Associations between factors in childhood and young adulthood and childlessness among women in their 40s: A national prospective cohort study.

BACKGROUND: While the risk factors for infertility are well-established, research on factors associated with voluntary childlessness is limited and mainly focused on adulthood factors. Thus, we examined the associations between factors in childhood and young adulthood and different types of childlessness. METHODS: The analysis included 4653 women from the Australian Longitudinal Study on Women's Health from 1996 to 2021. Childlessness was categorised as: voluntary, due to infertility issues, or due to other reasons. The associations between factors in childhood and young adulthood and childlessness were assessed using multinomial logistic regression models. RESULTS: In their 40s, 4.8 % of women were voluntarily childless, 6.7 % were childless due to infertility issues, and 7.8 % were childless due to other reasons. Regardless of types of childlessness, being childless was associated with poorer self-rated health during childhood and having been unpartnered and obese in young adulthood. Ex-smokers in young adulthood had lower odds of childlessness. Childhood physical abuse was associated with childlessness due to infertility issues and other reasons. Voluntary childlessness and childlessness due to infertility issues were associated with having identified as non-exclusively heterosexual in early adulthood. Lower social support in early adulthood was associated with voluntary childlessness and childlessness due to other reasons. LIMITATIONS: The direction of the associations could not be determined and using self-reported data may introduce recall bias. CONCLUSIONS: Factors in childhood and young adulthood were associated with different types of childlessness, highlighting the importance of adopting a life course perspective when studying childlessness.

Adherence to 24-h movement behaviour guidelines in families with multiple children.

BACKGROUND: In 2019, the World Health Organization (WHO) launched the first global movement guidelines for children that combined sleep, physical activity and screen time. Our previous research showed that adherence to age-specific guidelines for screen time was challenging for families with children in different age groups. We aimed to determine whether families with children in different age-based movement guideline categories have poorer adherence to the broader 24-h movement guidelines than those with all children in the same age category. METHODS: Data were from the 1973-1978 cohort of the Australian Longitudinal Study on Women's Health (seventh survey, 2015) and the women's three youngest children (aged ≤12) (Mothers and their Children's Health sub-study, 2016/2017). The sample was 1787 women (families) with 4064 children (mean age 7.2 [SD 2.9]). Whether children in the family were in the same or different age-based category was determined by matching children's ages in a family against age-based guideline categories for the 24-h movement behaviours. The association between children in the family being in the same or different age-based guideline category on adherence to 24-h movement guidelines, both collectively and individually, was analysed by adjusted logistic regression (binary and multinomial). RESULTS: Families with children in the same age guideline categories had double the odds of having all children meet 24-h movement guidelines (adjusted odds ratio [OR] 1.95 [95% confidence interval, CI: 1.32, 2.86]). Families with children in the same age categories on the screen guideline had higher odds of all children meeting (2.25 [1.73, 2.93]) and lower odds of some meeting/some failing the screen guideline (0.18 [0.14, 0.25]), than families with all children in different age categories. Families with children in the same age categories on the physical activity guideline had lower odds of all children meeting (0.57 [0.43, 0.75]) or some meeting/some failing the physical activity guideline (0.08 [0.06, 0.12]). No associations were found for sleep guidelines. CONCLUSIONS: Families with multiple children may need practical advice and strategies on how to adhere to guidelines when children span age categories. This could form part of public health strategies that raise awareness of the guidelines and may improve guideline adherence.

Is being childless associated with a woman's risk of overweight and obesity? Results from a national longitudinal study.

AIM: To examine the association between motherhood status (mothers, voluntarily childless, involuntarily childless) and overweight and obesity over 22 years. METHODS: A total of 4092 women aged 18-23 years were followed from 1996 to 2018. Motherhood status was defined by women's reports on their fertility, attempts to conceive, use of in vitro fertilisation and fertility hormones, and number of biological children. Associations between motherhood status and overweight and obesity were examined using generalised estimating equations models, adjusting for socio-demographic characteristics, lifestyle factors, depressive symptoms, early life factors, and polycystic ovary syndrome (PCOS). RESULTS: At age 40-45 years, 12% of women were voluntarily childless and 5% were involuntarily childless. The prevalence of overweight and obesity increased with age and women who were voluntarily or involuntarily childless had higher prevalence of obesity than mothers in all surveys. After adjusting for covariates, compared with mothers, women who were voluntarily childless had higher odds of being overweight (odds ratio [OR], 95% confidence interval [CI]: 1.29, 1.09-1.52) and obese (OR, 95% CI: 1.65, 1.29-2.12). Involuntary childlessness was not associated with being overweight (OR, 95% CI: 1.05, 0.82-1.33), and its association with obesity was attenuated after adjusting for PCOS in the final model (OR, 95% CI: 1.40, 0.99-1.98). CONCLUSIONS: Around one in nine Australian women remained voluntarily childless by their late reproductive years. On average, they had higher odds of being overweight and obese than mothers, suggesting that overweight and obesity prevention programs should consider tailoring their advice by motherhood status.

Managing Screen Use in the Under-Fives: Recommendations for Parenting Intervention Development.

The impact of excessive screen use on children's health and development is a public health concern and many countries have published recommendations to limit and guide the use of screen media in childhood. Despite this, international studies report that the majority of parents and children do not adhere to screen use recommendations. Existing research aiming to understand children' screen use has largely focused on older children, and on demographic and structural aspects of the child's environment. Parents play a central role in determining young children's screen use and identify numerous barriers to developing healthy screen use practices with their children. However, no clear models exist that incorporate key parenting factors in understanding children's screen use, which presents an impediment to intervention development. Likewise, while some evidence exists for interventions to improve children's screen use behaviours, most are focused on older children and parental involvement has generally been limited. In this paper, we overview key factors associated with screen use in young children (< 5 years) and summarise the existing evidence base for interventions designed to support healthy screen use. This paper proposes a conceptual model linking aspects of parenting and the socio-ecological environment to young children's screen use. Our proposed model could be used to design longitudinal studies of screen use predictors and outcomes, and inform intervention development. Finally, the paper provides key recommendations for future research, intervention development and testing.

Do mothers or females without children have better health-related quality of life across their reproductive years?

PURPOSE: To compare health-related quality of life (HRQoL) between mothers and females who were voluntarily or involuntarily childless, across their reproductive years. METHODS: 4100 females born in 1973-78 from the Australian Longitudinal Study on Women's Health were followed for 22 years. Motherhood status was defined by females' reports in Survey 8 (2018, 40-45 years) on their fertility, attempts to conceive, use of in vitro fertilization and fertility hormones, and number of children. HRQoL was assessed in each survey using the 36-Item Short Form Survey (SF-36). Linear mixed models were used to assess the associations between motherhood status and HRQoL. RESULTS: Over 22 years, compared with females who were voluntarily childless, mothers on average had better HRQoL (shown by scores 1.5 to 3.4 points higher on five of the eight SF-36 subscales), while females who were involuntarily childless scored 2.2 to 3.0 points lower on three of eight SF-36 subscales. Compared with females who were voluntarily childless, teen mothers (age at first birth < 20 years) scored lower on role limitations due to physical problems subscale (b = -5.5, 95% CI: -9.3, -1.6), while females with either two, or three or more children scored 1.6 to 4.8 points higher on seven of eight SF-36 subscales. CONCLUSIONS: Females who were childless had poorer HRQoL than mothers. Further research is needed to understand the underlying mechanisms, which could inform policymakers on how to reduce the health disparities and improve long-term health outcomes for females.

History of pre-pregnancy maternal symptoms of binge eating and childhood behavioral problems in girls and boys.

OBJECTIVE: To explore whether children of mothers with pre-pregnancy binge eating (BE) symptoms have more behavioral difficulties compared with those without and whether associations are moderated by ED symptoms and other maternal health and social factors measured during childhood. METHOD: Pre-pregnancy BE symptoms were collected by the Australian Longitudinal Study on Women's Health at Survey 1 (in 1996) and/or at Survey 2 (in 2000) using questions mapped to DSM BE criterion 1. In 2016/7, 2180 women from the 1973-78 cohort provided data on externalizing and internalizing behavior, measured by Strengths and Difficulties Questionnaire, on 4054 of their children (2-12 years) in the Mothers and their Children's Health study. Covariates were markers of other ED symptoms, sociodemographic, social support, and mental health factors collected proximally to the child outcomes. Hierarchical multivariable regression models, using generalized estimating equations accounting for clustering of children within mothers, were used. RESULTS: Pre-pregnancy BE symptoms were associated with child behavior, with associations only moderated after adjustment for proximal markers of ED (girls internalizing behavior, b (95%CI) .30 (-.02, .61); boys externalizing behavior .34 (-.04, .73)) or social support (girls externalizing behavior 0.26 (-.08, .61)). Pre-pregnancy BE symptoms were not associated with boys internalizing behavior (-.27 (-.02, 0.57)). DISCUSSION: Studies with repeated ED measures should test hypotheses that these associations vary by timing of ED measurement. Identification of young women at risk of BE symptoms pre-pregnancy, as well as when children are older, may enable health services, treatment programs, and supports to minimize longer term effects on children. PUBLIC SIGNIFICANCE STATEMENT: A history of binge eating symptoms up to 10 years pre-pregnancy in mothers is associated with behavior problems in their girls and boys at average age of 7. However, the association is moderated by behaviors of eating disorders and social support in the mothers during childhood. Identification of ED symptoms prior to pregnancy, and then after childbirth, might enable health services to intervene to maximize child and mother outcomes.

Maternal factors associated with interbirth intervals in Australia: Results from a population-based longitudinal study.

BACKGROUND AND OBJECTIVE: Short and long intervals between successive births are associated with adverse birth outcomes, especially in low-income and middle-income countries, yet the birth intervals in high-income countries remain relatively understudied. The aim was to examine maternal factors associated with birth intervals in Australia. METHODS: The sample comprised 6130 participants in the Australian Longitudinal Study on Women's Health who were born in 1973-1978, had two or more births, and responded to regular surveys between 1996 and 2018. Interbirth interval (IBI) was defined as the time between successive live births. Maternal factors were examined using accelerated failure time models. RESULTS: For women with only two births (n = 3802), the median time to the second birth was 34.0 months (IQR 23.1, 46.2) with shorter IBI associated with higher socioeconomic status (eg, university education (31.9 months), less income stress (31.1)), and longer IBI associated with age over 35 (39.7), fair/poor health (43.0), untreated fertility problems (45.5), miscarriage (39.4), or abortion (41.0). For women with three or more births (n = 2328), the median times to the second and third births were 31.2 months (19.9, 42.1) and 36.5 months (25.3, 50.1), respectively; some factors were consistent between the first IBI and second IBI (eg, university education and being married were associated with shorter IBI), whereas income stress was associated with longer first IBI but not with second IBI. CONCLUSIONS: Understanding maternal factors associated with birth intervals in a high-income country like Australia may enable more nuanced tailoring of guidelines for prepregnancy care.

Psychological distress in young Australian women by area of residence: findings from the Australian Longitudinal Study on Women's Health.

BACKGROUND: The association between psychological distress and area of residence has been extensively discussed and debated. However, the focus has been largely on men and area of residence is often dichotomised to urban and rural. The aim of this study is to examine the association between psychological distress and area of residence in young Australian women using a broader geographical measure. METHODS: Data were from 8961 women aged 19-26 in the 1989-95 cohort of the Australian Longitudinal Study on Women's Health in 2015. The association between area of residence (measured by the Modified Monash Model) and psychological distress (measured by the K10), adjusted for demographic factors, indicators of socioeconomic position and health behaviour characteristics, was analysed using logistic regression. RESULTS: Women in regional centres had lower odds of high to very high psychological distress compared with women in metropolitan areas (adjusted odds ratio 0.73 (95% confidence interval 0.60-0.89)). Women living in large rural towns, medium rural towns and small rural towns/remote/very remote communities had similar levels of psychological distress as women living in metropolitan areas. LIMITATIONS: ALSWH uses self-report questionnaires which may introduce potential self-report bias. The small sample size in areas outside of metropolitan areas resulted in the need to collapse small rural towns, remote communities and very remote communities into one category. CONCLUSIONS: The subtle regional differences in levels of psychological distress in young women in Australia highlights the importance of the link between health and where people live and suggests further work is required to understand the regional differences and encourage location specific mental health services.

Screen time and child behaviour and health-related quality of life: Effect of family context.

This study investigated family contextual effects on the association between screen time, behaviour and health-related quality of life (HRQOL) in child siblings. Data were from 1772 participants in the Australian Longitudinal Study of Women's Health 1973-78 cohort and their three youngest children (N = 4010 siblings) aged two to 12, collected in Mothers and their Children's Health cross-sectional sub-study (2016/17). The exposure was average daily recreational screen time (televisions, computers, tablets, mobile phones, electronic games). Outcomes were child overall behaviour and prosocial behaviour, and psychosocial and physical HRQOL. Multilevel models were used to test 1) the absolute effect of screen time, and 2) change in the child's outcomes when their own screen time changes relative to their siblings (within-family contextual effects) and change in the child's outcomes when the sibling average screen time changes (between-family contextual effects). The children were average 7.37 years (SD 2.76). There was an absolute effect of screen time on behaviour and HRQOL. Between-family effects were found for child total behaviour (0·22 (95%CI, 0.06, 0.37)) and prosocial behaviour (-0.10 (-0.17, -0.04)), but there were no within-family effects. For HRQOL, within-family effects were found for psychosocial (-0.97 (-1.91, -0.02)) and physical (-1.32 (-2.25, -0.39)) HRQOL, but no between-family effects were found. In conclusion, the higher the average screen time by all children in the family, the worse the child's behaviour, while the greater the deviation of the child's screen time from their siblings, the poorer their HRQOL. Family contextual factors should be considered in screen time research and screen time recommendations.

Longitudinal associations between lifestyle, socio-economic position and physical functioning in women at different life stages.

Women's physical functioning declines with age and the rate of decline increases with age, but substantial disparities exist in trajectories over time. To inform development of interventions to optimise physical functioning across the adult life span, the aim is to explore which lifestyle and socio-economic position (SEP) factors contribute to disparities in physical functioning across the adult life span in women. Younger (born 1973-1978, n = 14,247), middle-aged (born 1946-1951, n = 13,715) and older (born 1921-1926, n = 12,432) participants from the Australian Longitudinal Study on Women's Health completed six questionnaires between 1996 and 2012 at approximate 3-year intervals. Physical functioning was measured with a 10-item subscale of the Short-Form Health Survey (score 1-100). Relationships between age and physical functioning were modelled using spline regression, stratified by baseline categories of physical activity, alcohol intake, smoking status, level of education, managing on income and index of neighbourhood socio-economic disadvantage for area. Multivariable models excluding one of the six factors were compared with models including all six factors to examine the relative importance of each factor. Women with unhealthy lifestyles (inactive, smokers or risky alcohol intake) and lower SEP had lower levels of physical functioning and more rapid declines across the adult life span. The variables with the greatest relative contribution to the models for physical functioning differed by age cohort: i.e. education and physical activity in younger women, managing on income and physical activity in middle-aged women and physical activity in older women. For optimal physical functioning, socio-economic factors seemed particularly important in younger and middle-aged women, while physical activity seemed important at all ages.

Fall Risk Factors in Mid-Age Women: The Australian Longitudinal Study on Women's Health.

INTRODUCTION: In contrast to older adults, little is known about risk factors for falls in adults aged 50-64 years, despite a high prevalence of falls in this age group. The aim was to identify risk factors for falls in mid-age women and explore how associations change with age. METHODS: Data were analyzed in 2016 from women aged 50-55 years in 2001 (born 1946-1951) in the Australian Longitudinal Study on Women's Health. The predictor variables were health-related factors (measured 2001, 2004, 2007, 2010) and the outcome was falls in the past 12 months (measured 2004, 2007, 2010, 2013). Prospective associations between predictor variables and falls measured 3 years later were analyzed using logistic regression with complete data for 4,629, 7,096, 5,911, and 5,774 participants. RESULTS: In surveys, 20.5% (2004), 30.7% (2007), 30.5% (2010), and 26.6% (2013) of women reported a fall in the previous 12 months. In the univariable models, most factors were associated with falls 3 years later. In the multivariable models, higher odds of falling were found for overweight and obese women compared with healthy weight women at all survey intervals (OR range, 1.15-1.43). Impaired vision (OR range, 1.25-1.35) and poor physical functioning (OR range, 1.24-1.66) were associated with falls at three survey intervals. Depression (OR range, 1.31-1.42), leaking urine (OR range, 1.25-1.49), stiff/painful joints (OR range, 1.26-1.62), severe tiredness (OR range, 1.29-1.49), osteoporosis (OR range, 1.25-1.52), and hormone replacement therapy (OR range, 0.69-0.79) were associated with falls at two survey intervals. There was no obvious age-related increase or decrease in the number of statistically significant associations. CONCLUSIONS: Identified fall risk factors varied over time, highlighting that falling involves a complex interplay of risk factors in mid-age women.

Intimate personal violence and caregiving: Influences on physical and mental health in middle-aged women.

OBJECTIVES: To investigate if women with a history of having experienced intimate partner violence (IPV) who undertook caregiving would experience worse mental and physical health compared to those without caregiving roles. STUDY DESIGN AND MAIN OUTCOME MEASURES: IPV, caregiving history and data on covariates were collected between 1996 and 2010 from 8453 participants in the Australian Longitudinal Study on Women's Health aged between 45 and 65 over the course of the study. Regression analyses were used to analyse the association of IPV and caregiving (categorised as IPV+caregiving, IPV+no caregiving, no IPV+caregiving, no IPV+no caregiving), with and without adjustment for covariates, on mental and physical health-related quality of life (HRQOL), depressive symptoms and perceived stress, measured in 2010. RESULTS: Experiencing IPV and being a caregiver was associated with poor health outcomes on three of the four outcomes (depressive symptoms, OR 2.08, 95% CI 1.58, 2.75; stress, OR 2.11, 95% CI 1.55, 2.87; physical HRQOL ß -2.39, 95% CI -3.34, -1.44; all p≤0.001, fully adjusted) compared with not experiencing IPV or caregiving. On these outcomes, IPV and caregiving combined had a stronger association than IPV or caregiving separately. For mental HRQOL, a weaker association was found (OR 1.41 95% CI 1.02, 1.95, fully adjusted, p=0.04). CONCLUSIONS: This paper provides evidence for the cumulative health impact of stressful life events, both those that are perpetrated against an individual (violence) and those undertaken with a degree of personal agency (caregiving). The findings underscore the need to understand the drivers of poor health, for clinicians to ask about life circumstances of patients experiencing poor health, and for the provision of referral pathways for complex cases.

Adult Pre-pregnancy Weight Change and Risk of Developing Hypertensive Disorders in Pregnancy.

BACKGROUND: While the association of pre-pregnancy body mass index (BMI) and hypertensive disorders in pregnancy (HDP) is well documented, little is known about the relationship between pre-pregnancy weight change and HDP. We examined the impact of adult pre-pregnancy weight change on the development of HDP. METHODS: We included 2914 women, surveyed about every three years since 1996, from the 1973-78 cohort of the Australian Longitudinal Study on Women's Health. Women without hypertension or HDP were followed-up between 2003 and 2012. Generalised estimating equations were used to assess the effect of baseline BMI (mean age 20 years) and pre-pregnancy weight change on the incidence of HDP. RESULTS: Over 9 years of follow up, 301 incident HDP cases (6.3%) were reported from 4813 pregnancies. Overweight and obese women at the baseline survey were 1.67 (95% CI 1.3, 2.2) and 2.15 (95% CI 1.4, 3.3) times more likely to develop HDP than normal weight women, respectively. Compared with stable weight women, women with small (>1.5-2.5%) or moderate/high (>2.5%) annual weight gain had elevated risk of HDP (RR 1.67 95% CI 1.3, 2.2; RR 2.31, 95% CI 1.8, 3.0, respectively). Women who reported annual weight loss (>1.5%) between baseline and the average age of 24 years were 46% (95% CI 0.4, 0.8) less likely to develop HDP. CONCLUSIONS: Pre-pregnancy weight gain is associated with an increased risk of HDP, whereas early adult weight loss is associated with lower risk of HDP.

Factors associated with educational mobility in mid-age Australian women.

The educational mobility of mid-age women is rarely studied. We analysed the baseline socio-economic position (SEP) and health factors associated with obtaining further education in 4117 mid-age Australian women between 1996 and 2010 (aged 45-50 at baseline, 62-67 at follow-up) from a population-based study. Women either unemployed or working part-time at baseline had higher odds of a stable low and middle education over time (ORs ranging from 1.61 to 3.86) versus educational mobility. Apart from obesity, characteristics that may signal an unhealthy lifestyle in early mid-life were not useful indicators of women's future educational mobility.

Pre-pregnancy weight change and incidence of gestational diabetes mellitus: A finding from a prospective cohort study.

AIMS: In a population-based cohort study we examined the associations between early adult pre-pregnancy weight change and the risk of gestational diabetes mellitus (GDM). METHODS: The study included 3111 women from the 1973-78 cohort of the Australian Longitudinal Study on Women's Health. These women have been surveyed regularly since 1996. Women without diabetes and GDM were followed-up between 2003 and 2012. Generalized estimating equations were used to assess the effect of baseline (1996, mean age 20years) and pre-pregnancy body mass index (BMI) and the pre-pregnancy weight changes on the incidence of GDM. The full models were adjusted for sociodemographic and lifestyle factors. RESULTS: From 2003 to 2012, 229GDM cases (4.4%) were reported in 5242 pregnancies. Relative to normal BMI women, obese women at baseline (RR: 1.8, 95% CI: 1.1, 2.8) and prior to pregnancy (RR: 2.7, 95% CI: 2.0, 3.6) were at greater risk of GDM. Weight gains prior to each study pregnancy were strongly associated with increased GDM risk with an adjusted RR ranging from 2.0 to 2.9. Within under/normal range of BMI, women with a moderate/high (>2.5%/year) weight gain had 2.7 (95% CI: 1.3, 5.5) times the risk of GDM compared with women with stable weight. CONCLUSIONS: Early adult weight gain, even within normal BMI range, is an important risk factor for the development of GDM. Weight gain prevention from early adulthood to prior to pregnancy appears to be the main strategy to prevent the incidence of GDM.

Lifestyle and Socioeconomic Determinants of Multimorbidity Patterns among Mid-Aged Women: A Longitudinal Study.

BACKGROUND: Little is known about patterns of associative multimorbidity and their aetiology. We aimed to identify patterns of associative multimorbidity among mid-aged women and the lifestyle and socioeconomic factors associated with their development. METHODS: Participants were from the Australian Longitudinal Study on Women's Health. We included 4896 women born 1946-51, without multimorbidity in 1998. We identified multimorbidity patterns at survey 6 (2010) using factor analysis, and related these patterns to baseline lifestyle and socioeconomic factors using logistic regression. We dichotomised factor scores and determined odds ratios (ORs) with 95% confidence intervals (CIs) for associations between characteristics and odds of a high versus low factor score. RESULTS: We identified five multimorbidity patterns: psychosomatic; musculoskeletal; cardiometabolic; cancer; and respiratory. Overweight and obesity were respectively associated with increased odds of having a high score for the musculoskeletal (adjusted ORs 1.45 [95% CI 1.23, 1.70] and 2.14 [95% CI 1.75, 2.60]) and cardiometabolic (adjusted ORs 1.53 [95% CI 1.31, 1.79] and 2.46 [95% CI 2.02, 2.98]) patterns. Physical inactivity was associated with increased odds of a high score for the psychosomatic, musculoskeletal and cancer patterns (adjusted ORs 1.41 [95% CI 1.13, 1.76]; 1.39 [95% CI 1.11, 1.74]; and 1.35 [95% CI 1.08, 1.69]). Smoking was associated with increased odds of a high score for the respiratory pattern. Education and ability to manage on income were associated with increased odds of a high score for the psychosomatic pattern (adjusted ORs 1.34 [95% CI 1.03, 1.75] and 1.73 [95% CI 1.37, 1.28], respectively) and musculoskeletal pattern (adjusted ORs 1.43 [95% CI 1.10, 1.87] and 1.38 [1.09, 1.75], respectively). CONCLUSIONS: Distinct multimorbidity patterns can be identified among mid-aged women. Social inequality, physical activity and BMI are risk factors common to multiple patterns and are appropriate targets for reducing the risk of specific multimorbidity groups in mid-life women.

Diabetes in Pregnancy and Childhood Cognitive Development: A Systematic Review.

CONTEXT: The effect of diabetes during pregnancy on the cognitive development of offspring is unclear because of inconsistent findings from limited studies. OBJECTIVE: This review was aimed to provide the best available scientific evidence on the associations between maternal pregnancy diabetes and the cognitive development of offspring. DATA SOURCES: A search was conducted in the Embase, CINAHL, PubMed, PsycINFO, and Scopus databases. STUDY SELECTION: Studies addressing the cognitive development of offspring (aged ≤12 years) as outcome and any diabetes in pregnancy as an exposure were included. DATA EXTRACTION: Data were extracted and evaluated for quality by 2 independent reviewers. RESULTS: Fourteen articles were eligible for the review. Ten studies investigated the associations between maternal pregestational diabetes or both pregestational and gestational diabetes and offspring's cognitive development; 6 studies found at least 1 negative association. Four studies exclusively examined the relationships between gestational diabetes and offspring's cognitive development; 2 studies found a negative association, 1 a positive association, and 1 a null association. The use of diverse cognitive and diabetes assessment tools/criteria, as well as statistical power, contributed to the inconsistent findings. LIMITATIONS: The English-language restriction and publication bias in the included studies are potential limitations. CONCLUSIONS: Although there are few data available regarding the associations between maternal pregnancy diabetes and offspring's cognitive development, this review found that maternal diabetes during pregnancy seems to be negatively associated with offspring's cognitive development. Large prospective studies that address potential confounders are needed to confirm the independent effect of maternal diabetes during pregnancy.

Cohort Profile Update: Australian Longitudinal Study on Women's Health.

In 1996 the Australian Longitudinal Study on Women's Health recruited a nationally representative sample of more than 40,000 women in three age cohorts, born in 1973-78, 1946-51 and 1921-26. At least six waves of 3-yearly surveys have been completed. Although the focus remains on factors affecting the health and well-being of women and their access to and use of health services across urban, rural and remote areas of Australia, the study has now been considerably expanded by linkage to other health data sets. For most women who have ever participated in the study, linked records are now available for: government-subsidized non-hospital services (e.g. all general practitioner visits); pharmaceutical prescriptions filled; national death index, including codes for multiple causes of death; aged care assessments and services; cancer registries; and, for most states and territories, hospital admissions and perinatal data. Additionally, a large cohort of women born in 1989-95 have been recruited. The data are available to approved collaborators, with more than 780 researchers using the data so far. Full details of the study materials and data access procedures are available at [http://www.alswh.org.au/].