Age at Menarche and Asthma Onset Among US Girls and Women: Findings from NHANES, 2001-2018

Age at Menarche and Asthma Onset Among US Girls and Women: Findings from NHANES, 2001-2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Age at Menarche and Asthma Onset Among US Girls and Women: Findings from NHANES, 2001-2018 Li Cai, Lan Qiu, Yaqi Wang, Li Wu, Xiaojie Wu, Ruijun Xu, Yuewei Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-910534/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Findings on the association between early menarche and asthma onset remain inconsistent and the evidence in the US is lacking. Furthermore, there was no clear separation of childhood- and adult-onset asthma in previous studies. Therefore, we aim at quantitatively estimating the association of age at menarche with risk of childhood- and adult-onset asthma separately in US girls and women. Methods: We conducted a retrospective cohort study of 24,282 US girls and women aged less than 80 years by using continuous NHANES data in 2001-2018. Weighted Cox proportional-hazards regression models with censoring ages of 19 and 79 were used to separately estimate hazard ratios of childhood- and adult-onset asthma associated with age at menarche. Results: Each one-year increase of age at menarche was significantly associated with a 17% (HR [95%CI]: 0.83 [0.77, 0.90]) decrease in the risk of childhood-onset asthma. Compared with age at menarche of 12-14, we observed a 60% (HR [95%CI]: 1.60 [1.22, 2.09]) increased risk of childhood-onset asthma for early menarche (age at menarche <12 years) and 41% (HR [95%CI]: 0.59 [0.32, 1.08]) decreased risk for late menarche (age at menarche ≥15 years). Race, family income, education and family history of asthma did not modify these associations. No significant association between age at menarche and adult-onset asthma. Conclusions: In this US nationally representative study, we found that early menarche was associated with increased risk of childhood-onset asthma, but not adult-onset asthma. These findings help demonstrate early menarche may be a risk factor for childhood-onset asthma in US, indicating timely and effective management of special individuals with early menarche for preventing asthma. Pulmonology adult-onset asthma childhood-onset asthma menarche National Health and Nutrition Examination Survey US population Figures Figure 1 Figure 2 Background Asthma is a major public health concern in the US, costing about $ 80 billion for asthma-related mortality and medical usage in 2013. 1 Although numbers of risk factors such as genetic susceptibility 2 , 3 , environment tobacco smoke, 4 , 5 air pollution, 6 diet and obesity 7 , 8 have been explored and asthma control strategies have been applied, the prevalence of asthma has been increased in the US between 2001-2010. 9 Sex differences in asthma prevalence that switch from male to female predominance during adolescence and adulthood 10 suggest effect of puberty on asthma incidence. Compared with men, women are more likely to suffer from asthma after puberty. Age at menarche is regarded as a convenient marker for the timing of puberty in girls. Given that the increasing prevalence of asthma 11 is coincided with declining trends in age at menarche, 12 – 14 several studies have investigated the effect of age at menarche on asthma. However, the results remain inconsistent. For example, the positive association between early menarche and risk of asthma was observed in women from UK, Poland, and Canada, 15 – 19 but not for those from Swiss and Germany. 18 , 20 , 21 To date, there was no evidence for the effect of early menarche on asthma among US general population yet, except for one study conducted in non-Hispanic and well-educated pregnant women. 22 Furthermore, although all previous studies focused on asthma onset, few clearly separated patients into childhood- and adult-onset asthma. 22 Due to the differences in the prevalence, physiopathological mechanisms and clinical characteristics between childhood- and adult-onset asthma, 23 , 24 it is necessary to clearly separate the two types of asthma when identifying the effects of potential risk factors for asthma onset. Here, we used data from the National Health and Nutrition Examination Survey (NHANES), a nationally representative sample of the US population, to quantitatively estimate the associations of age at menarche with risk of childhood- and adult-onset asthma separately. Effect modifications of race, income and family history of asthma on the associations was further examined. Methods Data sources and study population The continuous NHANES is a cross-sectional survey designed to assess the health and nutritional status of children and adults in the US. It included a series of nationally representative interviews and health examinations through cycles of 2-year intervals since 1999. In each cycle, a sample representative of the civilian noninstitutionalized resident population of the US was selected using a complex, stratified, multistage probability cluster sampling design. Due to lacking information on age at asthma among participants aged ≥20 in cycle 1999-2000, we included nine cycles between 2001-2018 in this analysis. Exposure and outcome In this study, we defined age at menarche as the exposure, and defined asthma onset as the outcome. Information on menarche and asthma was obtained based on self-reported responses to specific questions. Participants were asked for age at menarche by the question “ How old were you when you had your first menstrual period? ”. Information on asthma onset was collected by the question “ Has a doctor or other health professional ever told you that you have asthma? ” . Participants with positive answers were further asked “ How old were you when you were first told you had asthma?” to obtain age at asthma onset . Childhood- and adult-onset asthma were defined as age at asthma onset <20, and ≥20 respectively. Covariates Information on demographic variables such as age group (<20, 20-39, 40-59, and ≥60), race (Mexican American and other Hispanic, Non-Hispanic white, Non-Hispanic black, and other), and ratio of family income to poverty (<1 and ≥1) were collected according to self-reported responses to questionnaires. Family history of asthma were defined as close relative had asthma by the question “ Including living and deceased, were any of close biological that is, blood relatives including father, mother, sisters or brothers, ever told by a health professional that they had asthma? ”. Body mass index (BMI) was calculated according to height and weight, which were measured in a mobile examination center using standardized techniques and equipment. All missing responses in covariates were classified into “Unknown” group in the analysis. Statistical analysis Accounting for differential probabilities of selection and the complex sample design, we used the survey design variables including masked variance pseudo-PSU and pseudo-stratum to adjust the standard errors. We constructed sample weights by combining nine-year cycles of the continuous NHANES from 2001-2002 to 2017-2018 to account for unequal probabilities of selection and nonresponse. Participants were divided into three groups including early menarche, normal and late menarche by age at menarche of <12, 12-14 and ≥15 years. Nelson-Aalen analysis were used to estimate the cumulative-hazard rates of the three groups. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional-hazards regression models to estimate the associations between age at menarche and risk of asthma. Two models were performed to test the reliability and stability of the results. The first model included age at menarche alone and used age as the timescale without adjustment (Model 1), while the second was adjusted for race, income, height, and family history of asthma (Model 2). Meanwhile, we fitted models with different censoring age to identify the associations of age at menarche with childhood- and adult-onset asthma separately. To estimate the risk of childhood-onset asthma, we used models with censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics, for adult-onset asthma, we excluded those who suffered from asthma before 20 years old (N=560), and then fitted models with censoring age at 79 years. We estimated the HRs associated with each one-year increase in age at menarche by including age at menarche as a continuous variable in the models. To examine the shape of the exposure-response association, we further conducted categorical analyses by dividing age at menarche into three categories including early (age at menarche <12 years), normal (age at menarche during 12-14 years), and late menarche (age at menarche ≥15 years), and used normal age at menarche as the reference category. Stratified analyses were conducted to investigate whether any of covariates can modify the associations in separate Cox proportional-hazards regression models, with exclusion of the stratification variable. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC) and R (version 3.6.0). Results The analysis of the 2001-2018 data was from 42,540 girls and women who aged less than 80 years and completed both the interview and examination. The unweighted sample sizes for the selection process of the participants in this study were summarized in Figure 1. After excluded 18,258 participants lacking information on menarche or asthma, aged at menarche of 20 or more, or aged at menarche after asthma onset, there were 24,282 examined samples extracted from the nine-cycle NHANES. The sample size for different age at menarche by age group, race, ratio of family income to poverty, and family history of asthma are shown in Table 1. The included participants were aged between 12 to 79 years, and 24.5% were reported as early menarche. There were 9.0% participants (unweighted) suffering from asthma after menarche, including 560 childhood-onset asthma (2.3%) and 1623 adult-onset asthma (6.7%). Asthma prevalence by category of age at menarche was 10.7%, 8.5%, and 8.1% for early, normal and late menarche, respectively, while the mean (SD) of age at asthma onset was 30.5 (16.5), 34.7 (16.2), and 39.0 (16.3) years for early, normal, and late menarche, respectively. Early menarche has the highest cumulative-hazard rates than normal or late menarche ( p <0.001) (Shown in Figure 2). Table 2 presents the HRs for risk of both childhood- and adult-onset asthma associated with age at menarche. Analyses adjusting for race, income, height, and family history of asthma revealed that early menarche was significantly associated with increased risk of childhood-onset asthma. Each one-year increase in age at menarche was significantly associated with a 17% (HR [95%CI]: 0.83 [0.77, 0.90]) reduction in risk of childhood-onset asthma. The categorical analyses showed a 60% (HR [95%CI]: 1.60 [1.22, 2.09]) increased risk of childhood asthma for early menarche and 41% (HR [95%CI]: 0.59 [0.32, 1.08]) decreased risk for late menarche, when compared to those who had menarche in normal age (Model 2). However, the inverse associations were not detected for adult-onset asthma (HR [95%CI]: 0.97 [0.94, 1.01]). Similar results were found in unadjusted models (Model 1). Table 3 shows results of the stratified analyses. When compared with normal menarche, we found significant associations of early menarche with increased risk of childhood-onset asthma in all subgroups except for other race (all p values < 0.05). Remarkable decreased risks were observed in other race and participants with family history of asthma (HRs [95%CIs]: 0.04 [0.01, 0.30] and 0.41 [0.20, 0.84] respectively). There was no significant association of early or late menarche with risk of adult-onset asthma (all p values > 0.05). None of the race, ratio of family income to poverty, or family history of asthma modified the association between age at menarche and risk of childhood- or adult-onset asthma (all p values for effect modification > 0.05). Discussion In this large sample of the US population, we quantitatively assessed the exposure-response association of age at menarche with risk of childhood- and adult-onset asthma separately. A novel effect of early menarche was only observed on childhood-onset asthma. Each one-year increase in age at menarche was associated with 17% decrease in risk of childhood asthma. There was about 60% increased risk of childhood-onset asthma for early menarche and 41% decreased risk for late menarche when compared to those with normal menarche. None of race, family income, or family history of asthma could modify the associations. The link between age at menarche and asthma onset appears to be equivocal. Studies from Germany and Swiss did not observe any effect of menarche on asthma among young populations 21, 25 . In contrast, a 60%, 108% and 134% increase in risk of asthma onset were reported in British, US and Canadian girls who had early menarche, respectively. 16, 18, 19 Notably, the study from British reported that the girls with early menarche had more asthma at all ages, but the association reached statistical significance only among girls age 11 years at the time of follow-up. 18 Similar results were also observed in a Sweden study of 2492 adults aged 18-60 years, 20 but inconsistent with the findings from a recently published study which included 0.24 million women aged 40-69 years based on UK biobank data and reported 8% increase in the risk of asthma for early menarche and 8% decrease for late menarche by using mendelian randomization. 15 One possible reason for the inconsistent results in these studies might be the different ages at menarche used as the reference category (including age of 12-13, 18, 26 12-14, 15 >12, 16 ≥12, 20, 22 and 12.66 19 years). A meta-analysis helped solve the problem by combining the findings from of seven cohort studies with consistent definition of early menarche as age at menarche>12 years. Results of the meta-analysis study showed a 37% increase in risk of asthma for early menarche when comparing groups with late menarche in women aged from 7 to 57 years. 27 Our findings confirmed and extended the adverse effect of early menarche on asthma onset in US general population. By further distinguishing the childhood- and adult-onset asthma in our study, we found the novel effect of early menarche only on childhood asthma rather than adult-onset asthma. Although there was no guideline for clear distinction between childhood and adult-onset asthma, several obvious differences such as symptoms and sensitivity to allergens were observed. 28 The results from our study indicate potential differences in risk factors and pathogenesis of the two types of asthma. The underlying mechanisms for the early menarche related asthma is still unclear. Menarche is an indicator of pubertal onset for women and early menarche is generally considered to be a sign of precocious puberty, companying with changes of sex hormone levels. A recent nationwide study of US adults reported the association between sex hormone levels and the risk of asthma, 29 providing a possible reason for increased risk of asthma onset among participants with early menarche. Besides, other risk factors associated with precocious puberty such as obesity, depression, anxiety, and psychosomatic symptoms 30, 31 have been demonstrated to participate in activating inflammatory mediators, 32 which have been regarded as important role on asthma development. 27, 33, 34 Our results have important public health implication. Asthma is one of the leading chronic diseases, affecting 339.4 million people and contributing to 420,000 deaths globally in 2016. 35, 36 It was estimated that there were about 6.2 million children under the age of 18 with asthma. 37 The present study confirms and extends previous research by quantifying the effect of age at menarche on the risks of childhood asthma, suggesting early menarche may be a risk factor for childhood-onset asthma in US. Timely and effective management of individuals with early menarche should be a part of the prevention for asthma. There are several strengths in this study. To our knowledge, this is the first representative study to quantitatively estimate the association of age at menarche with asthma onset in a general population of US girls and women, covering all races in the US and those aged from 12 to 79 years. Furthermore, we identified childhood- and adult-onset asthma according to age at asthma onset, accounting for the effect of asthma phenotypes on the association. 38 In addition, most previous studies used logistic regression models to assess the associations, 18-20, 22, 39, 40 ignoring the effect of the event time. Due to the potential impact of age at menarche upon the time asthma takes to happen, it seems to be more appropriate to account for time scales in the analyses. Therefore, we performed Cox proportional-hazards regression models with age as the timescale to study the age at menarche that are significantly associated with the timing of the asthma onset. Limitations The main limitation of this study is that the definitions of age at menarche and asthma were based on self-report rather than medical records, which might cause recall bias. Continuous available examination data or prospective study design should be considered to help increase the reliability in the further studies. Conclusions In summary, this study provides a comprehensive picture of association of age at menarche with childhood- and adult-onset asthma among the US girls and women. The observed linear association between age at menarche and risk of childhood-onset asthma provided evidence for the detrimental effect of precocious puberty on respiratory health during childhood and adolescence. These findings emphasize the needs and importance of precocious interventions for prevention of asthma, especially during childhood and adolescence. Abbreviations NHANES: National Health and Nutrition Examination Survey NCHS: National Center for Health Statistics BMI: Body mass index HRs: Hazard ratios CIs: confidence intervals Declarations Ethics approval and consent to participate NHANES was approved by the National Center for Health Statistics (NCHS) research ethics review board (Protocol #98-12, #2005-06, #2011-17, and #2018-01), and all the adult participants enrolled had written consent. Consent for publication Not applicable. Availability of data and materials The datasets generated and analyzed during the current study are available at NHANES official website (https://wwwn.cdc.gov/nchs/nhanes/Default.aspx). Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of China (grant number 81803189). The funders had no role in the design and conduct of the study, or in collection, management, analysis, and interpretation of the data, or in preparation, review, or approval of the manuscript, or in decision to submit the manuscript for publication. Authors' contributions Y.Z. and Y.L. supervised the entire study, including procedures, conception, design, and completion. L.C. were major contributors in data analysis and writing the manuscript. L.C., L.Q., Y.W., L.W., X.W., and R.X. participated in the interpretation of the data and in revisions to the article. All authors read and approved the final manuscript. Acknowledgements Not applicable References Nurmagambetov T, Kuwahara R, Garbe P. The Economic Burden of Asthma in the United States, 2008-2013. Ann Am Thorac Soc. 2018,15(3):348-356. Bleecker ER, Postma DS, Meyers DA. Evidence for multiple genetic susceptibility loci for asthma. Am J Respir Crit Care Med. 1997,156(4 Pt 2):S113-6. Postma DS, Bleecker ER, Amelung PJ, Holroyd KJ, Xu J, Panhuysen CI, et al. Genetic susceptibility to asthma--bronchial hyperresponsiveness coinherited with a major gene for atopy. N Engl J Med. 1995,333(14):894-900. Hedman L, Bjerg A, Sundberg S, Forsberg B, Rönmark E. Both environmental tobacco smoke and personal smoking is related to asthma and wheeze in teenagers. Thorax. 2011,66(1):20-5. Lajunen K, Kalliola S, Kotaniemi-Syrjänen A, Malmberg LP, Pelkonen AS, Mäkelä MJ. Environmental Tobacco Smoke Affects Lung Function of Preschoolers with Asthma Even after a Decade. Am J Respir Crit Care Med. 2019,199(4):534-536. Liu Y, Pan J, Zhang H, Shi C, Li G, Peng Z, et al. Short-Term Exposure to Ambient Air Pollution and Asthma Mortality. Am J Respir Crit Care Med. 2019,200(1):24-32. Xu S, Gilliland FD, Conti DV. Elucidation of causal direction between asthma and obesity: a bi-directional Mendelian randomization study. Int J Epidemiol. 2019,48(3):899-907. Peters U, Dixon AE, Forno E. Obesity and asthma. J Allergy Clin Immunol. 2018,141(4):1169-1179. Akinbami LJ, Moorman JE, Simon AE, Schoendorf KC. Trends in racial disparities for asthma outcomes among children 0 to 17 years, 2001-2010. J Allergy Clin Immunol. 2014,134(3):547-553.e5. Vink NM, Postma DS, Schouten JP, Rosmalen JG, Boezen HM. Gender differences in asthma development and remission during transition through puberty: the TRacking Adolescents' Individual Lives Survey (TRAILS) study. J Allergy Clin Immunol. 2010,126(3):498-504.e1-6. Global Asthma Network. The Global Asthma Report 2018. http://globalasthmareport.org/. Accessed 30 Dec 2020. Anderson SE, Must A. Interpreting the continued decline in the average age at menarche: results from two nationally representative surveys of U.S. girls studied 10 years apart. J Pediatr. 2005,147(6):753-60. Cabanes A, Ascunce N, Vidal E, Ederra M, Barcos A, Erdozain N, et al. Decline in age at menarche among Spanish women born from 1925 to 1962. BMC Public Health. 2009,9:449. Tryggvadóttir L, Tulinius H, Lárusdóttir M. A decline and a halt in mean age at menarche in Iceland. Ann Hum Biol. 1994,21(2):179-86. Minelli C, van der Plaat DA, Leynaert B, Granell R, Amaral AFS, Pereira M, et al. Age at puberty and risk of asthma: A Mendelian randomisation study. PLoS Med. 2018,15(8):e1002634. Salam MT, Wenten M, Gilliland FD. Endogenous and exogenous sex steroid hormones and asthma and wheeze in young women. J Allergy Clin Immunol. 2006,117(5):1001-7. Drosdzol A, Skrzypulec V, Wilk K, Rachel M. The influence of bronchial asthma on menstrual cycle. J Physiol Pharmacol. 2007,58 Suppl 5(Pt 1):165-73. Gnatiuc L, Kato B, Matheson MC, Newson RB, Jarvis DL. The association of asthma with BMI and menarche in the 1958 British Birth Cohort. J Asthma. 2013,50(7):751-8. Al-Sahab B, Hamadeh MJ, Ardern CI, Tamim H. Early menarche predicts incidence of asthma in early adulthood. Am J Epidemiol. 2011,173(1):64-70. Hansen S, Probst-Hensch N, Bettschart R, Pons M, Leynaert B, Gómez Real F, et al. Early menarche and new onset of asthma: Results from the SAPALDIA cohort study. Maturitas. 2017,101:57-63. Wei J, Gerlich J, Genuneit J, Nowak D, Vogelberg C, von Mutius E, et al. Hormonal factors and incident asthma and allergic rhinitis during puberty in girls. Ann Allergy Asthma Immunol. 2015,115(1):21-27.e2. Fida NG, Williams MA, Enquobahrie DA. Association of Age at Menarche and Menstrual Characteristics with Adult Onset Asthma among Reproductive Age Women. Reprod Syst Sex Disord. 2012,1(3):111. Moorman JE, Akinbami LJ, Bailey CM, Zahran HS, King ME, Johnson CA, et al. National surveillance of asthma: United States, 2001-2010. Vital Health Stat 3. 2012,(35):1-58. Jenkins HA, Cherniack R, Szefler SJ, Covar R, Gelfand EW, Spahn JD. A comparison of the clinical characteristics of children and adults with severe asthma. Chest. 2003,124(4):1318-24. Protudjer JL, Lundholm C, Bergström A, Kull I, Almqvist C. Puberty and asthma in a cohort of Swedish children. Ann Allergy Asthma Immunol. 2014,112(1):78-9. Matheson MC, Burgess JA, Lau MY, Lowe AJ, Gurrin LC, Hopper JL, et al. Hormonal contraception increases risk of asthma among obese but decreases it among nonobese subjects: a prospective, population-based cohort study. ERJ Open Res. 2015,1(2):00026-2015. Lieberoth S, Gade EJ, Brok J, Backer V, Thomsen SF. Age at menarche and risk of asthma: systematic review and meta-analysis. J Asthma. 2014,51(6):559-65. Moore WC, Meyers DA, Wenzel SE, Teague WG, Li H, Li X, et al. Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program. Am J Respir Crit Care Med. 2010,181(4):315-23. Han YY, Forno E, Celedón JC. Sex Steroid Hormones and Asthma in a Nationwide Study of U.S. Adults. Am J Respir Crit Care Med. 2020,201(2):158-166. Gill D, Brewer CF, Del Greco M F, Sivakumaran P, Bowden J, Sheehan NA, et al. Age at menarche and adult body mass index: a Mendelian randomization study. Int J Obes (Lond). 2018,42(9):1574-1581. Patton GC, Hibbert ME, Carlin J, Shao Q, Rosier M, Caust J, et al. Menarche and the onset of depression and anxiety in Victoria, Australia. J Epidemiol Community Health. 1996,50(6):661-6. Scott HA, Gibson PG, Garg ML, Upham JW, Wood LG. Sex hormones and systemic inflammation are modulators of the obese-asthma phenotype. Allergy. 2016,71(7):1037-47. Lange P, Parner J, Prescott E, Ulrik CS, Vestbo J. Exogenous female sex steroid hormones and risk of asthma and asthma-like symptoms: a cross sectional study of the general population. Thorax. 2001,56(8):613-6. McCleary N, Nwaru BI, Nurmatov UB, Critchley H, Sheikh A. Endogenous and exogenous sex steroid hormones in asthma and allergy in females: A systematic review and meta-analysis. J Allergy Clin Immunol. 2018,141(4):1510-1513.e8. GBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017,390(10100):1211-1259. https://doi.org/10.1016/S0140-6736(17)32154-2. GBD 2016 Causes of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017,390(10100):1151-1210.https://doi.org/10.1016/S0140-6736(17)32152-9. Zahran HS, Bailey CM, Damon SA, Garbe PL, Breysse PN. Vital Signs: Asthma in Children - United States, 2001-2016. MMWR Morb Mortal Wkly Rep. 2018,67(5):149-155. Tan DJ, Walters EH, Perret JL, Lodge CJ, Lowe AJ, Matheson MC, et al. Age-of-asthma onset as a determinant of different asthma phenotypes in adults: a systematic review and meta-analysis of the literature. Expert Rev Respir Med. 2015,9(1):109-23. Varraso R, Siroux V, Maccario J, Pin I, Kauffmann F, Epidemiological Study on the Genetics and Environment of Asthma. Asthma severity is associated with body mass index and early menarche in women. Am J Respir Crit Care Med. 2005,171(4):334-9. Macsali F, Real FG, Plana E, Sunyer J, Anto J, Dratva J, et al. Early age at menarche, lung function, and adult asthma. Am J Respir Crit Care Med. 2011,183(1):8-14. Tables Table 1. Unweight Sample Sizes for US population from the NHANES, 2001-2018 (N=24,282). Variable No. (%) of participants Overall Age at menarche, year Early menarche (<12 years) Normal menarche (12-14 years) Late menarche (≥15 years) No. of participants 24,282 5937 15,378 2967 Age group, year <20 5240 (21.6) 1809 (30.5) 3264 (21.2) 167 (5.6) 20-39 6732 (27.7) 1636 (27.6) 4304 (28.0) 792 (26.7) 40-59 6654 (27.4) 1425 (24.0) 4205 (27.3) 1024 (34.5) ≥60 5656 (23.3) 1067 (18.0) 3605 (23.4) 984 (33.2) Race Mexican American and other Hispanic 7080 (29.2) 1964 (33.1) 4305 (28.0) 811 (27.3) Non-Hispanic white 9400 (38.7) 2000 (33.7) 6347 (41.3) 1053 (35.5) Non-Hispanic black 5517 (22.7) 1535 (25.9) 3286 (21.4) 696 (23.5) Other 2285 (9.4) 438 (7.4) 1440 (9.4) 407 (13.7) Ratio of family income to poverty <1 5388 (22.2) 1421 (23.9) 3287 (21.4) 680 (22.9) ≥1 17045 (70.2) 4067 (68.5) 10925 (71.0) 2053 (69.2) Unknown 1849 (7.6) 449 (7.6) 1166 (7.6) 234 (7.9) Family history of asthma Yes 5043 (20.8) 1378 (23.2) 3078 (20.0) 587 (19.8) No 16,307 (67.2) 3605 (60.7) 10,460 (68.0) 2242 (75.6) Unknown 2932 (12.1) 954 (16.1) 1840 (12.0) 138 (4.7) Asthma Childhood-onset asthma* 560 (2.3) 234 (3.9) 301 (2.0) 25 (0.8) Adult-onset asthma † 1623 (6.7) 401 (6.8) 1008 (6.6) 214 (7.2) No asthma 22,099 (91.0) 5302 (89.3) 14,069 (91.5) 2728 (91.9) *Childhood-onset asthma was using models with censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics † Adult-onset asthma was using models with censoring age at 79 years, after excluding those suffered from asthma before 20. Table 2. Hazard Ratios for Childhood- and Adult-onset Asthma Associated with Age at Menarche in US girls and Women. Type of asthma Model Hazard ratios (95%CI) p value for trend † Each one-year old increase * Age at menarche, years Early menarche (<12 years) Normal menarche (12-14 years) Late menarche (≥15 years) Childhood-onset asthma ‡ (N=24,282) Model 1 ll 0.81 (0.75, 0.89) 1.67 (1.28, 2.19) 1 (ref) 0.57 (0.31, 1.05) <0.0001 Model 2** 0.83 (0.77, 0.90) 1.60 (1.22, 2.09) 1 (ref) 0.59 (0.32, 1.08) <0.0001 Adult-onset asthma § (N=23,722) Model 1 ll 0.97 (0.94, 1.00) 1.07 (0.92, 1.24) 1 (ref) 0.87 (0.71, 1.06) 0.06 Model 2 ** 0.97 (0.94, 1.01) 1.04 (0.90, 1.21) 1 (ref) 0.86 (0.70, 1.04) 0.10 *Estimated changes for the relationship of age at menarche with risk of adult asthma was conducted by continuous analyses. † p values for trend of the coefficients in categorical analyses are the p values for the estimated changes by the age at menarche as continuous variable. ‡ Childhood-onset asthma was using models with censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics § Adult-onset asthma was using models with censoring age at 79 years, after excluding those suffered from asthma before 20. ll Model 1 included only age at menarche. **Model 2 were further adjusted for race, income, height, and family history of asthma. Table 3. Hazard Ratios for Childhood- and Adult-onset Asthma Associated with Age at Menarche by Stratified Analysis. Type of asthma Variates Age at menarche, year * p value for effect modification Early menarche (<12 years) Normal menarche (12-14 years) Late menarche (≥15 years) Childhood-onset asthma † (N=24,282) Race 0.71 Mexican American and other Hispanic 2.05 (1.17, 3.61) 1 (ref) 0.93 (0.39, 2.21) Non-Hispanic white 1.59 (1.13, 2.24) 1 (ref) 0.65 (0.31, 1.37) Non-Hispanic black 1.47 (1.07, 2.03) 1 (ref) 0.48 (0.18, 1.25) Other 1.27 (0.54, 2.95) 1 (ref) 0.04 (0.01, 0.30) Ratio of family income to poverty 0.99 <1 1.71 (1.10, 2.65) 1 (ref) 0.47 (0.20, 1.10) ≥1 1.60 (1.17, 2.19) 1 (ref) 0.66 (0.31, 1.41) Family history of asthma 0.54 Yes 1.64 (1.08, 2.49) 1 (ref) 0.41 (0.20, 0.84) No 1.52 (1.04, 2.22) 1 (ref) 0.80 (0.36, 1.80) Adult-onset asthma ‡ (N=23,722) Race 0.47 Mexican American and other Hispanic 0.84 (0.63, 1.11) 1 (ref) 0.81 (0.56, 1.17) Non-Hispanic white 1.03 (0.86, 1.24) 1 (ref) 0.86 (0.67, 1.12) Non-Hispanic black 1.28 (0.98, 1.66) 1 (ref) 1.13 (0.82, 1.57) Other 1.15 (0.70, 1.86) 1 (ref) 0.63 (0.35, 1.15) Ratio of family income to poverty 0.90 <1 1.14 (0.81, 1.62) 1 (ref) 1.32 (0.97, 1.80) ≥1 1.03 (0.86, 1.23) 1 (ref) 0.81 (0.64, 1.03) Family history of asthma 0.67 Yes 1.10 (0.88, 1.38) 1 (ref) 0.81 (0.56, 1.16) No 1.01 (0.82, 1.25) 1 (ref) 0.88 (0.69, 1.13) *All models were adjusted for race, income, height, and family history of asthma, with excluding the stratification variable. Interaction testing was performed by including an interaction term of each covariate and age at menarche. † Childhood onset asthma was using models with censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics. ‡ Adult-onset asthma was using models with censoring age at 79 years, after excluding those suffered from asthma before 20. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-910534","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":53428647,"identity":"9856bdc0-1ceb-4b22-af0a-f1635d483042","order_by":0,"name":"Li Cai","email":"","orcid":"","institution":"Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Cai","suffix":""},{"id":53428648,"identity":"b4ddc35a-f7fd-4de2-931a-c03b6b626d63","order_by":1,"name":"Lan Qiu","email":"","orcid":"","institution":"Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lan","middleName":"","lastName":"Qiu","suffix":""},{"id":53428649,"identity":"f858663b-0240-4b26-9d95-824c21514b69","order_by":2,"name":"Yaqi Wang","email":"","orcid":"","institution":"Sun Yat-Sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yaqi","middleName":"","lastName":"Wang","suffix":""},{"id":53428650,"identity":"2e1429f6-51f7-4ed5-9723-60f64f2532a6","order_by":3,"name":"Li Wu","email":"","orcid":"","institution":"Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Wu","suffix":""},{"id":53428651,"identity":"e7cc8ec3-6aa3-42b5-9094-c29efdb3dde0","order_by":4,"name":"Xiaojie Wu","email":"","orcid":"","institution":"Wuhan No 1 Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaojie","middleName":"","lastName":"Wu","suffix":""},{"id":53428652,"identity":"96be94ac-da3d-4d2f-950c-972d93038110","order_by":5,"name":"Ruijun Xu","email":"","orcid":"","institution":"Sun Yat-Sen University School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ruijun","middleName":"","lastName":"Xu","suffix":""},{"id":53428653,"identity":"ce62b283-8842-4226-912b-4a4af00069e2","order_by":6,"name":"Yuewei Liu","email":"","orcid":"","institution":"Sun Yat-Sen University School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuewei","middleName":"","lastName":"Liu","suffix":""},{"id":53428654,"identity":"8531e960-7ad1-4b84-88d2-bfb3f80be7c1","order_by":7,"name":"Yun Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYDADAwYGxgdAmoePFC3MBiAtbKRoYZMAMQhqkW8/+/Azb9sde3P2HrPKrzl2MmwMzA8f3cBn+Jl0Y2netmfMlj1nzG7LbksGOozN2DgHr3vSGIBaDrMZ3Mgxuy25jRmohYdNGp8W+f5nzL+BWnhAWoolt9UT1sJwI40NZIsESAvjx22HCWsxuPGMzXLOucMGBmeOFUszbjvOw8ZMwC/y/WnMN96UHbY3ON688ePPbdX2/OzNDx/jdRgQMPFAGcxgBjMB5SDA+AOdMQpGwSgYBaMAGQAAg8BCT0u5Rt8AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3017-4453","institution":"Guangzhou Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Zhou","suffix":""}],"badges":[],"createdAt":"2021-09-16 10:51:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-910534/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-910534/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13930934,"identity":"fddaef08-9752-4855-aba7-7938ef560535","added_by":"auto","created_at":"2021-09-23 22:52:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":257431,"visible":true,"origin":"","legend":" Unweighted sample sizes for the selected process of the study participants in NHANES, 2001-2018.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-910534/v1/589835c1a71b91ac6e14b174.png"},{"id":13930933,"identity":"cdd88422-9943-4a94-b1ba-4dc5e025e584","added_by":"auto","created_at":"2021-09-23 22:52:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":229340,"visible":true,"origin":"","legend":"Cumulative-hazard rates in participants with early menarche (yellow broken line), normal menarche (red broken line) and late menarche (blue broken line) from the National Health and Nutrition Examination Survey, 2001-2018 (N=24,282).","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-910534/v1/d1fd93f86d6050acd1915fdb.png"},{"id":13930940,"identity":"9a0ad6dd-1259-4160-9880-7dbe4e86de3a","added_by":"auto","created_at":"2021-09-23 22:52:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":897167,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-910534/v1/2e30b340-beee-4a87-8b32-ce38e545a86f.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eAge at Menarche and Asthma Onset Among US Girls and Women: Findings from NHANES, 2001-2018\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003e Asthma is a major public health concern in the US, costing about \u003cspan\u003e$\u003c/span\u003e80\u0026nbsp;billion for asthma-related mortality and medical usage in 2013.\u003csup\u003e \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e \u003c/sup\u003e Although numbers of risk factors such as genetic susceptibility \u003csup\u003e \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e \u003c/sup\u003e, environment tobacco smoke,\u003csup\u003e \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e \u003c/sup\u003e air pollution,\u003csup\u003e \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e \u003c/sup\u003e diet and obesity\u003csup\u003e \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e \u003c/sup\u003e have been explored and asthma control strategies have been applied, the prevalence of asthma has been increased in the US between 2001-2010.\u003csup\u003e \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e \u003c/sup\u003e \u003c/p\u003e \u003cp\u003eSex differences in asthma prevalence that switch from male to female predominance during adolescence and adulthood\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e suggest effect of puberty on asthma incidence. Compared with men, women are more likely to suffer from asthma after puberty. Age at menarche is regarded as a convenient marker for the timing of puberty in girls. Given that the increasing prevalence of asthma\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e is coincided with declining trends in age at menarche,\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e several studies have investigated the effect of age at menarche on asthma. However, the results remain inconsistent. For example, the positive association between early menarche and risk of asthma was observed in women from UK, Poland, and Canada,\u003csup\u003e\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e but not for those from Swiss and Germany.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e To date, there was no evidence for the effect of early menarche on asthma among US general population yet, except for one study conducted in non-Hispanic and well-educated pregnant women.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Furthermore, although all previous studies focused on asthma onset, few clearly separated patients into childhood- and adult-onset asthma.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Due to the differences in the prevalence, physiopathological mechanisms and clinical characteristics between childhood- and adult-onset asthma,\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e it is necessary to clearly separate the two types of asthma when identifying the effects of potential risk factors for asthma onset.\u003c/p\u003e \u003cp\u003eHere, we used data from the National Health and Nutrition Examination Survey (NHANES), a nationally representative sample of the US population, to quantitatively estimate the associations of age at menarche with risk of childhood- and adult-onset asthma separately. Effect modifications of race, income and family history of asthma on the associations was further examined.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData sources and study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe continuous NHANES is a cross-sectional survey designed to assess the health and nutritional status of children and adults in the US. It included a series of nationally representative interviews and health examinations through cycles of 2-year intervals since 1999. In each cycle, a sample representative of the civilian noninstitutionalized resident population of the US was selected using a complex, stratified, multistage probability cluster sampling design. Due to lacking information on age at asthma among participants aged\u0026nbsp;\u0026ge;20 in cycle 1999-2000, we included nine cycles between 2001-2018 in this analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure and outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we defined age at menarche as the exposure, and defined asthma onset as the outcome. Information on menarche and asthma was obtained based on self-reported responses to specific questions. Participants were asked for age at menarche by the question \u0026ldquo;\u003cem\u003eHow old were you when you had your first menstrual period?\u003c/em\u003e\u0026rdquo;. Information on asthma onset was collected by the question \u0026ldquo;\u003cem\u003eHas a doctor or other health professional ever told you that you have asthma?\u003c/em\u003e\u003cem\u003e\u0026rdquo;\u003c/em\u003e. Participants with positive answers were further asked \u0026ldquo;\u003cem\u003eHow old were you when you were first told you had asthma?\u0026rdquo;\u003c/em\u003e to obtain age at asthma onset\u003cem\u003e.\u0026nbsp;\u003c/em\u003eChildhood- and adult-onset asthma were defined as age at asthma onset \u0026lt;20, and\u0026nbsp;\u0026ge;20 respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCovariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformation on demographic variables such as age group (\u0026lt;20, 20-39, 40-59, and\u0026nbsp;\u0026ge;60), race (Mexican American and other Hispanic, Non-Hispanic white, Non-Hispanic black, and other), and ratio of family income to poverty (\u0026lt;1 and\u0026nbsp;\u0026ge;1) were collected according to self-reported responses to questionnaires. Family history of asthma were defined as close relative had asthma by the question \u0026ldquo;\u003cem\u003eIncluding living and deceased, were any of close biological that is, blood relatives including father, mother, sisters or brothers, ever told by a health professional that they had asthma?\u003c/em\u003e\u0026rdquo;. Body mass index (BMI) was calculated according to height and weight, which were measured in a mobile examination center using standardized techniques and equipment. All missing responses in covariates were classified into \u0026ldquo;Unknown\u0026rdquo; group in the analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccounting for differential probabilities of selection and the complex sample design, we used the survey design variables including masked variance pseudo-PSU and pseudo-stratum to adjust the standard errors. We constructed sample weights by combining nine-year cycles of the continuous NHANES from 2001-2002 to 2017-2018 to account for unequal probabilities of selection and nonresponse. Participants were divided into three groups including early menarche, normal and late menarche by age at menarche of \u0026lt;12, 12-14 and\u0026nbsp;\u0026ge;15 years. Nelson-Aalen analysis were used to estimate the cumulative-hazard rates of the three groups. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional-hazards regression models\u0026nbsp;to estimate the associations\u0026nbsp;between age at menarche and risk of asthma.\u0026nbsp;Two\u0026nbsp;models were performed to test the reliability and stability of the results. The first model included age at menarche alone and used age as the timescale without adjustment (Model 1), while the second was adjusted for\u0026nbsp;race, income, height, and family history of asthma\u0026nbsp;(Model 2).\u0026nbsp;Meanwhile, we fitted models with different censoring age to identify the associations of age at menarche with childhood- and adult-onset asthma separately. To estimate the risk of childhood-onset asthma, we used models with censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics, for adult-onset asthma, we excluded those who suffered from asthma before 20 years old (N=560), and then fitted models with censoring age at 79 years. We estimated the HRs associated with each one-year increase in age at menarche by including age at menarche as a continuous variable in the models. To examine the shape of the exposure-response association, we further conducted categorical analyses by dividing age at menarche into three categories including early (age at menarche \u0026lt;12 years), normal (age at menarche during 12-14 years), and late menarche (age at menarche\u0026nbsp;\u0026ge;15 years), and used normal age at menarche as the reference category.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStratified analyses were conducted to investigate whether any of covariates can modify the associations in separate Cox proportional-hazards regression models, with exclusion of the stratification variable. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC) and R (version 3.6.0).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe analysis of the 2001-2018 data was from 42,540 girls and women who aged less than 80 years and completed both the interview and examination. The unweighted sample sizes for the selection process of the participants in this study were summarized in Figure 1. After excluded 18,258 participants lacking information on menarche or asthma, aged at menarche of 20 or more, or aged at menarche after asthma onset, there were 24,282 examined samples extracted from the nine-cycle NHANES.\u003c/p\u003e\n\u003cp\u003eThe sample size for different age at menarche by age group, race, ratio of family income to poverty, and family history of asthma are shown in Table 1. The included participants were aged between 12 to 79 years, and 24.5% were reported as early menarche. There were 9.0% participants (unweighted) suffering from asthma after menarche, including 560 childhood-onset asthma (2.3%) and 1623 adult-onset asthma (6.7%). Asthma prevalence by category of age at menarche was 10.7%, 8.5%, and 8.1% for early, normal and late menarche, respectively, while the mean (SD) of age at asthma onset was 30.5 (16.5), 34.7 (16.2), and 39.0 (16.3) years for early, normal, and late menarche, respectively. Early menarche has the highest cumulative-hazard rates than normal or late menarche (\u003cem\u003ep\u003c/em\u003e \u0026lt;0.001) (Shown in Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 presents the HRs for risk of both childhood- and adult-onset asthma associated with age at menarche. Analyses adjusting for race, income, height, and family history of asthma revealed that early menarche was significantly associated with increased risk of childhood-onset asthma. Each one-year increase in age at menarche was significantly associated with a 17% (HR [95%CI]: 0.83 [0.77, 0.90]) reduction in risk of childhood-onset asthma. The categorical analyses showed a 60% (HR [95%CI]: 1.60 [1.22, 2.09]) increased risk of childhood asthma for early menarche and 41% (HR [95%CI]: 0.59 [0.32, 1.08]) decreased risk for late menarche, when compared to those who had menarche in normal age (Model 2). However, the inverse associations were not detected for adult-onset asthma (HR [95%CI]: 0.97 [0.94, 1.01]). Similar results were found in unadjusted models (Model 1).\u003c/p\u003e\n\u003cp\u003eTable 3 shows results of the stratified analyses. When compared with normal menarche, we found significant associations of early menarche with increased risk of childhood-onset asthma in all subgroups except for other race (all \u003cem\u003ep\u003c/em\u003e values \u0026lt; 0.05). Remarkable decreased risks were observed in other race and participants with family history of asthma (HRs [95%CIs]: 0.04 [0.01, 0.30] and 0.41 [0.20, 0.84] respectively). There was no significant association of early or late menarche with risk of adult-onset asthma (all \u003cem\u003ep\u003c/em\u003e values \u0026gt; 0.05). None of the race, ratio of family income to poverty, or family history of asthma modified the association between age at menarche and risk of childhood- or adult-onset asthma (all \u003cem\u003ep\u003c/em\u003e values for effect modification \u0026gt; 0.05).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large sample of the US population, we quantitatively assessed the exposure-response association of age at menarche with risk of childhood- and adult-onset asthma separately. A novel effect of early menarche was only observed on childhood-onset asthma. Each one-year increase in age at menarche was associated with 17% decrease in risk of childhood asthma. There was about 60% increased risk of childhood-onset asthma for early menarche and 41% decreased risk for late menarche when compared to those with normal menarche. None of race, family income, or family history of asthma could modify the associations.\u003c/p\u003e\n\u003cp\u003eThe link between age at menarche and asthma onset appears to be equivocal. Studies from Germany and Swiss did not observe any effect of menarche on asthma among young populations\u0026nbsp;\u003csup\u003e21, 25\u003c/sup\u003e. In contrast, a 60%, 108% and 134% increase in risk of asthma onset were reported in British, US and Canadian girls who had early menarche, respectively.\u003csup\u003e16, 18, 19\u003c/sup\u003e Notably, the study from British reported that the girls with early menarche had more asthma at all ages, but the association reached statistical significance only among girls age 11 years at the time of follow-up.\u003csup\u003e18\u003c/sup\u003e Similar results were also observed in a Sweden study of 2492 adults aged 18-60 years,\u003csup\u003e20\u003c/sup\u003e but inconsistent with the findings from a recently published study which included 0.24 million women aged 40-69 years based on UK biobank data and reported 8% increase in the risk of asthma for early menarche and 8% decrease for late menarche by using mendelian randomization.\u003csup\u003e15\u003c/sup\u003e One possible reason for the inconsistent results in these studies might be the different ages at menarche used as the reference category (including age of 12-13,\u003csup\u003e18, 26\u003c/sup\u003e 12-14,\u003csup\u003e15\u003c/sup\u003e \u0026gt;12,\u003csup\u003e16\u003c/sup\u003e\u0026nbsp; \u0026ge;12,\u003csup\u003e20, 22\u003c/sup\u003e and 12.66\u003csup\u003e19\u003c/sup\u003e years). A meta-analysis helped solve the problem by combining the findings from of seven cohort studies with consistent definition of early menarche as age at menarche\u0026gt;12 years. Results of the meta-analysis study showed a 37% increase in risk of asthma for early menarche when comparing groups with late menarche in women aged from 7 to 57 years.\u003csup\u003e27\u003c/sup\u003e Our findings confirmed and extended the adverse effect of early menarche on asthma onset in US general population. By further distinguishing the childhood- and adult-onset asthma in our study, we found the novel effect of early menarche only on childhood asthma rather than adult-onset asthma. Although there was no guideline for clear distinction between childhood and adult-onset asthma, several obvious differences such as symptoms and sensitivity to allergens were observed.\u003csup\u003e28\u003c/sup\u003e The results from our study indicate potential differences in risk factors and pathogenesis of the two types of asthma.\u003c/p\u003e\n\u003cp\u003eThe underlying mechanisms for the early menarche related asthma is still unclear. Menarche is an indicator of pubertal onset for women and early menarche is generally considered to be a sign of precocious puberty, companying with changes of sex hormone levels. A recent nationwide study of US adults reported the association between sex hormone levels and the risk of asthma,\u003csup\u003e29\u003c/sup\u003e providing a possible reason for increased risk of asthma onset among participants with early menarche. Besides, other risk factors associated with precocious puberty such as obesity, depression, anxiety, and psychosomatic symptoms\u003csup\u003e30, 31\u003c/sup\u003e have been demonstrated to participate in activating inflammatory mediators,\u003csup\u003e32\u003c/sup\u003e which have been regarded as important role on asthma development.\u003csup\u003e27, 33, 34\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur results have important public health implication. Asthma is one of the leading chronic diseases,\u0026nbsp;affecting 339.4 million people\u0026nbsp;and contributing to 420,000 deaths globally in 2016.\u003csup\u003e35, 36\u003c/sup\u003e It was estimated that there were about 6.2 million children under the age of 18 with asthma.\u003csup\u003e37\u003c/sup\u003e The present study confirms and extends previous research by quantifying the effect of age at menarche on the risks of childhood asthma, suggesting early menarche may be a risk factor for childhood-onset asthma in US. Timely and effective management of individuals with early menarche should be a part of the prevention for asthma. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere are several strengths in this study. To our knowledge, this is the first representative study to quantitatively estimate the association of age at menarche with asthma onset in a general population of US girls and women, covering all races in the US and those aged from 12 to 79 years. Furthermore, we identified childhood- and adult-onset asthma according to age at asthma onset, accounting for the effect of asthma phenotypes on the association.\u003csup\u003e38\u003c/sup\u003e In addition, most previous studies used logistic regression models to assess the associations,\u003csup\u003e18-20, 22, 39, 40\u003c/sup\u003e ignoring the effect of the event time. Due to the potential impact of age at menarche upon the time asthma takes to happen, it seems to be more appropriate to account for time scales in the analyses. Therefore, we performed Cox proportional-hazards regression models with age as the timescale to study the age at menarche that are significantly associated with the timing of the asthma onset.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main limitation of this study is that the definitions of age at menarche and asthma were based on self-report rather than medical records, which might cause recall bias. Continuous available examination data or prospective study design should be considered to help increase the reliability in the further studies.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study provides a comprehensive picture of association of age at menarche with childhood- and adult-onset asthma among the US girls and women. The observed linear association between age at menarche and risk of childhood-onset asthma provided evidence for the detrimental effect of precocious puberty on respiratory health during childhood and adolescence. These findings emphasize the needs and importance of precocious interventions for prevention of asthma, especially during childhood and adolescence.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eNHANES:\u0026nbsp;\u003c/strong\u003eNational Health and Nutrition Examination Survey\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNCHS:\u0026nbsp;\u003c/strong\u003eNational Center for Health Statistics\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI:\u0026nbsp;\u003c/strong\u003eBody mass index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHRs:\u0026nbsp;\u003c/strong\u003eHazard ratios\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCIs:\u0026nbsp;\u003c/strong\u003econfidence intervals\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNHANES was approved by the National Center for Health Statistics (NCHS) research ethics review board (Protocol #98-12, #2005-06, #2011-17, and #2018-01), and all the adult participants enrolled had written consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available at NHANES official website (https://wwwn.cdc.gov/nchs/nhanes/Default.aspx).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (grant number 81803189). The funders had no role in the design and conduct of the study, or in collection, management, analysis, and interpretation of the data, or in preparation, review, or approval of the manuscript, or in decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.Z. and Y.L. supervised the entire study, including procedures, conception, design, and completion. L.C. were major contributors in data analysis and writing the manuscript. L.C., L.Q., Y.W., L.W., X.W., and R.X. participated in the interpretation of the data and in revisions to the article. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNurmagambetov T, Kuwahara R, Garbe P. The Economic Burden of Asthma in the United States, 2008-2013. Ann Am Thorac Soc. 2018,15(3):348-356.\u003c/li\u003e\n\u003cli\u003eBleecker ER, Postma DS, Meyers DA. Evidence for multiple genetic susceptibility loci for asthma. Am J Respir Crit Care Med. 1997,156(4 Pt 2):S113-6.\u003c/li\u003e\n\u003cli\u003ePostma DS, Bleecker ER, Amelung PJ, Holroyd KJ, Xu J, Panhuysen CI, et al. Genetic susceptibility to asthma--bronchial hyperresponsiveness coinherited with a major gene for atopy. N Engl J Med. 1995,333(14):894-900.\u003c/li\u003e\n\u003cli\u003eHedman L, Bjerg A, Sundberg S, Forsberg B, R\u0026ouml;nmark E. Both environmental tobacco smoke and personal smoking is related to asthma and wheeze in teenagers. Thorax. 2011,66(1):20-5.\u003c/li\u003e\n\u003cli\u003eLajunen K, Kalliola S, Kotaniemi-Syrj\u0026auml;nen A, Malmberg LP, Pelkonen AS, M\u0026auml;kel\u0026auml; MJ. Environmental Tobacco Smoke Affects Lung Function of Preschoolers with Asthma Even after a Decade. Am J Respir Crit Care Med. 2019,199(4):534-536.\u003c/li\u003e\n\u003cli\u003eLiu Y, Pan J, Zhang H, Shi C, Li G, Peng Z, et al. Short-Term Exposure to Ambient Air Pollution and Asthma Mortality. Am J Respir Crit Care Med. 2019,200(1):24-32.\u003c/li\u003e\n\u003cli\u003eXu S, Gilliland FD, Conti DV. Elucidation of causal direction between asthma and obesity: a bi-directional Mendelian randomization study. Int J Epidemiol. 2019,48(3):899-907.\u003c/li\u003e\n\u003cli\u003ePeters U, Dixon AE, Forno E. Obesity and asthma. J Allergy Clin Immunol. 2018,141(4):1169-1179.\u003c/li\u003e\n\u003cli\u003eAkinbami LJ, Moorman JE, Simon AE, Schoendorf KC. Trends in racial disparities for asthma outcomes among children 0 to 17 years, 2001-2010. J Allergy Clin Immunol. 2014,134(3):547-553.e5.\u003c/li\u003e\n\u003cli\u003eVink NM, Postma DS, Schouten JP, Rosmalen JG, Boezen HM. Gender differences in asthma development and remission during transition through puberty: the TRacking Adolescents\u0026apos; Individual Lives Survey (TRAILS) study. J Allergy Clin Immunol. 2010,126(3):498-504.e1-6.\u003c/li\u003e\n\u003cli\u003eGlobal Asthma Network. The Global Asthma Report 2018. http://globalasthmareport.org/. Accessed 30 Dec 2020. \u003c/li\u003e\n\u003cli\u003eAnderson SE, Must A. Interpreting the continued decline in the average age at menarche: results from two nationally representative surveys of U.S. girls studied 10 years apart. J Pediatr. 2005,147(6):753-60.\u003c/li\u003e\n\u003cli\u003eCabanes A, Ascunce N, Vidal E, Ederra M, Barcos A, Erdozain N, et al. Decline in age at menarche among Spanish women born from 1925 to 1962. BMC Public Health. 2009,9:449.\u003c/li\u003e\n\u003cli\u003eTryggvad\u0026oacute;ttir L, Tulinius H, L\u0026aacute;rusd\u0026oacute;ttir M. A decline and a halt in mean age at menarche in Iceland. Ann Hum Biol. 1994,21(2):179-86.\u003c/li\u003e\n\u003cli\u003eMinelli C, van der Plaat DA, Leynaert B, Granell R, Amaral AFS, Pereira M, et al. Age at puberty and risk of asthma: A Mendelian randomisation study. PLoS Med. 2018,15(8):e1002634.\u003c/li\u003e\n\u003cli\u003eSalam MT, Wenten M, Gilliland FD. Endogenous and exogenous sex steroid hormones and asthma and wheeze in young women. J Allergy Clin Immunol. 2006,117(5):1001-7.\u003c/li\u003e\n\u003cli\u003eDrosdzol A, Skrzypulec V, Wilk K, Rachel M. The influence of bronchial asthma on menstrual cycle. J Physiol Pharmacol. 2007,58 Suppl 5(Pt 1):165-73.\u003c/li\u003e\n\u003cli\u003eGnatiuc L, Kato B, Matheson MC, Newson RB, Jarvis DL. The association of asthma with BMI and menarche in the 1958 British Birth Cohort. J Asthma. 2013,50(7):751-8.\u003c/li\u003e\n\u003cli\u003eAl-Sahab B, Hamadeh MJ, Ardern CI, Tamim H. Early menarche predicts incidence of asthma in early adulthood. Am J Epidemiol. 2011,173(1):64-70.\u003c/li\u003e\n\u003cli\u003eHansen S, Probst-Hensch N, Bettschart R, Pons M, Leynaert B, G\u0026oacute;mez Real F, et al. Early menarche and new onset of asthma: Results from the SAPALDIA cohort study. Maturitas. 2017,101:57-63.\u003c/li\u003e\n\u003cli\u003eWei J, Gerlich J, Genuneit J, Nowak D, Vogelberg C, von Mutius E, et al. Hormonal factors and incident asthma and allergic rhinitis during puberty in girls. Ann Allergy Asthma Immunol. 2015,115(1):21-27.e2.\u003c/li\u003e\n\u003cli\u003eFida NG, Williams MA, Enquobahrie DA. Association of Age at Menarche and Menstrual Characteristics with Adult Onset Asthma among Reproductive Age Women. Reprod Syst Sex Disord. 2012,1(3):111.\u003c/li\u003e\n\u003cli\u003eMoorman JE, Akinbami LJ, Bailey CM, Zahran HS, King ME, Johnson CA, et al. National surveillance of asthma: United States, 2001-2010. Vital Health Stat 3. 2012,(35):1-58.\u003c/li\u003e\n\u003cli\u003eJenkins HA, Cherniack R, Szefler SJ, Covar R, Gelfand EW, Spahn JD. A comparison of the clinical characteristics of children and adults with severe asthma. Chest. 2003,124(4):1318-24.\u003c/li\u003e\n\u003cli\u003eProtudjer JL, Lundholm C, Bergstr\u0026ouml;m A, Kull I, Almqvist C. Puberty and asthma in a cohort of Swedish children. Ann Allergy Asthma Immunol. 2014,112(1):78-9.\u003c/li\u003e\n\u003cli\u003eMatheson MC, Burgess JA, Lau MY, Lowe AJ, Gurrin LC, Hopper JL, et al. Hormonal contraception increases risk of asthma among obese but decreases it among nonobese subjects: a prospective, population-based cohort study. ERJ Open Res. 2015,1(2):00026-2015.\u003c/li\u003e\n\u003cli\u003eLieberoth S, Gade EJ, Brok J, Backer V, Thomsen SF. Age at menarche and risk of asthma: systematic review and meta-analysis. J Asthma. 2014,51(6):559-65.\u003c/li\u003e\n\u003cli\u003eMoore WC, Meyers DA, Wenzel SE, Teague WG, Li H, Li X, et al. Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program. Am J Respir Crit Care Med. 2010,181(4):315-23.\u003c/li\u003e\n\u003cli\u003eHan YY, Forno E, Celed\u0026oacute;n JC. Sex Steroid Hormones and Asthma in a Nationwide Study of U.S. Adults. Am J Respir Crit Care Med. 2020,201(2):158-166.\u003c/li\u003e\n\u003cli\u003eGill D, Brewer CF, Del Greco M F, Sivakumaran P, Bowden J, Sheehan NA, et al. Age at menarche and adult body mass index: a Mendelian randomization study. Int J Obes (Lond). 2018,42(9):1574-1581.\u003c/li\u003e\n\u003cli\u003ePatton GC, Hibbert ME, Carlin J, Shao Q, Rosier M, Caust J, et al. Menarche and the onset of depression and anxiety in Victoria, Australia. J Epidemiol Community Health. 1996,50(6):661-6.\u003c/li\u003e\n\u003cli\u003eScott HA, Gibson PG, Garg ML, Upham JW, Wood LG. Sex hormones and systemic inflammation are modulators of the obese-asthma phenotype. Allergy. 2016,71(7):1037-47.\u003c/li\u003e\n\u003cli\u003eLange P, Parner J, Prescott E, Ulrik CS, Vestbo J. Exogenous female sex steroid hormones and risk of asthma and asthma-like symptoms: a cross sectional study of the general population. Thorax. 2001,56(8):613-6.\u003c/li\u003e\n\u003cli\u003eMcCleary N, Nwaru BI, Nurmatov UB, Critchley H, Sheikh A. Endogenous and exogenous sex steroid hormones in asthma and allergy in females: A systematic review and meta-analysis. J Allergy Clin Immunol. 2018,141(4):1510-1513.e8.\u003c/li\u003e\n\u003cli\u003eGBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017,390(10100):1211-1259. https://doi.org/10.1016/S0140-6736(17)32154-2.\u003c/li\u003e\n\u003cli\u003eGBD 2016 Causes of Death Collaborators. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017,390(10100):1151-1210.https://doi.org/10.1016/S0140-6736(17)32152-9.\u003c/li\u003e\n\u003cli\u003eZahran HS, Bailey CM, Damon SA, Garbe PL, Breysse PN. Vital Signs: Asthma in Children - United States, 2001-2016. MMWR Morb Mortal Wkly Rep. 2018,67(5):149-155.\u003c/li\u003e\n\u003cli\u003eTan DJ, Walters EH, Perret JL, Lodge CJ, Lowe AJ, Matheson MC, et al. Age-of-asthma onset as a determinant of different asthma phenotypes in adults: a systematic review and meta-analysis of the literature. Expert Rev Respir Med. 2015,9(1):109-23.\u003c/li\u003e\n\u003cli\u003eVarraso R, Siroux V, Maccario J, Pin I, Kauffmann F, Epidemiological Study on the Genetics and Environment of Asthma. Asthma severity is associated with body mass index and early menarche in women. Am J Respir Crit Care Med. 2005,171(4):334-9.\u003c/li\u003e\n\u003cli\u003eMacsali F, Real FG, Plana E, Sunyer J, Anto J, Dratva J, et al. Early age at menarche, lung function, and adult asthma. Am J Respir Crit Care Med. 2011,183(1):8-14.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Unweight Sample Sizes for US population from the NHANES, 2001-2018 (N=24,282).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"37.37373737373738%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" width=\"62.62626262626262%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. (%) of participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"20.967741935483872%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"79.03225806451613%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at menarche, year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026lt;12 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.416666666666664%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(12-14 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026ge;15 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eNo. of participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e24,282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e5937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e15,378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e2967\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eAge group, year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003e\u0026lt;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e5240 (21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1809 (30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e3264 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e167 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003e20-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e6732 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1636 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e4304 (28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e792 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 40-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e6654 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1425 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e4205 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e1024 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e5656 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1067 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e3605 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e984 (33.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eMexican American and other Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e7080 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1964 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e4305 (28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e811 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eNon-Hispanic white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e9400 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e2000 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e6347 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e1053 (35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eNon-Hispanic black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e5517 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1535 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e3286 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e696 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e2285 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e438 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e1440 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e407 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eRatio of family income to poverty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e5388 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1421 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e3287 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e680 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003e\u0026ge;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e17045 (70.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e4067 (68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e10925 (71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e2053 (69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1849 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e449 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e1166 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e234 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eFamily history of asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e5043 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e1378 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e3078 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e587 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e16,307 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e3605 (60.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e10,460 (68.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e2242 (75.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e2932 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e954 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e1840 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e138 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eChildhood-onset asthma*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e560 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e234 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e301 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e25 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eAdult-onset asthma\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1623 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e401 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e1008 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e214 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.755102040816325%\"\u003e\n \u003cp\u003eNo asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e22,099 (91.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\"\u003e\n \u003cp\u003e5302 (89.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e14,069 (91.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.306122448979592%\"\u003e\n \u003cp\u003e2728 (91.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Childhood-onset asthma was using models with\u0026nbsp;censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eAdult-onset asthma was using models\u0026nbsp;with censoring age at 79 years, after excluding those suffered from asthma before 20.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eHazard Ratios for Childhood- and Adult-onset Asthma Associated with Age at Menarche in US girls and Women.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"19.387755102040817%\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of asthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"8.16326530612245%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" width=\"61.224489795918366%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard ratios (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"11.224489795918368%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value for trend\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEach one-year old increase\u003c/strong\u003e *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at menarche, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.232558139534884%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026lt;12 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.55813953488372%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(12-14 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.2093023255814%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026ge;15 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.791666666666668%\"\u003e\n \u003cp\u003eChildhood-onset asthma\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(N=24,282)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.625%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.583333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.791666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003eModel 1\u003csup\u003ell\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.625%\"\u003e\n \u003cp\u003e0.81 (0.75, 0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e1.67 (1.28, 2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.583333333333334%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e0.57 (0.31, 1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.791666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003eModel 2**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.625%\"\u003e\n \u003cp\u003e0.83 (0.77, 0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e1.60 (1.22, 2.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.583333333333334%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e0.59 (0.32, 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.791666666666668%\"\u003e\n \u003cp\u003eAdult-onset asthma\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(N=23,722)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.625%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.583333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.791666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003eModel 1\u003csup\u003ell\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.625%\"\u003e\n \u003cp\u003e0.97 (0.94, 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e1.07 (0.92, 1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.583333333333334%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e0.87 (0.71, 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.791666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003eModel 2 **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.625%\"\u003e\n \u003cp\u003e0.97 (0.94, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.541666666666666%\"\u003e\n \u003cp\u003e1.04 (0.90, 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.583333333333334%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e0.86 (0.70, 1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.458333333333334%\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Estimated changes for the relationship of age at menarche with risk of adult asthma was conducted by continuous analyses.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e values for trend of the coefficients in categorical analyses are the \u003cem\u003ep\u003c/em\u003e values for the estimated changes by the age at menarche as continuous variable.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026Dagger;\u003c/sup\u003eChildhood-onset asthma was using models with\u0026nbsp;censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003eAdult-onset asthma was using models\u0026nbsp;with censoring age at 79 years, after excluding those suffered from asthma before 20.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ell\u003c/sup\u003eModel 1 included only age at menarche.\u003c/p\u003e\n\u003cp\u003e**Model 2 were further adjusted for race, income, height, and family history of asthma.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Hazard Ratios for Childhood- and Adult-onset Asthma Associated with Age at Menarche by Stratified Analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"16.161616161616163%\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of asthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"30.303030303030305%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"41.41414141414141%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at menarche, year\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"12.121212121212121%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value for effect modification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026lt;12 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(12-14 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLate menarche\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026ge;15 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003eChildhood-onset asthma\u003csup\u003e\u0026dagger;\u003c/sup\u003e (N=24,282)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eMexican American and other Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e2.05 (1.17, 3.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.93 (0.39, 2.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eNon-Hispanic white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.59 (1.13, 2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.65 (0.31, 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eNon-Hispanic black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.47 (1.07, 2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.48 (0.18, 1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.27 (0.54, 2.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.04 (0.01, 0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eRatio of family income to poverty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.71 (1.10, 2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.47 (0.20, 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u0026ge;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.60 (1.17, 2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.66 (0.31, 1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eFamily history of asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.64 (1.08, 2.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.41 (0.20, 0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.52 (1.04, 2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.80 (0.36, 1.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003eAdult-onset asthma\u003csup\u003e\u0026Dagger;\u003c/sup\u003e (N=23,722)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eMexican American and other Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.84 (0.63, 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.81 (0.56, 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eNon-Hispanic white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.03 (0.86, 1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.86 (0.67, 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eNon-Hispanic black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.28 (0.98, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.13 (0.82, 1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.15 (0.70, 1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.63 (0.35, 1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eRatio of family income to poverty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.14 (0.81, 1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.32 (0.97, 1.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003e\u0026ge;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.03 (0.86, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.81 (0.64, 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eFamily history of asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.10 (0.88, 1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.81 (0.56, 1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.3265306122449%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.612244897959183%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e1.01 (0.82, 1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"14.285714285714286%\"\u003e\n \u003cp\u003e1 (ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003e0.88 (0.69, 1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*All models were adjusted for race, income, height, and family history of asthma, with excluding the stratification variable. Interaction testing was performed by including an interaction term of each covariate and age at menarche.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eChildhood onset asthma was using models with\u0026nbsp;censoring age at 19 years, and participants first had asthma at age of 20 or more were treated as non-asthmatics.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026Dagger;\u003c/sup\u003eAdult-onset asthma was using models with censoring age at 79 years, after excluding those suffered from asthma before 20.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"adult-onset asthma, childhood-onset asthma, menarche, National Health and Nutrition Examination Survey, US population","lastPublishedDoi":"10.21203/rs.3.rs-910534/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-910534/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eFindings on the association between early menarche and asthma onset remain inconsistent and the evidence in the US is lacking. Furthermore, there was no clear separation of childhood- and adult-onset asthma in previous studies. Therefore, we aim at quantitatively estimating the association of age at menarche with risk of childhood- and adult-onset asthma separately in US girls and women.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a retrospective cohort study of 24,282 US girls and women aged less than 80 years by using continuous NHANES data in 2001-2018. Weighted Cox proportional-hazards regression models with censoring ages of 19 and 79 were used to separately estimate hazard ratios of childhood- and adult-onset asthma associated with age at menarche. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Each one-year increase of age at menarche was significantly associated with a 17% (HR [95%CI]: 0.83 [0.77, 0.90]) decrease in the risk of childhood-onset asthma. Compared with age at menarche of 12-14, we observed a 60% (HR [95%CI]: 1.60 [1.22, 2.09]) increased risk of childhood-onset asthma for early menarche (age at menarche \u0026lt;12 years) and 41% (HR [95%CI]: 0.59 [0.32, 1.08]) decreased risk for late menarche (age at menarche ≥15 years). Race, family income, education and family history of asthma did not modify these associations. No significant association between age at menarche and adult-onset asthma.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e In this US nationally representative study, we found that early menarche was associated with increased risk of childhood-onset asthma, but not adult-onset asthma. These findings help demonstrate early menarche may be a risk factor for childhood-onset asthma in US, indicating timely and effective management of special individuals with early menarche for preventing asthma.\u003c/p\u003e","manuscriptTitle":"Age at Menarche and Asthma Onset Among US Girls and Women: Findings from NHANES, 2001-2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-23 22:52:32","doi":"10.21203/rs.3.rs-910534/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"215e3488-81b3-4a6f-bd4c-52b7eccde989","owner":[],"postedDate":"September 23rd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":7384848,"name":"Pulmonology"}],"tags":[],"updatedAt":"2021-09-23T22:52:33+00:00","versionOfRecord":[],"versionCreatedAt":"2021-09-23 22:52:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-910534","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-910534","identity":"rs-910534","version":["v1"]},"buildId":"-D5TCW68w8eVRRLyjaTIo","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}