder (SUD) cohort] were approached and informed about the study; 4266 (198 from the specialist SUD cohort) of these met eligibility criteria and were invited to participate. A total of 1534 (37.7%) and 89 (44.9%) women from the general and specialist cohorts, respectively, provided consent and completed at least one study measure. The participation rates of eligible women for individual hospitals ranged from 22.2% to 55.0%, with an overall participation rate of 44.0% for NSW and 25.0% for WA. Figure 1 View largeDownload slide Triple B Pregnancy Cohort Study: study flow diagram of mother, partner and infant participation rates (N = 1534 families) for the general antenatal sample. *The 8-week follow-up interview for partners was introduced after the pilot study. As such, 8-week data were unavailable for 60 participating partners, as it was not offered. **In some families, only infants were assessed at 12 months. Figure 1 View largeDownload slide Triple B Pregnancy Cohort Study: study flow diagram of mother, partner and infant participation rates (N = 1534 families) for the general antenatal sample. *The 8-week follow-up interview for partners was introduced after the pilot study. As such, 8-week data were unavailable for 60 participating partners, as it was not offered. **In some families, only infants were assessed at 12 months. Figure 2 View largeDownload slide Triple B Pregnancy Cohort Study. Study flow diagram of mother and infant participation rates (N = 88) for the specialist substance use disorder (SUD) antenatal sample. **In some families, only infants were assessed at 12 months; in total, 50 families remained in the cohort. Figure 2 View largeDownload slide Triple B Pregnancy Cohort Study. Study flow diagram of mother and infant participation rates (N = 88) for the specialist substance use disorder (SUD) antenatal sample. **In some families, only infants were assessed at 12 months; in total, 50 families remained in the cohort. Participation rates Figures 1 and 2 present study flow diagrams of mother and infant participation rates, and of partners, separated by non-exposed and substance use-exposed groups, respectively. Of those who participated, 79 withdrew (six from the specialist SUD cohort), and a further 65 (18 from the specialist cohort) were lost to follow-up before giving birth (attrition rate: 7.8% and 31.5% for general and specialist SUD cohorts, respectively). The remaining 1414 mothers in the general cohort gave birth to a total of 1453 offspring which included 37 twin pairs and one set of triplets. In the specialist SUD cohort, 65 singletons were born. Parents of twins and triplets were asked to complete a separate survey about each child. Data were collected on 1264 (86.87%) of eligible partners from the general cohort, either directly (n = 842), or indirectly (n = 422) via maternal report. Cohort characteristics The characteristics of participating mothers and infants are presented in Table 1. Partner characteristics are presented in Table 2. Maternal and partner data were collected in trimester 3; data on the infant were collected at the 8-weeks postnatal follow-up and were derived from infant Blue Books completed at birth by hospital staff. Compared with the Australian population, the Triple B general antenatal cohort is similar to the Australian population on rates of employment (z = 1.40; P = 0.08), and the proportion of participants of Aboriginal or Torres Strait Islander origin (z = −0.53; P = 0.23). The sex distribution of infants was also similar to Australian population figures (z = −0.46; P = 0.32), although other infant characteristics differed from the general population, with longer gestation at birth (z = 13.8; P < 0.001; Somers’ d = 0.000; 95% CI −0.066, 0.068), higher birthweight (z = 3.82; P = 0.001; Somers’ d = 0.07; 95% CI −0.01, 0.13) and a higher proportion of twins/multiple births (z = 4.55; P < 0.001; Cohen's h = 0.12; 95% CI 0.042, 0.186). Mothers in the cohort were also older (z = 12.86; P < 0.001, Somers’ d = 0.11; 95% CI 0.05, 0.17), more socioeconomically advantaged (SEIFA; t1577 = 31.56; P < 0.001; Cohen’s d = 0.47; 95% CI 0.42, 0.52), and better educated than the general population (university educated, z = 18.84; P < 0.001; Cohen’s h = 0.49; 95% CI 0.44, 0.55). In addition, binomial tests showed that there were more women born overseas (z = 15.03; P < 0.001; Cohen’s h = 0.36; 95% CI 0.31, 0.41), a higher proportion of nulliparous women (z = 10.70; P < 0.001; Cohen’s h = 0.28; 95% CI 0.22, 0.33) and fewer living in single-parent households (z = −11.45; P < 0.001; Cohen’s h = 0.36; 95% CI 0.31, 0.41) compared with general population figures. Table 1 Mother and infant cohort characteristics and comparison with Australian population data Mothers’ characteristics  General cohort at trimester 3 (n = 1498)a  Specialist SUD cohort at trimester 3 (n = 81)a  Australian population  Mean age (years)  32.5 (SD = 5.1) Range: 17–52 Median: 33.0  28.8 (SD = 5.6) Range: 17–42 Median: 28.0  In 2013, the median age of Australian women giving birth was 30.8 years29  Mean Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)  1047.2 (SD = 57.8) Range: 790–1164  1028.7 (SD = 60.8) Range: 853–1,122  IRSAD is standardized to a distribution with a mean score of 1000, and a standard deviation of 100.30  Education  n (%)  n (%)   Year 10 or below  92 (6.1)  47 (58.0)  In 2014, 63.6% of females aged 20–64 had a post-high school qualification; 31.0% had a university degree. Corresponding figures for 30–34 year-old females show that 74.1% had a post-school qualification; 43.3% had a university degree31   Year 12  170 (11.4)  9 (11.1)   Diploma, trade qualification  223 (14.9)  19 (23.4)   University/college degree  1008 (67.3)  6 (7.4)  Employment       Employed (full or part time)  1001 (66.8)  12 (14.8)  In 2012–13, 65.1% of females aged 20–74 were employed32  Country of birth       Australia  832 (55.5)  72 (88.9)  In 2011, 27% of people living in Australia were born overseas33 and 15.7% of the population were born in non main English-speaking countries34   Other English-speaking  279 (18.6)  6 (7.4)   Non main English-speaking  382 (25.5)  3 (3.7)  Single-parent household  90 (6.0)  44 (54.3)  In 2012, 17.2% of families with children under 15 were single-mother families35  Aboriginal/Torres Strait Islander  34 (2.3)  12 (14.8)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  Parity         0  841 (56.1)  28 (34.6)  In 2012, 42.4% of mothers had no previous pregnancies; 33.2% had one; 14.1% had two; 8.5% had three or more19   1  439 (29.3)  29 (35.8)   2  150 (10.0)  10 (12.4)   3 or more  68 (4.1)  12 (14.8)    Infants’ characteristics  General cohort at trimester 3 (n = 1453)a  Specialist SUD cohort at trimester 3 (n = 65)a  Australian population      n (%)  n (%)    Female  696 (47.9)  28 (43.1)  In 2012, 48.5% of live births were females19  Twins/triplets  77 (5.3)  0 (0.0)  In 2012, 3.0% of births were twins or other multiple births19  Mean gestation in weeks  39.2 (SD = 1.82)  Range: 27–43  38.3 (SD = 2.6) Range: 30–42  In 2012, the mean gestational age for all babies was 38.7 weeks19  Mean birthweight in kilograms  3.42 (SD = 0.55) Range: 0.98–5.70  3.13 (SD = 0.67) Range: 1.33–5.24  In 2011, the mean birthweight of liveborn babies was 3.37kg37  Mothers’ characteristics  General cohort at trimester 3 (n = 1498)a  Specialist SUD cohort at trimester 3 (n = 81)a  Australian population  Mean age (years)  32.5 (SD = 5.1) Range: 17–52 Median: 33.0  28.8 (SD = 5.6) Range: 17–42 Median: 28.0  In 2013, the median age of Australian women giving birth was 30.8 years29  Mean Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)  1047.2 (SD = 57.8) Range: 790–1164  1028.7 (SD = 60.8) Range: 853–1,122  IRSAD is standardized to a distribution with a mean score of 1000, and a standard deviation of 100.30  Education  n (%)  n (%)   Year 10 or below  92 (6.1)  47 (58.0)  In 2014, 63.6% of females aged 20–64 had a post-high school qualification; 31.0% had a university degree. Corresponding figures for 30–34 year-old females show that 74.1% had a post-school qualification; 43.3% had a university degree31   Year 12  170 (11.4)  9 (11.1)   Diploma, trade qualification  223 (14.9)  19 (23.4)   University/college degree  1008 (67.3)  6 (7.4)  Employment       Employed (full or part time)  1001 (66.8)  12 (14.8)  In 2012–13, 65.1% of females aged 20–74 were employed32  Country of birth       Australia  832 (55.5)  72 (88.9)  In 2011, 27% of people living in Australia were born overseas33 and 15.7% of the population were born in non main English-speaking countries34   Other English-speaking  279 (18.6)  6 (7.4)   Non main English-speaking  382 (25.5)  3 (3.7)  Single-parent household  90 (6.0)  44 (54.3)  In 2012, 17.2% of families with children under 15 were single-mother families35  Aboriginal/Torres Strait Islander  34 (2.3)  12 (14.8)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  Parity         0  841 (56.1)  28 (34.6)  In 2012, 42.4% of mothers had no previous pregnancies; 33.2% had one; 14.1% had two; 8.5% had three or more19   1  439 (29.3)  29 (35.8)   2  150 (10.0)  10 (12.4)   3 or more  68 (4.1)  12 (14.8)    Infants’ characteristics  General cohort at trimester 3 (n = 1453)a  Specialist SUD cohort at trimester 3 (n = 65)a  Australian population      n (%)  n (%)    Female  696 (47.9)  28 (43.1)  In 2012, 48.5% of live births were females19  Twins/triplets  77 (5.3)  0 (0.0)  In 2012, 3.0% of births were twins or other multiple births19  Mean gestation in weeks  39.2 (SD = 1.82)  Range: 27–43  38.3 (SD = 2.6) Range: 30–42  In 2012, the mean gestational age for all babies was 38.7 weeks19  Mean birthweight in kilograms  3.42 (SD = 0.55) Range: 0.98–5.70  3.13 (SD = 0.67) Range: 1.33–5.24  In 2011, the mean birthweight of liveborn babies was 3.37kg37  aIndividual sample sizes for each characteristic vary slightly due to missing data. Table 2 Partner cohort characteristics and comparison with Australian population data Partner characteristics  General antenatal cohort at trimester 3 (n = 1245)a,b  Australian population  Age in years  35.0 (SD = 5.9)   Range: 17–59  Median: 35.0  The median age of fathers for births registered in 2013 was 33.0 years29    n (%)    Same-sex (female)  15 (1.2)  In 2011, 0.7% of Australian couples were same-sex couples38  Education     Year 10 or below  111 (8.9)  In 2014, 65.6% of males aged 20–64 had a post-high school qualification, with 26.0% having a university degree31   Year 12  154 (12.4)   Diploma, trade qualification  260 (20.9)   University/college degree  692 (55.6)  Employment    In 2012–13, 78.8% of males aged 20–74 were employed32   Employed (full or part time)  1145 (91.9)  Country of birth    In 2011, 27% of people living in Australia were born overseas, and 15.7% of the population were born in non main English-speaking countries34,39   Australia  651 (52.3)   Other English-speaking  284 (22.8)   Non main English-speaking  284 (22.8)  Aboriginal/Torres Strait Islander  19 (1.5)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  Partner characteristics  General antenatal cohort at trimester 3 (n = 1245)a,b  Australian population  Age in years  35.0 (SD = 5.9)   Range: 17–59  Median: 35.0  The median age of fathers for births registered in 2013 was 33.0 years29    n (%)    Same-sex (female)  15 (1.2)  In 2011, 0.7% of Australian couples were same-sex couples38  Education     Year 10 or below  111 (8.9)  In 2014, 65.6% of males aged 20–64 had a post-high school qualification, with 26.0% having a university degree31   Year 12  154 (12.4)   Diploma, trade qualification  260 (20.9)   University/college degree  692 (55.6)  Employment    In 2012–13, 78.8% of males aged 20–74 were employed32   Employed (full or part time)  1145 (91.9)  Country of birth    In 2011, 27% of people living in Australia were born overseas, and 15.7% of the population were born in non main English-speaking countries34,39   Australia  651 (52.3)   Other English-speaking  284 (22.8)   Non main English-speaking  284 (22.8)  Aboriginal/Torres Strait Islander  19 (1.5)  In 2011, 2.5% of Australia’s population identified as being of Aboriginal and/or Torres Strait Islander origin36  a Individual sample sizes for each characteristic vary slightly due to missing data. bIncludes participating and non-participating partners, where data are available. By contrast, the Triple B specialist SUD cohort reported higher levels of unemployment (z = −9.50; P < 0.001; Cohen’s h = 1.09; 95% CI 0.889, 1.34), higher proportions of Aboriginal or Torres Strait Islander participants (z = 7.10; P < 0.001; Cohen’s h = 0.47; 95% CI 0.22, 0.56), higher proportions of Australian-born mothers (z = −0.32; P = 0.001; Cohen’s h = 0.41; 95% CI 0.22, 0.68) and lower birthweights (z = −2.80; P = 0.005; Somers’ d = −0.41; 95% CI −0.75, −0.07) when compared with the Australian population. Mothers were also younger (z = −2.89; P = 0.004; Somers’ d = 0.11; 95% CI 0.05, 0.17), less educated (university educated; z = −0.65; P < 0.001; Cohen’s h = 0.90; 95% CI 0.69, 1.18), with more living in single-parent households (z = 8.85; P < 0.001; Cohen’s h = 0.80; 95% CI 0.58,1.03) compared with the Australian population. There were no differences in parity (z = −1.43; P = 0.08), the number of multiple births (z = −1.41; P = 0.08), infant gestational age (z = −0.26; P = 0.80) and infant sex distribution (z = −0.76; P = 0.22), between the specialist SUD cohort and the Australian population, although mothers in the specialist cohort were somewhat more socioeconomically advantaged (t = 4.25; P < 0.001; Cohen’s d = 0.29; 95% CI 0.07, 0.50). Demographic data were provided by 824 (97.9%) of the 842 participating partners for mothers in the general antenatal cohort. In addition, mothers in this group reported partner demographic characteristics for 418 (68.1%) of the 614 eligible partners who refused to participate. Comparisons with Australian population data suggest that the proportion of partners of Aboriginal or Torres Strait Islander origin was less than in the general population (z = −2.10; P = 0.02). However, like mothers, partners in the cohort appear to be slightly older (z = 10.55; P < 0.001; Somers’ d = 0.27; 95% CI 0.20, 0.34), more highly educated (university education; z = 24.54; P < 0.001; Cohen’s h = 0.64; 95% CI 0.58, 0.70), and more likely to be born overseas compared with the general population (z = 15.41; P < 0.001; Cohen’s h = 0.41; 95% CI 0.35, 0.47). In addition, the rate of employment was higher among partners in the cohort (z = 13.17; P < 0.001; Cohen’s h = 0.47; 95% CI 0.42, 0.53) and there was a higher proportion of same-sex partners in comparison with the general population (z = 2.20; P = 0.014; Cohen’s h = 0.05; 95% CI 0.01, 0.11). Comparisons were also conducted on the demographic characteristics of partners from the general cohort as a function of whether data were obtained via self-report, or indirectly via maternal report. These comparisons showed that the two partner groups did not differ on employment status (93.7% versus 95.2% in full- or part-time employment; χ2(1, N = 1215) = 1.06; P = 0.30), same-sex partner relationships [1.5% versus 0.7% female for partners who self-reported and those who were reported on indirectly, respectively [χ2(1, N = 1224) = 1.41; P = 0.24]; or Aboriginal or Torres Strait Islander origin [1.5% versus 1.7%; χ2(1, N = 1217) = 0.05; P = 0.83). Nevertheless, participating partners were slightly younger than refusers (mean age 34.7 versus 35.5 years; t1215 = −2.35; P = 0.01; Cohen’s d = 0.14; 95% CI 0.02, 0.26), and reported higher educational attainment [60.4% versus 50.1% completed university/college; χ2(1, N = 1245) = 11.75; P = 0.001; ϕ = 0.09; 95% CI 0.02, 0.19] . How often have they been followed up? Five assessment points are shown in Table 3. These include: trimester 1 (conception to 12 weeks), trimester 2 (13 weeks to 27 weeks), trimester 3 (28 weeks to birth) and an 8-week follow-up (8 weeks postnatal). A comprehensive developmental follow-up occurred at infant age 12 months. Mothers were assessed at all time points; partners at trimester 3, 8 weeks postnatal and the 12-month follow-up; and infants at the 8-week and 12-month follow-up. Survey response rates for eligible mothers and infants are presented in Figure 1. Table 3 Assessment schedule and methods of the Triple B Pregnancy Cohort Study Subject  Pregnancy trimester 1  Pregnancy trimester 2  Pregnancy trimester 3  Postnatal 8 weeks  Postnatal 12 months  Mother  Interview Questionnaire  Interview Questionnaire  Interview Questionnaire Urine sample  Interview Questionnaire Blue Book Buccal swab  Interview Questionnaire Observational assessment  Partner  –  –  Interview Questionnaire  Interview Questionnaire Buccal swab  Interview Questionnaire Observational assessment  Infant offspring  –  –  –  Blue Book Developmental assessment Buccal swab  Developmental / observational assessments Buccal swab  Subject  Pregnancy trimester 1  Pregnancy trimester 2  Pregnancy trimester 3  Postnatal 8 weeks  Postnatal 12 months  Mother  Interview Questionnaire  Interview Questionnaire  Interview Questionnaire Urine sample  Interview Questionnaire Blue Book Buccal swab  Interview Questionnaire Observational assessment  Partner  –  –  Interview Questionnaire  Interview Questionnaire Buccal swab  Interview Questionnaire Observational assessment  Infant offspring  –  –  –  Blue Book Developmental assessment Buccal swab  Developmental / observational assessments Buccal swab  In instances where women commenced participation after trimester 1 or 2, pregnancy assessments were completed for earlier waves retrospectively. What is attrition like? Attrition across the five waves of data collection for the general antenatal cohort has been low (Figure 1). Of the 1399 mothers remaining in the cohort following delivery, 118 (8.4%) withdrew or were lost to further follow-up, such that the total attrition rate at 12 months from the original cohort of 1534 was 16.0% (i.e. 84.0% retention). Of the 1436 infants included in the study, developmental data were collected from 1310 (91.2%) at the 12-month follow-up. Of the 842 general antenatal cohort partners who participated directly in the study, 57 (6.8%) withdrew or were lost to follow-up at 8 weeks, and a further 74 (8.8%) at 12 months (resulting in a total retention rate of 84.4%). Attrition rates for mothers from the specialist SUD drug and alcohol antenatal clinics were higher than for the general antenatal population [Figure 2; 46.1% versus 16.0%; χ2(1, N = 1623) = 52.5; P < 0.001; ϕ = 0.18; 95% CI 0.10, 0.26]. After infant delivery, 61 (68.5%) mothers remained in the study and, by 12 months, another 15 (24.6%) participants had withdrawn or were lost to follow-up, leaving a final retention rate of 53.9% from the original cohort. Mothers in the both cohorts who withdrew or were lost to follow-up by 12 months were younger than those who continued (general cohort mean age 30.8 versus 33.1 years; t289.8 = −5.47; P < 0.001; Cohen’s d = 0.44; 95% CI 0.30, 0.58; specialist cohort mean age 28.2 versus 30.2 years; t77.3 = −1.69; Cohen’s d = 0.37; 95% CI −0.06, 0.80) and had higher rates of unemployment [51.8% versus 30.0%; χ2(1, N = 1623) = 44.32; P < 0.001; ϕ = 0.17; 95% CI 0.10, 0.24]. In addition, participants in the general cohort who withdrew or were lost to follow-up at 12 months reported lower socioeconomic backgrounds through their Socio-Economic Indexes for Areas (SEIFA) scores (1027.7 versus 1050.5; t314.4 = −5.14; P < 0.001; Cohen’s d = 0.40; 95% CI 0.26, 0.54) and were more likely to be from WA than from NSW (31.3% versus 12.4%; χ2[1, N = 1534] = 72.74; P < 0.001; ϕ = 0.20; 95% CI 0.12, 0.28). Comparison of available infant data for both the general and the specialist SUD antenatal cohort who did complete the 12-month development assessment with those who did not, showed no differences in sex [general, 55.0% versus 51.8% male; χ2(1, N = 1453) = 0.49; P = 0.48; specialist, 58.8% versus 56.3% male; χ2(1, N = 55) = 0.03; P = 0.85], birthweight (general, 3.41 kg versus 3.42 kg; t1424 = −1.55; P = 0.44; specialist, 2.97 kg versus 3.18 kg; t56 = −1.07; P = 0.14), 5-min Apgar scores (general, 8.90 versus 8.93; t86.38 = −0.38; P = 0.35; specialist, 8.70 versus 8.80; t38 = −0.30; P = 0.38) and weeks’ gestation at birth (general, 38.88 versus 39.23; t140.25 = −1.59; p = 0.06; specialist, 35.13 versus 38.33; t58 = −0.27; p = 0.40). What has been measured? Table 4 provides a detailed overview of the measures included at each wave. Table 4 Mother, partner and infant measures at each assessment Parent measures  Trimester 1  Trimester 2  Trimester 3  8 weeks postnatal  12 months postnatal  Parent and household demographics             Birth date, gender, country of birth, Family composition, education, SEIFA40  –  –  ✓  –  –   Employment, income  ✓  ✓  ✓  ✓  ✓   Religiosity  –  –  ✓  –  ✓  Maternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  ✓  ✓  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  ✓  ✓  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43,44  ✓  ✓  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment  ✓  ✓  ✓  ✓  ✓  Paternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  –  –  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  –  –  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43  –  –  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment      ✓  ✓  ✓  Pre-conception             Alcohol, tobacco, illicit substance use, maternal – Q/F  –  –  ✓  –  –   Alcohol, tobacco, illicit substance use, paternal – Q/F  –  –  ✓  –  –   Pregnancy planning  –  –  ✓  –  –  Parent relationship functioning             Relationship adjustment/satisfaction, maternal45  –  –  ✓  –  ✓   Relationship adjustment/satisfaction, paternal45  –  –  ✓  –  ✓   Spousal abuse, maternal46  –  –  ✓  –  ✓   Spousal abuse, paternal46  –  –  ✓  –  ✓  Maternal general health             Diet (24-h food diary)/vitamin/supplement use  –  –  ✓  ✓  ✓   Physical health  –  –  ✓  ✓  ✓   Physical activity  –  –  ✓  –  ✓   Sexual health  –  –  ✓  ✓  ✓   Medical treatment  –  –  ✓  ✓  ✓   Pregnancy complications  –  –  ✓  ✓  –   Sleep  –  –  –  ✓  ✓  Paternal general health             Diet (2-h food diary)  –  –  ✓  –  ✓   Physical health  –  –  ✓  –  ✓   Physical activity  –  –  ✓  –  ✓   Medical treatment  –  –  ✓  –  ✓   Sleep  –  –  –  ✓  ✓  Parent measures  Trimester 1  Trimester 2  Trimester 3  8 weeks postnatal  12 months postnatal  Parent and household demographics             Birth date, gender, country of birth, Family composition, education, SEIFA40  –  –  ✓  –  –   Employment, income  ✓  ✓  ✓  ✓  ✓   Religiosity  –  –  ✓  –  ✓  Maternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  ✓  ✓  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  ✓  ✓  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43,44  ✓  ✓  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment  ✓  ✓  ✓  ✓  ✓  Paternal substance use and mental health             Age of first alcohol, tobacco, illicit substance use  –  –  ✓  –  –   Alcohol, tobacco, illicit substance, caffeine use – Q/F  –  –  ✓  ✓  ✓   Heavy episodic alcohol use – Q/F  –  –  ✓  ✓  ✓   Lifetime/past 12-month mental health diagnosis41,42  –  –  ✓  –  –   Depression, stress, anxiety43  –  –  ✓  ✓  ✓   Antisocial behaviour  –  –  ✓  –  –   Social functioning  –  –  ✓  –  ✓   Current treatment      ✓  ✓  ✓  Pre-conception             Alcohol, tobacco, illicit substance use, maternal – Q/F  –  –  ✓  –  –   Alcohol, tobacco, illicit substance use, paternal – Q/F  –  –  ✓  –  –   Pregnancy planning  –  –  ✓  –  –  Parent relationship functioning             Relationship adjustment/satisfaction, maternal45  –  –  ✓  –  ✓   Relationship adjustment/satisfaction, paternal45  –  –  ✓  –  ✓   Spousal abuse, maternal46  –  –  ✓  –  ✓   Spousal abuse, paternal46  –  –  ✓  –  ✓  Maternal general health             Diet (24-h food diary)/vitamin/supplement use  –  –  ✓  ✓  ✓   Physical health  –  –  ✓  ✓  ✓   Physical activity  –  –  ✓  –  ✓   Sexual health  –  –  ✓  ✓  ✓   Medical treatment  –  –  ✓  ✓  ✓   Pregnancy complications  –  –  ✓  ✓  –   Sleep  –  –  –  ✓  ✓  Paternal general health             Diet (2-h food diary)  –  –  ✓  –  ✓   Physical health  –  –  ✓  –  ✓   Physical activity  –  –  ✓  –  ✓   Medical treatment  –  –  ✓  –  ✓   Sleep  –  –  –  ✓  ✓  What has it found? Data on alcohol and substance use in pregnancy and the postnatal period are presented in Table 5. Rates of alcohol, tobacco and illicit substance use during pregnancy were highest in the period preceding pregnancy awareness, and decreased considerably after pregnancy awareness in the general cohort [trimester 1 before versus afternawareness [χ2(1, N = 1302) = 548.48; P < 0.00; OR = 0.03; 95% CI OR 0.01, 0.04; χ2(1, N = 1300) = 108.04, P < 0.001; OR = 0.01; 95% CI OR 0.00, 0.05; χ2(1, N = 1301) = 36.36, P < 0.001; OR = 0.05; 95% CI OR 0.01, 0.18, respectively]. For women in the specialist cohort, decreases in alcohol and illicit substance use following pregnancy awareness were also highest in trimester 1 [χ2(1, N = 70) = 20.17; P < 0.001; OR = 0.04; 95% CI OR 0.00, 0.27; χ2(1, N = 70) = 14.00; P < 0.001; OR = 0.00; 95% CI OR 0.00, 0.30]. Tobacco use, however, remained unchanged [χ2(1, N = 70) = 0.67; P = 0.414 before and after pregnancy awareness in trimester 1]. Table 5 Alcohol and other substance use in the Triple B Cohort during pregnancy and following delivery   Trimester 1 pre-awareness N = 1389an (%)   Trimester 1 post-awareness N = 1599bn (%)   Trimester 2 N = 1554 n (%)   Trimester 3 N = 1447 n (%)   8 weeks postnatal N = 1449 n (%)   Alcohol  General  Specialist  General  Specialist  General  Specialist  General  Specialist  General  Specialist  Typical frequency of consumption                       Never  503 (38.3)  36 (46.8)  1229 (80.9)  62 (78.5)  1038 (70.6)  69 (82.1)  977 (70.4)  50 (83.3)  530 (38.1)  35 (59.3)   Less than once per month  158 (12.0)  7 (9.1%)  100 (6.6)  6 (7.5)  129 (8.8)  4 (4.8)  104 (7.5)  5 (8.3)  225 (16.2)  14 (23.7)   Once per month  35 (2.7)  6 (7.8%)  34 (2.2)  2 (2.5)  72 (4.9)  5 (6.0)  52 (3.8)  1 (1.7)  82 (5.9)  3 (5.1)   2–3 times per month  74 (5.6)  –  55 (3.6)  1 (1.3)  87 (5.9)  1 (1.2)  86 (6.2)  –  105 (7.6)  1 (1.7)   1–2 times per week  308 (23.5)  13 (16.9)  84 (5.5)  6 (7.6)  121 (8.2)  3 (3.6)  134 (9.7)  4 (6.7)  273 (19.6)  5 (8.5)   3–4 times per week  133 (10.1)  9 (11.7)  11 (0.7)  2 (2.5)  18 (1.22)  1 (1.2)  22 (1.6)  –  118 (8.5)  –   5–6 times per week  40 (3.1)  3 (3.9)  1 (0.1)  –  1 (0.1)  1 (1.2)  4 (0.3)  –  29 (2.1)  1 (1.7)   Daily  61 (4.7)  3 (3.9)  6 (0.4)  –  4 (0.3)  –  8 (0.6)  –  28 (2.0)  –  Drinkers:  809  41  291  17  432  15  410  10  860  24  Median number of standard drinks consumed per typical occasion  3.0 (IQR = 3.0)  4.5 (IQR = 6.0)  1.5 (IQR = 0.4)  3.0 (IQR = 3.0  1.5 (IQR = 0.5)  2.0 (IQR = 1.5)  1.5 (IQR = 0.3)  2.3 (IQR = 3.0)  1.5 (IQR = 0.5)  2.7 (IQR = 4.1)  Binge drinking during period  >4 drinks on one occasion)  416 (51.4)  30 (73.2)  26 (8.9)  7 (41.2)  17 (3.9)  4 (26.7)  14 (3.4)  4 (40.0)  158 (18.4)  10 (41.7)  Median quantity per week (standard drinks)  4.5 (IQR = 9.4)  6.8 (IQR = 24.8)  0.6 (IQR = 2.1)  2.3 (IQR = 4.1)  0.5 (IQR = 2.1)  0.8 (IQR = 6.4)  0.9 (IQR = 2.1)  1.5 (IQR = 2.1)  1.9 (IQR = 4.1)  0.5 (IQR = 4.0)  Tobacco                       Any smoking during period  185 (14.1)  67 (87.0)  86 (5.7)  67 (84)  62 (4.2)  63 (74.1)  50 (3.6)  44 (73.3)  88 (6.3)  49 (83.1)   Median number of cigarettes per week (among smokers)  35.0 (IQR = 75.5)  82.5 (IQR = 84.0)  28.0 (IQR = 49.0)  70.0 (IQR = 77.5)  28.0 (IQR = 66.5)  49.0 (IQR = 49.0)  21.0 (IQR = 67.0)  42.0 (IQR = 42.0)  17.5 (IQR = 52.8)  56.0 (IQR = 56.0)  Illicit drug use                       Used cannabis during period  40 (3.1)  38 (49.4)  14 (0.9)  30 (38.0)  14 (1.0)  26 (30.6)  5 (0.4)  12 (20.0)  13 (0.9)  9 (15.3)   Used other illicit drugs  21 (1.6)  26 (34.2)  0 (0.0)  11 (13.9)  1 (0.1)  8 (9.4)  –  2 (3.3)  4 (0.3)  –    Trimester 1 pre-awareness N = 1389an (%)   Trimester 1 post-awareness N = 1599bn (%)   Trimester 2 N = 1554 n (%)   Trimester 3 N = 1447 n (%)   8 weeks postnatal N = 1449 n (%)   Alcohol  General  Specialist  General  Specialist  General  Specialist  General  Specialist  General  Specialist  Typical frequency of consumption                       Never  503 (38.3)  36 (46.8)  1229 (80.9)  62 (78.5)  1038 (70.6)  69 (82.1)  977 (70.4)  50 (83.3)  530 (38.1)  35 (59.3)   Less than once per month  158 (12.0)  7 (9.1%)  100 (6.6)  6 (7.5)  129 (8.8)  4 (4.8)  104 (7.5)  5 (8.3)  225 (16.2)  14 (23.7)   Once per month  35 (2.7)  6 (7.8%)  34 (2.2)  2 (2.5)  72 (4.9)  5 (6.0)  52 (3.8)  1 (1.7)  82 (5.9)  3 (5.1)   2–3 times per month  74 (5.6)  –  55 (3.6)  1 (1.3)  87 (5.9)  1 (1.2)  86 (6.2)  –  105 (7.6)  1 (1.7)   1–2 times per week  308 (23.5)  13 (16.9)  84 (5.5)  6 (7.6)  121 (8.2)  3 (3.6)  134 (9.7)  4 (6.7)  273 (19.6)  5 (8.5)   3–4 times per week  133 (10.1)  9 (11.7)  11 (0.7)  2 (2.5)  18 (1.22)  1 (1.2)  22 (1.6)  –  118 (8.5)  –   5–6 times per week  40 (3.1)  3 (3.9)  1 (0.1)  –  1 (0.1)  1 (1.2)  4 (0.3)  –  29 (2.1)  1 (1.7)   Daily  61 (4.7)  3 (3.9)  6 (0.4)  –  4 (0.3)  –  8 (0.6)  –  28 (2.0)  –  Drinkers:  809  41  291  17  432  15  410  10  860  24  Median number of standard drinks consumed per typical occasion  3.0 (IQR = 3.0)  4.5 (IQR = 6.0)  1.5 (IQR = 0.4)  3.0 (IQR = 3.0  1.5 (IQR = 0.5)  2.0 (IQR = 1.5)  1.5 (IQR = 0.3)  2.3 (IQR = 3.0)  1.5 (IQR = 0.5)  2.7 (IQR = 4.1)  Binge drinking during period  >4 drinks on one occasion)  416 (51.4)  30 (73.2)  26 (8.9)  7 (41.2)  17 (3.9)  4 (26.7)  14 (3.4)  4 (40.0)  158 (18.4)  10 (41.7)  Median quantity per week (standard drinks)  4.5 (IQR = 9.4)  6.8 (IQR = 24.8)  0.6 (IQR = 2.1)  2.3 (IQR = 4.1)  0.5 (IQR = 2.1)  0.8 (IQR = 6.4)  0.9 (IQR = 2.1)  1.5 (IQR = 2.1)  1.9 (IQR = 4.1)  0.5 (IQR = 4.0)  Tobacco                       Any smoking during period  185 (14.1)  67 (87.0)  86 (5.7)  67 (84)  62 (4.2)  63 (74.1)  50 (3.6)  44 (73.3)  88 (6.3)  49 (83.1)   Median number of cigarettes per week (among smokers)  35.0 (IQR = 75.5)  82.5 (IQR = 84.0)  28.0 (IQR = 49.0)  70.0 (IQR = 77.5)  28.0 (IQR = 66.5)  49.0 (IQR = 49.0)  21.0 (IQR = 67.0)  42.0 (IQR = 42.0)  17.5 (IQR = 52.8)  56.0 (IQR = 56.0)  Illicit drug use                       Used cannabis during period  40 (3.1)  38 (49.4)  14 (0.9)  30 (38.0)  14 (1.0)  26 (30.6)  5 (0.4)  12 (20.0)  13 (0.9)  9 (15.3)   Used other illicit drugs  21 (1.6)  26 (34.2)  0 (0.0)  11 (13.9)  1 (0.1)  8 (9.4)  –  2 (3.3)  4 (0.3)  –  aSample size is reduced as questions regarding pre- and post-awareness were introduced after the study had commenced (questions not included for n = 221). Also excludes 8 women who had no pre-awareness data as they were reportedly aware of their pregnancy immediately. bPost-awareness data were not available for 18 women who did not know they were pregnant in trimester 1. Overall, following pregnancy awareness and during the course of pregnancy, 36.94% and 30.26% of women consumed any alcohol, 6.02% and 86.84% smoked cigarettes and 1.37% and 52.63% consumed illicit drugs in the general and specialist groups, respectively. The quantity of alcohol consumption in the sample was generally low, averaging around two standard drinks per occasion in the specialist cohort and less than one in the generalist cohort. Alcohol use16–18 was comparable with that of the general population for the two subgroups, whereas tobacco smoking,1,20 and illicit drug use20 were lower in the general cohort subgroup but higher for the specialist subgroup, compared with the general population during pregnancy. A number of articles have been published on the Triple B Cohort.21–28 McCormack et al.21 examined the patterns and predictors of alcohol consumption by women before awareness of pregnancy, and change in alcohol use following pregnancy recognition. Binge and heavy drinking were common in the early weeks of pregnancy, before pregnancy recognition (15.5% and 19.3%, respectively). Importantly, the rate of alcohol-exposed pregnancies was shown to be considerably higher than previous estimates when the period preceding pregnancy recognition is taken into account. Factors associated with changes in women’s alcohol use following pregnancy recognition included level of alcohol use preceding pregnancy recognition, older maternal age, pregnancy planning and illicit substance use. Heavy drinkers were more likely to cease drinking than low or moderate drinkers were. Women drinking at low or moderate levels were more likely to continue drinking at the same level than they were to cease completely, relative to heavy drinkers. The results have important relevance to health policy and preventive measures to minimize alcohol-related harms to mothers and their offspring. In regard to the SU group, there is a dearth of prospective data on women affected by substance use disorders during the perinatal period, often due to challenges with recruitment and retention. Yet understanding the experiences of these women at this time is critical to informing perinatal services to promote maternal well-being and infant development. A, prospective study on the SUD group found that these women experience psychosocial disadvantage, poorer bonding to their developing fetus in utero and elevated levels of perinatal distress and postnatal parenting stress.22 Findings highlight the critical importance of psychological and parenting support for these high-risk pregnant women and their offspring. What are the main strengths and weaknesses? The study provides five areas of innovation. First, it provides the most comprehensive longitudinal assessment of substance use in the perinatal period to date in Australia. Comprehensive assessment during this period will improve knowledge of the impact of substance use on infant development, and help identify critical risk thresholds and periods. Importantly, the study takes into account substance use behaviour both before and after pregnancy awareness; a distinction often overlooked in previous research. Second, this is the first study comparing pregnant women recruited from a general antenatal clinic and a substance dependence treatment clinic, allowing for substance use to be examined across a wide spectrum from low/moderate, to harmful/dependent use. This will improve understanding of the psychosocial and physical risk factors from varying levels of substance use. Third, the study is the first to comprehensively assess the impact of the partner’s substance use and mental health, both pre- and postnatally, on child health and family function. It also assesses the influence partners have on each other’s substance use. Fourth, collection of buccal cells from infants (at 8 weeks and 12 months) and parents (at infant age 12 months) will provide a basis for epigenetic research into factors conferring individual differences in risk for substance use in parents, and adverse effects of parental substance use on children23 (although we also note that cord blood samples were not obtained, limiting the potential of epigenetic studies related to developmental origins and the effect of pregnancy exposure to these substances). Finally, there is potential for data synthesis with intergenerational cohort studies. For example, major components of the Triple B Cohort assessments have been aligned with the Australian Temperament Project Generation Three Study (ATPG3) and the Victorian Intergenerational Health Cohort Study (VIHCS). This alignment has the potential to develop an integrated network of intergenerational cohorts, each focusing on specific prenatal and preconception periods. Specifically, the Triple B Cohort will provide rare and detailed data on exposures in pregnancy. The ATPG3 and VIHCS have a single antenatal assessment in trimester 3 but rich preconception data across three and two generations, respectively. The Triple B Study also captures key patterns of substance use for which there are major public health, prevention or treatment implications. Namely, it captures heavy/dependent substance use, addressed through oversampling pregnant women in treatment for substance use problems, and low to moderate (and binge) alcohol and tobacco use, which are adequately captured in the antenatal clinic sample (based on power analyses). Given the low prevalence of illicit substance use (other than cannabis) in pregnancy, it is unlikely that Triple B, or any other single study, unless very large scale, will be able to examine the impacts of low to moderate stimulant or opioid use on children. We also note that the sample is underpowered for genetic (but not epigenetic) research. Although the Triple B Study is a multi-site study conducted in two states, it was conducted in public urban hospitals and therefore is not representative of rural areas of Australia, nor of families that use private hospitals. The planned cross-comparison and harmonization of data with other major national and international cohorts may allow for increased pooled data and the potential capacity to examine outcomes of lower prevalence in smaller subgroups. A further potential limitation of the study relates to the generalizability and validity of inferences drawn from the study, given that the general antenatal cohort differs in a number of ways from the general population, and there was evidence to suggest that attrition was higher among women in less privileged socioeconomic circumstances. Nevertheless, the cohort includes participants from a range of demographic backgrounds and with varying substance use patterns, and overall attrition was low. In addition, as noted above, substance use in the general antenatal cohort during pregnancy was consistent with Australian population data. A major focus of the study was on comprehensive (prospective) data capture in the antenatal period; as such, there is a longer gap between the 8-week an 12-month assessments. This limits the capacity to understand how early postnatal exposures may affect growth and development. We do note, however, that information on some key developmental indicators (breastfeeding and sleep, for example), was assessed in the intervening period via recent retrospective reports. We also note that response rates for the study ranged from 38% to 45%. Whereas these rates are consistent with some recent longitudinal cohorts with hospital-based recruitment in Australia,15 the limitation is that risk estimates may reflect underestimation of the true estimates because the extreme end of the distribution is less likely to be captured. Finally, much of the information collected, including substance use data, was via self-report and is thus subject to potential biases. In order to address this limitation, 85 participants were randomly selected for urine analysis during their third trimester of pregnancy, to confirm self-reported illicit substance use. Agreement between self-reported substance use and urine analysis was 97%, indicating that the information provided was reliable. Despite these limitations, the study will improve understanding of the effects of parental substance use on infants and families, which can direct health policy. The results can inform development of public health prevention and early intervention campaigns to allow parents to make informed choices about substance use during the prenatal period. The results will also identify the health and obstetric needs of pregnant women characterized by harmful and/or risky patterns of substance use. Improvements in these areas may subsequently reduce developmental problems in infant and family functioning problems in the community. The results of this study can also inform national guidelines on use of alcohol and other substances before conception, in pregnancy and while breastfeeding, which may guide public health education and policy on substance use. Can I get hold of the data? Where can I find out more? Further information can be obtained through the National Drug and Alcohol Research Centre, University of New South Wales [https://ndarc.med.unsw.edu.au/project/triple-b-bumps-babies-and-beyond]. Enquires can be directed to Dr Hutchinson (corresponding author). Data access is governed by the investigators. Research proposals must be consistent with ethical approval and participant consent, confidentiality and data management. The study protocol for collaborative research requires ratification by the respective ethics committee affiliated with the research. Profile in a nutshell The Triple B Pregnancy Cohort Study is a longitudinal pregnancy cohort focused on understanding the impacts of parental alcohol and other drug use in pregnancy and postnatally on infant development and family functioning. The study recruited two sub-samples: (i) a general antenatal clinic sample of pregnant women and their partners (n = 1534 women; 841 of their partners); and (ii) a smaller sample of pregnant women with diagnosed substance use disorders (n = 89 women). Participants were recruited in 2009–13 at antenatal clinics in Sydney, NSW, and Perth, WA, Australia. The sample has been extensively examined through the gestational period with assessments in trimesters 1, 2 and 3 and at 8 weeks and 12 months postnatally; retention at 12 months was 84.0% and 73.8% for mothers in the general antenatal and substance use disorder clinics, respectively. The data collected include demographic, parental, familial and infant factors, with a focus on parental substance use and mental health, parenting practices, familial functioning and infant development. For information on collaboration with the Triple B Cohort dataset see [https://ndarc.med.unsw.edu.au/project/triple-b-bumps-babies-and-beyond]. Funding The research was funded by an Australian National Health and Medical Research Council (NHMRC) Project Grant #GNT630517 for $2,196,179 to R.P.M., D.H., S.A., J.N., E.E., L.B., S.J., C.O. and A.B., and was financially supported by the National Drug and Alcohol Research Centre (NDARC), University of New South Wales (UNSW). NDARC and the National Drug Research Institute (NDRI), Curtin University, are funded by the Australian Government under the Substance Misuse Prevention and Service Improvements Grants Fund. We also acknowledge financial support from Australian Rotary Health, the Foundation for Alcohol Research and Education, and the Financial Markets Foundation for Children (Australia). R.P.M. is financially supported by an NHMRC Principal Research Fellowship Award from the NHMRC, and D.H. is financially supported by an Australian Unity Industry Partner Senior Research Fellowship. C.O. is supported by an Australian Research Council Senior Research Fellowship (DORA: DP 130101459). E.E. is supported by an NHMRC Practitioner Fellowship #1021480. Acknowledgements We gratefully acknowledge the NDARC and NDRI research staff and students who assisted with collection of the data, the hospitals and antenatal clinics for their assistance with recruitment, and the study participants and their families. We wish to acknowledge Rosa Alati, Brandi Baylock, Lauren Bell, Elissa Bowey Annie Bleeker, Apo Demirkol, Genevive Eckstein, David Fergusson, Thea Gumbert, Helen Gunn, Jeannie Minnis, Colleen O’Leary, Vaughan Palmer, Jemma Pope, Jarrod Proudfoot, Candice Rainsford, Joanne Ross, Fiona Shand, Lisa Sin, Matthew Sunderland, Wendy Swift, Scarlet Wilcock and Jesse Young. We also wish to acknowledge the Cannabis Cohorts Research Consortium (NHMRC Project Grants: AAP1009381, AAP1064893). The Triple B Research Consortium includes the primary investigators already listed and: Joanne Cassar, Aurora Popescu, Gabrielle Campbell, Lee Taylor, Maria Gomez, Emma Black, Danya Braunstein, Laura Dewberry, Erin Kelly, Alex Aiken, Sarah Brann, Sara Clews, Sharon Dawe, Adrienne Gordon, Paul Haber, Dale Hamilton, Andrew Lewis, Nyanda McBride, Elizabeth Moore, Raewyn Mutch, Julee Oei, George Patton, Ronald Rapee, Tim Slade, Marian Shanahan, Christine Stephens, Samantha Teague and Meredith Ward. 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International Journal of EpidemiologyOxford University Press

Published: Feb 1, 2018

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