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      Age at natural menopause and risk of incident cardiovascular disease: a pooled analysis of individual patient data

      research-article
      , MD a , , PhD a , , Prof, PhD a , , PhD a , b , , Prof, PhD c , d , , PhD c , , Prof, PhD e , , Prof, PhD f , , Prof, PhD f , , Prof, PhD h , , Prof, PhD i , , Prof, PhD j , k , , Prof, PhD l , , Prof, PhD m , , PhD m , , PhD e , , Prof, PhD n , , Prof, PhD o , , Prof, PhD p , , Prof, PhD q , , PhD r , , Prof, PhD s , , PhD g , , PhD t , u , , Prof, PhD v , w , , Prof, PhD x , , Prof, PhD a , *
      The Lancet. Public Health
      Elsevier, Ltd

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          Summary

          Background

          Early menopause is linked to an increased risk of cardiovascular disease mortality; however, the association between early menopause and incidence and timing of cardiovascular disease is unclear. We aimed to assess the associations between age at natural menopause and incidence and timing of cardiovascular disease.

          Methods

          We harmonised and pooled individual-level data from 15 observational studies done across five countries and regions (Australia, Scandinavia, the USA, Japan, and the UK) between 1946 and 2013. Women who had reported their menopause status, age at natural menopause (if postmenopausal), and cardiovascular disease status (including coronary heart disease and stroke) were included. We excluded women who had hysterectomy or oophorectomy and women who did not report their age at menopause. The primary endpoint of this study was the occurrence of first non-fatal cardiovascular disease, defined as a composite outcome of incident coronary heart disease (including heart attack and angina) or stroke (including ischaemic stroke or haemorrhagic stroke). We used Cox proportional hazards models to estimate multivariate hazard ratios (HRs) and 95% CIs for the associations between age at menopause and incident cardiovascular disease event. We also adjusted the model to account for smoking status, menopausal hormone therapy status, body-mass index, and education levels. Age at natural menopause was categorised as premenopausal or perimenopausal, younger than 40 years (premature menopause), 40–44 years (early menopause), 45–49 years (relatively early), 50–51 years (reference category), 52–54 years (relatively late), and 55 years or older (late menopause).

          Findings

          Overall, 301 438 women were included in our analysis. Of these 301 438 women, 12 962 (4·3%) had a first non-fatal cardiovascular disease event after menopause, of whom 9369 (3·1%) had coronary heart disease and 4338 (1·4%) had strokes. Compared with women who had menopause at age 50–51 years, the risk of cardiovascular disease was higher in women who had premature menopause (age <40 years; HR 1·55, 95% CI 1·38–1·73; p<0·0001), early menopause (age 40–44 years; 1·30, 1·22–1·39; p<0·0001), and relatively early menopause (age 45–49 years; 1·12, 1·07–1·18; p<0·0001), with a significantly reduced risk of cardiovascular disease following menopause after age 51 years (p<0·0001 for trend). The associations persisted in never smokers, and were strongest before age 60 years for women with premature menopause (HR 1·88, 1·62–2·20; p<0·0001) and early menopause (1·40, 1·27–1·54; p<0·0001), but were attenuated at age 60–69 years, with no significant association observed at age 70 years and older.

          Interpretation

          Compared with women who had menopause at age 50–51 years, women with premature and early menopause had a substantially increased risk of a non-fatal cardiovascular disease event before the age of 60 years, but not after age 70 years. Women with earlier menopause need close monitoring in clinical practice, and age at menopause might also be considered as an important factor in risk stratification of cardiovascular disease for women.

          Funding

          Australian National Health and Medical Research Council.

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          Most cited references61

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          UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

          Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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            Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

            Summary Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding Bill & Melinda Gates Foundation.
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              Cohort profile: the English longitudinal study of ageing.

              The English Longitudinal Study of Ageing (ELSA) is a panel study of a representative cohort of men and women living in England aged ≥50 years. It was designed as a sister study to the Health and Retirement Study in the USA and is multidisciplinary in orientation, involving the collection of economic, social, psychological, cognitive, health, biological and genetic data. The study commenced in 2002, and the sample has been followed up every 2 years. Data are collected using computer-assisted personal interviews and self-completion questionnaires, with additional nurse visits for the assessment of biomarkers every 4 years. The original sample consisted of 11 391 members ranging in age from 50 to 100 years. ELSA is harmonized with ageing studies in other countries to facilitate international comparisons, and is linked to financial and health registry data. The data set is openly available to researchers and analysts soon after collection (http://www.esds.ac.uk/longitudinal/access/elsa/l5050.asp).
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                Author and article information

                Contributors
                Journal
                Lancet Public Health
                Lancet Public Health
                The Lancet. Public Health
                Elsevier, Ltd
                2468-2667
                03 October 2019
                November 2019
                03 October 2019
                : 4
                : 11
                : e553-e564
                Affiliations
                [a ]School of Public Health, University of Queensland, Brisbane, QLD, Australia
                [b ]Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
                [c ]Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
                [d ]Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
                [e ]Department of Epidemiology and Public Health, University College London, London, UK
                [f ]Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
                [g ]Institute of Cardiovascular Science, University College London, London, UK
                [h ]Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, USA
                [i ]Department of Public Health Sciences, University of California, Davis School of Medicine, Davis, CA, USA
                [j ]Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA
                [k ]Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, NY, USA
                [l ]Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
                [m ]Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK
                [n ]Department of Anthropology, University of Hawaii, Hilo, HI, USA
                [o ]Department of Anthropology, University of Massachusetts Amherst, Amherst, MA, USA
                [p ]Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
                [q ]School of Health Sciences, Gunma University, Maebashi, Japan
                [r ]Department of Public Health, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
                [s ]Fukushima Medical Center for Children and Women, Fukushima Medical University, Fukushima, Japan
                [t ]Parker Institute, Copenhagen University Hospital, Frederiksberg, Denmark
                [u ]Aarhus University, Aarhus, Denmark
                [v ]Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
                [w ]Clinical Effectiveness Research Group, Institute of Health and Society, University of Oslo, Oslo, Norway
                [x ]International Agency for Research on Cancer, World Health Organization, Lyon, France
                Author notes
                [* ]Correspondence to: Prof Gita D Mishra, School of Public Health, University of Queensland, Brisbane, QLD 4006, Australia g.mishra@ 123456uq.edu.au
                Article
                S2468-2667(19)30155-0
                10.1016/S2468-2667(19)30155-0
                7118366
                31588031
                de55dd28-cd44-466c-9065-60ec39ecdbd7
                © 2019 World Health Organization

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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