Sleep traits and thyroid gland: results from National Health and Nutrition Examination Survey 2007-2012 and Mendelian randomization analyses

Sleep traits and thyroid gland: results from National Health and Nutrition Examination Survey 2007-2012 and Mendelian randomization analyses | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sleep traits and thyroid gland: results from National Health and Nutrition Examination Survey 2007-2012 and Mendelian randomization analyses Rongliang Qiu, Jinbo Fu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4840632/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: Common sleep problems reduce quality of life and increase chronic disease risk. The relationship between sleep traits and thyroid function is unclear. This study explores the association between sleep traits and thyroid using NHANES data and Mendelian randomization (MR) analysis. Materials and Methods: Data from NHANES 2007-2012 were used to assess the relationship between sleep traits and thyroid function using weighted multivariable-adjusted logistic regression. A two-sample MR study was conducted using GWAS summary statistics, and methods like Inverse Variance Weighted (IVW) were used to explore the causal relationship between sleep traits and thyroid disease. Sensitivity analysis ensured robustness. Results: The study included 6919 NHANES participants. Logistic regression showed higher TSH levels in the long sleep group (P < 0.0001, β= 0.85, 95% CI: 0.54, 1.15). Lower FT3 levels were found in the normal sleep group (P = 0.0030, β= -0.06, 95% CI: -0.06, -0.00). TT4 levels were lower in those with sleep disorders (P = 0.0157, β= -0.11, 95% CI: -0.20, -0.02). Long sleep was positively associated with TGAb positivity (P = 0.0288, OR = 1.81, 95% CI: 1.06, 3.07), while sleep disorders were negatively associated with TGAb positivity (P = 0.0176, OR = 0.72, 95% CI: 0.56, 0.95). MR analysis indicated a positive association between long sleep and Graves' disease (GD) risk (P = 0.0240, OR = 99.98, 95% CI: 1.83, 5453.63), and a negative association between sleep duration and Hashimoto's thyroiditis (HT) risk (P = 0.0294, OR = 0.72, 95% CI: 0.54, 0.97). Conclusion: Sleep duration is associated with thyroid hormone levels and autoimmunity. Long sleep is linked to higher TSH levels, lower FT3 levels, and increased TGAb positivity risk, while sleep disorders are linked to lower TT4 levels and decreased TGAb positivity risk. MR studies suggest long sleep may increase GD risk, while shorter sleep may decrease HT risk. Epigenetics & Genomics Nutrition & Dietetics Endocrinology & Metabolism Head & Neck Surgery Mendelian randomization National Health and Nutrition Examination Survey sleep traits cross-sectional study causality Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. INTRODUCTION The thyroid gland is the largest endocrine gland in the body and its main function is to secrete thyroid hormones. The regulation of the availability of thyroid hormones, including triiodothyronine (T3) and thyroxine (T4), is a complex and diverse process. This regulation is not only at the central level, i.e., the hypothalamic-pituitary-thyroid (HPT) axis but also involves fine-tuning at the local level. At the local level, thyroid hormone availability is influenced by the differential expression of a variety of factors such as thyroid hormone transporter proteins, deiodinases, and thyroid nuclear hormone receptors 1 . In addition, transcriptional co-repressors and co-activators are involved in this regulatory process, which together ensure the homeostasis and efficient utilization of thyroid hormone in the body 1,2 . Active free thyroid hormones in the body include free triiodothyronine (FT3) and free thyroxine (FT4), which are converted to total T3 (TT3) and total T4 (TT4) when FT3 and FT4 are depleted 3 . Under physiologic conditions, circulating concentrations of thyroid-stimulating hormone (TSH) and FT4 are regulated by negative feedback through the HPT axis. In thyroid dysfunction, central regulation may fail, leading to abnormal changes in thyroid hormone levels and causing the corresponding symptoms of hypothyroidism or hyperthyroidism. Hashimoto’s thyroiditis (HT) is characterized by the presence of thyroid peroxidase antibodies (TPOAb) and thyroglobulin antibodies (TGAb), as well as diffuse lymphocytic infiltration of the thyroid tissue 4 . In contrast, Graves’disease (GD) is associated with autoantibodies against the TSH receptor 5 . HT and GD are the result of an attack by the immune system on the thyroid tissue, which ultimately manifests as changes in thyroid hormone levels, namely hyperthyroidism and hypothyroidism. Various lifestyle habits have been shown to cause changes in thyroid hormone levels, such as smoking, alcohol consumption, diet, and exercise 6 . In addition, almost all hormones are produced in a cyclical rhythm over 24 hours, and sleep has different effects on the regulation of this rhythm 7 . Sleep plays a vital role in maintaining overall physical and mental health. In the United States, approximately one-third of adults do not get the recommended 7 to 9 hours of sleep per night 8 . More worryingly, millions of Americans self-report sleep disorders each year 9 . It is worth noting that, based on observational data from the past few decades, some Western countries are also gradually showing a trend of sleep-related disorders and shortened sleep time 10 . Common sleep problems such as insufficient sleep, insomnia, and difficulty falling asleep not only reduce the quality of life, but also cause economic burdens and are closely related to physical and mental health and an increased risk of various chronic diseases (such as inflammation, metabolic syndrome, obesity, stroke, diabetes, and cancer) 11–16 . Hyperthyroidism and hypothyroidism are known to be common causes of sleep disorders. One study found that short sleepers have a higher risk of subclinical hyperthyroidism (elevated TSH) 17 . Another study showed that people with low thyroid hormone levels or even subclinical hypothyroidism (reduced TSH) typically have longer sleep latency and shorter sleep duration compared to people with normal thyroid function 18 . In contrast, the study by Lynn Kessler et al. evaluated the effects of prolonged, moderate sleep deprivation on the circadian rhythm of TSH secretion. While acute, extreme deprivation increases TSH secretion and release, chronic, moderate sleep deprivation suppresses TSH secretion 19 . However, the aforementioned studies were observational and had small sample sizes. Therefore, the present study was designed to explore the correlation between sleep traits (sleep duration and sleep disorder) and thyroid using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES). In addition, quantifying the causal effects of traditional observational studies is challenging as observational studies do not completely eliminate potential bias against confounders. Therefore, this study will also incorporate Mendelian randomization (MR) analyses to validate the findings of cross-sectional studies from the perspective of genetic variation and further assess the causal relationship between sleep characteristics (sleep duration, long sleep, short sleep, and insomnia) and thyroid disorders (hyperthyroidism, hypothyroidism, HT, and GD). 2. MATERIAL AND METHODS 2.1 Study design This study combined an observational epidemiologic study with MR analysis. Clinical associations between sleep traits (sleep duration and sleep disorder) and thyroid function were first explored by epidemiologic analysis of NHANES. Next, a two-sample MR analysis using genome-wide association study (GWAS) statistical pooled data was performed to validate the causal association between sleep traits (sleep duration, long sleep, short sleep, and insomnia) and thyroid disorders (hyperthyroidism, hypothyroidism, HT, and GD). MR relies on three basic assumptions: ( 1 ) the association hypothesis: genetic variation is associated with exposure; ( 2 ) the independence hypothesis: genetic variation is independent of confounding factors between exposure and outcome; and ( 3 ) the exclusivity hypothesis: genetic variation affects the outcome only through exposure. The flowchart of the MR study design is shown in Fig. 1 . 2.2 Epidemiological observation study 2.2.1 Data source The NHANES project is part of the National Center for Health Statistics (NCHS) and is a cross-sectional survey that uses a complex multistage probability sampling design to generate a nationally representative sample of the noninstitutionalized civilian population of the United States. The NCHS Research Ethics Review Board approved the NHANES study, and all NHANES participants signed informed consent. This study used data from the 2007 to 2012 NHANES cycles as a secondary analysis from a public data source, so no additional ethics approval or informed consent was required. Data on 30,442 participants from 2007–2012 were publicly available from the NHANES database ( https://www.cdc.gov/nchs/nhanes/index.htm ). Among all subjects, we excluded the following individuals: ( 1 ) individuals with missing data on thyroid function. ( 2 ) Individuals with missing information on sleep duration and sleep disorder (for participants who answered "don't know" or "refused", their data were considered as missing values). ( 3 ) Previous thyroid disease. ( 4 ) Pregnancy women. ( 4 ) Individuals with incomplete data on education, body mass index (BMI), poverty-to-income ratio (PIR). Finally, 6919 individuals were included. The flowchart of patient screening is shown in Fig. 2 . 2.2.2 Measurements and definitions The sleep traits addressed in this study included sleep duration and sleep disorder. Sleep duration was assessed based on a self-report questionnaire (SLD010H) in which participants were asked to answer the question "How much sleep do you usually get at night on weekdays or workdays?". If they reported 12 hours or more, it was recorded as 12 hours. According to the National Sleep Foundation's recommendations for sleep duration 20 , sleep duration was categorized into three groups in this study: short sleep ( 9 hours/day). The assessment of sleep disorder was based on a self-report questionnaire (SLD050H) and participants were asked to answer the question "Have you ever told a doctor or other health professional that you have trouble sleeping? ". Sleep disorder were categorized into two groups based on the responses: non-sleep disorder and sleep disorder. The serum samples involved in the outcome of this study for thyroid function indices included TSH, FT3, FT4, TT3, TT4, thyroglobulin (TG), TPOAb, and TGAb.The NHANES Laboratory/Healthcare Technician Procedures Manual for specimen collection and processing provides a comprehensive and detailed description of the methodology used in the collection and processing of serum specimens. TPOAb > 9.0 IU/mL and TGAb > 4.0 IU/mL were classified as positive, respectively. 2.2.3 Covariates Covariates in this study included race (Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black, and other races), age, sex (male and female), education (less than high school, high school or equivalent, and high school above), marital status (married/living with partner, widowed/divorced/separated, never married), BMI (less than normal, normal, overweight, obesity), PIR (low, medium, high), smoking status (no and yes), diabetes (no and yes), hypertension (no and yes) data were analyzed. Socioeconomic status was assessed using PIR values, and PIR was divided into three groups: low ( 3.5). Weight was divided into four groups: below normal (≤ 18.5 kg/m2), normal (> 18.5 and ≤ 25.0 kg/m2), overweight (> 25.0 and ≤ 30.0 kg/m2), and obese (> 30 kg/m2). 2.3 Mendelian randomization analysis 2.3.1 Data source The exposures included in this study were sleep traits, where sleep traits were categorized as long sleep, short sleep, sleep duration, and insomnia; and the outcomes included were thyroid-related disorders, which included hyperthyroidism, hypothyroidism, HT, and GD. Ethical approval or informed consent was not required as the data were obtained from secondary analyses of publicly available data sources. Specific information on the GWAS data in this study is detailed in the supplementary material: Table 1 . Table 1 Thyroid function and thyroid autoimmunity of NHANES (2007–2012) study population in sleep duration groups and sleep disorder groups. Characteristics Sleep duration P -value Sleep disorder P -value Total Short sleep Normal Long sleep Total Non-sleep disorder Sleep disorder N b 6919(100) 2816(40.7) 3934(56.86) 169(2.44) 6919(100) 5346(77.27) 1573(22.73) Gender b < 0.0001 < 0.0001 Male 2989(43.20) 770(27.35) 2150(54.66) 69(40.79) 3117(45.05) 2747(51.39) 370(23.53) Female 3930(56.80) 2046(72.65) 1784(45.34) 100(59.21) 3802(54.95) 2599(48.61) 1203(76.47) Age (year) a 60.07 ± 18.89 49.66 ± 17.22 51.02 ± 21.47 < 0.0001 52.18 ± 19.36 55.69 ± 13.06 < 0.0001 Race b < 0.0001 < 0.0001 Mexican American 232(3.35) 100(3.53) 119(3.03) 13(7.92) 219(3.16) 184(3.44) 35(2.22) Other hispanic 162(2.35) 83(2.96) 63(1.60) 16(9.79) 143(2.07) 111(2.08) 32(2.02) Non-Hispanic White 5345(77.25) 2324(82.53) 2912(74.01) 109(64.43) 5340(77.18) 3942(73.74) 1398(88.86) Non-Hispanic Black 986(14.25) 209(7.42) 756(19.23) 21(12.15) 1040(15.03) 961(17.98) 79(5.03) Other-race 194(2.80) 100(3.56) 84(2.13) 10(5.71) 177(2.56) 148(2.76) 29(1.87) BMI (kg/m2) b < 0.0001 < 0.0001 Less than normal 47(0.68) 16(0.55) 26(0.65) 5(3.18) 43(0.62) 36(0.67) 7(0.47) Normal 2567(37.10) 939(33.34) 1570(39.92) 58(33.96) 2713(39.21) 1720(32.19) 993(63.13) Overweight 2515(36.35) 1343(47.70) 1116(28.37) 56(33.22) 2306(33.33) 2050(38.34) 256(16.27) Obesity 1790(25.87) 518(18.40) 1222(31.06) 50(29.64) 1857(26.84) 1540(28.80) 317(20.12) Smoke b < 0.0001 < 0.0001 No 4031(58.26) 1253(44.50) 2688(68.33) 90(53.00) 4260(61.57) 3125(58.46) 1135(72.14) Yes 2888(41.74) 1563(55.50) 1246(31.67) 79(47.00) 2659(38.43) 2221(41.54) 438(27.86) Poverty-to-income ratio b < 0.0001 < 0.0001 Low 1355(19.59) 970(34.45) 311(7.91) 74(44.09) 1114(16.10) 896(16.77) 218(13.89) Medium 4362(63.04) 1284(45.60) 3015(76.63) 63(37.19) 4618(66.74) 3618(67.67) 1000(63.58) High 1202(17.37) 562(19.94) 608(15.46) 32(18.72) 1187(17.16) 832(15.56) 355(22.54) Education level b < 0.0001 < 0.0001 Less than high school 1775(25.65) 822(29.19) 898(22.83) 55(32.36) 1661(24.01) 1515(28.34) 146(9.29) High school or equivalent 702(10.15) 355(12.61) 290(7.37) 57(33.79) 642(9.28) 460(8.61) 182(11.57) High school above 4442(64.20) 1639(58.20) 2746(69.79) 57(33.85) 4616(66.71) 3371(63.05) 1245(79.14) Marital status b < 0.0001 < 0.0001 Married, or living with partner 4476(64.69) 1710(60.72) 2679(68.09) 87(51.51) 4598(66.45) 3352(62.69) 1246(79.21) Widowed, divorced, or separated 1078(15.58) 826(29.32) 209(5.31) 43(25.63) 881(12.74) 684(12.80) 197(12.54) Never married 1365(19.73) 280(9.96) 1046(26.60) 39(22.86) 1440(20.81) 1310(24.51) 130(8.26) Hypertension b < 0.0001 < 0.0001 No 4887(70.63) 1829(64.94) 2955(75.12) 103(61.18) 5005(72.34) 3754(70.22) 1251(79.52) Yes 2032(29.37) 987(35.06) 979(24.88) 66(38.82) 1914(27.66) 1592(29.78) 322(20.48) Diabetes b < 0.0001 < 0.0001 No 6036(87.24) 2701(95.91) 3185(80.95) 150(88.49) 5951(86.01) 4469(83.60) 1482(94.19) Yes 883(12.76) 115(4.09) 749(19.05) 19(11.51) 968(13.99) 877(16.40) 91(5.81) TSH (mIU/L) a 1.60 ± 1.20 1.91 ± 1.42 2.32 ± 4.11 < 0.0001 1.69 ± 1.44 2.40 ± 1.06 < 0.0001 FT3 (pg/mL) a 3.12 ± 0.43 3.16 ± 0.29 3.11 ± 0.41 0.0002 3.15 ± 0.35 3.12 ± 0.26 0.0167 FT4 (ng/dL) a 0.86 ± 0.23 0.74 ± 0.10 0.81 ± 0.18 < 0.0001 0.78 ± 0.17 0.79 ± 0.10 0.0037 TT3 (ng/dL) a 107.33 ± 18.54 113.73 ± 16.53 111.61 ± 22.99 < 0.0001 109.51 ± 16.26 121.80 ± 19.03 < 0.0001 TT4 (ug/dL) a 8.07 ± 1.45 6.79 ± 1.66 8.03 ± 1.64 < 0.0001 6.89 ± 1.64 8.51 ± 1.35 < 0.0001 TG (ng/mL) a 17.62 ± 19.82 11.09 ± 18.73 18.54 ± 25.06 < 0.0001 12.12 ± 19.42 17.61 ± 18.42 < 0.0001 TPOAb b 0.0008 0.1501 Negative 6654(96.17) 2687(95.41) 3813(96.93) 154(90.85) 6669(96.39) 5163(96.58) 1506(95.75) Positive 265(3.83) 129(4.59) 121(3.07) 15(9.15) 250(3.61) 183(3.42) 67(4.25) TGAb b 0.0029 0.3568 Negative 6750(97.56) 2739(97.26) 3856(98.01) 155(91.87) 6761(97.72) 5229(97.82) 1532(97.39) Positive 169(2.44) 77(2.74) 78(1.99) 14(8.13) 158(2.28) 117(2.18) 41(2.61) a :Continuous Variables: weighted mean (SD). b :Categorical variable: actual frequency (weighted percentage). Abbreviations: TSH, thyroid-stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TT3, total T3; TT4, total T4; TG, thyroglobulin; TPOAb, thyroid peroxidase antibody; TGAb: thyroglobulin antibody; BMI, body mass index; SD, Standard deviation. Hassan S Dashti et al. 21 obtained genetic association data on sleep duration using GWAS data published by the UK Biobank for 446,118 adults of European ancestry. In this study, the mean self-reported habitual sleep duration was 7.2 hours with a standard deviation of 1.1 hours. Subsequent analysis converted the continuous variable of sleep duration into a categorical variable. There were 106,192 cases of short sleep (< 7 hours) and 34,184 cases of long sleep (≥ 9 hours). Jacqueline M Lane et al. 22 analyzed self-reported insomnia symptoms in 453,379 European participants in the UK Biobank. Participants were asked to answer the question “Do you have difficulty falling asleep or wakeing up in the middle of the night?”. The analysis showed that 29% reported frequent insomnia symptoms (“usually”), and the prevalence was higher in women (32% vs. 24%) and older participants, shift workers, and those who self-reported shorter sleep duration. The GWAS data of hyperthyroidism and hypothyroidism were obtained from IEU OPEN GWAS. The genetic association data of hyperthyroidism included 3545 cases and 459,388 controls. The genetic association data of hypothyroidism included 22,687 cases and 440,246 controls. The GWAS data for HT and GD were compiled and published in 2021 by Saori Sakaue et al. 23 . The pooled data for GD included 395,640 European participants (15,654 cases and 379,986 controls). The pooled GWAS data for HT included 458,620 European participants (1678 cases and 456,942 controls). 2.3.2 Selection of instrument variables The selection criteria for instrumental variables (IVs) were as follows:( 1 ) single nucleotide polymorphism (SNP) loci with genome-wide significance were screened from the exposure database. ( 2 ) Perform the PLINK clustering algorithm with a 10,000 kb linkage disequilibrium (LD) window to ensure independence (R 2 < 0.0001). ( 3 ) Excluded SNP with F statistic 10 indicates strongly associated IVs.( 4 ) Harmonized the exposure and outcome datasets and excluded palindromic sequences to ensure that the effects of SNP on exposure and outcome were from the same allele. SNP used as IVs in this study are listed in Supplementary material: Tables 2 , 3 , 4, and 5. Table 2 Effects of sleep duration and sleep disorders on thyroid function. Model 1 a P -value Model 2 a P -value β (95% CI) β (95% CI) TSH (mIU/L) Sleep duration Short sleep Reference Reference Normal 0.15(0.06,0.25) 0.0018 0.09(−0.01,0.18) 0.0767 Long sleep 0.97(0.66,1.28) < 0.0001 0.85(0.54,1.15) < 0.0001 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder 0.01(−0.10,0.12) 0.8354 −0.06(−0.17,0.05) 0.3043 FT3 (pg/mL) Sleep duration Short sleep Reference Reference Normal −0.04(−0.07,−0.01) 0.0036 −0.03(−0.06,−0.00) 0.0030 Long sleep −0.12(−0.21,−0.04) 0.0053 −0.06(−0.14,0.02) 0.1517 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder −0.08(−0.11,−0.05) < 0.0001 −0.02(−0.06,,0.01) 0.1149 FT4 (ng/dL) Sleep duration Short sleep Reference Reference Normal 0.01(−0.00,0.01) 0.0875 0.01(−0.00,0.01) 0.1088 Long sleep 0.02(−0.00,0.04) 0.1099 0.01(−0.01,0.04) 0.2219 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder −0.01(−0.02,0.00) 0.0670 −0.01(−0.02,0.00) 0.0614 TT3 (ng/dL) Sleep duration Short sleep Reference Reference Normal −1.08(−2.26,0.10) 0.0731 −0.47(−1.62,0.67) 0.4180 Long sleep −5.06(−8.85,−1.28) 0.0088 −2.83(−6.46,0.81) 0.1275 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder −1.83(−3.20,−0.46) 0.0089 −0.11(−1.47,1.24) 0.8690 TT4 (ug/dL) Sleep duration Short sleep Reference Reference Normal -−0.00(−0.08,0.08) 0.9727 0.04(−0.04,0.11) 0.3589 Long sleep 0.25(−0.01,0.50) 0.0455 0.21(−0.04,0.45) 0.0961 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder −0.04(−0.13,0.05) 0.3646 −0.11(−0.20,−0.02) 0.0157 Model 1 a : no covariates were adjusted. Model 2 b : age, gender, race, poverty-to-income ratio, marital, body mass index, smoke, education level, marital status, hypertension, diabetes were adjusted. Abbreviations: TSH, thyroid-stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TT3, total T3; TT4, total T4; TG, thyroglobulin. Table 3 Effects of sleep duration and sleep disorders on thyroid autoimmunity. Model 1 a P -value Model 2 a P -value OR (95% CI) OR(95% CI) TPOAb b Sleep duration Short sleep Reference Reference Normal 1.14(0.96,1.36) 0.1309 1.03(0.86,1.23) 0.7563 Long sleep 1.64(1.02,2.65) 0.0416 1.39(0.85,2.27) 0.1857 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder 0.90(0.73,1.10) 0.2993 0.83(0.67,1.02) 0.0803 TGAb b Sleep duration Short sleep Reference Reference Normal 1.21(0.98,1.50) 0.0737 1.10(0.88,1.36) 0.4096 Long sleep 2.23(1.33,3.74) 0.0024 1.81(1.06,3.07) 0.0288 Sleep disorder Non-sleep disorder Reference Reference Sleep disorder 0.77(0.60,1.00) 0.0478 0.72(0.56,0.95) 0.0176 Model 1 a : no covariates were adjusted. Model 2 b : age, gender, race, poverty-to-income ratio, marital, body mass index, smoke, education level, marital status, hypertension, diabetes were adjusted. Abbreviations: TSH, thyroid-stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TT3, total T3; TT4, total T4; TG, thyroglobulin. 2.4 Statistical Analyses 2.4.1 Cross-Sectional study All statistical analyses were performed according to the recommendations of the Centers for Disease Control and Prevention using appropriate NHANES sampling weights. Continuous variables are expressed as standard deviation (x ± s), whereas categorical variables are expressed as n (%). Between-group differences were assessed by weighted linear regression for continuous variables or weighted chi-square test for categorical variables. The association between sleep behavior and thyroid was studied by multiple linear regression using two different models. The first model did not adjust for covariates. The second model adjusted for age, gender, race, education, marital status, PIR, BMI, smoking, diabetes, and hypertension. All analyses were performed by EmpowerStats (4.0) ( http://www.empowerstats.com ) and R software ( http://www.r-project.org ) using MEC weights. p values < 0.05 were considered statistically significant. 2.4.2 Two-Sample mendelian randomization All MR analyses were performed using the TwoSampleMR package in R (4.2.1) software. In this study, the inverse variance weighted (IVW) method was used to pool the Wald estimates of individual SNP for weighted linear regression to summarize the total effect value. IVW, as the main analysis method, can provide unbiased causal effect estimates in the absence of horizontal pleiotropy. At the same time, to improve the robustness of the results, MR-Egger regression and weighted median estimator (WME) were used as supplementary methods of IVW because these methods can provide more reliable effect estimates under more relaxed conditions. In addition, we also used Cochran's Q test calculated by the IVW method to estimate heterogeneity. At the same time, the MR-Egger intercept test was used to evaluate and correct for potential pleiotropy. Finally, the robustness of the results was further verified by observing the funnel plot and leave-one-out plot. 3. RESULTS 3.1 Baseline characteristics The baseline characteristics of the participants are summarized in Table 1 . After strict screening, a total of 6919 subjects were included in this study. In the sleep duration group, 3930 (56.80%) were female, 5345 (77.25%) were non-Hispanic white, 2567 (37.10%) had normal BMI, 4362 (63.04%) had a medium PIR level, 4442 (64.20%) had an education level higher than high school, and 4476 (64.69%) were married or living with a partner. In addition, there were 2032 cases of hypertension, 883 cases of diabetes, and 2888 cases of smoking, of which 265 were TPOAb positive and 169 were TGAb positive. In the sleep disorder group, 3802 (54.95%) were female, 5340 (77.18%) were non-Hispanic white, 2713 (39.21%) had normal BMI, 4618 (66.74%) had a medium family income, 4616 (66.71%) had an education level higher than high school, and 4598 (66.45%) were married or living with a partner. In addition, 1914 had hypertension, 968 had diabetes, and 2659 smoked, of which 183 were TPOAb positive and 158 were TGAb positive. 3.2 Relationship between sleep traits and thyroid The results of the multivariate regression analyses have been presented in Tables 2 and 3 . In Model 2 adjusted for covariates, we found significantly higher TSH levels in the long-sleep group compared to those in the short-sleep group (P < 0.0001 β = 0.85, 95% CI: 0.54, 1.15). FT3 levels were lower in the normal group compared to those with short sleep (P = 0.0030 β = -0.06, 95% CI: -0.06, -0.00). Lower TT4 levels were also found in people with sleep disorder compared to those with non-sleep disorder (P = 0.0157 β = -0.11, 95% CI: -0.20, -0.02). In terms of thyroid autoimmunity, from model 2, it was found that long sleep was positively associated with the risk of TGAb positivity (P = 0.0288 OR = 1.81, 95% CI 1.06, 3.07), whereas sleep disorder were negatively associated with TGAb positivity (P = 0.0176 OR = 0.72, 95% CI: 0.56, 0.95). 3.3 Mendelian randomization analysis All MR analysis results have been presented in Figs. 3 , 4 , and 5 . IVW results indicate that there may be a positive association between long sleep and the risk of GD (P = 0.0240 OR = 99.98, 95% CI 1.83, 5453.63), while there may be a negative association between sleep duration and the risk of HT (P = 0.0294 OR = 0.72, 95% CI 0.54, 0.97). In this study, there was heterogeneity between sleep traits and hypothyroidism, heterogeneity between sleep duration and hyperthyroidism, heterogeneity between short sleep and insomnia and GD, and the remaining results showed no heterogeneity. or pleiotropic effects (P > 0.05) (Supplementary material: Table 6). We also observed the funnel plot, which was roughly symmetrical, indicating that the risk of bias was relatively low and the results were highly reliable (Supplementary material: Fig. 1 ). The leave-one-out method was used to eliminate SNP one by one, and no specific SNP was found to cause significant changes in the results (Supplementary material: Fig. 2 ). 4. DISCUSSION This study is the first to combine large-scale observational study data and MR analysis to explore the association between sleep traits and thyroid. In terms of thyroid function, cross-sectional studies have shown that compared with short sleep, long sleep TSH levels are significantly higher, and normal sleep FT3 levels are lower. It was also found that people with sleep disorder had lower TT4 levels than those with non-sleep disorder. In terms of thyroid autoimmunity, the study found that long sleep was positively correlated with the risk of TGAb positivity, while sleep disorder were negatively correlated with the risk of TGAb positivity. In addition, further two-sample MR analysis verified this conclusion, indicating that there may be a positive correlation between long sleep and GD risk, and there may be a negative correlation between sleep duration and HT risk. The HPT axis is controlled by the circadian rhythm system, which plays a key role in the sleep-wake cycle, and disruption of one axis leads to dysregulation of the other 24 . The results of previous studies have assessed, to varying degrees, the effects of sleep on thyroid function. There is evidence that sleep affects thyroid hormone secretion, leading to a decrease in the circadian amplitude of TSH, which in turn feedback suppresses thyroid hormones through the HPT axis 25 . Previous observational studies have observed circadian rhythm changes in TSH secretion to varying degrees 26–29 . Epidemiologic findings suggest that there are long-term effects of chronic circadian rhythm disruption on human health, and indeed chronic sleep deprivation disrupts rhythmic TSH secretion 24,30 . Although acute, extreme deprivation increases TSH secretion and increases the surge in TSH release, chronic, moderate sleep deprivation suppresses the effects of circadian TSH secretion 19 . The results of a recent study showed an increase in TSH levels and a decrease in FT3 levels with increasing sleep duration, which is broadly similar to our study 31 . A similar circadian rhythmicity of FT3 was found in another study by observing that FT3 peaked 90 minutes after TSH secretion in 86–100% of participants 29 . In contrast, FT4 did not show a clear circadian rhythm 29 . Regardless of the effects of sleep, TSH is regulated by circadian rhythms. Starting in the evening, concentrations increase dramatically, peak at 2–3 am, and do not decrease until the afternoon. Thus, although NAHANES self-reported the same sleep duration, the effect of sleep duration on TSH secretion may not be attributable only to duration, but may also vary depending on the individual's sleep onset and termination times. For example, Participant A slept from 9 p.m. to 3 a.m. (when TSH secretion was in the ascending phase), whereas Participant B slept from 2 a.m. to 9 a.m. (when TSH secretion was in the descending phase), and both individuals slept for the same duration of 7 hours; however, the effect of sleep on TSH secretion would differ depending on the period. Previous observational studies have shown a correlation between hypothyroidism and sleep. A study based on a Chinese population showed that subclinical hypothyroidism was a risk factor for poor sleep quality 18 . In addition, the results of another single-center retrospective study showed that patients with hypothyroidism were more likely to have early chronotype 32 . A large Korean cohort study showed that either too much or too little sleep was associated with an increased risk of subclinical thyroid dysfunction 17 . However, some studies have taken the opposite view, suggesting that there is no significant difference in subjective sleep measures between individuals with hyperthyroidism and normal thyroid function 33 . Similarly, a study by Akatsu et al. did not find a relationship between subclinical hypothyroidism and sleep quality 34 . The current evidence on the association between sleep and thyroid disorders is controversial, and the results of our MR study found no correlation between sleep traits (sleep duration, long sleep, short sleep, and insomnia) and thyroid disorders (hyperthyroidism and hypothyroidism). The association between the HPT axis and sleep can affect thyroid function, and the mutual interference between autoimmunity and sleep duration may further exacerbate the potential impact of sleep on thyroid function 35,36 . Although previously understudied in the context of thyroid autoimmune diseases, sleep disorder have been reported to increase the risk of multiple autoimmune diseases such as systemic lupus erythematosus, rheumatoid arthritis, and ankylosing spondylitis 37,38 . Some clinical studies have also observed that autoimmune disease activity is associated with sleep 39,40 . In addition, sleep is bi-directionally related to the immune system, and sleep can also regulate the immune system 35 . Therefore, sleep may play a role in the immune mechanism of autoimmune thyroid disease. Our cross-sectional study found that long sleep was positively associated with the risk of TGAb positivity, while sleep disorder were negatively associated with TGAb positivity. This was verified in further MR study results, indicating that long sleep may be positively associated with the risk of GD, while sleep duration may be negatively associated with the risk of HT. The main strength of this study is that it is the first to combine the NHANES observational study with the MR method to explore the association between sleep traits and thyroid. The strong sample size and thorough adjustment for multiple confounders allowed us to increase the confidence of the study results in the multivariate regression model. Although the cross-sectional study design limits causal inference, the MR analysis essentially produces a natural randomized controlled trial and provides high-power (p 10) SNP to evaluate the causal association between sleep traits and thyroid disease. However, we still need to consider the limitations of the study. First, although we tried to control various confounders, the data on sleep traits were self-reported, which may be subject to recall bias. Second, the sleep duration measurement only included sleep time on weekdays or workdays and did not include additional information related to sleep (such as shift work, working conditions, and sleep onset and end times), which limited the further analysis of the study results. Finally, our NHANES study focused on the U.S. population, while the MR study focused on people of European ancestry, which limits the generalizability of the study results. It is necessary to validate the current findings in the same ethnic or other ethnic populations in the future. 5. CONCLUSION Our cross-sectional study found that sleep duration was associated with TSH and FT3 levels, and sleep disorder were associated with TT4 levels. In terms of thyroid autoimmunity, long sleep was positively correlated with the risk of TGAb positivity, while sleep disorder were negatively correlated with TGAb positivity. Further through MR research, we speculate that long sleep may be positively correlated with the risk of GD, and sleep duration may be negatively correlated with the risk of HT. In the future, it is necessary to conduct more in-depth basic and clinical research to verify the accuracy of the research results and explore its potential mechanism of action. Declarations Acknowledgments We sincerely thank all the projects (NHANES, UK Biobank and IEU OPEN GWAS) who participated in this study. Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Rongliang Qiu and Jinbo Fu. The first draft of the manuscript was written by Rongliang Qiu and Jinbo Fu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding No funding was received for this research. Ethical Approval Not applicable. Conflict of interest All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Data availability statement The dataset analyzed in this study is publicly available and can be accessed as described below. No new data were generated. Data for observational studies were taken from the NHANES website: https://www.cdc.gov/nchs/nhanes/index.html. GWAS statistical summary data were obtained from UK Biobank and IEU OPEN GWAS, and the corresponding studies can be found in the Supplementary Material: tables 2, 3, 4 and 5. References Brent GA. Mechanisms of thyroid hormone action. J Clin Invest . Sep 2012;122(9):3035-43. doi:10.1172/JCI60047 Jing L, Zhang Q. Intrathyroidal feedforward and feedback network regulating thyroid hormone synthesis and secretion. Front Endocrinol (Lausanne) . 2022;13:992883. doi:10.3389/fendo.2022.992883 Brdar D, Gunjaca I, Pleic N, et al. The effect of food groups and nutrients on thyroid hormone levels in healthy individuals. Nutrition . Nov-Dec 2021;91-92:111394. doi:10.1016/j.nut.2021.111394 Ragusa F, Fallahi P, Elia G, et al. 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Mar 2016;11(1):81-9. doi:10.1016/j.jsmc.2015.10.007 Bin YS, Marshall NS, Glozier N. Secular trends in adult sleep duration: a systematic review. Sleep Med Rev . Jun 2012;16(3):223-30. doi:10.1016/j.smrv.2011.07.003 Smiley A, King D, Bidulescu A. The Association between Sleep Duration and Metabolic Syndrome: The NHANES 2013/2014. Nutrients . Oct 26 2019;11(11)doi:10.3390/nu11112582 Chen Y, Tan F, Wei L, et al. Sleep duration and the risk of cancer: a systematic review and meta-analysis including dose-response relationship. BMC Cancer . Nov 21 2018;18(1):1149. doi:10.1186/s12885-018-5025-y He Q, Sun H, Wu X, et al. Sleep duration and risk of stroke: a dose-response meta-analysis of prospective cohort studies. Sleep Med . Apr 2017;32:66-74. doi:10.1016/j.sleep.2016.12.012 Anothaisintawee T, Reutrakul S, Van Cauter E, Thakkinstian A. Sleep disturbances compared to traditional risk factors for diabetes development: Systematic review and meta-analysis. Sleep Med Rev . Dec 2016;30:11-24. doi:10.1016/j.smrv.2015.10.002 Hui SK, Grandner MA. Trouble Sleeping Associated With Lower Work Performance and Greater Health Care Costs: Longitudinal Data From Kansas State Employee Wellness Program. J Occup Environ Med . Oct 2015;57(10):1031-8. doi:10.1097/JOM.0000000000000534 Dowd JB, Goldman N, Weinstein M. Sleep duration, sleep quality, and biomarkers of inflammation in a Taiwanese population. Ann Epidemiol . Nov 2011;21(11):799-806. doi:10.1016/j.annepidem.2011.07.004 Kim W, Lee J, Ha J, et al. Association between Sleep Duration and Subclinical Thyroid Dysfunction Based on Nationally Representative Data. J Clin Med . Nov 18 2019;8(11)doi:10.3390/jcm8112010 Song L, Lei J, Jiang K, et al. The Association Between Subclinical Hypothyroidism and Sleep Quality: A Population-Based Study. Risk Manag Healthc Policy . 2019;12:369-374. doi:10.2147/RMHP.S234552 Kessler L, Nedeltcheva A, Imperial J, et al. Changes in serum TSH and free T4 during human sleep restriction. Sleep . Aug 2010;33(8):1115-8. doi:10.1093/sleep/33.8.1115 Hirshkowitz M, Whiton K, Albert SM, et al. National Sleep Foundation's sleep time duration recommendations: methodology and results summary. Sleep Health . Mar 2015;1(1):40-43. doi:10.1016/j.sleh.2014.12.010 Dashti HS, Jones SE, Wood AR, et al. Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates. Nat Commun . Mar 7 2019;10(1):1100. doi:10.1038/s41467-019-08917-4 Lane JM, Jones SE, Dashti HS, et al. Biological and clinical insights from genetics of insomnia symptoms. Nat Genet . Mar 2019;51(3):387-393. doi:10.1038/s41588-019-0361-7 Sakaue S, Kanai M, Tanigawa Y, et al. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet . Oct 2021;53(10):1415-1424. doi:10.1038/s41588-021-00931-x Ikegami K, Refetoff S, Van Cauter E, Yoshimura T. Interconnection between circadian clocks and thyroid function. Nat Rev Endocrinol . Oct 2019;15(10):590-600. doi:10.1038/s41574-019-0237-z Romijn JA, Adriaanse R, Brabant G, et al. Pulsatile secretion of thyrotropin during fasting: a decrease of thyrotropin pulse amplitude. J Clin Endocrinol Metab . Jun 1990;70(6):1631-6. doi:10.1210/jcem-70-6-1631 Ehrenkranz J, Bach PR, Snow GL, et al. Circadian and Circannual Rhythms in Thyroid Hormones: Determining the TSH and Free T4 Reference Intervals Based Upon Time of Day, Age, and Sex. Thyroid . Aug 2015;25(8):954-61. doi:10.1089/thy.2014.0589 Roelfsema F, Veldhuis JD. Thyrotropin secretion patterns in health and disease. Endocr Rev . Oct 2013;34(5):619-57. doi:10.1210/er.2012-1076 Roelfsema F, Pereira AM, Veldhuis JD, et al. Thyrotropin secretion profiles are not different in men and women. J Clin Endocrinol Metab . Oct 2009;94(10):3964-7. doi:10.1210/jc.2009-1155 Russell W, Harrison RF, Smith N, et al. Free triiodothyronine has a distinct circadian rhythm that is delayed but parallels thyrotropin levels. J Clin Endocrinol Metab . Jun 2008;93(6):2300-6. doi:10.1210/jc.2007-2674 Kettner NM, Katchy CA, Fu L. Circadian gene variants in cancer. Ann Med . Jun 2014;46(4):208-20. doi:10.3109/07853890.2014.914808 Wang M, Lu X, Zheng X, et al. The relationship between sleep duration and thyroid function in the adult US population: NHANES 2007-2012. PLoS One . 2023;18(9):e0291799. doi:10.1371/journal.pone.0291799 Arosemena MA, Ramos AR, Marcus EN, et al. Primary hypothyroidism and chronotypes in adult women. BMC Res Notes . Feb 14 2022;15(1):52. doi:10.1186/s13104-022-05934-3 Grabe HJ, Volzke H, Ludemann J, et al. Mental and physical complaints in thyroid disorders in the general population. Acta Psychiatr Scand . Oct 2005;112(4):286-93. doi:10.1111/j.1600-0447.2005.00586.x Akatsu H, Ewing SK, Stefanick ML, et al. Association Between Thyroid Function and Objective and Subjective Sleep Quality in Older Men: The Osteoporotic Fractures in Men (MrOS) Study. Endocr Pract . Jun 2014;20(6):576-86. doi:10.4158/EP13282.OR Besedovsky L, Lange T, Haack M. The Sleep-Immune Crosstalk in Health and Disease. Physiol Rev . Jul 1 2019;99(3):1325-1380. doi:10.1152/physrev.00010.2018 Irwin MR, Olmstead R, Carroll JE. Sleep Disturbance, Sleep Duration, and Inflammation: A Systematic Review and Meta-Analysis of Cohort Studies and Experimental Sleep Deprivation. Biol Psychiatry . Jul 1 2016;80(1):40-52. doi:10.1016/j.biopsych.2015.05.014 Cervilla O, Miro E, Martinez MP, et al. Sleep quality and clinical and psychological manifestations in women with mild systemic lupus erythematosus activity compared to women with fibromyalgia: A preliminary study. Mod Rheumatol . Nov 2020;30(6):1016-1024. doi:10.1080/14397595.2019.1679973 Hsiao YH, Chen YT, Tseng CM, et al. Sleep disorders and increased risk of autoimmune diseases in individuals without sleep apnea. Sleep . Apr 1 2015;38(4):581-6. doi:10.5665/sleep.4574 Young KA, Munroe ME, Harley JB, et al. Less than 7 hours of sleep per night is associated with transitioning to systemic lupus erythematosus. Lupus . Aug 2018;27(9):1524-1531. doi:10.1177/0961203318778368 Son CN, Choi G, Lee SY, et al. Sleep quality in rheumatoid arthritis, and its association with disease activity in a Korean population. Korean J Intern Med . May 2015;30(3):384-90. doi:10.3904/kjim.2015.30.3.384 Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryMaterial.xlsx 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. 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design.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/ff3334119d3f56816d723da9.png"},{"id":61811438,"identity":"30276289-c53e-4c08-a887-723b8754bdb8","added_by":"auto","created_at":"2024-08-05 20:27:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55326,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNHANES patient screening flowchart.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/b2b920b2229ee42652b5a2c4.png"},{"id":61811440,"identity":"fc4b8c63-d11a-44b5-b7df-f926b04b2342","added_by":"auto","created_at":"2024-08-05 20:27:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":84959,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of IVW methods for thyroid disease by different sleep traits.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/e60b80820f02adaa2f6d9fd7.png"},{"id":61812099,"identity":"151a709c-feb9-495e-872e-534b5415ee09","added_by":"auto","created_at":"2024-08-05 20:43:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":75332,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of weighted median methods for thyroid disease by different sleep traits.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/1b360f4c7e919aec46fa9cbe.png"},{"id":61811443,"identity":"6b2cf3c0-a421-4976-9daf-e8e71c5de9f8","added_by":"auto","created_at":"2024-08-05 20:27:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":86354,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of MR-Egger methods for thyroid disease by different sleep traits.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/bd97259a626dd834984835b1.png"},{"id":61812569,"identity":"37161d53-4e16-42d8-b96e-a097f230e3c0","added_by":"auto","created_at":"2024-08-05 20:51:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1575812,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/69f4c1dc-dfeb-4bd6-bdfd-dabc660dc00d.pdf"},{"id":61811444,"identity":"fb57e18a-54b5-4408-aa54-04aca3cb7537","added_by":"auto","created_at":"2024-08-05 20:27:31","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35699502,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4840632/v1/680fe422034e1d3329808432.xlsx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eSleep traits and thyroid gland: results from National Health and Nutrition Examination Survey 2007-2012 and Mendelian randomization analyses\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eThe thyroid gland is the largest endocrine gland in the body and its main function is to secrete thyroid hormones. The regulation of the availability of thyroid hormones, including triiodothyronine (T3) and thyroxine (T4), is a complex and diverse process. This regulation is not only at the central level, i.e., the hypothalamic-pituitary-thyroid (HPT) axis but also involves fine-tuning at the local level. At the local level, thyroid hormone availability is influenced by the differential expression of a variety of factors such as thyroid hormone transporter proteins, deiodinases, and thyroid nuclear hormone receptors\u003csup\u003e1\u003c/sup\u003e. In addition, transcriptional co-repressors and co-activators are involved in this regulatory process, which together ensure the homeostasis and efficient utilization of thyroid hormone in the body\u003csup\u003e1,2\u003c/sup\u003e. Active free thyroid hormones in the body include free triiodothyronine (FT3) and free thyroxine (FT4), which are converted to total T3 (TT3) and total T4 (TT4) when FT3 and FT4 are depleted\u003csup\u003e3\u003c/sup\u003e. Under physiologic conditions, circulating concentrations of thyroid-stimulating hormone (TSH) and FT4 are regulated by negative feedback through the HPT axis. In thyroid dysfunction, central regulation may fail, leading to abnormal changes in thyroid hormone levels and causing the corresponding symptoms of hypothyroidism or hyperthyroidism. Hashimoto\u0026rsquo;s thyroiditis (HT) is characterized by the presence of thyroid peroxidase antibodies (TPOAb) and thyroglobulin antibodies (TGAb), as well as diffuse lymphocytic infiltration of the thyroid tissue \u003csup\u003e4\u003c/sup\u003e. In contrast, Graves\u0026rsquo;disease (GD) is associated with autoantibodies against the TSH receptor\u003csup\u003e5\u003c/sup\u003e. HT and GD are the result of an attack by the immune system on the thyroid tissue, which ultimately manifests as changes in thyroid hormone levels, namely hyperthyroidism and hypothyroidism. Various lifestyle habits have been shown to cause changes in thyroid hormone levels, such as smoking, alcohol consumption, diet, and exercise\u003csup\u003e6\u003c/sup\u003e. In addition, almost all hormones are produced in a cyclical rhythm over 24 hours, and sleep has different effects on the regulation of this rhythm\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSleep plays a vital role in maintaining overall physical and mental health. In the United States, approximately one-third of adults do not get the recommended 7 to 9 hours of sleep per night\u003csup\u003e8\u003c/sup\u003e. More worryingly, millions of Americans self-report sleep disorders each year\u003csup\u003e9\u003c/sup\u003e. It is worth noting that, based on observational data from the past few decades, some Western countries are also gradually showing a trend of sleep-related disorders and shortened sleep time\u003csup\u003e10\u003c/sup\u003e. Common sleep problems such as insufficient sleep, insomnia, and difficulty falling asleep not only reduce the quality of life, but also cause economic burdens and are closely related to physical and mental health and an increased risk of various chronic diseases (such as inflammation, metabolic syndrome, obesity, stroke, diabetes, and cancer)\u003csup\u003e11\u0026ndash;16\u003c/sup\u003e. Hyperthyroidism and hypothyroidism are known to be common causes of sleep disorders. One study found that short sleepers have a higher risk of subclinical hyperthyroidism (elevated TSH)\u003csup\u003e17\u003c/sup\u003e. Another study showed that people with low thyroid hormone levels or even subclinical hypothyroidism (reduced TSH) typically have longer sleep latency and shorter sleep duration compared to people with normal thyroid function \u003csup\u003e18\u003c/sup\u003e. In contrast, the study by Lynn Kessler et al. evaluated the effects of prolonged, moderate sleep deprivation on the circadian rhythm of TSH secretion. While acute, extreme deprivation increases TSH secretion and release, chronic, moderate sleep deprivation suppresses TSH secretion\u003csup\u003e19\u003c/sup\u003e. However, the aforementioned studies were observational and had small sample sizes. Therefore, the present study was designed to explore the correlation between sleep traits (sleep duration and sleep disorder) and thyroid using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES). In addition, quantifying the causal effects of traditional observational studies is challenging as observational studies do not completely eliminate potential bias against confounders. Therefore, this study will also incorporate Mendelian randomization (MR) analyses to validate the findings of cross-sectional studies from the perspective of genetic variation and further assess the causal relationship between sleep characteristics (sleep duration, long sleep, short sleep, and insomnia) and thyroid disorders (hyperthyroidism, hypothyroidism, HT, and GD).\u003c/p\u003e"},{"header":"2. MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study design\u003c/h2\u003e\n \u003cp\u003eThis study combined an observational epidemiologic study with MR analysis. Clinical associations between sleep traits (sleep duration and sleep disorder) and thyroid function were first explored by epidemiologic analysis of NHANES. Next, a two-sample MR analysis using genome-wide association study (GWAS) statistical pooled data was performed to validate the causal association between sleep traits (sleep duration, long sleep, short sleep, and insomnia) and thyroid disorders (hyperthyroidism, hypothyroidism, HT, and GD). MR relies on three basic assumptions: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) the association hypothesis: genetic variation is associated with exposure; (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) the independence hypothesis: genetic variation is independent of confounding factors between exposure and outcome; and (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) the exclusivity hypothesis: genetic variation affects the outcome only through exposure. The flowchart of the MR study design is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Epidemiological observation study\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Data source\u003c/h2\u003e\n \u003cp\u003eThe NHANES project is part of the National Center for Health Statistics (NCHS) and is a cross-sectional survey that uses a complex multistage probability sampling design to generate a nationally representative sample of the noninstitutionalized civilian population of the United States. The NCHS Research Ethics Review Board approved the NHANES study, and all NHANES participants signed informed consent. This study used data from the 2007 to 2012 NHANES cycles as a secondary analysis from a public data source, so no additional ethics approval or informed consent was required.\u003c/p\u003e\n \u003cp\u003eData on 30,442 participants from 2007\u0026ndash;2012 were publicly available from the NHANES database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/index.htm\u003c/span\u003e\u003c/span\u003e). Among all subjects, we excluded the following individuals: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) individuals with missing data on thyroid function. (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) Individuals with missing information on sleep duration and sleep disorder (for participants who answered \u0026quot;don\u0026apos;t know\u0026quot; or \u0026quot;refused\u0026quot;, their data were considered as missing values). (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) Previous thyroid disease. (\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e) Pregnancy women. (\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e) Individuals with incomplete data on education, body mass index (BMI), poverty-to-income ratio (PIR). Finally, 6919 individuals were included. The flowchart of patient screening is shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Measurements and definitions\u003c/h2\u003e\n \u003cp\u003eThe sleep traits addressed in this study included sleep duration and sleep disorder. Sleep duration was assessed based on a self-report questionnaire (SLD010H) in which participants were asked to answer the question \u0026quot;How much sleep do you usually get at night on weekdays or workdays?\u0026quot;. If they reported 12 hours or more, it was recorded as 12 hours. According to the National Sleep Foundation\u0026apos;s recommendations for sleep duration\u003csup\u003e20\u003c/sup\u003e, sleep duration was categorized into three groups in this study: short sleep (\u0026lt;\u0026thinsp;7 hours/day), normal (7\u0026ndash;9 hours/day), and long sleep (\u0026gt;\u0026thinsp;9 hours/day). The assessment of sleep disorder was based on a self-report questionnaire (SLD050H) and participants were asked to answer the question \u0026quot;Have you ever told a doctor or other health professional that you have trouble sleeping? \u0026quot;. Sleep disorder were categorized into two groups based on the responses: non-sleep disorder and sleep disorder.\u003c/p\u003e\n \u003cp\u003eThe serum samples involved in the outcome of this study for thyroid function indices included TSH, FT3, FT4, TT3, TT4, thyroglobulin (TG), TPOAb, and TGAb.The NHANES Laboratory/Healthcare Technician Procedures Manual for specimen collection and processing provides a comprehensive and detailed description of the methodology used in the collection and processing of serum specimens. TPOAb\u0026thinsp;\u0026gt;\u0026thinsp;9.0 IU/mL and TGAb\u0026thinsp;\u0026gt;\u0026thinsp;4.0 IU/mL were classified as positive, respectively.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.3 Covariates\u003c/h2\u003e\n \u003cp\u003eCovariates in this study included race (Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black, and other races), age, sex (male and female), education (less than high school, high school or equivalent, and high school above), marital status (married/living with partner, widowed/divorced/separated, never married), BMI (less than normal, normal, overweight, obesity), PIR (low, medium, high), smoking status (no and yes), diabetes (no and yes), hypertension (no and yes) data were analyzed. Socioeconomic status was assessed using PIR values, and PIR was divided into three groups: low (\u0026lt;\u0026thinsp;1.5), medium (1.5\u0026ndash;3.5), and high (\u0026gt;\u0026thinsp;3.5). Weight was divided into four groups: below normal (\u0026le;\u0026thinsp;18.5 kg/m2), normal (\u0026gt;\u0026thinsp;18.5 and \u0026le;\u0026thinsp;25.0 kg/m2), overweight (\u0026gt;\u0026thinsp;25.0 and \u0026le;\u0026thinsp;30.0 kg/m2), and obese (\u0026gt;\u0026thinsp;30 kg/m2).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Mendelian randomization analysis\u003c/h2\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.1 Data source\u003c/h2\u003e\n \u003cp\u003eThe exposures included in this study were sleep traits, where sleep traits were categorized as long sleep, short sleep, sleep duration, and insomnia; and the outcomes included were thyroid-related disorders, which included hyperthyroidism, hypothyroidism, HT, and GD. Ethical approval or informed consent was not required as the data were obtained from secondary analyses of publicly available data sources. Specific information on the GWAS data in this study is detailed in the supplementary material: Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThyroid function and thyroid autoimmunity of NHANES (2007\u0026ndash;2012) study population in sleep duration groups and sleep disorder groups.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eShort sleep\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLong sleep\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-sleep disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6919(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2816(40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3934(56.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169(2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6919(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5346(77.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1573(22.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2989(43.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e770(27.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2150(54.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(40.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3117(45.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2747(51.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e370(23.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3930(56.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2046(72.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1784(45.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100(59.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3802(54.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2599(48.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1203(76.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (year)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.07\u0026thinsp;\u0026plusmn;\u0026thinsp;18.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.66\u0026thinsp;\u0026plusmn;\u0026thinsp;17.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.02\u0026thinsp;\u0026plusmn;\u0026thinsp;21.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52.18\u0026thinsp;\u0026plusmn;\u0026thinsp;19.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.69\u0026thinsp;\u0026plusmn;\u0026thinsp;13.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e232(3.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100(3.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119(3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(7.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e219(3.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e184(3.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e162(2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83(2.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63(1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(9.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143(2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111(2.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5345(77.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2324(82.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2912(74.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109(64.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5340(77.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3942(73.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1398(88.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e986(14.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e209(7.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e756(19.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(12.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1040(15.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e961(17.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79(5.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther-race\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e194(2.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100(3.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84(2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(5.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e177(2.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e148(2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(1.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m2)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47(0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(3.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43(0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36(0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2567(37.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e939(33.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1570(39.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58(33.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2713(39.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1720(32.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e993(63.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2515(36.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1343(47.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1116(28.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56(33.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2306(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2050(38.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e256(16.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1790(25.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e518(18.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1222(31.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50(29.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1857(26.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1540(28.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e317(20.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoke\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4031(58.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1253(44.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2688(68.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90(53.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4260(61.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3125(58.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1135(72.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2888(41.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1563(55.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1246(31.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79(47.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2659(38.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2221(41.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e438(27.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoverty-to-income ratio\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1355(19.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e970(34.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e311(7.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e74(44.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1114(16.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e896(16.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e218(13.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4362(63.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1284(45.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3015(76.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63(37.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4618(66.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3618(67.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1000(63.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1202(17.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e562(19.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e608(15.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(18.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1187(17.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e832(15.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e355(22.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1775(25.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e822(29.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e898(22.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55(32.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1661(24.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1515(28.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e146(9.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e702(10.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e355(12.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e290(7.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57(33.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e642(9.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e460(8.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e182(11.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4442(64.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1639(58.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2746(69.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57(33.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4616(66.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3371(63.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1245(79.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried, or living with partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4476(64.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1710(60.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2679(68.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87(51.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4598(66.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3352(62.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1246(79.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidowed, divorced, or separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1078(15.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e826(29.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e209(5.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43(25.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e881(12.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e684(12.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e197(12.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1365(19.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e280(9.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1046(26.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(22.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1440(20.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1310(24.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e130(8.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4887(70.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1829(64.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2955(75.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103(61.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5005(72.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3754(70.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1251(79.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2032(29.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e987(35.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e979(24.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66(38.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1914(27.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1592(29.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e322(20.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6036(87.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2701(95.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3185(80.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e150(88.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5951(86.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4469(83.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1482(94.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e883(12.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115(4.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e749(19.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(11.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e968(13.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e877(16.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91(5.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTSH (mIU/L)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFT3 (pg/mL)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFT4 (ng/dL)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT3 (ng/dL)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e107.33\u0026thinsp;\u0026plusmn;\u0026thinsp;18.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113.73\u0026thinsp;\u0026plusmn;\u0026thinsp;16.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111.61\u0026thinsp;\u0026plusmn;\u0026thinsp;22.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109.51\u0026thinsp;\u0026plusmn;\u0026thinsp;16.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121.80\u0026thinsp;\u0026plusmn;\u0026thinsp;19.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT4 (ug/dL)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG (ng/mL)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.62\u0026thinsp;\u0026plusmn;\u0026thinsp;19.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.09\u0026thinsp;\u0026plusmn;\u0026thinsp;18.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.54\u0026thinsp;\u0026plusmn;\u0026thinsp;25.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.12\u0026thinsp;\u0026plusmn;\u0026thinsp;19.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.61\u0026thinsp;\u0026plusmn;\u0026thinsp;18.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPOAb\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1501\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6654(96.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2687(95.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3813(96.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154(90.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6669(96.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5163(96.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1506(95.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e265(3.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e129(4.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121(3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(9.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250(3.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e183(3.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67(4.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTGAb\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3568\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6750(97.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2739(97.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3856(98.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e155(91.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6761(97.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5229(97.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1532(97.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169(2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77(2.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78(1.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(8.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158(2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e117(2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41(2.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003csup\u003ea\u003c/sup\u003e :Continuous Variables: weighted mean (SD).\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003csup\u003eb\u003c/sup\u003e :Categorical variable: actual frequency (weighted percentage).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eAbbreviations: TSH, thyroid-stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TT3, total T3; TT4, total T4; TG, thyroglobulin; TPOAb, thyroid peroxidase antibody; TGAb: thyroglobulin antibody; BMI, body mass index; SD, Standard deviation.\u003c/p\u003e\n \u003cp\u003eHassan S Dashti et al.\u003csup\u003e21\u003c/sup\u003e obtained genetic association data on sleep duration using GWAS data published by the UK Biobank for 446,118 adults of European ancestry. In this study, the mean self-reported habitual sleep duration was 7.2 hours with a standard deviation of 1.1 hours. Subsequent analysis converted the continuous variable of sleep duration into a categorical variable. There were 106,192 cases of short sleep (\u0026lt;\u0026thinsp;7 hours) and 34,184 cases of long sleep (\u0026ge;\u0026thinsp;9 hours).\u003c/p\u003e\n \u003cp\u003eJacqueline M Lane et al.\u003csup\u003e22\u003c/sup\u003e analyzed self-reported insomnia symptoms in 453,379 European participants in the UK Biobank. Participants were asked to answer the question \u0026ldquo;Do you have difficulty falling asleep or wakeing up in the middle of the night?\u0026rdquo;. The analysis showed that 29% reported frequent insomnia symptoms (\u0026ldquo;usually\u0026rdquo;), and the prevalence was higher in women (32% vs. 24%) and older participants, shift workers, and those who self-reported shorter sleep duration.\u003c/p\u003e\n \u003cp\u003eThe GWAS data of hyperthyroidism and hypothyroidism were obtained from IEU OPEN GWAS. The genetic association data of hyperthyroidism included 3545 cases and 459,388 controls. The genetic association data of hypothyroidism included 22,687 cases and 440,246 controls.\u003c/p\u003e\n \u003cp\u003eThe GWAS data for HT and GD were compiled and published in 2021 by Saori Sakaue et al.\u003csup\u003e23\u003c/sup\u003e. The pooled data for GD included 395,640 European participants (15,654 cases and 379,986 controls). The pooled GWAS data for HT included 458,620 European participants (1678 cases and 456,942 controls).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.2 Selection of instrument variables\u003c/h2\u003e\n \u003cp\u003eThe selection criteria for instrumental variables (IVs) were as follows:(\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) single nucleotide polymorphism (SNP) loci with genome-wide significance were screened from the exposure database. (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) Perform the PLINK clustering algorithm with a 10,000 kb linkage disequilibrium (LD) window to ensure independence (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) Excluded SNP with F statistic\u0026thinsp;\u0026lt;\u0026thinsp;10, as F\u0026thinsp;\u0026gt;\u0026thinsp;10 indicates strongly associated IVs.(\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e) Harmonized the exposure and outcome datasets and excluded palindromic sequences to ensure that the effects of SNP on exposure and outcome were from the same allele. SNP used as IVs in this study are listed in Supplementary material: Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, 4, and 5.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of sleep duration and sleep disorders on thyroid function.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel 1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel 2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTSH (mIU/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15(0.06,0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09(\u0026minus;0.01,0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97(0.66,1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85(0.54,1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01(\u0026minus;0.10,0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.06(\u0026minus;0.17,0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFT3 (pg/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.04(\u0026minus;0.07,\u0026minus;0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.03(\u0026minus;0.06,\u0026minus;0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.12(\u0026minus;0.21,\u0026minus;0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.06(\u0026minus;0.14,0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1517\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.08(\u0026minus;0.11,\u0026minus;0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.02(\u0026minus;0.06,,0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFT4 (ng/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01(\u0026minus;0.00,0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01(\u0026minus;0.00,0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02(\u0026minus;0.00,0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01(\u0026minus;0.01,0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2219\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.01(\u0026minus;0.02,0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.01(\u0026minus;0.02,0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT3 (ng/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;1.08(\u0026minus;2.26,0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.47(\u0026minus;1.62,0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;5.06(\u0026minus;8.85,\u0026minus;1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;2.83(\u0026minus;6.46,0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;1.83(\u0026minus;3.20,\u0026minus;0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.11(\u0026minus;1.47,1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8690\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT4 (ug/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u0026minus;0.00(\u0026minus;0.08,0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04(\u0026minus;0.04,0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25(\u0026minus;0.01,0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21(\u0026minus;0.04,0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0961\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.04(\u0026minus;0.13,0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.11(\u0026minus;0.20,\u0026minus;0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eModel 1\u003csup\u003ea\u003c/sup\u003e: no covariates were adjusted.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eModel 2\u003csup\u003eb\u003c/sup\u003e: age, gender, race, poverty-to-income ratio, marital, body mass index, smoke, education level, marital status, hypertension, diabetes were adjusted.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations: TSH, thyroid-stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TT3, total T3; TT4, total T4; TG, thyroglobulin.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of sleep duration and sleep disorders on thyroid autoimmunity.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel 1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel 2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTPOAb\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14(0.96,1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03(0.86,1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7563\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64(1.02,2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39(0.85,2.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90(0.73,1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83(0.67,1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0803\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTGAb\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21(0.98,1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10(0.88,1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong sleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.23(1.33,3.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.81(1.06,3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0288\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-sleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleep disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77(0.60,1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72(0.56,0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eModel 1\u003csup\u003ea\u003c/sup\u003e: no covariates were adjusted.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eModel 2\u003csup\u003eb\u003c/sup\u003e: age, gender, race, poverty-to-income ratio, marital, body mass index, smoke, education level, marital status, hypertension, diabetes were adjusted.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations: TSH, thyroid-stimulating hormone; FT3, free triiodothyronine; FT4, free thyroxine; TT3, total T3; TT4, total T4; TG, thyroglobulin.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Statistical Analyses\u003c/h2\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.1 Cross-Sectional study\u003c/h2\u003e\n \u003cp\u003eAll statistical analyses were performed according to the recommendations of the Centers for Disease Control and Prevention using appropriate NHANES sampling weights. Continuous variables are expressed as standard deviation (x\u0026thinsp;\u0026plusmn;\u0026thinsp;s), whereas categorical variables are expressed as n (%). Between-group differences were assessed by weighted linear regression for continuous variables or weighted chi-square test for categorical variables. The association between sleep behavior and thyroid was studied by multiple linear regression using two different models. The first model did not adjust for covariates. The second model adjusted for age, gender, race, education, marital status, PIR, BMI, smoking, diabetes, and hypertension.\u003c/p\u003e\n \u003cp\u003eAll analyses were performed by EmpowerStats (4.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.empowerstats.com\u003c/span\u003e\u003c/span\u003e) and R software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org\u003c/span\u003e\u003c/span\u003e) using MEC weights. p values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.2 Two-Sample mendelian randomization\u003c/h2\u003e\n \u003cp\u003eAll MR analyses were performed using the TwoSampleMR package in R (4.2.1) software. In this study, the inverse variance weighted (IVW) method was used to pool the Wald estimates of individual SNP for weighted linear regression to summarize the total effect value. IVW, as the main analysis method, can provide unbiased causal effect estimates in the absence of horizontal pleiotropy. At the same time, to improve the robustness of the results, MR-Egger regression and weighted median estimator (WME) were used as supplementary methods of IVW because these methods can provide more reliable effect estimates under more relaxed conditions. In addition, we also used Cochran\u0026apos;s Q test calculated by the IVW method to estimate heterogeneity. At the same time, the MR-Egger intercept test was used to evaluate and correct for potential pleiotropy. Finally, the robustness of the results was further verified by observing the funnel plot and leave-one-out plot.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline characteristics\u003c/h2\u003e \u003cp\u003eThe baseline characteristics of the participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. After strict screening, a total of 6919 subjects were included in this study. In the sleep duration group, 3930 (56.80%) were female, 5345 (77.25%) were non-Hispanic white, 2567 (37.10%) had normal BMI, 4362 (63.04%) had a medium PIR level, 4442 (64.20%) had an education level higher than high school, and 4476 (64.69%) were married or living with a partner. In addition, there were 2032 cases of hypertension, 883 cases of diabetes, and 2888 cases of smoking, of which 265 were TPOAb positive and 169 were TGAb positive. In the sleep disorder group, 3802 (54.95%) were female, 5340 (77.18%) were non-Hispanic white, 2713 (39.21%) had normal BMI, 4618 (66.74%) had a medium family income, 4616 (66.71%) had an education level higher than high school, and 4598 (66.45%) were married or living with a partner. In addition, 1914 had hypertension, 968 had diabetes, and 2659 smoked, of which 183 were TPOAb positive and 158 were TGAb positive.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Relationship between sleep traits and thyroid\u003c/h2\u003e \u003cp\u003eThe results of the multivariate regression analyses have been presented in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In Model 2 adjusted for covariates, we found significantly higher TSH levels in the long-sleep group compared to those in the short-sleep group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 β\u0026thinsp;=\u0026thinsp;0.85, 95% CI: 0.54, 1.15). FT3 levels were lower in the normal group compared to those with short sleep (P\u0026thinsp;=\u0026thinsp;0.0030 β = -0.06, 95% CI: -0.06, -0.00). Lower TT4 levels were also found in people with sleep disorder compared to those with non-sleep disorder (P\u0026thinsp;=\u0026thinsp;0.0157 β = -0.11, 95% CI: -0.20, -0.02).\u003c/p\u003e \u003cp\u003eIn terms of thyroid autoimmunity, from model 2, it was found that long sleep was positively associated with the risk of TGAb positivity (P\u0026thinsp;=\u0026thinsp;0.0288 OR\u0026thinsp;=\u0026thinsp;1.81, 95% CI 1.06, 3.07), whereas sleep disorder were negatively associated with TGAb positivity (P\u0026thinsp;=\u0026thinsp;0.0176 OR\u0026thinsp;=\u0026thinsp;0.72, 95% CI: 0.56, 0.95).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Mendelian randomization analysis\u003c/h2\u003e \u003cp\u003eAll MR analysis results have been presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. IVW results indicate that there may be a positive association between long sleep and the risk of GD (P\u0026thinsp;=\u0026thinsp;0.0240 OR\u0026thinsp;=\u0026thinsp;99.98, 95% CI 1.83, 5453.63), while there may be a negative association between sleep duration and the risk of HT (P\u0026thinsp;=\u0026thinsp;0.0294 OR\u0026thinsp;=\u0026thinsp;0.72, 95% CI 0.54, 0.97). In this study, there was heterogeneity between sleep traits and hypothyroidism, heterogeneity between sleep duration and hyperthyroidism, heterogeneity between short sleep and insomnia and GD, and the remaining results showed no heterogeneity. or pleiotropic effects (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Supplementary material: Table\u0026nbsp;6). We also observed the funnel plot, which was roughly symmetrical, indicating that the risk of bias was relatively low and the results were highly reliable (Supplementary material: Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The leave-one-out method was used to eliminate SNP one by one, and no specific SNP was found to cause significant changes in the results (Supplementary material: Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis study is the first to combine large-scale observational study data and MR analysis to explore the association between sleep traits and thyroid. In terms of thyroid function, cross-sectional studies have shown that compared with short sleep, long sleep TSH levels are significantly higher, and normal sleep FT3 levels are lower. It was also found that people with sleep disorder had lower TT4 levels than those with non-sleep disorder. In terms of thyroid autoimmunity, the study found that long sleep was positively correlated with the risk of TGAb positivity, while sleep disorder were negatively correlated with the risk of TGAb positivity. In addition, further two-sample MR analysis verified this conclusion, indicating that there may be a positive correlation between long sleep and GD risk, and there may be a negative correlation between sleep duration and HT risk.\u003c/p\u003e \u003cp\u003eThe HPT axis is controlled by the circadian rhythm system, which plays a key role in the sleep-wake cycle, and disruption of one axis leads to dysregulation of the other\u003csup\u003e24\u003c/sup\u003e. The results of previous studies have assessed, to varying degrees, the effects of sleep on thyroid function. There is evidence that sleep affects thyroid hormone secretion, leading to a decrease in the circadian amplitude of TSH, which in turn feedback suppresses thyroid hormones through the HPT axis\u003csup\u003e25\u003c/sup\u003e. Previous observational studies have observed circadian rhythm changes in TSH secretion to varying degrees\u003csup\u003e26\u0026ndash;29\u003c/sup\u003e. Epidemiologic findings suggest that there are long-term effects of chronic circadian rhythm disruption on human health, and indeed chronic sleep deprivation disrupts rhythmic TSH secretion\u003csup\u003e24,30\u003c/sup\u003e. Although acute, extreme deprivation increases TSH secretion and increases the surge in TSH release, chronic, moderate sleep deprivation suppresses the effects of circadian TSH secretion\u003csup\u003e19\u003c/sup\u003e. The results of a recent study showed an increase in TSH levels and a decrease in FT3 levels with increasing sleep duration, which is broadly similar to our study\u003csup\u003e31\u003c/sup\u003e. A similar circadian rhythmicity of FT3 was found in another study by observing that FT3 peaked 90 minutes after TSH secretion in 86\u0026ndash;100% of participants\u003csup\u003e29\u003c/sup\u003e. In contrast, FT4 did not show a clear circadian rhythm\u003csup\u003e29\u003c/sup\u003e. Regardless of the effects of sleep, TSH is regulated by circadian rhythms. Starting in the evening, concentrations increase dramatically, peak at 2\u0026ndash;3 am, and do not decrease until the afternoon. Thus, although NAHANES self-reported the same sleep duration, the effect of sleep duration on TSH secretion may not be attributable only to duration, but may also vary depending on the individual's sleep onset and termination times. For example, Participant A slept from 9 p.m. to 3 a.m. (when TSH secretion was in the ascending phase), whereas Participant B slept from 2 a.m. to 9 a.m. (when TSH secretion was in the descending phase), and both individuals slept for the same duration of 7 hours; however, the effect of sleep on TSH secretion would differ depending on the period.\u003c/p\u003e \u003cp\u003ePrevious observational studies have shown a correlation between hypothyroidism and sleep. A study based on a Chinese population showed that subclinical hypothyroidism was a risk factor for poor sleep quality\u003csup\u003e18\u003c/sup\u003e. In addition, the results of another single-center retrospective study showed that patients with hypothyroidism were more likely to have early chronotype\u003csup\u003e32\u003c/sup\u003e. A large Korean cohort study showed that either too much or too little sleep was associated with an increased risk of subclinical thyroid dysfunction\u003csup\u003e17\u003c/sup\u003e. However, some studies have taken the opposite view, suggesting that there is no significant difference in subjective sleep measures between individuals with hyperthyroidism and normal thyroid function\u003csup\u003e33\u003c/sup\u003e. Similarly, a study by Akatsu et al. did not find a relationship between subclinical hypothyroidism and sleep quality\u003csup\u003e34\u003c/sup\u003e. The current evidence on the association between sleep and thyroid disorders is controversial, and the results of our MR study found no correlation between sleep traits (sleep duration, long sleep, short sleep, and insomnia) and thyroid disorders (hyperthyroidism and hypothyroidism).\u003c/p\u003e \u003cp\u003eThe association between the HPT axis and sleep can affect thyroid function, and the mutual interference between autoimmunity and sleep duration may further exacerbate the potential impact of sleep on thyroid function\u003csup\u003e35,36\u003c/sup\u003e. Although previously understudied in the context of thyroid autoimmune diseases, sleep disorder have been reported to increase the risk of multiple autoimmune diseases such as systemic lupus erythematosus, rheumatoid arthritis, and ankylosing spondylitis\u003csup\u003e37,38\u003c/sup\u003e. Some clinical studies have also observed that autoimmune disease activity is associated with sleep\u003csup\u003e39,40\u003c/sup\u003e. In addition, sleep is bi-directionally related to the immune system, and sleep can also regulate the immune system\u003csup\u003e35\u003c/sup\u003e. Therefore, sleep may play a role in the immune mechanism of autoimmune thyroid disease. Our cross-sectional study found that long sleep was positively associated with the risk of TGAb positivity, while sleep disorder were negatively associated with TGAb positivity. This was verified in further MR study results, indicating that long sleep may be positively associated with the risk of GD, while sleep duration may be negatively associated with the risk of HT.\u003c/p\u003e \u003cp\u003eThe main strength of this study is that it is the first to combine the NHANES observational study with the MR method to explore the association between sleep traits and thyroid. The strong sample size and thorough adjustment for multiple confounders allowed us to increase the confidence of the study results in the multivariate regression model. Although the cross-sectional study design limits causal inference, the MR analysis essentially produces a natural randomized controlled trial and provides high-power (p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e) and strongly associated (F statistic\u0026thinsp;\u0026gt;\u0026thinsp;10) SNP to evaluate the causal association between sleep traits and thyroid disease. However, we still need to consider the limitations of the study. First, although we tried to control various confounders, the data on sleep traits were self-reported, which may be subject to recall bias. Second, the sleep duration measurement only included sleep time on weekdays or workdays and did not include additional information related to sleep (such as shift work, working conditions, and sleep onset and end times), which limited the further analysis of the study results. Finally, our NHANES study focused on the U.S. population, while the MR study focused on people of European ancestry, which limits the generalizability of the study results. It is necessary to validate the current findings in the same ethnic or other ethnic populations in the future.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eOur cross-sectional study found that sleep duration was associated with TSH and FT3 levels, and sleep disorder were associated with TT4 levels. In terms of thyroid autoimmunity, long sleep was positively correlated with the risk of TGAb positivity, while sleep disorder were negatively correlated with TGAb positivity. Further through MR research, we speculate that long sleep may be positively correlated with the risk of GD, and sleep duration may be negatively correlated with the risk of HT. In the future, it is necessary to conduct more in-depth basic and clinical research to verify the accuracy of the research results and explore its potential mechanism of action.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank all the projects (NHANES, UK Biobank and IEU OPEN\u0026nbsp;GWAS) who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Rongliang Qiu and Jinbo Fu. The first draft of the manuscript was written by Rongliang Qiu and Jinbo Fu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical Approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of interest\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers\u0026rsquo; bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData availability statement\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset analyzed in this study is publicly available and can be accessed as described below. No new data were generated. Data for observational studies were taken from the NHANES website: https://www.cdc.gov/nchs/nhanes/index.html. GWAS statistical summary data were obtained from UK Biobank and IEU OPEN GWAS, and the corresponding studies can be found in the Supplementary Material: tables 2, 3, 4 and 5.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBrent GA. Mechanisms of thyroid hormone action. \u003cem\u003eJ Clin Invest\u003c/em\u003e. Sep 2012;122(9):3035-43. doi:10.1172/JCI60047\u003c/li\u003e\n\u003cli\u003eJing L, Zhang Q. Intrathyroidal feedforward and feedback network regulating thyroid hormone synthesis and secretion. \u003cem\u003eFront Endocrinol (Lausanne)\u003c/em\u003e. 2022;13:992883. doi:10.3389/fendo.2022.992883\u003c/li\u003e\n\u003cli\u003eBrdar D, Gunjaca I, Pleic N, et al. The effect of food groups and nutrients on thyroid hormone levels in healthy individuals. \u003cem\u003eNutrition\u003c/em\u003e. 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Sleep quality in rheumatoid arthritis, and its association with disease activity in a Korean population. \u003cem\u003eKorean J Intern Med\u003c/em\u003e. May 2015;30(3):384-90. doi:10.3904/kjim.2015.30.3.384 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"The School of Clinical Medicine, Fujian Medical University","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":"Mendelian randomization, National Health and Nutrition Examination Survey, sleep traits, cross-sectional study, causality","lastPublishedDoi":"10.21203/rs.3.rs-4840632/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4840632/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eCommon sleep problems reduce quality of life and increase chronic disease risk. The relationship between sleep traits and thyroid function is unclear. This study explores the association between sleep traits and thyroid using NHANES data and Mendelian randomization (MR) analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eData from NHANES 2007-2012 were used to assess the relationship between sleep traits and thyroid function using weighted multivariable-adjusted logistic regression. A two-sample MR study was conducted using GWAS summary statistics, and methods like Inverse Variance Weighted (IVW) were used to explore the causal relationship between sleep traits and thyroid disease. Sensitivity analysis ensured robustness.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003c/em\u003eThe study included 6919 NHANES participants. Logistic regression showed higher TSH levels in the long sleep group (P \u0026lt; 0.0001, β= 0.85, 95% CI: 0.54, 1.15). Lower FT3 levels were found in the normal sleep group (P = 0.0030, β= -0.06, 95% CI: -0.06, -0.00). TT4 levels were lower in those with sleep disorders (P = 0.0157, β= -0.11, 95% CI: -0.20, -0.02). Long sleep was positively associated with TGAb positivity (P = 0.0288, OR = 1.81, 95% CI: 1.06, 3.07), while sleep disorders were negatively associated with TGAb positivity (P = 0.0176, OR = 0.72, 95% CI: 0.56, 0.95). MR analysis indicated a positive association between long sleep and Graves' disease (GD) risk (P = 0.0240, OR = 99.98, 95% CI: 1.83, 5453.63), and a negative association between sleep duration and Hashimoto's thyroiditis (HT) risk (P = 0.0294, OR = 0.72, 95% CI: 0.54, 0.97).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eSleep duration is associated with thyroid hormone levels and autoimmunity. Long sleep is linked to higher TSH levels, lower FT3 levels, and increased TGAb positivity risk, while sleep disorders are linked to lower TT4 levels and decreased TGAb positivity risk. MR studies suggest long sleep may increase GD risk, while shorter sleep may decrease HT risk.\u003c/p\u003e","manuscriptTitle":"Sleep traits and thyroid gland: results from National Health and Nutrition Examination Survey 2007-2012 and Mendelian randomization analyses","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-05 20:27:25","doi":"10.21203/rs.3.rs-4840632/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":"3cdd5806-ff5f-4a4f-975e-e4e13820d09c","owner":[],"postedDate":"August 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":35435973,"name":"Epigenetics \u0026 Genomics"},{"id":35435974,"name":"Nutrition \u0026 Dietetics"},{"id":35435975,"name":"Endocrinology \u0026 Metabolism"},{"id":35435976,"name":"Head \u0026 Neck Surgery"}],"tags":[],"updatedAt":"2024-08-05T20:27:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-05 20:27:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4840632","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4840632","identity":"rs-4840632","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}