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Figure 1.  Flowchart on the Selection of Eligible Studies
Flowchart on the Selection of Eligible Studies
Figure 2.  Association Between Age at Menopause and Postmenopausal Depression
Association Between Age at Menopause and Postmenopausal Depression

Thirteen studies (15 arms) reported the association of age at menopause as a continuous variable (2-year increments) with depression in postmenopausal women (P < .001). Odds ratios (ORs) in the individual studies are indicated by the data markers (shaded boxes around the data markers reflect the statistical weight of the study); 95% CIs are indicated by the error bars. The pooled-effect estimate with its 95% CI is depicted as a diamond.

Figure 3.  Association Between Duration of Reproductive Period and Postmenopausal Depression
Association Between Duration of Reproductive Period and Postmenopausal Depression

Five studies explored the effect of the duration of the reproductive period (continuous by 2-year increments) on depression in postmenopausal women (P = .007). Odds ratios (ORs) in the individual studies are indicated as data markers (shaded boxes around the data markers reflect the statistical weight of the study); 95% CIs are indicated by the error bars. The pooled-effect estimate with its 95% CI is depicted as a diamond.

Table.  Characteristics of the 14 Eligible Studies
Characteristics of the 14 Eligible Studies
1.
World Health Organization.  Mental health and older adults.http://www.who.int/mediacentre/factsheets/fs381/en/. Published 2013. Updated September 2015. Accessed May 26, 2015.
2.
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Barua  A, Ghosh  MK, Kar  N, Basilio  MA.  Prevalence of depressive disorders in the elderly.  Ann Saudi Med. 2011;31(6):620-624.PubMedGoogle ScholarCrossref
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Vos  T, Flaxman  AD, Naghavi  M,  et al.  Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010.  Lancet. 2012;380(9859):2163-2196.PubMedGoogle ScholarCrossref
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Wang  ZJ, Guo  M, Si  TM,  et al.  Association of depression with adverse cardiovascular events after percutaneous coronary intervention.  Coron Artery Dis. 2013;24(7):589-595.PubMedGoogle ScholarCrossref
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Sun  WJ, Xu  L, Chan  WM, Lam  TH, Schooling  CM.  Are depressive symptoms associated with cardiovascular mortality among older Chinese: a cohort study of 64,000 people in Hong Kong?  Am J Geriatr Psychiatry. 2013;21(11):1107-1115.PubMedGoogle ScholarCrossref
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Saz  P, Dewey  ME.  Depression, depressive symptoms and mortality in persons aged 65 and over living in the community: a systematic review of the literature.  Int J Geriatr Psychiatry. 2001;16(6):622-630.PubMedGoogle ScholarCrossref
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Kessler  RC, McGonagle  KA, Swartz  M, Blazer  DG, Nelson  CB.  Sex and depression in the National Comorbidity Survey, I: lifetime prevalence, chronicity and recurrence.  J Affect Disord. 1993;29(2-3):85-96.PubMedGoogle ScholarCrossref
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Soares  CN, Zitek  B.  Reproductive hormone sensitivity and risk for depression across the female life cycle: a continuum of vulnerability?  J Psychiatry Neurosci. 2008;33(4):331-343.PubMedGoogle Scholar
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Thys-Jacobs  S, McMahon  D, Bilezikian  JP.  Differences in free estradiol and sex hormone–binding globulin in women with and without premenstrual dysphoric disorder.  J Clin Endocrinol Metab. 2008;93(1):96-102.PubMedGoogle ScholarCrossref
11.
Schmidt  PJ, Nieman  LK, Danaceau  MA, Adams  LF, Rubinow  DR.  Differential behavioral effects of gonadal steroids in women with and in those without premenstrual syndrome.  N Engl J Med. 1998;338(4):209-216.PubMedGoogle ScholarCrossref
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Bloch  M, Schmidt  PJ, Danaceau  M, Murphy  J, Nieman  L, Rubinow  DR.  Effects of gonadal steroids in women with a history of postpartum depression.  Am J Psychiatry. 2000;157(6):924-930.PubMedGoogle ScholarCrossref
13.
Gordon  JL, Girdler  SS, Meltzer-Brody  SE,  et al.  Ovarian hormone fluctuation, neurosteroids, and HPA axis dysregulation in perimenopausal depression: a novel heuristic model.  Am J Psychiatry. 2015;172(3):227-236.PubMedGoogle ScholarCrossref
14.
Arevalo  MA, Azcoitia  I, Garcia-Segura  LM.  The neuroprotective actions of oestradiol and oestrogen receptors.  Nat Rev Neurosci. 2015;16(1):17-29.PubMedGoogle ScholarCrossref
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Hankin  BL, Abramson  LY.  Development of gender differences in depression: an elaborated cognitive vulnerability-transactional stress theory.  Psychol Bull. 2001;127(6):773-796.PubMedGoogle ScholarCrossref
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Burger  HG, Hale  GE, Robertson  DM, Dennerstein  L.  A review of hormonal changes during the menopausal transition: focus on findings from the Melbourne Women’s Midlife Health Project.  Hum Reprod Update. 2007;13(6):559-565.PubMedGoogle ScholarCrossref
17.
Stroup  DF, Berlin  JA, Morton  SC,  et al; Meta-analysis of Observational Studies in Epidemiology (MOOSE) group.  Meta-analysis of observational studies in epidemiology: a proposal for reporting.  JAMA. 2000;283(15):2008-2012.PubMedGoogle ScholarCrossref
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19.
Bezircioglu  I, Gulseren  L, Oniz  A, Kindiroglu  N.  Depression-anxiety and disability in the premenopausal and postmenopausal period [in Turkish].  Turkish J Psychiatry. 2004;15(3):199-207.Google Scholar
20.
Perquier  F, Ryan  J, Ancelin  ML, Mesrine  S, Clavel-Chapelon  F.  Lifetime endogenous reproductive factors and severe depressive symptoms in postmenopausal women: findings from the E3N cohort.  Menopause. 2013;20(11):1154-1163.PubMedGoogle ScholarCrossref
21.
Ryan  J, Carrière  I, Scali  J, Ritchie  K, Ancelin  ML.  Lifetime hormonal factors may predict late-life depression in women.  Int Psychogeriatr. 2008;20(6):1203-1218.PubMedGoogle ScholarCrossref
22.
Ünsal  A, Tozun  M, Ayranci  U.  Prevalence of depression among postmenopausal women and related characteristics.  Climacteric. 2011;14(2):244-251.PubMedGoogle ScholarCrossref
23.
Berecki-Gisolf  J, Begum  N, Dobson  AJ.  Symptoms reported by women in midlife: menopausal transition or aging?  Menopause. 2009;16(5):1021-1029.PubMedGoogle ScholarCrossref
24.
Ünsal  A. Ayranci  Ü, Tozun  M.  Prevalence of depression and its relationship with sociodemographic characteristics among women in a rural town of western Turkey [in Turkish].  Anatolian J Psychiatry. 2008;9:148-155.Google Scholar
25.
Wells  GA, Shea  B, O’Connel  D,  et al.  The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa Hospital Research Institute website. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Updated 2014. Accessed June 28, 2015.
26.
Psaltopoulou  T, Sergentanis  TN, Panagiotakos  DB, Sergentanis  IN, Kosti  R, Scarmeas  N.  Mediterranean diet, stroke, cognitive impairment, and depression: a meta-analysis.  Ann Neurol. 2013;74(4):580-591.PubMedGoogle ScholarCrossref
27.
Egger  M, Davey Smith  G, Schneider  M, Minder  C.  Bias in meta-analysis detected by a simple, graphical test.  BMJ. 1997;315(7109):629-634.PubMedGoogle ScholarCrossref
28.
Mantel  N, Haenszel  W.  Statistical aspects of the analysis of data from retrospective studies of disease.  J Natl Cancer Inst. 1959;22(4):719-748.PubMedGoogle Scholar
29.
DerSimonian  R, Laird  N.  Meta-analysis in clinical trials.  Control Clin Trials. 1986;7(3):177-188.PubMedGoogle ScholarCrossref
30.
Higgins  JPT, Green  S, eds. Cochrane Handbook for Systematic Reviews of Interventions; version 5.1.0 [updated March 2011]. The Cochrane Collaboration. http://www.cochrane-handbook.org. Published 2011. Accessed June 28, 2015.
31.
Orsini  N, Li  R, Wolk  A, Khudyakov  P, Spiegelman  D.  Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software.  Am J Epidemiol. 2012;175(1):66-73.PubMedGoogle ScholarCrossref
32.
StataCorp.  Stata Quick Reference and Index. College Station, TX: StataCorp LP; 2009.
33.
Bączyk  G, Chuchracki  M, Opala  T.  Effect of selected socio-demographic, clinical and biochemical factors on self-reported quality of life among post-menopausal women with osteoporosis.  Ann Agric Environ Med. 2013;20(4):843-848.PubMedGoogle Scholar
34.
Erez  HB, Weller  A, Vaisman  N, Kreitler  S.  The relationship of depression, anxiety and stress with low bone mineral density in post-menopausal women.  Arch Osteoporos. 2012;7:247-255.PubMedGoogle ScholarCrossref
35.
Jasienska  G, Ziomkiewicz  A, Górkiewicz  M, Pajak  A.  Body mass, depressive symptoms and menopausal status: an examination of the “Jolly Fat” hypothesis.  Womens Health Issues. 2005;15(3):145-151.PubMedGoogle ScholarCrossref
36.
Lambrinoudaki  I, Bouziou  G, Armeni  E,  et al.  Circulating androgens are associated with mood disturbances in young postmenopausal women.  Climacteric. 2015;18(2):205-213.PubMedGoogle ScholarCrossref
37.
Toffol  E, Heikinheimo  O, Partonen  T.  Associations between psychological well-being, mental health, and hormone therapy in perimenopausal and postmenopausal women: results of two population-based studies.  Menopause. 2013;20(6):667-676.PubMedGoogle ScholarCrossref
38.
Tsiligianni  IG, Tyrovolas  S, Bountziouka  V,  et al.  Depressive symptoms in postmenopausal women: results from the MEDIS Study.  Women Health. 2014;54(5):389-401.PubMedGoogle ScholarCrossref
39.
Whalley  LJ, Fox  HC, Starr  JM, Deary  IJ.  Age at natural menopause and cognition.  Maturitas. 2004;49(2):148-156.PubMedGoogle ScholarCrossref
40.
Bove  R, Secor  E, Chibnik  LB,  et al.  Age at surgical menopause influences cognitive decline and Alzheimer pathology in older women.  Neurology. 2014;82(3):222-229.PubMedGoogle ScholarCrossref
41.
Rocca  WA, Grossardt  BR, Geda  YE,  et al.  Long-term risk of depressive and anxiety symptoms after early bilateral oophorectomy.  Menopause. 2008;15(6):1050-1059.PubMedGoogle ScholarCrossref
42.
Mantani  A, Yamashita  H, Fujikawa  T, Yamawaki  S.  Higher incidence of hysterectomy and oophorectomy in women suffering from clinical depression: retrospective chart review.  Psychiatry Clin Neurosci. 2010;64(1):95-98.PubMedGoogle ScholarCrossref
43.
Jacobsen  BK, Heuch  I, Kvåle  G.  Age at natural menopause and all-cause mortality: a 37-year follow-up of 19,731 Norwegian women.  Am J Epidemiol. 2003;157(10):923-929.PubMedGoogle ScholarCrossref
44.
Ossewaarde  ME, Bots  ML, Verbeek  AL,  et al.  Age at menopause, cause-specific mortality and total life expectancy.  Epidemiology. 2005;16(4):556-562.PubMedGoogle ScholarCrossref
45.
Thomas  F, Renaud  F, Benefice  E, de Meeüs  T, Guegan  JF.  International variability of ages at menarche and menopause: patterns and main determinants.  Hum Biol. 2001;73(2):271-290.PubMedGoogle ScholarCrossref
46.
Ryan  J, Scali  J, Carrière  I,  et al.  Oestrogen receptor polymorphisms and late-life depression.  Br J Psychiatry. 2011;199(2):126-131.PubMedGoogle ScholarCrossref
47.
Soares  CN.  Can depression be a menopause-associated risk?  BMC Med. 2010;8:79.PubMedGoogle ScholarCrossref
48.
Osterlund  MK.  Underlying mechanisms mediating the antidepressant effects of estrogens.  Biochim Biophys Acta. 2010;1800(10):1136-1144.PubMedGoogle ScholarCrossref
49.
Lan  YL, Zhao  J, Li  S.  Update on the neuroprotective effect of estrogen receptor α against Alzheimer’s disease.  J Alzheimers Dis. 2015;43(4):1137-1148.PubMedGoogle Scholar
50.
Naismith  SL, Norrie  LM, Mowszowski  L, Hickie  IB.  The neurobiology of depression in later-life: clinical, neuropsychological, neuroimaging and pathophysiological features.  Prog Neurobiol. 2012;98(1):99-143.PubMedGoogle ScholarCrossref
51.
Alexopoulos  GS, Meyers  BS, Young  RC, Campbell  S, Silbersweig  D, Charlson  M.  “Vascular depression” hypothesis.  Arch Gen Psychiatry. 1997;54(10):915-922.PubMedGoogle ScholarCrossref
52.
Lloyd  AJ, Ferrier  IN, Barber  R, Gholkar  A, Young  AH, O’Brien  JT.  Hippocampal volume change in depression: late- and early-onset illness compared.  Br J Psychiatry. 2004;184:488-495.PubMedGoogle ScholarCrossref
53.
Diniz  BS, Butters  MA, Albert  SM, Dew  MA, Reynolds  CF  III.  Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies.  Br J Psychiatry. 2013;202(5):329-335.PubMedGoogle ScholarCrossref
54.
Atsma  F, Bartelink  ML, Grobbee  DE, van der Schouw  YT.  Postmenopausal status and early menopause as independent risk factors for cardiovascular disease: a meta-analysis.  Menopause. 2006;13(2):265-279.PubMedGoogle ScholarCrossref
55.
Rocca  WA, Bower  JH, Maraganore  DM,  et al.  Increased risk of cognitive impairment or dementia in women who underwent oophorectomy before menopause.  Neurology. 2007;69(11):1074-1083.PubMedGoogle ScholarCrossref
56.
Rasgon  NL, Magnusson  C, Johansson  AL, Pedersen  NL, Elman  S, Gatz  M.  Endogenous and exogenous hormone exposure and risk of cognitive impairment in Swedish twins: a preliminary study.  Psychoneuroendocrinology. 2005;30(6):558-567.PubMedGoogle ScholarCrossref
57.
McLay  RN, Maki  PM, Lyketsos  CG.  Nulliparity and late menopause are associated with decreased cognitive decline.  J Neuropsychiatry Clin Neurosci. 2003;15(2):161-167.PubMedGoogle ScholarCrossref
58.
Nofer  JR.  Estrogens and atherosclerosis: insights from animal models and cell systems.  J Mol Endocrinol. 2012;48(2):R13-R29.PubMedGoogle ScholarCrossref
59.
Zweifel  JE, O’Brien  WH.  A meta-analysis of the effect of hormone replacement therapy upon depressed mood.  Psychoneuroendocrinology. 1997;22(3):189-212.PubMedGoogle ScholarCrossref
60.
Soares  CN, Almeida  OP, Joffe  H, Cohen  LS.  Efficacy of estradiol for the treatment of depressive disorders in perimenopausal women: a double-blind, randomized, placebo-controlled trial.  Arch Gen Psychiatry. 2001;58(6):529-534.PubMedGoogle ScholarCrossref
61.
Schmidt  PJ, Nieman  L, Danaceau  MA,  et al.  Estrogen replacement in perimenopause-related depression: a preliminary report.  Am J Obstet Gynecol. 2000;183(2):414-420.PubMedGoogle ScholarCrossref
62.
Morrison  MF, Kallan  MJ, Ten Have  T, Katz  I, Tweedy  K, Battistini  M.  Lack of efficacy of estradiol for depression in postmenopausal women: a randomized, controlled trial.  Biol Psychiatry. 2004;55(4):406-412.PubMedGoogle ScholarCrossref
63.
Soares  CN.  Depression in peri- and postmenopausal women: prevalence, pathophysiology and pharmacological management.  Drugs Aging. 2013;30(9):677-685.PubMedGoogle ScholarCrossref
64.
Rossouw  JE, Anderson  GL, Prentice  RL,  et al; Writing Group for the Women’s Health Initiative Investigators.  Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women’s Health Initiative randomized controlled trial.  JAMA. 2002;288(3):321-333.PubMedGoogle ScholarCrossref
65.
Bodo  C, Rissman  EF.  New roles for estrogen receptor β in behavior and neuroendocrinology.  Front Neuroendocrinol. 2006;27(2):217-232.PubMedGoogle ScholarCrossref
66.
Harris  HA, Albert  LM, Leathurby  Y,  et al.  Evaluation of an estrogen receptor-β agonist in animal models of human disease.  Endocrinology. 2003;144(10):4241-4249.PubMedGoogle ScholarCrossref
67.
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Original Investigation
Meta-analysis
February 2016

Association of Age at Menopause and Duration of Reproductive Period With Depression After Menopause: A Systematic Review and Meta-analysis

Author Affiliations
  • 1Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
  • 2Program Medical Neurosciences, Charité-Universitätsmedizin, Berlin, Germany
  • 3Department of Women’s and Children’s Health, Uppsala University, Uppsala, Sweden
  • 4Division of Internal Medicine, Department of Medicine, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
JAMA Psychiatry. 2016;73(2):139-149. doi:10.1001/jamapsychiatry.2015.2653
Abstract

Importance  Estrogens have neuroprotective and antidepressive effects; however, associations between indices of reduced endogenous estrogens and risk for postmenopausal depression have not been systematically explored.

Objective  To investigate the association of age at menopause and the duration of the reproductive period with the risk for depression among postmenopausal women with naturally occurring menopause.

Data Sources  A search strategy for use of MEDLINE was developed (through January 1, 2015) using the key terms menopause, climacteric, reproductive period, depression, and mood disorders. References of included studies and reviews were also screened; authors were contacted to maximize synthesized evidence.

Study Selection  A total of 12 323 articles, without language restriction, were screened by pairs of reviewers to identify observational studies related to the study hypothesis; 14 studies were eligible for meta-analysis.

Data Extraction and Synthesis  Pairs of reviewers independently extracted information on study design and type of analysis by participants’ characteristics and methods of depression ascertainment. Study quality was assessed using the Newcastle-Ottawa Scale, and fixed- or random-effects models were implemented.

Main Outcomes and Measures  Pooled-effect estimates for depression, defined by psychiatric evaluation or validated instruments, by age at menopause and duration of the reproductive period.

Results  The 14 studies included in the meta-analysis represented 67 714 women. An inverse association (reported as odds ratio [OR]; 95% CI of 2-year increments) with depression in postmenopausal women was shown for increasing age at menopause (0.98; 0.96-0.99 [67 434 unique participants; 13 studies]) and duration of the reproductive period (0.98; 0.96-0.99 [54 715 unique participants; 5 studies]). Menopause at age 40 or more years compared with premature menopause was associated with a 50% decreased risk for depression (3033 unique participants; 4 studies). Pooling of studies examining severe depression showed a 5% decrease in risk of severe depression with increasing (2-year increment) age at menopause (52 736 unique participants; 3 studies); sensitivity analysis of studies controlling for past depression revealed similar results for age at menopause (0.98; 0.96-1.00 [48 894 unique participants; 3 studies). No heterogeneity or publication bias was evident in the main analyses.

Conclusions and Relevance  Longer exposure to endogenous estrogens, expressed as older age at menopause and longer reproductive period, is associated with a lower risk of depression in later life. Identifying women at higher risk for depression due to early menopause who could benefit from psychiatric intervention or estrogen-based therapies could be useful in the clinical setting.

Introduction

Mental disorders are an important public health issue,1 with the lifetime prevalence of major depression approximating 15% in high-income countries and 11% in low-income countries.2 Late-life depression affects up to 10% of the elderly population.3 Moreover, depressive disorders have been recognized as the second leading cause of disability across a person’s lifespan4 and have been consistently associated with adverse health outcomes, including cardiovascular disease5,6 and all-cause mortality.7

Sex discrepancies have been described in the epidemiologic studies2,8 of depression, with a doubled lifetime risk of major depression among women compared with men; this disparity is more profound during women’s reproductive years.9 Intense fluctuations of ovarian hormones observed premenstrually,10,11 during pregnancy and postpartum,12 and perimenopausally13 have been associated with depression and have been proposed as the reason for this female preponderance during the specified time windows. Estrogens are thought to exert neuroprotective actions via receptors that have been recognized in the brain.14 Furthermore, the higher vulnerability of women to stressful events and sex differences in stress response could partly explain the discrepancy.15

Transition in the postmenopausal period is linked to a relatively abrupt decrease in estrogen production16 and a gradual attenuation of sex differences in the prevalence of depression in the elderly population.14 Therefore, an advanced age at menopausal transition as a marker of longer exposure to endogenous estrogens could indicate a longer exposure to neuroprotective and antidepressive effects of estrogens. In this context, the aim of this systematic review and meta-analysis was to synthesize and quantify the results of published studies on the association between age at menopause or the duration of the reproductive period as markers of cumulative lifelong estrogen exposure and the risk of depression in postmenopausal women.

Methods

This systematic review was based on a predefined protocol (eMethods 1 in the Supplement). It was conducted in accordance with the Meta-analysis of Observational Studies in Epidemiology guidelines17 (eTable 1 in the Supplement).

Search Strategy and Eligibility Criteria

Relevant published scientific articles were sought in MEDLINE through January 1, 2015, using combinations of the following Medical Subject Headings: menopause, climacteric, reproductive period, depression, and mood disorders. The detailed search strategy is available in eMethods 2 in the Supplement. No restrictions on language, publication year, or study design were applied. Reference lists of the included studies and relevant reviews were thereafter hand searched for additional potentially eligible studies (snowball procedure).

Cohort, case-control, and cross-sectional studies exploring the association of depression with age at menopause and/or duration of the reproductive period in postmenopausal women with naturally occurring menopause were considered eligible. Age at menopause was preferably defined as 1 year following the last menstruation,18 but studies examining age at final menstruation were also considered for eligibility. Duration of the reproductive period was determined as the age at menopause minus the age at menarche. The diagnosis of depression must have been based on clinical diagnostic criteria or validated cutoff-point questionnaires. Case series, case reports, in vitro studies, animal studies, and investigations using nonvalidated instruments, questionnaires with no defined cutoff point, or questionnaires assessing depression as a self-reported symptom by a single question were excluded. Studies that included only women with depression and those that examined a population with preexisting severe psychiatric disorders were not eligible. Studies were also excluded if the population was limited to perimenopausal participants, breast cancer survivors with medically induced menopause, or women with surgically induced menopausal transition. When the participants included women who underwent naturally occurring or surgically induced menopause, the quantitative synthesis was limited to the cohort with naturally occurring menopause if those data were available; otherwise, the original effect estimates were included. Randomized clinical trials or intervention studies were considered for eligibility if they provided depression measurements at the preintervention phase. The investigators in those studies were contacted to provide appropriate analyses, potential clarifications, or missing data.

Investigators in nondirectly eligible studies (ie, including both exposure and outcome variables) were contacted to provide the multivariate regression analysis effect estimates of age at menopause and/or the duration of the reproductive period on depression encompassing at least the following adjusting factors: age, educational level, hormone therapy (HT) use, premenopausal depression history, smoking, body mass index, marital status, and parity. These variables were principally selected by confounding factors used by the studies included in this meta-analysis19-24 to achieve homogeneous effect estimates. Reminders were sent to investigators 1 month after the initial contact. In case of multiple publications referring to the same cohort, the most recent publication or the one with the largest sample was selected for inclusion in the meta-analysis, but information from all relevant studies was retained. The selection of eligible studies was performed by 6 investigators (including M.K.G., T.P.T., A.-A.D, and E.I.K.) in 3 pairs who independently screened the titles, abstracts, and full text of identified articles; consensus was provisioned to resolve any disagreement.

Data Extraction and Assessment of Quality

Abstracted descriptive data included general information (ie, year, author, title, journal, region of origin, and study period), study characteristics (ie, design, duration of follow-up, and inclusion and exclusion criteria of the participants), and characteristics of the participants (ie, cohort size and number of incident cases, number of cases and controls, matching factors in case-control studies, mean age, age range, ethnicity, definition and ascertainment of depression, ascertainment of age at menopause and duration of reproductive period, type of menopause, and HT use). Statistical analysis of the abstracted data included adjusting factors, reference category, and type of the effect estimate and results (ie, odds ratios [ORs] and 95% CIs). Maximally adjusted effect estimates were preferred. If the aforementioned data were not presented in the article, crude effect estimates and 95% CIs were de novo calculated from 2 × 2 tables using data available in the article.

The quality of the included studies was evaluated using the 9-item Newcastle-Ottawa Scale for cohort and case-control studies.25 However, because the effect estimates of all eligible studies were derived from cross-sectional analyses, the cohort subscale of the Newcastle-Ottawa Scale (6 items) after excluding items 4 (“demonstration that outcome of interest was not present at start of study”), 8 (“was follow-up long enough for outcomes to occur”), and 9 (“adequacy of follow-up of cohorts”) was used.26 For comparability questions, age was set a priori as the most important matching or adjustment factor. Publication bias was assessed by the Egger test in analyses including at least 10 study arms.27 Statistical significance was set at P < .10. Four of us (M.K.G., T.P.T., A.-A.D., and E.I.K.) performed data abstraction and quality assessment independently in pairs of 2; consensus was reached for disagreements.

Statistical Analysis

The ORs and 95% CIs of the different studies were pooled using fixed-effects (Mantel-Haenszel)28 or random-effects (DerSimonian-Laird)29 models, and pooled-effect estimates were calculated. Between-study heterogeneity was measured by the I2 and Cochran Q tests; significance was set at P < .10. In cases of significant between-study heterogeneity, a random-effects model was applied regardless of the I2 estimation.30 The significance level for the overall effect was set at P < .05.

Analysis was conducted separately for the effect of both independent variables of interest (ie, age at menopause and duration of the reproductive period) as continuous variables on the risk of depression. Based on the largest eligible study (51 088 women),20 2-year increments were chosen for the exposure variables. Different increment effect estimates of other included studies were thereafter converted to 2-year estimates to safeguard homogeneity. Studies reporting only category-specific ORs were included following ad hoc estimation of the log-linear trend using the generalized least-squares approach.31 Because this method requires the number of cases and controls by category of exposure and the presence of at least 3 levels of exposure, including baseline, it could not be applied to all studies. Therefore, an alternative analysis was carried out that included studies presenting results for age at menopause as a dichotomous categorical variable (≥40 vs <40 years).

Two sensitivity analyses were performed retaining studies controlling for the presence of premenopausal depression, as well as studies controlling for HT use. In a subanalysis, we examined the effect of age at menopause on severe postmenopausal depression, as defined by instruments used by the individual studies. A sensitivity analysis was then conducted including only studies defining age at menopause by the internationally accepted definition of 1 year following the last menstruation. Raw data contributed by authors who we contacted were modeled in multivariate logistic regression analyses to derive individual effect estimates that were subsequently synthesized in the meta-analysis (eMethods 2 in the Supplement). All statistical analyses were performed using Stata, version 11.1 (StataCorp).32 Data analysis was conducted from June 10 to August 13, 2015.

Results
Search Strategy and Contact of Authors

Figure 1 depicts the flowchart of the study selection process. The database search yielded 12 323 records; 12 057 of these were deemed irrelevant by title or abstract. The full text of the remaining 266 articles was assessed along with 13 potentially eligible articles derived from the snowball process. Of these 279 articles, 6 were eligible,19-24 133 were excluded (eTable 2 in the Supplement), and the authors of the remaining 140 articles were contacted for clarification. Of these 140 articles, 8 studies provided the requested analysis or raw data for analysis by the leading research team.33-40 Details regarding selection of the studies and contacting of the authors, as well as the full reference list, are available in eMethods 2 and the eReferences in the Supplement.

Thirteen of the 14 eligible studies contained data that could be included in the analysis on treating age at menopause as a continuous variable,20-24,33-40 and 4 studies were included in the analysis on treating age at menopause as a categorical variable.19,22,24,40 Five studies contributed data for analysis of the duration of the reproductive period, which was considered a continuous variable.20,21,37,39,40

The Table summarizes the abstracted data of the 14 nonoverlapping eligible studies (67 714 unique women). Ten of the studies were cross-sectional19,21,22,24,33-38 and 4 were cohort20,23,39,40 studies. Depression was diagnosed by validated self-report instruments in 12 studies.19-22,24,33-39 The DSM-III-R criteria were used for diagnosis of major depression in one study,40 and a history of physician-diagnosed depression was used in another study.23 Women not meeting the criteria determined in studies for the diagnosis of depression composed the control group. Among 12 studies reporting the type of menopause, only 4 provided separate analyses for naturally occurring menopause,33,35,39,40 whereas 8 studies included women who had undergone surgical menopause as well.19-24,36,37 Eight of 9 studies providing information for HT use included current or past users,19-21,23,36,37,39,40 and only 1 study included only women not using HT.35 The main continuous analysis for age at menopause included 67 434 postmenopausal women, among whom 8565 were considered to have postmenopausal depression, whereas the alternative main analysis including the duration of the reproductive period as the exposure of interest comprised 6591 women with depression symptoms among the 54 715 participants. All but 2 studies22,24 concerning age at menopause and all but 1 study21 containing data on the duration of the reproductive period provided multivariate analysis–derived effects. The most common adjusting factors (eTable 3 in the Supplement) included age (12 studies19-21,23,33-40), body mass index and obesity (11 studies19,20,23,33-40), educational level (10 studies19-21,23,33-38), smoking status (10 studies19,20,23,33-36,38-40), marital status (10 studies19-21,23,33,35-37,39,40), and HT use (7 studies20,21,33,36,37,39,40).

Quality of Studies

Quality assessment of the eligible studies using the Newcastle-Ottawa Scale is provided in eTable 4 in the Supplement. One study scored 6 of 6 possible points,40 8 scored 5 of 6 possible points,19,21,22,24,35,37-39 and the remaining 5 scored 4 of 6 possible points.20,23,33,34,36 The quality of the studies was most often compromised by the assessment of outcome; as expected in research projects, most studies used validated instruments to assess depression without subsequent clinical evaluation. An additional shortcoming in the 5 lower-quality studies pertained to the self-administered questionnaires used for the ascertainment of the 2 exposure variables instead of direct interviews.

Data Synthesis
Age at Menopause

After pooling effect estimates of the 15 study arms, which corresponded to 13 studies with age at menopause treated as a continuous variable,20-24,33-40 increasing age at menopause (2-year increments) was associated with a 2% decrease in the risk of depression in postmenopausal women (OR, 0.98; 95% CI, 0.96-0.99; heterogeneity I2 = 7.6%; P = .37 [67 434 unique participants]) (Figure 2). Excluding the study by Perquier et al,20 corresponding to a weight of 62% did not materially change the results (OR, 0.97; 95% CI, 0.95-0.99; heterogeneity, I2 = 11.2%; P = .33 [16 346 unique participants]).

The sensitivity analysis performed on 3 studies20,21,36(4 study arms) controlling for premenopausal depression did not alter the inverse association of age at menopause with postmenopausal depression (OR, 0.98; 95% CI, 0.96-1.00; heterogeneity, I2 = 22.1%; P = .28 [48 894 unique participants]) (eFigure 1 in the Supplement). The same results were also found in the sensitivity analysis retaining the 8 studies20,21,33,35-37,39,40 (10 study arms) controlling for HT use (OR, 0.98; 95% CI, 0.96-1.00; heterogeneity, I2 = 0.0%; P = .75 [56 813 unique participants]) (eFigure 2 in the Supplement). Moreover, in a subanalysis restricted to studies examining severe depression defined by appropriate cutoff points,20,21,38 (3 studies; 4 study arms) a 5% decrease was documented by a 2-year increase in age at menopause (OR, 0.95; 95% CI, 0.90-1.00; heterogeneity, I2 = 53.6%, P = .09 [52 736 unique participants]) (eFigure 3 in the Supplement). Lastly, in the sensitivity analysis of 7 studies21,22,24,33,36-38 (9 study arms) defining age at menopause as 1 year following the last menstruation, the results did not materially change (OR, 0.96; 95% CI, 0.94-0.98; heterogeneity, I2 = 0.0%; P = .75 [4809 unique participants]) (eFigure 4 in the Supplement).

In 4 studies (3033 women) providing data on women with premature menopause (<40 years),27-29,40 a sizeable doubling of risk of depression was found in this cohort compared with women who reported menopause at 40 years or older (OR, 0.49; 95% CI, 0.29-0.81; heterogeneity, I2 = 54.2%, P = .09) (eFigure 5 in the Supplement).

Reproductive Period

Results from the 5 studies (6 study arms) providing effect estimates for the association of reproductive period duration with postmenopausal depression risk20,21,37,39,40 yielded a same-size, statistically significant inverse association (2% for an increase of reproductive period duration by 2 years) as that found for age at menopause (OR, 0.98; 95% CI, 0.96-0.99; heterogeneity, I2 = 0.0%; P = .57 [54 715 unique participants; 5 studies]) (Figure 3). A sensitivity analysis, excluding the study by Perquier et al20 because of its substantial weight, showed an inverse but nonsignificant association between reproductive period and risk of depression (OR, 0.98; 95% CI, 0.94-1.01; heterogeneity, I2 = 0.0%; P = .41 [3627 unique participants]). Because of the paucity of studies reporting on reproductive period duration, it was not possible to conduct other sensitivity analyses as were performed for age at menopause.

Publication Bias

In the meta-analysis for age at menopause as a continuous variable, no publication bias was found (P = .83, Egger test). In the subsequent analyses and sensitivity analyses, publication bias was not assessed because fewer than 10 studies were included, which could potentially hamper the power of this test.

Discussion

An inverse association between the age at menopause, treated either as a continuous or categorical variable, and the risk of subsequent depression in postmenopausal women was shown in this meta-analysis. This effect was retained after controlling for premenopausal depression and HT use and was enhanced among studies examining the association of age at menopause with severe depression or among women with premature menopause. The same size effect estimate was found in alternative analyses using the duration of the reproductive period as an index of exposure to endogenous estrogens.

These findings indicate that a shorter exposure to endogenous estrogens that is linked to a longer duration of estrogen deficiency, assessed through proxy variables, increases the risk for subsequent late-life depression and emphasizes the importance of the neuroprotective and antidepressive properties of endogenous estrogens. Even though we excluded studies of women with surgically induced menopause to reduce confounding by indication, our findings are in accordance with previous studies reporting that early menopause due to oophorectomy increases the risk of depression later in life.41,42 Older age at menopause has also been proposed to be an index of general health associated with lower risk for all-cause and cardiovascular-specific mortality.43,44 Age at menarche does not seem to influence the risk of depression in postmenopausal women,20,21 possibly because it is characterized by lower variance among women compared with age at menopause.45 Thus, discrepancies in age at menarche may not reflect major differences in total exposure to endogenous estrogens.

The abundance and wide distribution of estrogen receptors across the brain and the association of their genetic polymorphisms with late-life depression46 argue for the role of estrogens in the modulation of behavioral effects; however, the exact pathways for their action remain unclear.47 Direct regulation of monoamine neurotransmitter systems that are involved in the pathogenesis of late-life depression, in addition to modulating actions on neuroplasticity and the hypothalamus-pituitary-adrenal axis, could partially mediate the antidepressive properties of estrogens.48,49

When considering the underlying pathologic mechanisms, the different disease properties between early-onset and late-life depression should be taken into account. Contrary to depression that occurs at younger ages, increasing evidence suggests that geriatric depression is more commonly associated with generalized cerebral abnormalities attributed to vascular dysregulation and neurodegeneration of frontal-subcortical neural circuits.50-53 Epidemiologic evidence has shown that an early age at menopause is an independent risk factor for cardiovascular disease54; in addition, it has been suggested that early menopause or oophorectomy before menopause increases the risk for subsequent cognitive decline and dementia.55-57 Therefore, the antidepressive effects of longer exposure to endogenous estrogens could be mediated through their action against cerebral atherosclerosis and neurodegeneration. Experimental studies have demonstrated a neuroprotective role of circulating estradiol, which acts in neurons and glial cells via the intracellular estrogen receptors α and β,14,49 as well as antiatherogenic actions including enhancement of endothelial function, blockage of smooth muscle cell proliferation, and inhibition of inflammation.58

Regarding the potentially protective effect of estrogen supplementation for the treatment or prevention of postmenopausal depression, estrogens and HT—either as monotherapy or as adjunct therapy—have been reported to improve the outcome of perimenopausal depression59-61 as opposed to the findings for depression in postmenopausal women,62 indicating a possible window of opportunity during perimenopause for the effective use of estrogen therapy in depression.63 Given the results of our study, it remains to be investigated whether women with menopause at younger ages could benefit by preventive use of HT against late-life depression, provided that adverse effects associated with long-term use are considered.64 In this context, the development of estrogen receptor subtype-specific ligands could decrease the proportion of estrogen therapy adverse effects.65,66

A major strength of this meta-analysis lies in its sound methodologic approach according to current guidelines. Following an independent dual screening of more than 12 000 articles, rigorous communication with authors of potentially eligible articles was conducted, offering them the opportunity to deliver raw data for estimation of the individual study effect estimates (3 studies) so as to maximize the synthesized evidence. Eventually, the study participants contributing information in main analyses were more than 67 000 women, with no significant heterogeneity noticed among included studies. Most of these studies used important confounding factors: age, obesity, HT use, smoking, and marital status. Sensitivity analyses were further performed, when possible, to assess the effect of remaining potential confounding factors, whereas no publication bias was evident in the age at menopause analysis.

The meta-analysis bears certain inherent limitations that are mainly attributed to the design and effect estimates reporting in the included studies. Despite the absence of significant heterogeneity among the included studies, variable methods for defining depression were used, including self-reporting. Depression was determined by different cutoff points; notably, 3 studies used a cutoff point indicating severe depression, but the rest defined depression by lower cutoff points. However, the subsequent sensitivity analysis led to a higher effect among studies examining exclusively severe depression. Because the severity of depressive disorders seems to be associated with the severity of underlying cerebral abnormalities,67,68 the differential risk may indicate a dose-dependent association of duration of exposure to endogenous estrogens with underlying lesions and depression.

Given the cross-sectionally derived effect estimates, the direction of the causality between depression and exposure variables cannot be explored. History of preexisting (premenopausal) depression should be considered since it is a strong predictor of late-life depression69,70 and has been associated with earlier menopause and ovarian aging.71,72 To limit this drawback, a subanalysis of studies controlling for past depression was conducted, indicating that the observed inverse association of a later menopausal transition with postmenopausal depression remained significant.

Moreover, given the potential effect of exogenous estrogen on depression risk, the inclusion of current or past HT users in most of the studies may have influenced our findings. Although most of the included studies adjusted for HT use and a sensitivity analysis restricted to studies controlling for this factor did not materially change the results, there is a possibility for residual confounding; only studies excluding HT users could sufficiently control for this factor.

An additional limitation involves the self-reporting of age at menopause contrasted to determination by direct interview. This difference may have nominally lowered the quality of several eligible studies, whereas the retrospectively elicited information in different time periods after menopause has potentially led to differential recall bias.73 Self-recalled age at menopause has been reported in one study to be in satisfactory agreement with gynecologic medical records,74 but this assertion cannot preclude recall bias. This finding is of particular importance when considering that women recruited by eligible studies potentially started HT use before their last menstruation, making it cumbersome to determine the time of menopause. We attempted to assess heterogeneity regarding age at menopause definition through a sensitivity analysis confined to the 7 studies using the internationally accepted definition of 1 year after the last menstruation; the results remained essentially unchanged.

Because not all studies controlled for factors affecting lifetime estrogen exposure, including oral contraceptive use, breastfeeding, and number of pregnancies, residual confounding may remain an issue; the paucity of data in the published studies did not allow for meta-regression analyses. Similarly, none of the studies controlled for autoimmune diseases, and no meta-regression analyses could be conducted for cognition, cardiovascular disease, and psychological parameters, such as stressful experiences. Another limitation is that statistical power of the conducted subanalyses may have been hampered by the low number of included studies. Finally, participants in most of the studies were from Western communities, pointing to the need for more ethnically diverse populations and more generalizable findings given the geographic discrepancies in the timing of menopause.75

Conclusions

This meta-analysis suggests a potentially protective effect of increasing duration of exposure to endogenous estrogens as assessed by age at menopause as well as by the duration of the reproductive period. The findings provide epidemiologic support for the involvement of estrogen deficiency in the pathophysiology of late-life depression. If confirmed in prospective and culturally diverse studies controlling for potential confounders and assessing depression via psychiatric evaluation, these findings could have a significant clinical effect by allowing for the identification of a group of women at higher risk for depression who may benefit from psychiatric monitoring or estrogen-based therapies. Based on those data, health care professionals and health policy planners may recognize the extent of depression in the menopausal group and plan accordingly for treatment.

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Article Information

Corresponding Author: Eleni Th Petridou, MD, MPH, PhD, Department of Hygiene, Epidemiology, and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 75 Mikras Asias St, Athens, Greece 11527 (epetrid@med.uoa.gr).

Submitted for Publication: September 3, 2015; final revision received October 23, 2015; accepted October 26, 2015.

Published Online: January 6, 2016. doi:10.1001/jamapsychiatry.2015.2653.

Author Contributions: Drs Georgakis and Petridou had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Georgakis, Diamantaras, Skalkidou, Daskalopoulou, Petridou.

Acquisition, analysis, or interpretation of data: Georgakis, Thomopoulos, Diamantaras, Kalogirou, Daskalopoulou, Petridou.

Drafting of the manuscript: Georgakis, Diamantaras, Kalogirou, Petridou.

Critical revision of the manuscript for important intellectual content: Thomopoulos, Diamantaras, Skalkidou, Daskalopoulou, Petridou.

Statistical analysis: Georgakis, Thomopoulos, Diamantaras.

Administrative, technical, or material support: Georgakis, Thomopoulos, Kalogirou.

Study supervision: Daskalopoulou, Petridou.

Conflict of Interest Disclosures: None reported.

Additional Contributions: Anton Ryzhov, PhD (National Cancer Registry of Ukraine, National Institute of Cancer, Kyiv, Ukraine), Naliya Bikmurzina, MD, MSc (Charité-Universitätsmedizin, Berlin, Germany), and Sultan Eser, MD, PhD (Izmir Cancer Registry, Izmir Hub, Izmir & Hacettepe University Institute of Public Health, Ankara, Turkey), translated foreign-language articles. Prodromos Kanavidis, MD (National and Kapodistrian University of Athens), developed the screening platform for retrieved abstracts, and Yessica-Haydee Gomez, MSc (McGill University Health Center, Montreal, Quebec, Canada), searched for missing full-text articles and data abstraction. Theodoros Karavasilis, MD, and Ioannis Mavromatis, MD (National and Kapodistrian University of Athens), participated in the selection of studies. We thank the authors of the studies who provided primary data or analyses based on their data. Specifically, the following contributors are acknowledged: the staff of the Rush Alzheimer’s Disease Center for providing raw data on their studies and participants in the Religious Orders Study, Rush Memory and Aging Project, and Minority Aging and Research Study (these studies were supported by grants P30AG10161, R01AG17917, and R01AG15819 from the National Institute on Aging); the Steering Committee of Aberdeen Birth Cohort Study for providing raw data regarding Aberdeen Birth Cohort Study; Andrzej Pajak, MD, PhD, and Agnieszka Dorynska, PhD, for providing the requested analysis based on their data; Hany Burstein Erez, PhD, for providing the requested analysis as well as raw data of his study; Elena Toffol, MD, PhD, for sending the requested analysis based on her data; Grażyna Bączyk, MA, PhD, who sent us the analysis as requested; Ioanna G. Tsiligianni, MD, MPH, PhD, Stefanos Tyrovolas, PhD, and Demosthenes B. Panagiotakos, PhD, for providing us with the requested analysis based on their data; Ioanna Lambrinoudaki, MD, PhD, and Eleni Armeni, MD, PhD, for providing the requested analysis; Florence Perquier, MSc, for providing additional analyses based on the data in her published study; and Diana M. van Die, BA, for providing primary data based on her study. We also thank all authors who replied to the request for additional data, as detailed in the Supplement.

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