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Enregistrement W2569117527 · doi:10.1093/ije/dyw308

Cohort Profile: The Western Australian Pregnancy Cohort (Raine) Study–Generation 2

2016· article· en· W2569117527 sur OpenAlexfundno aff
Leon Straker, Jenny Mountain, Angela Jacques, Scott W. White, Anne Smith, LOUIS I. LANDAU, Fiona Stanley, John P. Newnham, Craig E. Pennell, Peter R. Eastwood

Notice bibliographique

RevueInternational Journal of Epidemiology · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueBirth, Development, and Health
Établissements canadiensnon disponible
Organismes subventionnairesMedical Research CouncilSpinnaker Health Research FoundationPrincess Margaret Hospital FoundationEdith Cowan UniversityCanadian Institutes of Health ResearchNational Health and Medical Research CouncilWomen and Infants Research FoundationRaine Medical Research FoundationPfizerTelstra FoundationCurtin University of TechnologyAsthma Foundation of Western AustraliaNational Medical Research CouncilHealthway
Mots-clésCohortMedicineCohort studyPregnancyObstetricsDemographyInternal medicineBiology

Résumé

récupéré en direct d'OpenAlex

The Western Australian Pregnancy Cohort (Raine) Study (www.rainestudy.org.au) was established 1989-1991 with the then stated purpose: to develop a large cohort of Western Australian children studied from 18 weeks’ gestation to ascertain the relative contributions of familial risk factors, fetal growth, placental development and environmental insults to outcome in infancy and to the precursors of adult morbidity. This cohort, with complete intrauterine, perinatal and childhood data, will enable evaluation of the interaction between these factors, subsequent lifestyle patterns and environmental exposures which contribute to ill health during life.1 Establishment of the cohort involved combining funding for ‘a randomised controlled trial of the influence of serial fetal ultrasounds on birth outcomes’ from the National Health and Medical Research Council of Australia2 and funding to investigate ‘the origins of disease in the fetus, the child and the young adult’ from the Raine Medical Research Foundation.1 The conceptual framework for the study was initially based around the developmental origins of health and disease, but has since evolved into a life-course framework taking into account the multiple interacting domains of genetics, phenotypes (cardiometabolic, respiratory, immunological, hormonal, musculoskeletal, psychological, vision and hearing, body composition and growth), behaviours (physical activity, sedentary behaviour, sleep, diet, drug use, risk taking), the environment (sunlight, chemical exposures, spatial environment) and other developmental outcomes (education, work). Pregnant women presenting at the public antenatal clinic at King Edward Memorial Hospital (at that time it was the only tertiary women’s and infants’ hospital in Perth, Western Australia) and nearby private practice clinics between May 1989 and November 19913 were invited to participate. Women were invited if they were between 16 and 20 weeks pregnant, had sufficient proficiency in English, were expected to deliver at the hospital and intended to remain in Western Australia. A total of 2900 women (‘Generation 1’) were enrolled into the study. There were 2868 live births–the index participants of ‘Generation 2’–including 60 sets of twins (n = 120) and two sets of triplets (n = 6), from 2826 mothers (see Figure 1). Flow diagram of Raine Study cohort participation. The cohort has been regularly followed up since birth. The number of participants has gradually decreased over time (Figure 1) and the proportion of eligible participants (those who have not died, withdrawn, been lost or deferred) providing data at each assessment remained relatively constant across childhood and adolescence, but has reduced in young adulthood (Figure 2). The reduced participation rate at the 2-year follow-up was due to the study running out of resources to complete data collection of the whole cohort. Raine Study cohort participation rates across life-course periods. The representativeness and presence of potential biases in the cohort have been examined with three sets of analyses. Eligibility and consent rates at the recruiting clinics were evaluated. Comparisons were made between the cohort participants and the Western Australian population at birth, childhood (year 8), adolescence (years 14 and 17) and young adulthood (years 20 and 22). Comparisons were also made between cohort participants and non-participants for all follow-ups. At the time of recruitment, to assess whether the Raine Study cohort was representative of the population presenting at the recruitment sites, 6 months of clinic records in the middle of the recruitment period were audited. In the 131 clinic sessions, 1420 women presented as new attendees and 707 (50%) were eligible. Reasons for ineligibility were: 36% were > 20 weeks’ gestation; 8% had language difficulties; 4% planned to deliver elsewhere; and 2% had psychosocial problems precluding long-term follow-up. Of the 707 eligible, 633 (90%) agreed to participate during the audited period.3 At birth, the characteristics of the Raine cohort were compared with those of all live births (excluding Raine births) in Western Australia during the 3-year recruitment period, using data from the WA Department of Health Midwives Notification System and Hospital Morbidity Database. Comparisons were made of birthweight, gestation age, neonatal nursery admission, pregnancy complications, caesarean sections, maternal age, parity, marital status and race. Overall, the characteristics of Raine participants were similar to all Western Australian contemporaneous births except that Raine Study participants had slightly more pregnancies with complications and caesarean deliveries, and had more first-time mothers and unmarried mothers (see Table 1). Comparison of Raine Study cohort families at birth with the Western Australian (WA) population of babies born contemporaneously, using linked data derived from the Western Australian Department of Health Midwives Notification System and Hospital Morbidity Database Index of Relative Soci-economic Disadvantage. Comparison of Raine Study cohort families at birth with the Western Australian (WA) population of babies born contemporaneously, using linked data derived from the Western Australian Department of Health Midwives Notification System and Hospital Morbidity Database Index of Relative Soci-economic Disadvantage. At the 8-year follow-up, the characteristics of participating cohort families were compared with the Year 2001 Western Australian Population Census data (see Table 2). Demographic factors compared included family structure, state of residence, parents’ place of birth, education, labour force participation and occupational status, income level and language spoken at home. Overall differences between Raine Study and WA population families were small except for more Raine parents residing in WA, being born overseas, more with post-secondary and tertiary education and in clerical/retail occupations, and less parents having low incomes. Comparison of Raine Study cohort families at childhood (age 8 years) with contemporaneous Western Australian (WA) Census population (2001 census data) Maternal education: WA 2001 Census data based on adult female education levels; Raine data based on maternal education levels attained by 8 years. Parent occupation: WA 2001 Census data based on 35-44 age category for all persons to correspond to median maternal age and available paternal age at 8 years [Raine: parent age median (interquartile range): maternal = 37.2 (33.1, 41.2); paternal = 39.9 (36.2, 43.8)]; Raine data based on highest level occupation of either parent at 8 years. Not in labour force or not stated. Family income: WA 2001 Census data based on weekly family income for single and couple parent families: low, < $400 per week (pw); medium, $400-$800 pw; high, > $800 pw; Raine family income level at 8 years: low, < $25K per annum (pa); medium, $25K-$60K pa; high, > $60K pa. Comparison of Raine Study cohort families at childhood (age 8 years) with contemporaneous Western Australian (WA) Census population (2001 census data) Maternal education: WA 2001 Census data based on adult female education levels; Raine data based on maternal education levels attained by 8 years. Parent occupation: WA 2001 Census data based on 35-44 age category for all persons to correspond to median maternal age and available paternal age at 8 years [Raine: parent age median (interquartile range): maternal = 37.2 (33.1, 41.2); paternal = 39.9 (36.2, 43.8)]; Raine data based on highest level occupation of either parent at 8 years. Not in labour force or not stated. Family income: WA 2001 Census data based on weekly family income for single and couple parent families: low, < $400 per week (pw); medium, $400-$800 pw; high, > $800 pw; Raine family income level at 8 years: low, < $25K per annum (pa); medium, $25K-$60K pa; high, > $60K pa. At the 14- and 17-year follow-ups, the cohort family characteristics of participants were compared with Year 2006 Western Australian Population Census data of families living in Western Australian with 15-17 year old children, as this was the most appropriately representative Western Australian demographic for comparison for either follow-up (see Table 3). Demographic factors compared included family structure, parents’ place of birth, education, labour force and occupational status, income level and an index of advantage/disadvantage. Overall, the characteristics of the Raine families were similar to contemporaneous Western Australian families. There were no substantial differences in proportions of family structure or index of socioeconomic advantage/disadvantage. There were more Raine families living in urban areas and with tertiary education. At 14 years, there were more Raine parents in clerical/administrative occupations and middle incomes, and at 17 these differences were reduced with a shift of Raine parents to technical and professional occupations and higher incomes. Comparison of Raine Study cohort families at adolescence (ages 14 and 17 years) with contemporaneous Western Australian (WA) Census population (2006 Census data) Index of Relative Socioeconomic Advantage and Disadvantage. Out of % in labour force. By choice. Comparison of Raine Study cohort families at adolescence (ages 14 and 17 years) with contemporaneous Western Australian (WA) Census population (2006 Census data) Index of Relative Socioeconomic Advantage and Disadvantage. Out of % in labour force. By choice. At the 20- and 22-year follow-ups, the characteristics of cohort members participating in data collection were compared with contemporaneous Year 2011 Western Australian Census Data of 20- and 22-year-old males and females living in Western Australia as the most appropriately representative Western Australian demographic for comparison (see Table 4; and Supplementary Tables 1 and 2, showing sex-specific comparisons, are available as Supplementary data at IJE online). Demographic factors compared included family structure, education completed, labour force status, occupation, work hours and income level. Overall, most comparisons showed the Raine cohort had similar proportions as all Western Australian young adults. Exceptions with more marked proportional differences (> 10%) indicated that the Raine cohort at 17 years had more employed in clerical/retail, more working 40 or more hours a week and more with higher incomes. Comparison of Raine Study cohort participants at young adulthood (ages 20 and 22 years) with contemporaneous Western Australian (WA) Census population (2011 Census data) Out of total n employed in labour force. Comparison of Raine Study cohort participants at young adulthood (ages 20 and 22 years) with contemporaneous Western Australian (WA) Census population (2011 Census data) Out of total n employed in labour force. To assess any attrition bias, the characteristics at infancy of participants and non-participants were compared at each follow-up (see Tables 5, 6 and 7). In general, the proportions of participants and non-participants across a number of infant characteristics remained constant across all follow-ups. An exception was a gradual reduction in participation of infants of Aboriginal and Torres Strait Islander ethnicity. Comparison of participants and non-participants across childhood follow-ups by infant characteristics at birth % of mean birthweight for gestational age based on WA norms (Roberts 1999). Small for gestational age (GA): < 90% expected birthweight. Large for GA: > 110% expected birthweight (both based on Australian birthweight norms). Emergency caesarean section. ATSI: Aboriginal or Torres Strait Islander. P < 0.001. Comparison of participants and non-participants across childhood follow-ups by infant characteristics at birth % of mean birthweight for gestational age based on WA norms (Roberts 1999). Small for gestational age (GA): < 90% expected birthweight. Large for GA: > 110% expected birthweight (both based on Australian birthweight norms). Emergency caesarean section. ATSI: Aboriginal or Torres Strait Islander. P < 0.001. Comparison of participants and non-participants across adolescent follow-ups by infant characteristics at birth % of mean birthweight for gestational age based on WA norms (Roberts 1999). Small for gestational age (GA): < 90% expected birthweight (based on Australian birthweight norms). Large for GA: > 110% expected birthweight (based on Australian birthweight norms). Emergency caesarean section. ATSI: Aboriginal or Torres Strait Islander. P < 0.001, ** < 0.01 for differences between participants and non-participants (comparisons based on chi-square tests). Comparison of participants and non-participants across adolescent follow-ups by infant characteristics at birth % of mean birthweight for gestational age based on WA norms (Roberts 1999). Small for gestational age (GA): < 90% expected birthweight (based on Australian birthweight norms). Large for GA: > 110% expected birthweight (based on Australian birthweight norms). Emergency caesarean section. ATSI: Aboriginal or Torres Strait Islander. P < 0.001, ** < 0.01 for differences between participants and non-participants (comparisons based on chi-square tests). Comparison of participants and non-participants across young adult follow-ups by infant characteristics at birth % of mean birthweight for gestational age based on Western Australian norms (Roberts 1999). Small for gestational age (GA): < 90% expected birthweight (based on Australian birthweight norms). Large for GA: > 110% expected birthweight (based on Australian birthweight norms). Emergency caesarean section. ATSI: Aboriginal or Torres Strait Islander. P < 0.001. Comparison of participants and non-participants across young adult follow-ups by infant characteristics at birth % of mean birthweight for gestational age based on Western Australian norms (Roberts 1999). Small for gestational age (GA): < 90% expected birthweight (based on Australian birthweight norms). Large for GA: > 110% expected birthweight (based on Australian birthweight norms). Emergency caesarean section. ATSI: Aboriginal or Torres Strait Islander. P < 0.001. The cohort has been assessed on 14 separate occasions. Initial assessment was at 18 weeks gestation, and subsequent assessments were undertaken at 34 weeks, at birth and at ages 1, 2, 3, 5, 8, 10, 14, 17, 18, 20 and 22 years. Currently assessment of participants at age 27 years is under way. Early assessments typically included primary and secondary caregiver reporting via questionnaire and clinical assessments of the child participant. For the 14- and 17-year follow-ups, index participants provided self-report information to complement caregiver reporting and continued to perform clinical assessments. From the 18-year follow-up onwards, index participants provided self-report information along with performing clinical assessments. Specific assessments of reproduction were undertaken in females at the 14-year follow-up and in males at the 20-year follow-up. At the 18-year follow-up, participants with mobility problems or a history of mental health issues were not invited due to the social stressor assessment. Currently the database holds > 70 000 phenotypic measures and > 20 million genetic variants on each participant, as well as over 170 000 biological samples in storage. A list of measurements obtained at each follow-up is presented in Tables 8-11. Raine Study measurements in perinatal period Raine Study measurements in perinatal period Raine Study measurements in childhood period (age in years) Raine Study measurements in childhood period (age in years) Raine Study measurements in adolescent period (age in years) Raine Study measurements in adolescent period (age in years) Raine Study measurements in early adulthood period (age in years) Raine Study measurements in early adulthood period (age in years) Since its genesis in 1989, over 400 peer-reviewed journal papers have been published using the Raine Study data; a full list is available on website [http://www.rainestudy.org.au/research-findings/publications/], along with brief lay summaries of these papers [http://www.rainestudy.org.au/research-findings/highlights/]. The publications used measurements collected during the antenatal/perinatal, infancy, childhood, adolescent and early adulthood periods. Broadly, the nature of the measurements collected over the years and used in these papers can be characterized as being either: (i) genetic; (ii) phenotypic; (iii) behavioural; (iv) environmental; or (iv) educational or work-related. The randomized controlled trial demonstrated that a protocol of five prenatal scans, compared with a single mid-pregnancy morphology scan alone, does not prevent preterm birth or improve pregnancy outcomes.3 Follow-up to 8 years of age from the multiple and single prenatal ultrasound groups provided strong evidence that ultrasound imaging studies are safe,4 as did follow-up of eye structure and function at 20 years of age.5 The unique serial fetal biometry measures have been used to develop customized fetal growth charts.6 Genome-wide association studies have identified genetic variants associated with fetal growth,7 birthweight,8 asthma,9 obesity,10 cognition11 in childhood, vitamin D levels in adolescence12 and myopia in young adulthood.13 Exome array analysis has identified mutations in a number of genes associated with a later age of menarche.14 Epigenetic studies have identified DNA methylation that is related to adiposity in young adulthood.15 Maternal exposure to life stresses during pregnancy predicts increased weight but lower blood pressure in offspring at 20 years of age.16 Passive smoking exposure over childhood and adolescence predicts reduced HDL-cholesterol during adolescence in girls but not boys.17 An adiposity trajectory characterized by an accelerated rate of growth in infancy predicts greater insulin resistance in adolescence.18 Maternal smoking during pregnancy predicts decreased offspring respiratory function in infancy19 and asthma in adolescence.20 Low cytokine levels at birth predict increased risk of asthma, wheeze and allergy in childhood.21 Metabolic risks are increased in girls with polycystic ovary syndrome.22 Menstrual irregularity was common in adolescent girls regardless of polycystic ovary syndrome status.23 Over one-quarter of young men do not meet World Health Organization reference criteria for morphologically normal sperm.24 Acute response patterns to social stress have been characterized and related to gender, health-related behaviours and adiposity.25 Maternal vitamin D deficiency during pregnancy predicts lower bone mass of offspring in young adulthood.26 The presence of back pain in adolescence is associated with the presence of back pain in their carers.27 Depressed mood in adolescence is associated with neck pain in adolescence.28 High concentrations of testosterone in cord blood predicts language impairment in early childhood.29 Gestational hypertension predicts poorer mental ill-health trajectories across childhood and adolescence.30 Being perceived as overweight by one’s parents in middle childhood predicts increased risk of eating disorder in early adolescence.31 Increased life-course sun exposure, as quantified by conjunctival UV autofluorescence, is related to reduced risk of myopia in young adulthood.32 There was no evidence to suggest that exposure to anaesthesia as a child reduces visual acuity or increases myopia in young adulthood.33 Breastfeeding for more than 6 months is protective against otitis media at 3 years of age.34 A trajectory characterized by less than 14 h/week TV viewing across childhood and adolescence predicts lower body fat in young adulthood.35 Trajectories characterized by participation in sports across childhood and adolescence predict better physical health in young adulthood.36 Higher screen time exposure in early childhood predicts lower physical activity and higher BMI in later childhood but not in adolescence.37 Breastfeeding reduces the risk of asthma in childhood.38 A good quality breakfast is associated with better mental health in adolescence.39 Higher consumption of energy drinks is associated with higher anxiety in young adult males.40 Contrary to expectations, earlier age of menarche is not related to age at first sexual intercourse.41 Antenatal exposure to phthalates is related to reduced ovarian reserve in adolescent girls.42 Higher sun exposure is related to pterygium presence in young adults.43 A better quality diet in early childhood predicts better middle school achievement.44 A better quality diet in adolescence is related to better school achievement.45 Work absenteeism is identified as a significant issue for young adults and is associated with spinal pain and mental ill health.46 A major strength of the Raine Study is the breadth, depth and duration of longitudinal data gathered from 14 separate follow-up assessments over 25 years. Specifically, these data included objective clinical assessments at nearly every follow-up in addition to subjective questionnaire assessments. The data and measures along with genetic data and The data also longitudinal data on over 25 years. the continued of a representative cohort of the strong of and and The of the Raine Study to the of its the of the cohort and the gradual attrition of its The Raine Study to and the available the data and are published on the study website in a The Raine Study is a study health and across the life from birth to young Index participants were 2868 live births from 2900 mothers at around 18 weeks’ gestation who were the tertiary perinatal hospital and private clinics in Perth, Western between May and November assessments and clinical measurements were undertaken at 18 and weeks of gestation, birth and 1, 2, 3, 5, 8, 10, 14, 17, 18, 20 and 22 years of A follow-up is under at 27 years of Over index participants remain and eligible for follow-up. Data on and an of educational and occupational factors have been biological samples and Over 400 papers have been published in and on Raine Study from the antenatal to young adulthood periods. its the Raine Study and of its Supplementary data are available at IJE The Raine Study funding from the of Western the Raine Medical Research the Women and Research and of data collection and of data has been provided by the National Health and Medical Research Council of Australia and in King Edward Memorial Hospital Research Raine Medical Research the of Western Australian the Medical Research of Hospital Medical Research Women and Research Health of Health National Research Hospital Health and Council for Western Australia Department of Health Health and Western Australia Department of Health Research of has been by substantial from King Edward Memorial and of The no of The to the Raine Study participants and their families for their participation in the study and the Raine Study for their to and data

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,099
Score d'incertitude au seuil0,197

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,113
Tête enseignante GPT0,414
Écart entre enseignants0,301 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations228
Publié2016
Routes d'admission1
Résumé présentnon

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Même revueInternational Journal of EpidemiologyMême sujetBirth, Development, and HealthTravaux en français237 207