Cohort Profile: The Australian Longitudinal Study on Women’s Health (ALSWH) 1989–95 cohort

Loxton, Deborah; Tooth, Leigh; Harris, Melissa L.; Forder, Peta; Dobson, Annette; Powers, Jennifer R.; Brown, Wendy J.; Byles, Julie; Mishra, Gita D.

doi:10.1093/ije/dyx133

Cited by 66 publications

(68 citation statements)

References 20 publications

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“…Details of the study methods and representativeness of the samples have been published elsewhere [18]. In 2013, another cohort of women then aged 18-23 (born 1989-95, n = 17,012) was recruited using a variety of methods and these women have been surveyed annually using a web-based questionnaire [19]. At every survey, women are asked to report their weight and height.…”

Section: Data Setsmentioning

confidence: 99%

“…This makes use of continuous APC terms particularly appropriate. We use two data sets from large nationally representative samples analysed separately: repeated cross-sectional data from the Australian National Health Surveys since 1995 [16,17]; and longitudinal data from four cohorts of participants in the Australian Longitudinal Study on Women's Health that commenced in 1996 [18,19]. Firstly, we present four plots commonly used in cancer epidemiology to explore APC effects [20].…”

Section: Introductionmentioning

confidence: 99%

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Flexible age-period-cohort modelling illustrated using obesity prevalence data

Dobson

Hockey

Chan

et al. 2020

BMC Med Res Methodol

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Background: Use of generalized linear models with continuous, non-linear functions for age, period and cohort makes it possible to estimate these effects so they are interpretable, reliable and easily displayed graphically. To demonstrate the methods we use data on the prevalence of obesity among Australian women from two independent data sources obtained using different study designs. Methods: We used data from two long-running nationally representative studies: seven cross-sectional Australian National Health Surveys conducted between 1995 and 2017-18, each involving 6000-8000 women; and the Australian Longitudinal Study on Women's Health which started in 1996 and involves more than 57,000 women in four age cohorts who are re-surveyed at three-yearly intervals or annually. Age-period-cohort analysis was conducted using generalized linear models with splines to describe non-linear continuous effects. Results: When analysed in the same way both data sets showed similar patterns. Prevalence of obesity increased with age until late middle age and then declined; increased only slightly across surveys; but increased steadily with birth year until the 1960s and then accelerated. Conclusions: The methods illustrated here make the estimation and visualisation of age, period and cohort effects accessible and interpretable. Regardless of how the data are collected (from repeated cross-sectional surveys or longitudinal cohort studies), it is clear that younger generations of Australian women are becoming heavier at younger ages. Analyses of trends in obesity should include cohort, in addition to age and period, effects in order to focus preventive strategies appropriately.

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Section: Data Setsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flexible age-period-cohort modelling illustrated using obesity prevalence data

Dobson

Hockey

Chan

et al. 2020

BMC Med Res Methodol

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“…Given that the current generation of young adult women is heavier and appears to be gaining weight at a faster rate than previous generations , the premise that excess weight is a prominent risk factor for developing UI is concerning. Data from the Australian Longitudinal Study on Women's Health show that the proportion of 18‐ to 23‐year‐old women who had excess weight (overweight/obesity) increased from 20% among 18‐ to 23‐year‐olds in 1996 to 33% among women in the same age range in 2013 . Notably, the proportion of young women who had obesity more than doubled.…”

Section: Introductionmentioning

confidence: 99%

Overweight and obesity as major, modifiable risk factors for urinary incontinence in young to mid‐aged women: a systematic review and meta‐analysis

2018

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The purpose of this review and meta-analysis was to evaluate overweight and obesity as risk factors for urinary incontinence in young to mid-aged women. Understanding these relationships during this life stage is important as early onset increases the risk for developing severe and persistent incontinence. A systematic search resulted in 497 citations, 14 of which were retained for review. Data were analysed by overweight and obesity and by subtype of urinary incontinence - stress, urge, mixed and severe. When compared with 'normal' body mass index, overweight was associated with a one-third increase in risk of urinary incontinence (relative risk = 1.35, 95% confidence interval = 1.20-1.53), while the risk was doubled in women with obesity (relative risk = 1.95, 95% confidence interval = 1.58-2.42). When estimates were pooled according to urinary incontinence subtype, there was no statistical difference in risk. Overweight and obesity are strong predictors of urinary incontinence, with a significantly greater risk observed for obesity. Clinical advice to young women at risk of, or presenting with, obesity should not be limited to metabolic health only but should emphasize the role of excess weight on pelvic floor weakening and subsequent risk of incontinence.

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“…The strengths of our study include using an unselected, population-based cohort which is broadly representative of the Australian population [45], thereby making the results of our study more generalizable. Uncommon associations were also able to be studied given the large sample size we had which improves the statistical power of our results.…”

Section: Discussionmentioning

confidence: 99%

“…Intentional oversampling from rural and remote areas were performed to study health experiences of women from non-metropolitan areas [44]. In 2012 and 2013, a fourth cohort of women aged 18-23, born 1989-1995, was added to the study [45]. Ethical approval was obtained from the Human Research Ethics Committees from the University of Queensland, the University of Newcastle, Medicare and the Department of Health.…”

Section: Study Population and Methodsmentioning

confidence: 99%

Perinatal Mental Health in Women with Polycystic Ovary Syndrome: A Cross-Sectional Analysis of an Australian Population-Based Cohort

Tay

Teede

Boyle

et al. 2019

JCM

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Women with polycystic ovary syndrome (PCOS) have many risk factors associated with perinatal mental disorders, but research in this area is scarce. This study aims to compare the prevalence of common perinatal mental disorders in women with and without PCOS, and examine the relationship between PCOS and common perinatal mental disorders. We performed a cross-sectional study on self-reported data of 5239 women born between 1973 to 1978 in the Australian Longitudinal Study on Women's Health. Compared with women not reporting PCOS, women reporting PCOS had higher prevalence of antenatal depression (8.9% vs. 4.4%, p < 0.001), antenatal anxiety (11.7% vs. 5.6%, p < 0.001), postnatal depression (26.8% vs. 18.6%, p < 0.001) and postnatal anxiety (18.4% vs. 12.0%, p < 0.001). PCOS was positively associated with antenatal depression and/or anxiety (adjusted odds ratio 1.8, 95% confidence interval 1.2-2.6) but not postnatal depression and/or anxiety after controlling for sociodemographic and lifestyle factors, reproductive history, obstetric complications and pre-existing depression and anxiety. General perinatal guidelines currently do not recognize PCOS as a risk factor and the international evidence based PCOS guideline noted inadequate evidence in this area. This paper addresses the gap in literature and highlights the need to screen for common perinatal mental disorders in women with PCOS.

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Cohort Profile: The Australian Longitudinal Study on Women’s Health (ALSWH) 1989–95 cohort

Cited by 66 publications

References 20 publications

Flexible age-period-cohort modelling illustrated using obesity prevalence data

Flexible age-period-cohort modelling illustrated using obesity prevalence data

Overweight and obesity as major, modifiable risk factors for urinary incontinence in young to mid‐aged women: a systematic review and meta‐analysis

Perinatal Mental Health in Women with Polycystic Ovary Syndrome: A Cross-Sectional Analysis of an Australian Population-Based Cohort

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