Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-13T04:13:19.213Z Has data issue: false hasContentIssue false

Parity and the risk of incident dementia: a COSMIC study

Published online by Cambridge University Press:  20 October 2020

J. B. Bae
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea Department of Psychiatry, Seoul National University, College of Medicine, Seoul, South Korea
D. M. Lipnicki
Affiliation:
Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
J. W. Han
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea Department of Psychiatry, Seoul National University, College of Medicine, Seoul, South Korea
P. S. Sachdev
Affiliation:
Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia Dementia Collaborative Research Centre, University of New South Wales, Sydney, Australia
T. H. Kim
Affiliation:
Department of Psychiatry, Yonsei University Wonju Severance Christian Hospital, Wonju, South Korea
K. P. Kwak
Affiliation:
Department of Psychiatry, Dongguk University Gyeongju Hospital, Gyeongju, South Korea
B. J. Kim
Affiliation:
Department of Psychiatry, Gyeongsang National University, School of Medicine, Jinju, South Korea
S. G. Kim
Affiliation:
Department of Neuropsychiatry, Soonchunhyang University Bucheon Hospital, Bucheon, South Korea
J. L. Kim
Affiliation:
Department of Psychiatry, School of Medicine, Chungnam National University, Daejeon, South Korea
S. W. Moon
Affiliation:
Department of Psychiatry, School of Medicine, Konkuk University and Konkuk University Chungju Hospital, Chungju, South Korea
J. H. Park
Affiliation:
Department of Neuropsychiatry, Jeju National University Hospital, Jeju, South Korea
S.-H. Ryu
Affiliation:
Department of Psychiatry, School of Medicine, Konkuk University and Konkuk University Medical Center, Seoul, South Korea
J. C. Youn
Affiliation:
Department of Neuropsychiatry, Kyunggi Provincial Hospital for the Elderly, Yongin, South Korea
D. Y. Lee
Affiliation:
Department of Psychiatry, Seoul National University, College of Medicine, Seoul, South Korea Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
D. W. Lee
Affiliation:
Department of Neuropsychiatry, Inje University Sanggye Paik Hospital, Seoul, South Korea
S. B. Lee
Affiliation:
Department of Psychiatry, Dankook University Hospital, Cheonan, South Korea
J. J. Lee
Affiliation:
Department of Psychiatry, Dankook University Hospital, Cheonan, South Korea
J. H. Jhoo
Affiliation:
Department of Neuropsychiatry, Kangwon National University Hospital, Chuncheon, South Korea
I. Skoog
Affiliation:
Department of Psychiatry and Neurochemistry, Institute of Neuroscience of Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
J. Najar
Affiliation:
Department of Psychiatry and Neurochemistry, Institute of Neuroscience of Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
T. R. Sterner
Affiliation:
Department of Psychiatry and Neurochemistry, Institute of Neuroscience of Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
N. Scarmeas
Affiliation:
1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Medical School, Athens, Greece Department of Neurology, Columbia University, New York, USA
M. Yannakoulia
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
E. Dardiotis
Affiliation:
Neurology Department, University Hospital of Larissa, University of Thessaly, Larissa, Greece
S. Riedel-Heller
Affiliation:
Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany
S. Roehr
Affiliation:
Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany
A. Pabst
Affiliation:
Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany
D. Ding
Affiliation:
Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
Q. Zhao
Affiliation:
Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
X. Liang
Affiliation:
Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
A. Lobo
Affiliation:
Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
C. De-la-Cámara
Affiliation:
Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
E. Lobo
Affiliation:
Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
K. W. Kim*
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea Department of Psychiatry, Seoul National University, College of Medicine, Seoul, South Korea Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, Korea
for Cohort Studies of Memory in an International Consortium (COSMIC)
Affiliation:
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
*
Author for correspondence: Ki Woong Kim, E-mail: kwkimmd@snu.ac.kr
Rights & Permissions [Opens in a new window]

Abstract

Aims

To investigate the association between parity and the risk of incident dementia in women.

Methods

We pooled baseline and follow-up data for community-dwelling women aged 60 or older from six population-based, prospective cohort studies from four European and two Asian countries. We investigated the association between parity and incident dementia using Cox proportional hazards regression models adjusted for age, educational level, hypertension, diabetes mellitus and cohort, with additional analysis by dementia subtype (Alzheimer dementia (AD) and non-Alzheimer dementia (NAD)).

Results

Of 9756 women dementia-free at baseline, 7010 completed one or more follow-up assessments. The mean follow-up duration was 5.4 ± 3.1 years and dementia developed in 550 participants. The number of parities was associated with the risk of incident dementia (hazard ratio (HR) = 1.07, 95% confidence interval (CI) = 1.02–1.13). Grand multiparity (five or more parities) increased the risk of dementia by 30% compared to 1–4 parities (HR = 1.30, 95% CI = 1.02–1.67). The risk of NAD increased by 12% for every parity (HR = 1.12, 95% CI = 1.02–1.23) and by 60% for grand multiparity (HR = 1.60, 95% CI = 1.00–2.55), but the risk of AD was not significantly associated with parity.

Conclusions

Grand multiparity is a significant risk factor for dementia in women. This may have particularly important implications for women in low and middle-income countries where the fertility rate and prevalence of grand multiparity are high.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Introduction

Dementia is one of many disorders with gender differences (Mazure and Swendsen, Reference Mazure and Swendsen2016) and women show a greater prevalence of dementia than men (Winblad et al., Reference Winblad, Amouyel, Andrieu, Ballard, Brayne, Brodaty, Cedazo-Minguez, Dubois, Edvardsson and Feldman2016). However, longitudinal cohort studies investigating whether the incidence of dementia differs by gender have shown conflicting results. Prospective cohort studies in high-income countries (HIC) such as the USA, the Netherlands and the UK reported no gender differences in the incidence of dementia (Bachman et al., Reference Bachman, Wolf, Linn, Knoefel, Cobb, Belanger, White and D'agostino1993; Paykel et al., Reference Paykel, Brayne, Huppert, Gill, Barkley, Gehlhaar, Beardsall, Girling, Pollitt and O'connor1994; Ruitenberg et al., Reference Ruitenberg, Ott, Van Swieten, Hofman and Breteler2001). On contrary, the 10/66 Dementia Research Group used longitudinal data from six middle-income countries (MIC), including Cuba, the Dominican Republic, Venezuela, Peru, Mexico and China and found that women showed a higher risk of incident dementia than men even after controlling for age, education and occupational attainment (Prince et al., Reference Prince, Acosta, Ferri, Guerra, Huang, Rodriguez, Salas, Sosa, Williams, Dewey, Acosta, Jotheeswaran and Liu2012). Higher rates of incident dementia for women in MIC but not HIC may be attributable to the greater gender differences in education, socialeconomic status, lifestyle and health conditions of MIC compared to those of HIC (Medel-Anonuevo, Reference Medel-Anonuevo1995). Pregnancy and childbirth are the most distinctive experiences of women that may change hormone levels, health conditions and lifestyles, and women in MIC have more childbirths on average than women in HIC (United Nations, 2019).

Several studies have shown parity to be associated with the risks for cognitive impairment and dementia. In a case-control study from Germany, the chances of having at least one child and the number of children were both greater among 106 women with Alzheimer's disease (AD) than among 189 women without dementia (Ptok et al., Reference Ptok, Barkow and Heun2002). In a cross-sectional study from China on 4796 postmenopausal women, grand multiparous women (five or more childbirths) showed about 1.3-fold higher risk of cognitive impairment than women with 1–4 parities (Li et al., Reference Li, He, Chen, Xiao, Lin, Shen, Wang, Zhai, Shang and Lin2016). In a retrospective analysis on the pooled data of 3549 women from two population-based cohort studies in Korea and Greece, we found that grand multiparous women showed about 1.7-fold higher risk of AD than women with one–four parities (Jang et al., Reference Jang, Bae, Dardiotis, Scarmeas, Sachdev, Lipnicki, Han, Kim, Kwak and Kim2018). However, the risk of dementia associated with parity reported from these previous studies employing case-control or cross-sectional designs is subject to various biases; a selection bias (Tripepi et al., Reference Tripepi, Jager, Dekker and Zoccali2010) due to the shorter life expectancy of grand multiparous women than women with four parities or less (Hinkula et al., Reference Hinkula, Kauppila, Nayha and Pukkala2006), a prevalence-incidence bias (Hill, Reference Hill2003) due to the lower mortality from dementia in grand multiparous women than women with four parities or less (Hinkula et al., Reference Hinkula, Kauppila, Nayha and Pukkala2006) and information bias (Tripepi et al., Reference Tripepi, Jager, Dekker and Zoccali2010) due to the greater risk of inaccurate information on parity from dementia patients than from cognitively normal elderly individuals.

In this study, we conducted a pooled analysis on the longitudinal data from six population-based prospective cohort studies (four European and two Asian cohorts) to more accurately determine the effect of parity on the risk of incident dementia in older women.

Methods

Study population

We pooled baseline and follow-up data for community-dwelling women aged 60 or older from six members of the Cohort Studies of Memory in an International Consortium (COSMIC) collaboration (Table 1) (Riedel-Heller et al., Reference Riedel-Heller, Busse, Aurich, Matschinger and Angermeyer2001; Lobo et al., Reference Lobo, Lopez-Anton, Santabarbara, De-La-Cámara, Ventura, Quintanilla, Roy, Campayo, Lobo and Palomo2011; Sachdev et al., Reference Sachdev, Lipnicki, Kochan, Crawford, Rockwood, Xiao, Li, Li, Brayne and Matthews2013; Dardiotis et al., Reference Dardiotis, Kosmidis, Yannakoulia, Hadjigeorgiou and Scarmeas2014; Ding et al., Reference Ding, Zhao, Guo, Meng, Wang, Yu, Luo, Zhou, Yu, Zheng, Chu, Mortimer, Borenstein and Hong2014; Thorvaldsson et al., Reference Thorvaldsson, Karlsson, Skoog, Skoog and Johansson2017; Han et al., Reference Han, Kim, Kwak, Kim, Kim, Kim, Kim, Kim, Moon, Park, Park, Byun, Suh, Seo, So, Ryu, Youn, Lee, Lee, Lee, Lee, Lee, Lee, Jeong, Jeong, Jhoo, Han, Hong and Kim2018). The included cohorts varied in size from 1016 to 6818 participants. From an initial sample of 11 300 women, we excluded 1010 who did not have data on educational level, hypertension, diabetes mellitus (DM) or parity and 534 diagnosed as having dementia at baseline, giving a final sample of 9756 women.

Table 1. Contributing cohorts

H70, Gothenburg H70 Birth Cohort Studies; HELIAD, Hellenic Longitudinal Investigation of Aging and Diet; KLOSCAD, Korean Longitudinal Study on Cognitive Aging and Dementia; LEILA75+, Leipzig Longitudinal Study of the Aged; SAS, Shanghai Aging Study; ZARADEMP, Zaragoza Dementia Depression Project.

The participants of all studies were randomly sampled.

a Numbers at the baseline assessment.

b Mean ± standard deviation (range).

c Mean ± standard deviation (range), numbers of children in the H70 and LEILA 75+ and numbers of childbirths in other studies.

Ethics approval

This study was approved by the University of New South Wales Human Research Ethics Committee (Ref: # HC12446). Each of the six contributing studies had previously obtained ethics approval from their respective institutional review boards and all participants provided informed consent.

Measures

The main outcomes of the present analysis were incident all-cause dementia, AD and non-Alzheimer dementia (NAD). All studies provided data on dementia diagnosis, based on DSM-IV criteria (American Psychiatric Association, 1994) in five studies (Riedel-Heller et al., Reference Riedel-Heller, Busse, Aurich, Matschinger and Angermeyer2001; Lobo et al., Reference Lobo, Lopez-Anton, Santabarbara, De-La-Cámara, Ventura, Quintanilla, Roy, Campayo, Lobo and Palomo2011; Dardiotis et al., Reference Dardiotis, Kosmidis, Yannakoulia, Hadjigeorgiou and Scarmeas2014; Ding et al., Reference Ding, Zhao, Guo, Meng, Wang, Yu, Luo, Zhou, Yu, Zheng, Chu, Mortimer, Borenstein and Hong2014; Han et al., Reference Han, Kim, Kwak, Kim, Kim, Kim, Kim, Kim, Moon, Park, Park, Byun, Suh, Seo, So, Ryu, Youn, Lee, Lee, Lee, Lee, Lee, Lee, Jeong, Jeong, Jhoo, Han, Hong and Kim2018) and DSM-III-R criteria (American Psychiatric Association, 1987) in one (Thorvaldsson et al., Reference Thorvaldsson, Karlsson, Skoog, Skoog and Johansson2017). Four studies (Dardiotis et al., Reference Dardiotis, Kosmidis, Yannakoulia, Hadjigeorgiou and Scarmeas2014; Ding et al., Reference Ding, Zhao, Guo, Meng, Wang, Yu, Luo, Zhou, Yu, Zheng, Chu, Mortimer, Borenstein and Hong2014; Thorvaldsson et al., Reference Thorvaldsson, Karlsson, Skoog, Skoog and Johansson2017; Han et al., Reference Han, Kim, Kwak, Kim, Kim, Kim, Kim, Kim, Moon, Park, Park, Byun, Suh, Seo, So, Ryu, Youn, Lee, Lee, Lee, Lee, Lee, Lee, Jeong, Jeong, Jhoo, Han, Hong and Kim2018) diagnosed AD according to the NINCDS-ADRDA criteria (McKhann et al., Reference McKhann, Drachman, Folstein, Katzman, Price and Stadlan1984) and two studies (Riedel-Heller et al., Reference Riedel-Heller, Busse, Aurich, Matschinger and Angermeyer2001; Lobo et al., Reference Lobo, Lopez-Anton, Santabarbara, De-La-Cámara, Ventura, Quintanilla, Roy, Campayo, Lobo and Palomo2011) according to DSM-IV criteria (American Psychiatric Association, 1994). The main exposure was the number of parities. We assigned parity as the number of childbirths in four cohorts and as the number of children in two cohorts. Other data included age, sex, educational level and the presence of hypertension and DM, which were all harmonised when necessary. For the presence of hypertension and DM, we used all available information from a study relevant to diagnoses (medical history record, self-reported history, use of relevant medication and measured blood pressure or glucose level exceeding values indicated by international guidelines).

Analysis

We compared the continuous variables between groups using one-way analysis of variance with Scheffé's post hoc analysis and categorical variables using chi-square tests.

We evaluated the relationship between parity and incident dementia using Cox proportional hazards regression models with time-dependent covariates. We used calendar time as the time axis. The primary outcome was incident dementia and the risk factor of primary interest was the number of parities. Participants who developed dementia during follow-up were censored at the midpoint between their last assessment date when without dementia and their first assessment date when diagnosed with dementia. Participants who remained dementia-free during the follow-up were censored at the most recent assessment date. We initially analysed the number of parities as a continuous variable and estimated hazard ratios (HRs) and 95% confidence intervals (CIs) with unadjusted and adjusted Cox proportional hazards regression models. The adjusted model included age, educational level, hypertension, DM and cohort as covariates. Next, we categorised parity into three strata – no parity (nulliparity), 1–4 parities and five or more parities (grand multiparity) (Babinszki et al., Reference Babinszki, Kerenyi, Torok, Grazi, Lapinski and Berkowitz1999) because both grand multiparity and nulliparity have been previously associated with the risk of AD (Ptok et al., Reference Ptok, Barkow and Heun2002; Jang et al., Reference Jang, Bae, Dardiotis, Scarmeas, Sachdev, Lipnicki, Han, Kim, Kwak and Kim2018), as well as the risks of medical diseases such as DM and coronary heart disease (Lawlor, Reference Lawlor2003; Nicholson et al., Reference Nicholson, Asao, Brancati, Coresh, Pankow and Powe2006). We investigated the association of parity with the risks of AD, and NAD separately. We also analysed the four cohort studies that provided the number of childbirths and the two cohort studies that provided the number of children separately.

The KLOSCAD team harmonised and pooled the dataset and performed the analyses using the Statistical Package for Social Sciences, v20 (SPSS Inc., Chicago, IL).

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request

Results

Of 9756 women dementia-free at baseline, 7010 completed one or more follow-up assessments. The mean follow-up duration was 5.4 ± 3.1 years (Table 2). During the follow-up period, dementia developed in 550 participants (AD in 380 and NAD in 170). Compared to participants who remained dementia-free during follow-up, those who did not complete a follow-up assessment were older and less educated and those who developed dementia were older, had more hypertension and DM and gave more childbirths (Table 3).

Table 2. Design and results of follow-up assessments according to cohorts

H70, Gothenburg H70 Birth Cohort Studies; HELIAD, Hellenic Longitudinal Investigation of Aging and Diet; KLOSCAD, Korean Longitudinal Study on Cognitive Aging and Dementia; LEILA75+, Leipzig Longitudinal Study of the Aged; SAS, Shanghai Aging Study; ZARADEMP, Zaragoza Dementia Depression Project; AD, Alzheimer dementia; NAD, non-Alzheimer's disease.

a Mean ± standard deviation.

b Numbers of dementia-free participants at baseline who completed one or more follow-up assessments.

Table 3. Baseline characteristics of the participants

a Analysis of variance with Scheffe's posthoc comparison for continuous variables and chi square tests for categorical variables. The level of significance was considered to be P < 0.05.

Parity as continuous

As shown in Table 4, the risk of dementia increased by 7% for every parity in the adjusted Cox hazard model (HR = 1.07, 95% CI = 1.02–1.13). The risk of NAD increased by 12% for every parity (HR = 1.12, 95% CI = 1.02–1.23), but the risk of AD was not significantly associated with the number of parities (HR = 1.05, 95% CI = 0.99–1.11).

Table 4. Associations between number of parities and the risk of incident dementia

AD, Alzheimer's disease; NAD, non-Alzheimer's disease.

Values represent hazard ratio with 95% confidence intervals in the parentheses.

a Cox proportional hazards model adjusting for age, educational level, hypertension, diabetes mellitus and cohort.

Parity as categorical

Compared to the one–four parities group, grand multiparity increased the risk of dementia by 30% (HR = 1.30, 95% CI = 1.02–1.67) but nulliparity did not (HR = 0.84, 95% CI = 0.63–1.12). Grand multiparity increased the risk of NAD by 60% (HR = 1.60, 95% CI = 1.00–2.55), but was not associated with the risk of AD. Nulliparity was not associated with the risk of either NAD or AD (Table 4).

When we analysed the four cohort studies that provided the number of childbirths and the two cohort studies that provided the number of children separately, the number of parities was associated with the risk of dementia in both groups, although the association was not statistically significant in the cohorts that provided the number of children (HR = 1.08, 95% CI = 1.02–1.14 for the cohorts providing the number of childbirths; HR = 1.02, 95% CI = 0.91–1.14 for the cohorts providing the number of children).

Discussion

We analysed pooled data for 7010 women older women drawn from six population-based prospective cohort studies, four in Europe and two in Asia. Our results show the number of parities to be associated with the risk of incident dementia. Grand multiparity increased the risk of dementia by 30%, which is comparable to the relative risk of dementia due to some well-known risk factors (1.37 for current/ever smoking (Beydoun et al., Reference Beydoun, Beydoun, Gamaldo, Teel, Zonderman and Wang2014), 1.41 for low social participation (Kuiper et al., Reference Kuiper, Zuidersma, Oude Voshaar, Zuidema, Van Den Heuvel, Stolk and Smidt2015), 1.33 for midlife obesity (Albanese et al., Reference Albanese, Launer, Egger, Prince, Giannakopoulos, Wolters and Egan2017) and 1.21 for vitamin D deficiency (Shen and Ji, Reference Shen and Ji2015)). Although the association of parity and the risk of dementia in women has been reported by case-control and cross-sectional studies (Ptok et al., Reference Ptok, Barkow and Heun2002; Jang et al., Reference Jang, Bae, Dardiotis, Scarmeas, Sachdev, Lipnicki, Han, Kim, Kwak and Kim2018), this is the first prospective study to demonstrate an association between them.

Studies from HIC have reported a similar rate of incident dementia for men and women (Bachman et al., Reference Bachman, Wolf, Linn, Knoefel, Cobb, Belanger, White and D'agostino1993; Paykel et al., Reference Paykel, Brayne, Huppert, Gill, Barkley, Gehlhaar, Beardsall, Girling, Pollitt and O'connor1994; Ruitenberg et al., Reference Ruitenberg, Ott, Van Swieten, Hofman and Breteler2001), but those from MIC showed women to have about 40% higher rates on incident dementia than men, even after controlling for age, educational level and occupational attainment (Prince et al., Reference Prince, Acosta, Ferri, Guerra, Huang, Rodriguez, Salas, Sosa, Williams, Dewey, Acosta, Jotheeswaran and Liu2012). In the 1960s MIC had a fertility rate of nearly 6, almost twice that of HIC (United Nations, 2019). Given this, our results suggest that greater rates of incident dementia for women than for men in MIC could be at least partly attributable to high fertility rates and a prevalence of grand multiparity that is over 20% (Mueller et al., Reference Mueller, Mueller, Odegaard, Gross, Koh, Yuan and Pereira2013; Jang et al., Reference Jang, Bae, Dardiotis, Scarmeas, Sachdev, Lipnicki, Han, Kim, Kwak and Kim2018; Solanke, Reference Solanke2019). Grand multiparity is also likely to be a risk for dementia among women in low-income countries for which the mean fertility rate was 4.6 in 2017 and where grand multiparity is still common (United Nations, 2019).

The association between parity and the risk of incident dementia is potentially explained by a number of mechanisms. First, low high-density lipoprotein (HDL) levels have been associated with the development of dementia (Rasmussen et al., Reference Rasmussen, Tybjærg-Hansen, Nordestgaard and Frikke-Schmidt2015) and AD (Reitz et al., Reference Reitz, Tang, Schupf, Manly, Mayeux and Luchsinger2010), and parous women were reported to have lower HDL levels than nulliparous women for 3 years after childbirth (Lewis et al., Reference Lewis, Funkhouser, Raczynski, Sidney, Bild and Howard1996). This appears to be a persistent effect, as a significant trend toward lower HDL levels with increasing parity has been shown in old age (Humphries et al., Reference Humphries, Westendorp, Bots, Spinelli, Carere, Hofman and Witteman2001). Second, changes in glucose metabolism induced by parity might increase the risk of dementia. We controlled for DM, which is a known risk factor of dementia (Ott et al., Reference Ott, Stolk, Van Harskamp, Pols, Hofman and Breteler1999). However, higher than average glucose levels in elderly individuals without DM have also been associated with an increased risk of incident dementia (Crane et al., Reference Crane, Walker, Hubbard, Li, Nathan, Zheng, Haneuse, Craft, Montine and Kahn2013). Insulin sensitivity drops to 50% in the third trimester of pregnancy and grand multiparity is associated with an increased risk of subsequent clinical insulin resistance in premenopausal women (Abdelsalam and Elamin, Reference Abdelsalam and Elamin2017). It has also been reported that postmenopausal women with four or more children have higher insulin resistance than nulliparous and primiparous women (Humphries et al., Reference Humphries, Westendorp, Bots, Spinelli, Carere, Hofman and Witteman2001). Third, estrogen has a neuroprotective effect (Barha and Galea, Reference Barha and Galea2010; Inagaki et al., Reference Inagaki, Gautreaux and Luine2010) and low serum bioavailable estradiol has been associated with the risk of cognitive impairment (Yaffe et al., Reference Yaffe, Lui, Grady, Cauley, Kramer and Cummings2000). Since parous women were found to have lower levels of a urinary estradiol metabolite than nulliparous women (Munro et al., Reference Munro, Stabenfeldt, Cragun, Addiego, Overstreet and Lasley1991; Barrett et al., Reference Barrett, Parlett, Windham and Swan2014), and a lower free estradiol index reportedly related to the number of parities in postmenopausal women (Chavez-MacGregor et al., Reference Chavez-Macgregor, Van Gils, Van Der Schouw, Monninkhof, Van Noord and Peeters2008), parity might affect the risk of dementia by exposing women to reduced serum estrogen for much of their adult life. Although these influences of multiparity may increase the risks of both AD and NAD, our results suggest that they may more strongly affect the risk of NAD. Cerebrovascular diseases that are closely associated with lipid and glucose metabolisms are the most common cause of NAD (Rizzi et al., Reference Rizzi, Rosset and Roriz-Cruz2014) and vascular dementia was the most common type of incident NAD in the current study.

This study has several strengths compared to previous studies that were case-control or cross-sectional. First, our dataset consists of more than 7000 elderly women from six international population-based cohorts, which is much larger and more representative than the datasets in previous studies. Second, the probability of information bias was relatively low. In case-control and cross-sectional studies, dementia patients with severe cognitive impairment might recall their parity experience incorrectly and it might introduce information bias. However, the current study obtained information on parity when the participants were dementia-free. Lastly, any effect of mortality on the results was also likely to be smaller. Cross-sectional studies assess participants at a single time point and dementia patients with a longer survival rate are more likely to be included than those with a shorter survival rate. Because grand multiparous women show a decreased risk of mortality from dementia (Hinkula et al., Reference Hinkula, Kauppila, Nayha and Pukkala2006), a prevalence-incidence bias might affect the results of cross-sectional studies.

This study also has limitations. Changes in lifestyle and behaviours induced by parity and socialeconomic status which associated with the number of parities could be associated with the risk of incident dementia and have affected our results, and while we controlled for educational level, hypertension, DM and cohort, other confounders might have influenced our outcomes. Adoption or death of children might have distorted parity information because parity data were based on the number of children in two cohorts and the number of childbirths in four cohorts. In addition, the effect of parity on the risk of dementia could be over- or under-estimated because we excluded about one-tenth of participants whose information on educational level, hypertension, DM or parity were not available.

In conclusion, grand multiparity is a significant risk factor for dementia in women. This may have particularly important implications for women in low and middle-income countries where the fertility rate and prevalence of grand multiparity are high.

Acknowledgements

The Sydney COSMIC team comprises Perminder S. Sachdev (head of COSMIC, and joint study leader of the Sydney Memory and Ageing Study); Darren M. Lipnicki (COSMIC study co-ordinator), Steve R Makkar, John D Crawford, Anbupalam Thalamuthu, Nicole A. Kochan, Yvonne Leung, and Jessica W. Lo.

Affiliations of the authors with the contributing studies are as follows (*indicates study leader or joint study leader):

Gothenburg H70 Birth cohort Studies: Ingmar Skoog*, Jenna Najar, Therese Rydberg Sterner;

Hellenic Longitudinal Investigation of Aging and Diet: Nikolaos Scarmeas*, Mary Yannakoulia, Efthimios Dardiotis; Korean Longitudinal Study on Cognitive Aging and Dementia: Ki Woong Kim*, Ji Won Han, Jong Bin Bae; Leipzig Longitudinal Study of the Aged: Steffi G. Riedel-Heller*, Susanne Roehr, Alexander Pabst;

Shanghai Aging Study: Ding Ding*. Qianhua Zhao, Xiaoniu Liang; Zaragoza Dementia Depression Project: Antonio Lobo*, Concepción De-la-Cámara, Elena Lobo.

Further COSMIC study leaders: Yuda Turana (Atma Jaya Cognitive & Aging Research), Erico Castro-Costa (Bambui Cohort Study of Aging), Bagher Larijani and Iraj Nabipour (Bushehr Elderly Health Program), Kenneth Rockwood (Canadian Study of Health & Aging), Xiao Shifu (Chinese Longitudinal Aging Study), Richard B. Lipton and Mindy J. Katz (Einstein Aging Study), Pierre-Marie Preux and Maëlenn Guerchet (Epidemiology of Dementia in Central Africa), Linda Lam (Hong Kong Memory and Ageing Prospective Study), Ingmar Skoog (Gothenburg H70 Birth Cohort Studies), Toshiharu Ninimiya (Hisayama Study), Richard Walker (Identification and Intervention for Dementia in Elderly Africans study), Hugh Hendrie (Indianapolis Ibadan Dementia Project), Juan J. Llibre-Rodriguez (Cuban Health and Alzheimer Study), Karen Ritchie(Etude Santé Psychologique et Traitement), Kenichi Meguro (Kurihara Study), Martin van Boxtel (Maastricht Ageing Study), Marcia Scazufca (São Paulo Ageing & Health Study), Antonio Guaita (Invecchiamento Cerebrale in Abbiategrasso), Liang-Kung Chen (I-Lan Longitudinal Aging Study), Suzana Shahar (LRGS TUA: Neuroprotective Model for Healthy Longevity among Malaysian Older Adults), Jacqueline Dominguez (Marikina Memory and Aging Project), Murali Krishna (Mysore studies of Natal effects on Ageing and Health), Mary Ganguli (Monongahela Valley Independent Elders Survey), Kaarin J. Anstey (Personality and Total Health Through Life Project), Michael Crowe (Puerto Rican Elderly: Health Conditions study), Mary N. Haan (Sacramento Area Latino Study on Aging), Shuzo Kumagai (Sasaguri Genkimon Study), Tze Pin Ng (Singapore Longitudinal Ageing Studies (I)), Henry Brodaty (Sydney Memory and Ageing Study), Kenichi Meguro (Tajiri Project), Richard Mayeux and Nicole Schupf (Washington Heights Inwood and Columbia Aging Project).

COSMIC NIH grant investigators: Perminder Sachdev: Scientia Professor of Neuropsychiatry; Co-Director, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney; Director, Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia. Mary Ganguli: Professor of Psychiatry, Neurology, and Epidemiology, University of Pittsburgh. Ronald Petersen: Professor of Neurology; Director, Mayo Clinic Alzheimer's Disease Research Center and the Mayo Clinic Study of Aging. Richard Lipton: Edwin S. Lowe Professor and Vice Chair of Neurology, Albert Einstein College of Medicine. Karen Ritchie: Professor and Director of the Neuropsychiatry Research Unit of the French National Institute of Research (INSERM U1061). Ki-Woong Kim: Professor of Brain and Cognitive Sciences, Director of National Institute of Dementia of Korea. Louisa Jorm: Director, Centre for Big Data Research in Health and Professor, Faculty of Medicine, UNSW Sydney, Australia. Henry Brodaty: Scientia Professor of Ageing & Mental Health; Co-Director, Centre for Healthy Brain Ageing (CHeBA), UNSW Sydney; Director, Dementia Collaborative Research Centre (DCRC); Senior Consultant, Old Age Psychiatry, Prince of Wales Hospital.

Financial support

Funding for COSMIC comes from a National Health and Medical Research Council of Australia Program Grant (ID 1093083), the National Institute On Aging of the National Institutes of Health under Award Number RF1AG057531, and philanthropic contributions to The Dementia Momentum Fund (UNSW Project ID PS38235). Funding for the contributing studies is as follows:

H70: The Swedish Research Council (2015-02830, 2013-8717), Swedish Research Council for Health, Working Life and Welfare (2013-2300, 2013-2496), the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALF-716681), Alzheimerfonden, Hjärnfonden, The Alzheimer's Association Stephanie B. Overstreet Scholars (IIRG-00-2159), The Alzheimer's Association Zenith Award (ZEN-01-3151)

HELIAD: IIRG-09133014 from the Alzheimer's Association; 189 10276/8/9/2011 from the ESPA-EU program Excellence Grant (ARISTEIA), which is co-funded by the European Social Fund and Greek National resources, and ΔΥ2β/οικ.51657/14.4.2009 from the Ministry for Health and Social Solidarity (Greece);

KLOSCAD: the Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea [Grant No. HI09C1379 (A092077)];

LEILA75+: the Interdisciplinary Centre for Clinical Research at the University of Leipzig (Interdisziplinäres Zentrum für Klinische Forschung/IZKF; grant 01KS9504);

SAS: Shanghai Brain-Intelligence Project [STCSM 16JC1420500], Natural Science Foundation and Major Basic Research Program of Shanghai [16JC1420100], National Natural Science Foundation of China [81773513], Scientific Research Plan Project of Shanghai Science and Technology Committee [17411950701, 17411950106], Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01), ZHANGJIANG LAB, Tianqiao and Chrissy Chen Institute, and the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, Fudan University.

ZARADEMP: Supported by grants from the Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spanish Ministry of Economy and Competitiveness, Madrid, Spain (grants 94/1562, 97/1321E, 98/0103, 01/0255, 03/0815, 06/0617, G03/128), and the Fondo Europeo de Desarrollo Regional (FEDER) of the European Union and Gobierno de Aragón, Group #19.

The sponsors were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other funders.

Conflict of Interest

None.

Ethical standards

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human subjects/patients were approved by the University of New South Wales Human Research Ethics Committee (Ref: # HC12446). Each of the six contributing studies had previously obtained ethics approval from their respective institutional review boards and written informed consent was obtained from all subjects/patients.

References

Abdelsalam, K and Elamin, A (2017) Influence of grand multiparity on the levels of insulin, glucose and HOMA-IR in comparison with nulliparity and primiparity. Pakistan Journal of Biological Sciences 20, 4246.Google Scholar
Albanese, E, Launer, LJ, Egger, M, Prince, MJ, Giannakopoulos, P, Wolters, FJ and Egan, K (2017) Body mass index in midlife and dementia: systematic review and meta-regression analysis of 589,649 men and women followed in longitudinal studies. Alzheimers & Dementia 8, 165178.Google ScholarPubMed
American Psychiatric Association (1987) Diagnostic and Statistical Manual of Mental Disorders; Revised (DSM-III-R). Washington, DC: American Psychiatric Association.Google Scholar
American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders. Washington, DC: American Psychiatric Association.Google Scholar
Babinszki, A, Kerenyi, T, Torok, O, Grazi, V, Lapinski, RH and Berkowitz, RL (1999) Perinatal outcome in grand and great-grand multiparity: effects of parity on obstetric risk factors. American Journal of Obstetrics and Gynecology 181, 669674.CrossRefGoogle ScholarPubMed
Bachman, DL, Wolf, PA, Linn, R, Knoefel, J, Cobb, J, Belanger, A, White, L and D'agostino, R (1993) Incidence of dementia and probable Alzheimer's disease in a general population: the Framingham study. Neurology 43, 515515.CrossRefGoogle Scholar
Barha, CK and Galea, LA (2010) Influence of different estrogens on neuroplasticity and cognition in the hippocampus. Biochimica et Biophysica Acta 1800, 1056–67.CrossRefGoogle ScholarPubMed
Barrett, ES, Parlett, LE, Windham, GC and Swan, SH (2014) Differences in ovarian hormones in relation to parity and time since last birth. Fertility and Sterility 101, 177380 e1.CrossRefGoogle ScholarPubMed
Beydoun, MA, Beydoun, HA, Gamaldo, AA, Teel, A, Zonderman, AB and Wang, Y (2014) Epidemiologic studies of modifiable factors associated with cognition and dementia: systematic review and meta-analysis. BMC Public Health 14, 643.CrossRefGoogle ScholarPubMed
Chavez-Macgregor, M, Van Gils, CH, Van Der Schouw, YT, Monninkhof, E, Van Noord, PA and Peeters, PH (2008) Lifetime cumulative number of menstrual cycles and serum sex hormone levels in postmenopausal women. Breast Cancer Research and Treatment 108, 101–12.CrossRefGoogle ScholarPubMed
Crane, PK, Walker, R, Hubbard, RA, Li, G, Nathan, DM, Zheng, H, Haneuse, S, Craft, S, Montine, TJ and Kahn, SE (2013) Glucose levels and risk of dementia. New England Journal of Medicine 369, 540548.CrossRefGoogle ScholarPubMed
Dardiotis, E, Kosmidis, MH, Yannakoulia, M, Hadjigeorgiou, GM and Scarmeas, N (2014) The hellenic longitudinal investigation of aging and diet (HELIAD): rationale, study design, and cohort description. Neuroepidemiology 43, 914.CrossRefGoogle ScholarPubMed
Ding, D, Zhao, Q, Guo, Q, Meng, H, Wang, B, Yu, P, Luo, J, Zhou, Y, Yu, L, Zheng, L, Chu, S, Mortimer, JA, Borenstein, AR and Hong, Z (2014) The Shanghai aging study: study design, baseline characteristics, and prevalence of dementia. Neuroepidemiology 43, 114–22.CrossRefGoogle ScholarPubMed
Han, JW, Kim, TH, Kwak, KP, Kim, K, Kim, BJ, Kim, SG, Kim, JL, Kim, TH, Moon, SW, Park, JY, Park, JH, Byun, S, Suh, SW, Seo, JY, So, Y, Ryu, S-H, Youn, JC, Lee, KH, Lee, DY, Lee, DW, Lee, SB, Lee, JJ, Lee, JR, Jeong, H, Jeong, H-G, Jhoo, JH, Han, K, Hong, JW and Kim, KW (2018) Overview of the Korean longitudinal study on cognitive aging and dementia. Psychiatry Investigation. 15, 767.CrossRefGoogle ScholarPubMed
Hill, G (2003) Neyman's bias re-visited. Journal of Clinical Epidemiology 56, 293296.CrossRefGoogle ScholarPubMed
Hinkula, M, Kauppila, A, Nayha, S and Pukkala, E (2006) Cause-specific mortality of grand multiparous women in Finland. American Journal of Epidemiology 163, 367–73.CrossRefGoogle ScholarPubMed
Humphries, KH, Westendorp, IC, Bots, ML, Spinelli, JJ, Carere, RG, Hofman, A and Witteman, JC (2001) Parity and carotid artery atherosclerosis in elderly women: the Rotterdam study. Stroke 32, 22592264.CrossRefGoogle ScholarPubMed
Inagaki, T, Gautreaux, C and Luine, V (2010) Acute estrogen treatment facilitates recognition memory consolidation and alters monoamine levels in memory-related brain areas. Hormones and Behavior 58, 415426.CrossRefGoogle ScholarPubMed
Jang, H, Bae, JB, Dardiotis, E, Scarmeas, N, Sachdev, PS, Lipnicki, DM, Han, JW, Kim, TH, Kwak, KP and Kim, BJ (2018) Differential effects of completed and incomplete pregnancies on the risk of Alzheimer disease. Neurology 91, e643e651.CrossRefGoogle ScholarPubMed
Kuiper, JS, Zuidersma, M, Oude Voshaar, RC, Zuidema, SU, Van Den Heuvel, ER, Stolk, RP and Smidt, N (2015) Social relationships and risk of dementia: a systematic review and meta-analysis of longitudinal cohort studies. Ageing Research Reviews 22, 3957.CrossRefGoogle ScholarPubMed
Lawlor, DA (2003) Is the association between parity and coronary heart disease due to biological effects of pregnancy or adverse lifestyle risk factors associated with child-rearing?: Findings from the British women's heart and health study and the British regional heart study. Circulation 107, 12601264.CrossRefGoogle ScholarPubMed
Lewis, CE, Funkhouser, E, Raczynski, JM, Sidney, S, Bild, DE and Howard, BV (1996) Adverse effect of pregnancy on high density lipoprotein (HDL) cholesterol in young adult women: the CARDIA study. American Journal of Epidemiology 144, 247254.CrossRefGoogle ScholarPubMed
Li, FD, He, F, Chen, TR, Xiao, YY, Lin, ST, Shen, W, Wang, XY, Zhai, YJ, Shang, XP and Lin, JF (2016) Reproductive history and risk of cognitive impairment in elderly women: a cross-sectional study in eastern China. Journal of Alzheimer's Disease 49, 139–47.CrossRefGoogle ScholarPubMed
Lobo, A, Lopez-Anton, R, Santabarbara, J, De-La-Cámara, C, Ventura, T, Quintanilla, M, Roy, J, Campayo, A, Lobo, E and Palomo, T (2011) Incidence and lifetime risk of dementia and Alzheimer's disease in a Southern European population. Acta Psychiatrica Scandinavica 124, 372383.CrossRefGoogle Scholar
Mazure, CM and Swendsen, J (2016) Sex differences in Alzheimer's disease and other dementias. The Lancet Neurology 15, 451452.CrossRefGoogle ScholarPubMed
McKhann, G, Drachman, D, Folstein, M, Katzman, R, Price, D and Stadlan, EM (1984) Clinical diagnosis of Alzheimer's disease report of the NINCDS-ADRDA work group* under the auspices of department of health and human services task force on Alzheimer's disease. Neurology 34, 939939.CrossRefGoogle ScholarPubMed
Medel-Anonuevo, C (1995) Women, Education and Empowerment: Pathways Towards Autonomy. UIE Studies 5. Hamburg: United Nations Educational, Scientific, and Cultural Organization.Google Scholar
Mueller, N, Mueller, N, Odegaard, A, Gross, M, Koh, W, Yuan, J and Pereira, M (2013) Higher parity is associated with an increased risk of type-II diabetes in Chinese women: the Singapore Chinese health study. BJOG: An International Journal of Obstetrics & Gynaecology 120, 14831489.CrossRefGoogle ScholarPubMed
Munro, CJ, Stabenfeldt, G, Cragun, J, Addiego, L, Overstreet, J and Lasley, B (1991) Relationship of serum estradiol and progesterone concentrations to the excretion profiles of their major urinary metabolites as measured by enzyme immunoassay and radioimmunoassay. Clinical Chemistry 37, 838844.CrossRefGoogle ScholarPubMed
Nicholson, WK, Asao, K, Brancati, F, Coresh, J, Pankow, JS and Powe, NR (2006) Parity and risk of type 2 diabetes: the atherosclerosis risk in communities study. Diabetes Care 29, 2349–54.CrossRefGoogle ScholarPubMed
Ott, A, Stolk, R, Van Harskamp, F, Pols, H, Hofman, A and Breteler, M (1999) Diabetes mellitus and the risk of dementia: the Rotterdam study. Neurology 53, 19371937.CrossRefGoogle ScholarPubMed
Paykel, ES, Brayne, C, Huppert, FA, Gill, C, Barkley, C, Gehlhaar, E, Beardsall, L, Girling, DM, Pollitt, P and O'connor, D (1994) Incidence of dementia in a population older than 75 years in the United Kingdom. Archives of General Psychiatry 51, 325332.CrossRefGoogle Scholar
Prince, M, Acosta, D, Ferri, CP, Guerra, M, Huang, Y, Rodriguez, JJL, Salas, A, Sosa, AL, Williams, JD, Dewey, ME, Acosta, I, Jotheeswaran, AT and Liu, Z (2012) Dementia incidence and mortality in middle-income countries, and associations with indicators of cognitive reserve: a 10/66 Dementia Research Group population-based cohort study. The Lancet 380, 5058.CrossRefGoogle Scholar
Ptok, U, Barkow, K and Heun, R (2002) Fertility and number of children in patients with Alzheimer's disease. Archives of Women's Mental Health 5, 83–6.CrossRefGoogle ScholarPubMed
Rasmussen, KL, Tybjærg-Hansen, A, Nordestgaard, BG and Frikke-Schmidt, R (2015) Plasma levels of apolipoprotein E and risk of dementia in the general population. Annals of Neurology 77, 301311.CrossRefGoogle ScholarPubMed
Reitz, C, Tang, MX, Schupf, N, Manly, JJ, Mayeux, R and Luchsinger, JA (2010) Association of higher levels of high-density lipoprotein cholesterol in elderly individuals and lower risk of late-onset Alzheimer disease. Archives of Neurology 67, 1491–7.CrossRefGoogle ScholarPubMed
Riedel-Heller, SG, Busse, A, Aurich, C, Matschinger, H and Angermeyer, MC (2001) Prevalence of dementia according to DSM–III–R and ICD–10: results of the Leipzig longitudinal study of the aged (LEILA75+) Part 1. The British Journal of Psychiatry 179, 250254.CrossRefGoogle ScholarPubMed
Rizzi, L, Rosset, I and Roriz-Cruz, M (2014) Global epidemiology of dementia: Alzheimer's and vascular types. BioMed Research Internationa 2014, 908915.Google ScholarPubMed
Ruitenberg, A, Ott, A, Van Swieten, JC, Hofman, A and Breteler, MM (2001) Incidence of dementia: does gender make a difference? Neurobiology of Aging 22, 575580.CrossRefGoogle Scholar
Sachdev, PS, Lipnicki, DM, Kochan, NA, Crawford, JD, Rockwood, K, Xiao, S, Li, J, Li, X, Brayne, C and Matthews, FE (2013) COSMIC (Cohort Studies of Memory in an International Consortium): an international consortium to identify risk and protective factors and biomarkers of cognitive ageing and dementia in diverse ethnic and sociocultural groups. BMC Neurology 13, 165.CrossRefGoogle Scholar
Shen, L and Ji, HF (2015) Vitamin D deficiency is associated with increased risk of Alzheimer's disease and dementia: evidence from meta-analysis. Nutrition Journal 14, 76.CrossRefGoogle ScholarPubMed
Solanke, BL (2019) Maternal socio-demographic factors associated with low parity and grand multiparity in Nigeria. Women & Health 59, 118.Google ScholarPubMed
Thorvaldsson, V, Karlsson, P, Skoog, J, Skoog, I and Johansson, B (2017) Better cognition in new birth cohorts of 70 year olds, but greater decline thereafter. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences 72, 1624.CrossRefGoogle ScholarPubMed
Tripepi, G, Jager, KJ, Dekker, FW and Zoccali, C (2010) Selection bias and information bias in clinical research. Nephron Clinical Practice 115, c94–9.CrossRefGoogle ScholarPubMed
United Nations (2019) World Population Prospects: 2019. New York: United Nations.Google Scholar
Winblad, B, Amouyel, P, Andrieu, S, Ballard, C, Brayne, C, Brodaty, H, Cedazo-Minguez, A, Dubois, B, Edvardsson, D and Feldman, H (2016) Defeating Alzheimer's disease and other dementias: a priority for European science and society. The Lancet Neurology 15, 455532.CrossRefGoogle ScholarPubMed
Yaffe, K, Lui, L-Y, Grady, D, Cauley, J, Kramer, J and Cummings, SR (2000) Cognitive decline in women in relation to non-protein-bound oestradiol concentrations. The Lancet 356, 708712.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Contributing cohorts

Figure 1

Table 2. Design and results of follow-up assessments according to cohorts

Figure 2

Table 3. Baseline characteristics of the participants

Figure 3

Table 4. Associations between number of parities and the risk of incident dementia