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Li H, Curry CL, Fischer-Colbrie T, Onnela JP, Williams MA, Hauser R, Coull BA, Jukic AMZ, Mahalingaiah S. Seasonal variations of menstrual cycle length in a large, US-based, digital cohort. Int J Hyg Environ Health 2024; 256:114308. [PMID: 38103472 PMCID: PMC10872302 DOI: 10.1016/j.ijheh.2023.114308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/30/2023] [Accepted: 12/01/2023] [Indexed: 12/19/2023]
Affiliation(s)
- Huichu Li
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | | | | | - Jukka-Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | - Michelle A Williams
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA
| | - Anne Marie Z Jukic
- Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, 27709, NC, USA
| | - Shruthi Mahalingaiah
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
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Vidafar P, Spitschan M. Light on Shedding: A Review of Sex and Menstrual Cycle Differences in the Physiological Effects of Light in Humans. J Biol Rhythms 2023; 38:15-33. [PMID: 36367137 PMCID: PMC9902977 DOI: 10.1177/07487304221126785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
The human circadian system responds to light as low as 30 photopic lux. Furthermore, recent evidence shows that there are huge individual differences in light sensitivity, which may help to explain why some people are more susceptible to sleep and circadian disruption than others. The biological mechanisms underlying the differences in light sensitivity remain largely unknown. A key variable of interest in understanding these individual differences in light sensitivity is biological sex. It is possible that in humans, males and females differ in their sensitivity to light, but the evidence is inconclusive. This is in part due to the historic exclusion of women in biomedical research. Hormonal fluctuations across the menstrual cycle in women has often been cited as a confound by researchers. Attitudes, however, are changing with funding and publication agencies advocating for more inclusive research frameworks and mandating that women and minorities participate in scientific research studies. In this article, we distill the existing knowledge regarding the relationship between light and the menstrual cycle. There is some evidence of a relationship between light and the menstrual cycle, but the nature of this relationship seems dependent on the timing of the light source (sunlight, moonlight, and electric light at night). Light sensitivity may be influenced by biological sex and menstrual phase but there might not be any effect at all. To better understand the relationship between light, the circadian system, and the menstrual cycle, future research needs to be designed thoughtfully, conducted rigorously, and reported transparently.
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Affiliation(s)
- Parisa Vidafar
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
- Translational Sensory and Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Manuel Spitschan
- Translational Sensory and Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- TUM Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
- TUM Institute for Advanced Study, Technical University of Munich, Garching, Germany
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Gibson EA, Li H, Fruh V, Gabra M, Asokan G, Jukic AMZ, Baird DD, Curry CL, Fischer-Colbrie T, Onnela JP, Williams MA, Hauser R, Coull BA, Mahalingaiah S. Covid-19 vaccination and menstrual cycle length in the Apple Women's Health Study. NPJ Digit Med 2022; 5:165. [PMID: 36323769 PMCID: PMC9628464 DOI: 10.1038/s41746-022-00711-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022] Open
Abstract
COVID-19 vaccination may be associated with change in menstrual cycle length following vaccination. We estimated covariate-adjusted differences in mean cycle length (MCL), measured in days, between pre-vaccination cycles, vaccination cycles, and post-vaccination cycles within vaccinated participants who met eligibility criteria in the Apple Women's Health Study, a longitudinal mobile-application-based cohort of people in the U.S. with manually logged menstrual cycles. A total of 9652 participants (8486 vaccinated; 1166 unvaccinated) contributed 128,094 cycles (median = 10 cycles per participant; inter-quartile range: 4-22). Fifty-five percent of vaccinated participants received Pfizer-BioNTech's mRNA vaccine, 37% received Moderna's mRNA vaccine, and 8% received the Johnson & Johnson/Janssen (J&J) vaccine. COVID-19 vaccination was associated with a small increase in MCL for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimated follicular phase vaccination was associated with increased MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated.
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Affiliation(s)
- Elizabeth A. Gibson
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Huichu Li
- grid.38142.3c000000041936754XDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Victoria Fruh
- grid.38142.3c000000041936754XDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Malaika Gabra
- grid.38142.3c000000041936754XDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Gowtham Asokan
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Anne Marie Z. Jukic
- grid.280664.e0000 0001 2110 5790Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC USA
| | - Donna D. Baird
- grid.280664.e0000 0001 2110 5790Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC USA
| | | | | | - Jukka-Pekka Onnela
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Michelle A. Williams
- grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Russ Hauser
- grid.38142.3c000000041936754XDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Brent A. Coull
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Shruthi Mahalingaiah
- grid.38142.3c000000041936754XDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA
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Kuzmenko NV, Tsyrlin VA, Pliss MG. Seasonal Dynamics of Melatonin, Prolactin,
Sex Hormones and Adrenal Hormones in Healthy People: a Meta-Analysis. J EVOL BIOCHEM PHYS+ 2021. [DOI: 10.1134/s0022093021030029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Zhou G, Yang M, Chai J, Sun R, Zhang J, Huang H, Zhang Y, Deng Q, Jiang L, Ba Y. Preconception ambient temperature and preterm birth: a time-series study in rural Henan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:9407-9416. [PMID: 33145731 DOI: 10.1007/s11356-020-11457-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 10/27/2020] [Indexed: 06/11/2023]
Abstract
Changes in the preconception ambient temperature (PAT) can affect the gametogenesis, disturbing the development of the embryo, but the health risks of PAT on the developing fetus are still unclear. Here, based on the National Free Preconception Health Examination Project in the rural areas of Henan Province, we evaluate the effects of PAT on preterm birth (PTB). Data of 1,231,715 records from self-reported interviews, preconception physical examination, early gestation follow-up, and postpartum follow-up were collected from 1 January 2013 to 31 December 2016. Generalized additive models were used to assess the cumulative and lag effects of PAT upon PTB. The significant cumulative effects of mean temperature within 2 weeks and 3 weeks on the risk of PTB, especially upon late PTB (34-36 weeks) (P < 0.05), were observed. Exposure to extreme heat (> 90th percentile) within 2 weeks (RR = 1.470) and 3 weeks (RR = 1.375) before conception could increase the risk of PTB. After stratifying PTB, exposure to extreme heat within 2 weeks before conception can increase the risks of early (< 34 weeks) and late PTB (P < 0.05). Besides, exposure to extreme cold (< 10th percentile) within 3 weeks or longer before conception can elevate the risk of PTB, especially late PTB. The significant lag effects of temperature changes on the risk of early PTB (lag-8 days or earlier) were observed. In conclusion, the risk of PTB was susceptible to PAT changes within 2 weeks or longer before conception. Our findings provide (i) guidance for rural couples to make pregnancy plans and (ii) scientific evidence for the government to formulate policies to prevent PTB.
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Affiliation(s)
- Guoyu Zhou
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- Yellow River Institute for Ecological Protection & Regional Coordinated Development, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Meng Yang
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Jian Chai
- National Health Commission Key Laboratory of Birth Defects Prevention, Zhengzhou, 450002, Henan, People's Republic of China
- Key Laboratory of Population Defects Prevention, Henan Provincial Research, Zhengzhou, 450002, Henan, People's Republic of China
- Henan Institute of Reproduction Health Science and Technology, Zhengzhou, 450002, Henan, People's Republic of China
| | - Renjie Sun
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Junxi Zhang
- National Health Commission Key Laboratory of Birth Defects Prevention, Zhengzhou, 450002, Henan, People's Republic of China
- Key Laboratory of Population Defects Prevention, Henan Provincial Research, Zhengzhou, 450002, Henan, People's Republic of China
- Henan Institute of Reproduction Health Science and Technology, Zhengzhou, 450002, Henan, People's Republic of China
| | - Hui Huang
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Yawei Zhang
- Department of Environment Health Science, Yale University School of Public Health, New Haven, CT, USA
| | - Qihong Deng
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
- School of Energy Science and Engineering, Xiangya School of Public Health, Central South University, Changsha, 410083, Hunan, People's Republic of China
| | - Lifang Jiang
- National Health Commission Key Laboratory of Birth Defects Prevention, Zhengzhou, 450002, Henan, People's Republic of China.
- Key Laboratory of Population Defects Prevention, Henan Provincial Research, Zhengzhou, 450002, Henan, People's Republic of China.
- Henan Institute of Reproduction Health Science and Technology, Zhengzhou, 450002, Henan, People's Republic of China.
| | - Yue Ba
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
- Yellow River Institute for Ecological Protection & Regional Coordinated Development, School of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
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Michels KA, Mendola P, Schliep KC, Yeung EH, Ye A, Dunietz GL, Wactawski-Wende J, Kim K, Freeman JR, Schisterman EF, Mumford SL. The influences of sleep duration, chronotype, and nightwork on the ovarian cycle. Chronobiol Int 2019; 37:260-271. [PMID: 31778080 DOI: 10.1080/07420528.2019.1694938] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Despite research indicating that sleep disorders influence reproductive health, the effects of sleep on reproductive hormone concentrations are poorly characterized. We prospectively followed 259 regularly menstruating women across one to two menstrual cycles (the BioCycle Study, 2005-2007), measuring fasting serum hormone concentrations up to eight times per cycle. Women provided information about daily sleep in diaries and chronotype and night/shift work on a baseline questionnaire. We evaluated percent differences in mean hormone concentrations, the magnitude of shifts in the timing and amplitude of hormone peaks, and the risk for sporadic anovulation associated with self-reported sleep patterns and night/shift work. We estimated chronotype scores - categorizing women below and above the interquartile range (IQR) as "morning" and "evening" chronotypes, respectively. For every hour increase in daily sleep duration, mean estradiol concentrations increased by 3.9% (95% confidence interval [CI] 2.0, 5.9%) and luteal phase progesterone by 9.4% (CI 4.0, 15.2%). Receiving less than 7 hours of sleep per day was associated with slightly earlier rises in peak levels for several hormones. Women reporting night/shift work (n = 77) had lower testosterone relative to women employed without night/shift work (percent difference: -9.9%, CI -18.4, -0.4%). Women with morning chronotypes (n = 47) had earlier rises in estradiol during their cycles and potentially an earlier rise in luteinizing hormone. Compared to those who had intermediate chronotypes, women with evening chronotypes (n = 42) had a later luteinizing hormone peak of borderline statistical significance. A reduced risk for sporadic anovulation was suggested, but imprecise, for increasing hours of daily sleep leading up to ovulation (risk ratio 0.79, CI 0.59, 1.06), while an imprecise increased risk was observed for women with morning chronotypes (risk ratio 2.50, CI 0.93, 6.77). Sleep-related hormonal changes may not greatly alter ovarian function in healthy women, but have the potential to influence gynecologic health.
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Affiliation(s)
- Kara A Michels
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Pauline Mendola
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Karen C Schliep
- Department of Family and Preventive Medicine, Division of Public Health, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Edwina H Yeung
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Aijun Ye
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Galit L Dunietz
- Division of Sleep Medicine, Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, New york, USA
| | - Keewan Kim
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Joshua R Freeman
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Enrique F Schisterman
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Sunni L Mumford
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
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Jukic AMZ, Wilcox AJ, McConnaughey DR, Weinberg CR, Steiner AZ. 25-Hydroxyvitamin D and Long Menstrual Cycles in a Prospective Cohort Study. Epidemiology 2018; 29:388-396. [PMID: 29337846 PMCID: PMC5882585 DOI: 10.1097/ede.0000000000000804] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Vitamin D insufficiency is associated with subfertility and prolonged estrus cycles in animals, but humans have not been well studied. METHODS A prospective time-to-pregnancy study, Time to Conceive (2010-2015), collected up to 4 months of daily diary data. Participants were healthy, late reproductive-aged women in North Carolina who were attempting pregnancy. We examined menstrual cycle length as a continuous variable and in categories: long (35+ days) and short (≤25 days). Follicular phase length and luteal phase length were categorized as long (18+ days) or short (≤10 days). We estimated associations between those lengths and serum 25-hydroxyvitamin D (25[OH]D) using linear mixed models and marginal models. RESULTS There were 1,278 menstrual cycles from 446 women of whom 5% were vitamin D deficient (25[OH]D, <20 ng/ml), 69% were between 20 and 39 ng/ml, and 26% were 40 ng/ml or higher. There was a dose-response association between vitamin D levels and cycle length. Compared with the highest 25(OH)D level (≥40 ng/ml), 25(OH)D deficiency was associated with almost three times the odds of long cycles (adjusted odds ratio [aOR] = 2.8 [95% confidence interval (CI) = 1.0, 7.5]). The aOR was 1.9 (1.1, 3.5) for 20 to <30 ng/ml. The probability of a long follicular phase and the probability of a short luteal phase both increased with decreasing 25(OH)D. CONCLUSIONS Lower levels of 25(OH)D are associated with longer follicular phase and an overall longer menstrual cycle. Our results are consistent with other evidence supporting vitamin D's role in the reproductive axis, which may have broader implications for reproductive success.
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Affiliation(s)
- Anne Marie Z. Jukic
- Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, One Church St, 6 floor, New Haven, CT, 06510
| | - Allen J. Wilcox
- Epidemiology Branch, National Institute of Environmental Health Sciences, PO Box 12233, Research Triangle Park, NC 27709
| | | | - Clarice R. Weinberg
- Biostatistics Branch, National Institute of Environmental Health Sciences, PO Box 12233, Research Triangle Park, NC 27709
| | - Anne Z. Steiner
- Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, NC
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