Hypothyroidism phenotypes, clinical characteristics and factors associated with nodular thyroid disease in patients with hypothyroidism in southern Ghana: A 6-year retrospective study

Hypothyroidism phenotypes, clinical characteristics and factors associated with nodular thyroid disease in patients with hypothyroidism in southern Ghana: A 6-year retrospective study | 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 Hypothyroidism phenotypes, clinical characteristics and factors associated with nodular thyroid disease in patients with hypothyroidism in southern Ghana: A 6-year retrospective study Samuel Ametepe, Brian Yaw Entsiey Nyarko, Isaac Wormekpor, Bright Kantah, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5705599/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Apr, 2025 Read the published version in BMC Endocrine Disorders → Version 1 posted 3 You are reading this latest preprint version Abstract Background This study aimed to describe the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid among hypothyroid patients at the University of Ghana Hospital in southern Ghana. Methods This study was a 6-year hospital-based retrospective study that extracted data from 221 patients with hypothyroidism from the archival records of the University of Ghana Hospital using a checklist. These include socio-demography (age, gender, marital status, residential status, educational level), lifestyle variables (anthropometry, smoking status, alcohol intake), and co-morbidities, as well as ultrasound imaging findings of the thyroid. Serum thyroid hormone levels were used to classify hypothyroidism phenotypes. Bivariate and multivariate logistic regression analyses were performed to identify factors associated with nodular thyroid disease. Result The frequency of primary, subclinical, and secondary hypothyroidism was 81.4%, 16.3%, and 2.3%, respectively. Fatigue [120(54.3%)], heavy menstrual loss [54/160(33.8%)], and cold intolerance [73(33.0%)], were predominant symptoms while 54/57 (94.7%) were overweight/obese, 23/32 (71.9%) had dyslipidaemia whereas 7/34 (20.6%) had hypertension. The odds of developing nodular thyroid disease were 2.11 times higher (95% CI: 1.07–4.17; p = 0.032) in males than in females. Conclusion Our results provide insight into the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid, emphasizing male gender as an independent predictor of nodular thyroid disease. Our findings also emphasize the need for lifestyle adjustment as a mitigating strategy in the management of hypothyroidism. However, prospective studies are required to confirm the findings or investigate the histological characteristics of thyroid nodules in patients with hypothyroidism. Hypothyroidism phenotypes clinical characteristics nodular thyroid hypothyroidism Figures Figure 1 1. Introduction Hypothyroidism (underactive thyroid disease) is a common thyroid disorder in which the thyroid gland fails to produce enough hormones. Hormones released by the thyroid gland are transported through the bloodstream, where they exert their physiological effect in nearly every part of the body. Thyroid hormones control cellular metabolism that produces the body’s energy needs and thus affects the heartbeat and the body’s temperature ( 1 ). Hypothyroidism affects up to approximately 5% of the general population, with an estimated 5% undiagnosed. In comparison, more than 99% of patients with hypothyroidism present with the primary phenotype ( 2 ). Data derived from the National Health and Nutrition Examination Survey suggest that about one in 300 persons in the United States has hypothyroidism, while autoimmune thyroid disease is the most common etiology of hypothyroidism ( 3 ). A study by Yang et al.( 4 ) also indicates that the prevalence of hypothyroidism increases with age and is higher in females than in males. Moreover, previous studies have shown an association between hypothyroidism and pregnancy. Nicolaou et al. ( 5 ) found that hypothyroidism was present in 2.3–3.5% of pregnancies, with overt hypothyroidism accounting for 0.3–0.5% and subclinical hypothyroidism accounting for 2–3% in iodine-sufficient areas. Meanwhile, worldwide, environmental iodine deficiency is the most common cause of thyroid disorders, including hypothyroidism, but in areas of iodine sufficiency, Hashimoto’s disease (chronic autoimmune thyroiditis) is the most common cause of thyroid failure ( 6 ). The symptoms of hypothyroidism are non-specific, including mild to moderate weight gain, fatigue, poor concentration, depression, and menstrual irregularities, while the consequences of untreated or under-treated hypothyroidism may lead to cardiovascular disease and increased mortality ( 2 ). Also, untreated hypothyroidism can contribute to dyslipidaemia, infertility, cognitive impairment, and neuromuscular dysfunction ( 7 ). In severe hypothyroidism, various comorbidities, including congestive heart failure, pericarditis, pleural effusion, intestinal obstruction, and pseudo-obstruction, as well as coagulation disorders, have been reported ( 8 ), and these could increase the risk of mortality. In sub-Saharan African countries, including Ghana, very little data on thyroid disease exists in the literature. However, a prevalence of 13.1% thyroid disorders was reported in a five-year retrospective analysis to ascertain the spectrum of endocrine disorders in Central Ghana ( 9 ). A recent work by Aidoo et al, ( 10 ) found that primary hypothyroidism (22.3%), euthyroid sick syndrome (6.5%), and subclinical hypothyroidism (4.6%) were among the most frequently reported thyroid disorders. In addition, the frequency of asymptomatic thyroid nodules in a study conducted among six communities in the Assin North District was 11.3% ( 11 ) while 7.7% of hospital admissions from a 9-year review study in a leading tertiary hospital were attributed to thyroid disorders ( 12 ). To reduce endemic iodine deficiency and its consequent disorders among Ghanaians, the universal salt iodization program was instituted in 1996 ( 13 ). However, the program was riddled with poor coverage that resulted from a lack of proper monitoring and coordination of activities. To ascertain its effectiveness, a study that sought to compare the prevalence of thyroid disorders pre- and post-intervention suggests higher rates post-intervention ( 9 ) The outcome, therefore, indicates that the quest to achieve the elimination of iodine deficiency disorders by the World Health Organization (WHO) on the African continent ( 14 – 16 ) had suffered a setback. Moreover, despite the high risk of thyroid disorders, research work focusing on examining the burden of hypothyroidism and its phenotypes, clinical presentations, and factors contributing to the prevalence of thyroid nodular disease remains underexplored in sub-Saharan countries, including Ghana. To bridge this knowledge gap, the current study was designed to describe the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid disease in patients who presented with hypothyroidism in Accra, southern Ghana. 2. Materials and Methods 2.1 Study Design and Study Site The research was a retrospective study spanning a 6-year (2015–2020) review of electronic records of patients diagnosed with hypothyroidism at the University of Ghana Hospital in southern Ghana. The University of Ghana Hospital, also referred to as Legon Hospital, was established and inaugurated in 1957, and the University of Ghana formally owns it. The hospital is located approximately 12.6 kilometers (about 7.83 miles) from the main Accra–Aburi road. The hospital is a quasi-government hospital with a bed capacity of 130, which includes general wards, maternity, casualty and emergency wards, pediatric and dental units, a pharmacy, as well as an operating theatre and laboratory. The hospital was first founded to address the healthcare requirements of the student body, staff, and their dependents, but its services are now open to the public. 2.2 Study Population and Sampling Technique The study population included conveniently sampled patients who were clinically diagnosed with hypothyroidism. 2.3 Inclusion and Exclusion Criteria Data on 228 patients with hypothyroidism were initially extracted from the electronic record of the Hospital. Seven out of 228 patients did not meet the definition of hypothyroidism based on the serum thyroid biomarker levels; hence, these were excluded from the study. The resulting 221 patients were finally included in this study. 2.4 Sample Size Determination Since information on the prevalence of hypothyroidism in Ghana is scanty from existing literature, we could not calculate the sample size for this study hence, the sample size of 221 patients was based on all individuals with hypothyroidism who met the inclusion criteria between 2015 and 2020. 2.5 Data Collection Technique The checklist was designed to capture socio-demography (age, gender, marital status, area of residence, and educational level) lifestyle variables (anthropometry, smoking status, and alcohol intake), and clinical details (signs and symptoms, and co-morbid conditions such as hypertension, diabetes mellitus, renal failure, sickle cell disease, HIV infection, etc.) as well as ultrasound imaging findings (multi nodules, single nodule, and diffused type) and laboratory findings (including hormonal profiles and lipid profiles) from the hospital’s electronic database. 2.5.1 Biochemical Investigation Thyroid function profiles (TSH, FT3, and FT4) available were performed based on the sandwich ELISA (Enzyme-Linked Immunosorbent Assay) method on a microplate reader using reagents from the manufacturers (Human Diagnostics, Germany). Briefly, the sandwich ELISA is an antibody-based technique that quantifies the amount of protein, hormone, or analyte of interest in a sample. Capture and detection antibodies bind to nonoverlapping epitopes on the protein to sandwich the protein, hence the name, Sandwich ELISA. Following the addition of the detection antibody, a chemical substrate is added to produce a colorimetric signal that an ELISA plate reader can read. ( 17 ). The following were the reference ranges of each biomarker based on those provided by the reagent manufacturer; Thyroid-stimulating hormone (TSH) --- 0.3–4.0 mIU/L Free triiodothyronine (FT3) ----------------- 1.4–4.2 pg/ml Free tetraiodothyronine (FT4) ----------- 0.8–2.0 ng/dl 2.6 Definition of Hypothyroidism Phenotypes, Dyslipidaemia and Obesity Subclinical hypothyroidism was defined as low TSH, normal FT4, and FT3 levels. Primary hypothyroidism was defined as elevated TSH, low FT4 and FT3 levels, while secondary hypothyroidism was defined as low TSH, low FT4 and FT3 levels. Dyslipidaemia was defined according to the National Cholesterol Education Program-Adult Treatment Panel (NCEP-ATP) III (TC > 5.17 mmol/l or TG > 1.7 mmol/l or HDL-c < 1.03 mmol/l in men, and HDL-c 4.1 mmol/l) ( 18 ). Overweight and obesity were defined as BMI between 25.00 and 29.9 kg/m 2 and ≥ 30.00 kg/m 2 according to the WHO criteria ( 19 ). 2.7 Data Analysis Data on the hospital’s database, which was based on an Excel Spreadsheet, was extracted, cleaned, and exported to the Statistical Package for Social Sciences (SPSS) software version 22 for analysis. Continuous variables were presented as mean and standard deviation, while categorical variables were presented as frequency and their corresponding proportion. Bivariate and multivariate logistic regression analyses were performed to determine the crude and adjusted odds ratios of factors associated with nodular thyroid. The parameters included in the regression models were age, gender, marital status, educational level, residential status, blood pressure levels, body mass index, dyslipidemia, the presence of chronic conditions, smoking, and alcohol intake statuses. 3. Results This study included 221 eligible patients with hypothyroidism. The majority were females [160 (72.4%)], 143 (64.7%) married, 86 (38.9%) were within the 31–50 years age category while 183(60.2%) were residents within the Accra Metropolis, and 90 (40.7%) had attained a tertiary level of education at the time of this study. The history of current and past smoking statuses were 16/221 (7.2%) and 8/205 (3.9%), respectively, whereas current and past alcohol consumptions were 455/211 (20.4%) and 14/176 (8.0%), respectively (Table 1 ). Table 1 General demographic and behavioral characteristics of the study participants Variables Frequency Percent Total 221 100.0 Age (years) ≤ 30 84 38.0 31–50 86 38.9 51–70 40 18.1 > 70 11 5.0 Marital Status Single 78 35.3 Married 143 64.7 Gender Male 61 27.6 Female 160 72.4 Area of Residence Within-Accra Metropolis 133 60.2 Outside-Accra Metropolis 88 39.8 Educational level Tertiary 90 40.7 Secondary 57 25.8 Basic 38 17.2 None 36 16.3 Body Mass Index*(Total = 57) Normal 3 5.3 Overweight & Obesity 54 94.7 Current Smoking Status No 205 92.8 Yes 16 7.2 Past Smoking Status (Total = 205) No 197 96.1 Yes 8 3.9 Current Alcohol Intake No 176 79.6 Yes 45 20.4 Past Alcohol Intake (Total = 176) No 162 92.0 Yes 14 8.0 Data presented as frequency and the corresponding proportion Clinical presentations at diagnosis among patients with hypothyroidism Fatigue was the most predominant symptom [120(54.3%)], followed by heavy menstrual period [54/160(33.8%)], cold intolerance (33.0%), weight gain (27.6%), constipation (16.7%), and other less frequent symptoms (below 2%). The most frequently observed signs were slow pulse rate (28.1%), heavy hair loss (10.0%), miscarriages 15/160 (9.4%), and tremor (5.9%) (Table 2 ). Table 2 Clinical presentation at diagnosis among patients with hypothyroidism. Variables Frequency Percent Total 221 100.0 Symptoms Fatigue 120 54.3 Heavy Menstrual Period (Total = 160) 54 33.8 Cold Intolerance 73 33.0 Weight Gain 61 27.6 Constipation 37 16.7 Irregular Menstrual period (Total = 160) 3 1.9 Anxiety 4 1.8 Palpitation 3 1.4 Heat Intolerance 1 0.5 Signs Slow Pulse Rate 62 28.1 Heavy Hair Loss 22 10.0 Miscarriages (Total = 160) 15 9.4 Tremor 13 5.9 Rapid Pulse Rate 6 2.7 Eyes and Face Swelling 4 1.8 Excessive Sweating 2 0.9 Data presented as frequency and the corresponding proportion Prevalence of comorbid conditions among patients with hypothyroidism. Thirty-four (34) out of 221 patients reported with chronic conditions. Of these, 7(20.6%) had hypertension, 5 had sickle cell disease (14.7%), and 11.8% each had diabetes mellitus and hepatitis B virus (HBV) infection. Also, 54/57 (94.7%) were overweight/obese, whereas 23/32 (71.9%) had dyslipidaemia (Table 3 ). Table 3 Prevalence of comorbid conditions among patients with hypothyroidism. Comorbidities Frequency Percentage Total 34 15.4 Hypertension 7 20.6 Sickle Cell Disease 5 14.7 Diabetes mellitus 4 11.8 HBV infection 4 11.8 Renal failure 4 11.8 Alzheimer's disease 1 2.9 Arthritis 1 2.9 Asthma 1 2.9 Cancer 1 2.9 Cervical neoplasm 1 2.9 HCV infection 1 2.9 Hypotension 1 2.9 Liver failure 1 2.9 Prostate cancer 1 2.9 Tuberculosis 1 2.9 Overweight & Obesity (Total = 57) 54 94.7 Dyslipidaemia (Total = 32) 23 71.9 Data presented as frequency and the corresponding proportion Prevalence of hypothyroidism phenotypes and ultrasound imaging characteristics of the thyroid among patients with hypothyroidism The most frequent hypothyroidism phenotype was primary hypothyroidism [180 (81.4%)], followed by subclinical hypothyroidism (16.3%). Concerning ultrasound imaging characteristics of the thyroid, 49(22.2%) had multinodules, 30(13.6%) and 28 (12.7%0) had diffuse type and single-nodule, respectively. However, the majority [114(51.6%)] of hypothyroid patients presented with normal thyroid (Fig. 1 ). Factors associated with abnormal thyroid based on ultrasound imaging among study participants The univariate analysis did not reveal any statistically significant association between abnormal thyroid and sociodemographic, lifestyle, and clinical variables of interest. However, upon adjusting for potential confounders in the multivariate analysis, the odds of developing nodular thyroid disease were 2.11 times higher (95% CI: 1.07–4.17; p = 0.032) in males than in females (Table 4 ). Table 4 Factors associated with nodular thyroid based on ultrasound imaging findings among patients with hypothyroidism Thyroid type Variables Total n(%) Nodular n(%)[95% CI) Normal n(%)[95% CI) cOR[95% CI] p-value aOR[95% CI] p-value Overall 221(100) 107(48.4)[41.8–55] 114(51.6)[45–58.2] Age (years) ≤ 30 84(38.0) 43(51.2)[40.5–61.9] 41(48.8)[38.1–59.5] 1 1 31–50 86(38.9) 43(50.0)[39.4–60.6] 43(50.0)[39.4–60.6] 0.95[0.52–1.74] 0.877 1.34[0.55–3.27] 0.515 51–70 40(18.1) 19(47.5)[32.0–63.0] 21(52.5)[37.0–68] 0.86[0.41–1.83] 0.701 1.24[0.43–3.59] 0.687 > 70 11(5.0) 2(18.2)[-4.6–41] 9(81.8)[59.0–104.6] 0.21[0.04–1.04] 0.056 0.26[0.04–1.49] 0.130 Gender Male 61(27.6) 35(57.4)[45.0–69.8] 26(42.6)[30.2–55.0] 0.49[0.10–1.08] 0.103 2.11[1.07–4.17] 0.032 Female 160(72.4) 72(45.0)[37.3–52.7] 88(55.0)[47.3–62.7] 1 1 Marital Status Single 78(35.3) 41(52.6)[41.5–63.6] 37(47.4)[36.4–58.5] 1 1 Married 143(64.7) 66(46.2)[38–54.3] 77(53.8)[45.7–62.0] 0.77[0.45–1.34] 0.363 0.73[0.31–1.75] 0.484 Educational Level Tertiary 90(40.7) 38(42.2)[32.0–52.4] 52(57.8)[47.6–68.0] 1 1 Secondary 57(25.8) 30(52.6)[39.7–65.6] 27(47.4)[34.4–60.3] 1.52[0.78–2.96] 0.218 1.59[0.79–3.20] 0.195 Basic 38(17.2) 18(47.4)[31.5–63.2] 20(52.6)[36.8–68.5] 1.23[0.57–2.64] 0.592 1.36[0.61–3.04] 0.451 None 36(16.3) 21(58.3)[42.2–74.4] 15(41.7)[25.6–57.8] 1.92[0.88–4.19] 0.104 2.21[0.96–5.08] 0.062 Residential Status Within Accra Metro 133(60.2) 60(45.1)[36.7–53.6] 73(54.9)[46.4–63.3] 1 1 Outside Accra Metro 88(39.8) 47(0.032] 41(46.6)[36.2–57.0] 1.39[0.81–2.39] 0.228 1.52[0.86–2.69] 0.153 Blood Pressure Low/Normal 187(84.6) 87(46.5)[39.4–53.7] 100(53.5)[46.3–60.6] 1 1 High 34(15.4) 20(58.8)[42.3–75.4] 14(41.2)[24.6–57.7] 1.64[0.78–3.44] 0.190 1.84[0.84–4.04] 0.130 Body Mass Index* Normal 3(5.3) 2(66.7)[13.3–120.0] 1(33.3)[-20.0–86.7] 1 Overweight/Obesity 54(94.7) 26(48.1)[34.8–61.5] 28(51.9)[38.5–65.2] 0.46[0.04–5.42] 0.541 - Total 57(25.8) 28(49.1)[36.1–62.1] 29(50.9)[37.9–63.9] Dyslipidaemia ¥ No 9(28.1) 7(77.8)[50.6–104.9] 2(22.2)[-4.9–49.4] 1 Yes 23(71.9) 13(56.5)[36.3–76.8] 10(43.5)[23.2–63.7] 0.37[0.06–2.19] 0.274 - Total 32(14.5) 20(62.5)[45.7–79.3] 12(37.5)[20.7–54.3] Chronic Condition No 187(84.6) 92(49.2)[42.0–56.4] 95(50.8)[43.6–58.0] 1 1 Yes 34(15.4) 15(44.1)[27.4–60.8] 19(55.9)[39.2–72.6] 0.91[0.41–2.02] 0.822 0.96[0.41–2.29] 0.932 Past/current smoker No 197(89.1) 95(48.2)[41.2–55.2] 102(51.8)[44.8–58.8] 1 1 Yes 24(10.9) 12(50.0)[30.0–70.0] 12(50.0)[30.0–70.0] 1.07[0.46–2.51] 0.869 0.69[0.27–1.78] 0.447 Past/current drinker No 162(73.3) 81(50.0)[42.3–57.7] 81(50.0)[42.3–57.7] 1 1 Yes 59(26.7) 26(44.1)[31.4–56.8] 33(55.9)[43.3–68.6] 0.79[0.43–1.43] 0.435 0.77[0.40–1.47] 0.432 - Observations too small for logistics regression * Reported for participants whose weight and height measurements were available to calculate BMI ¥ Reported for participants whose lipid profile measurements were available to diagnose dyslipidaemia 4. Discussion In this study, we investigated the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid disease among patients with hypothyroidism based on a retrospective data extracted at a single-center facility in southern Ghana during a 6-year period (2015–2020). We found that primary hypothyroidism was the most frequently reported phenotype of hypothyroidism, followed by subclinical hypothyroidism and secondary or central hypothyroidism based on biochemical findings. Fatigue, heavy menstrual period, and cold intolerance were predominant symptoms, while overweight/obesity, dyslipidaemia, and hypertension were commonly reported co-morbid conditions. The odds of nodular thyroid based on ultrasound findings were significantly higher in males compared to females. According to Chiovato et al. ( 2 ), over 99% of hypothyroid patients suffer from primary hypothyroidism. Jain et al. ( 20 ) also reported that primary hypothyroidism is the most frequent phenotype among Indian patients with hypothyroidism. These findings are consistent with the high frequency of primary hypothyroidism (81.4%), although lower compared to Chiovato et al. ( 2 ), which may be attributed to differences in population characteristics. Conversely, the frequency of subclinical hypothyroidism in our study (16.3%) is moderately higher than the overall prevalence of subclinical hypothyroidism (12.9%) reported in China ( 21 ) but approximately four-fold higher than what was reported in Korea (3.1%) ( 22 ). The difference in the results may be due to the difference in the hospital-based study design adopted for our study as opposed to the population-based nationwide study employed in the Asian studies. It is suggested that iodine deficiency is the most common cause of hypothyroidism globally, underscoring the critical role of iodine in thyroid hormone metabolism, whereas autoimmune thyroiditis (Hashimoto’s disease) is the most common cause of primary hypothyroidism in iodine-replete areas ( 6 ). In Ghana, the 2014 Annual Health Report indicated that iodine deficiency disorders were still high despite the introduction of the mandatory iodization of salt program in 1996 ( 23 ). Sarfo-Kantanka et al. ( 9 ), who compared the prevalence of thyroid disorders before and after the introduction of the program, also found a progressive increase in the prevalence of autoimmune thyroid disorders. Thus, the apparent failure of the iodization intervention program reinforces the need to intensify health education programs aimed at promoting regular consumption of iodine-fortified diets. Screening the healthy population regularly to identify antibodies to the thyroid could help initiate early treatment and management to prevent the development of overt hypothyroidism. Fatigue [120(54.3%)], heavy menstrual loss [54/160(33.8%)], and cold intolerance [73(33.0%)], were predominant in our study participants. The findings in relation to fatigue were corroborated by Ruiz-Pacheco et al. ( 24 ), who reported that 63% of patients with primary hypothyroidism presented with asthenia. Kaudha et al. ( 25 ) also found that fatigue or exercise intolerance was among the prominent symptoms in hypothyroid children with underlying sickle cell anemia, which is in tandem with our findings. In hypothyroidism, the underactive thyroid slows down the body’s metabolism, often leading to many symptoms, including lethargy and fatigue ( 26 ). The frequency of menorrhagia found in this study aligns with a previous study ( 27 ), and it is postulated to be due to complex mechanisms that impair hemostasis in the coagulation cascade and neuro-endocrine dysfunction leading to dysfunctional uterine bleeding ( 28 ). Cold intolerance is associated with hypothyroidism due to the hypoactivity of the thyroid hormones, which are responsible for the regulation of body temperature ( 29 ). The presence of metabolic syndrome or its components, namely, hypertension, insulin resistance, abdominal obesity, and dyslipidemia, is a prominent feature of hypothyroidism, which increases the risk of cardiovascular disease ( 30 ). Consistent with this study's findings, 94.7% of the hypothyroid patients were overweight/obese, 71.9% had dyslipidemia, and 20.6% had hypertension. With regard to nodular thyroid abnormalities, 22.2% had multinodular thyroid glands while 13.6% and 12.7% had diffuse type and single-nodular thyroid gland, respectively, indicating that overall, at least two out of five patients were positive for thyroid gland abnormality upon ultrasound examination. Moreover, the multivariate regression analysis showed that gender is an independent predictor of nodular thyroid. Thus, the odds of developing nodular thyroid disease in males were approximately twice (aOR = 2.11; 95% CI: 1.07–4.17; p = 0.032) higher compared to their female counterparts. The reason for the male preponderance to nodular thyroid disease cannot be inferred directly from our study. However, advancing age and iodine deficiency have been shown to be strongly linked to nodular thyroid disease ( 31 ) which was not assessed in the current study, hence could not be verified. Our findings also highlight the need for thorough clinical assessment and management of nodular thyroid disease among males with hypothyroidism. In contrast, Dauksiene et al. ( 32 ) found that female gender was an independent risk factor for the presence of both goiter and thyroid nodules in euthyroid subjects. Moreover, our study findings contradict the lack of association found between gender and thyroid volume, or nodularity, among type 2 diabetic patients and non-diabetics ( 33 ). Hence, it could also be speculated that differences in the association between gender and nodular thyroid disease may stem from the differences in the sample characteristics. Despite the important findings presented in the current study, some limitations are acknowledged. The retrospective study design did not allow for the collection of comprehensive data, including dietary patterns, which are known to be involved in the pathogenesis of thyroid disorders. The cross-sectional design also limits the interpretation of any causality between the study variables and the outcome. Since this is a hospital-based study, the generalization of the findings is also limited. The adoption of a convenient sampling technique could potentially introduce selection bias, while the classification of nodular thyroid disease was based on imaging findings rather than histological findings, which is widely regarded as the gold standard. Moreover, the findings related to obesity and dyslipidaemia should be interpreted within the context that data were available for only 57 and 32 participants, respectively, whereas a larger part of the electronic records reviewed had missing data. 5. Conclusion Our results provide insight into the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid disease, emphasizing the male gender as an independent predictor of nodular thyroid disease. Our findings also emphasize the need for adjustment in lifestyle practices as a mitigating strategy for the management of hypothyroidism. However, prospective studies are required to confirm the findings or investigate the histological characteristics of thyroid nodules in patients with hypothyroidism. Abbreviations HIV: Human immune deficiency virus TSH: Thyroid stimulating hormone FT3: Free triiodothyronine FT4: Free tetraiodothyronine (FT4) ELISA: Enzyme-linked immunosorbent assay WHO: World Health Organization SPSS: Statistical Package for the Social Sciences TG: Triglycerides HDL- High-density lipoprotein cholesterol NCEP-ATP III- National Cholesterol Education Programme and Adult Treatment Panel III Declarations Ethics approval and consent to participate Ethical approval was obtained from the Research and Ethical Review Committee of the Department of Medical Laboratory Technology, Accra Technical University, with protocol number ATU/MLT/ET/01200009B/2020-2021. The management of the University of Ghana Hospital also gave permission to carry out this study. However, due to the retrospective study design, obtaining consent from participants to participate in this study was not plausible, so this was not required. Consent for publication Not applicable Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author on request . Competing interests There are no competing interests to declare. Funding No funding was obtained for this study. Clinical Trial Number : Not Applicable Authors’ contributions SA, SYL, CO, BYEN, IW, and, BK : Conceptualised and designed the experiments; Carried out the experiments; Provided reagents, logistics, analysis tools, or data; wrote the paper. PKK, ENA, and JOY: Carried out the experiments; Analysed and interpreted the data; wrote the paper. AI, ENYN, BAK, and MA: Provided reagents, logistics, carried out the experiments, analysis tools, or data; wrote the paper. All authors of this paper have read and approved the final version submitted. Acknowledgments We would like to express our appreciation to the management of the University of Ghana Hospital for permitting us to carry out this investigation. References Chawda N, Jain S, Solanki B. Open Access A study of cardiovascular manifestations in hypothyroidism A Study of Cardiovascular Manifestations in Hypothyroidism. Orig Res Ser Endocrinol. 2022;4(3):68–77. Chiovato L, Magri F, Carlé A. Hypothyroidism in Context: Where We’ve Been and Where We’re Going. Adv Ther. 2019;36:47–58. Gaitonde DY, Rowley KD, Sweeney LB. Hypothyroidism: An update. Am Fam Physician. 2012;86(3):244–51. Yang M, Cao S. Gender and Age-Specific Differences in the Association of Thyroid Function and Hyperuricemia in Chinese: A Cross-Sectional Study. Int J Endocrinol. 2022;2022. Nicolaou V, Droste C, Huddle KRL, Dickens C, Menezes CN, Shires R. A retrospective analysis of thyroid disease in pregnancy at chris hani baragwanath academic hospital, Soweto, South Africa. S Afr J Obstet Gynaecol. 2017;23(3):85–8. Vanderpump MPJ. The epidemiology of thyroid disease. Br Med Bull. 2011;99(1):39–51. Devaraj T V., Salina S. Prevalence of hypothyroidism in Kannur; a coastal district in Kerala. Thyroid Res Pract. 2021;18(2):55–60. Kostoglou-Athanassiou I, Ntalles K. Hypothyroidism - New aspects of an old disease. Hippokratia. 2010;14(2):82–7. Sarfo-Kantanka O, Kyei I, Sarfo FS, Ansah EO. Thyroid Disorders in Central Ghana: The Influence of 20 Years of Iodization. J Thyroid Res. 2017;2017. Aidoo ED, Ababio GK, Arko-Boham B, Tagoe EA, Aryee NA. Thyroid dysfunction among patients assessed by thyroid function tests at a tertiary care hospital: a retrospective study. Pan Afr Med J. 2024;49. Morna MT, Tuoyire DA, Jimah BB, Eliason S, Appiah AB, Rahman GA. Prevalence and characterization of asymptomatic thyroid nodules in Assin North District, Ghana. PLoS One [Internet]. 2022;17(2 February):1–12. Available from: http://dx.doi.org/10.1371/journal.pone.0263365 Sarfo-Kantanka O, Ansah EO, Kyei I, Barnes NA. Causes and predictors of mortality among Ghanaians hospitalised with endocrine disorders. Int Health. 2019;12(2):107–15. Nyumuah RO, Hoang TCC, Amoaful EF, Agble R, Meyer M, Wirth JP, et al. Implementing large-scale food fortification in Ghana: lessons learned. Food Nutr Bull. 2012;33(4 Suppl):293–300. Elizabeth N. Pearce, Maria Andersson and MBZ. Global iodine nutrition: where do we stand in 2013? Thyroid Res Pract. 2013;Vol. 23, N. Ogbera A, Kuku S. Epidemiology of thyroid diseases in Africa. Indian J Endocrinol Metab. 2011;15(6):82. Adesunkanmi ARK, Makinde ON. Goitre prevalence in pregnant women attending antenatal clinic in a teaching hospital. J Obstet Gynaecol (Lahore). 2003;23(2):156–9. Fisher T. Elisa Guide ThermoFisher. Kit Man. 2014;597(815):421–4. Rezaianzadeh A, Namayandeh SM, Sadr SM. National Cholesterol Education Program Adult Treatment Panel III versus International Diabetic Federation definition of metabolic syndrome, which one is associated with diabetes mellitus and coronary artery disease? Int J Prev Med. 2012;3(8):552–8. Kanazawa M, Yoshiike N, Osaka T, Numba Y, Zimmet P, Inoue S. Criteria and classification of obesity in Japan and Asia-Oceania. World Rev Nutr Diet. 2005;94:1–12. Jain HK, Sharma AK, Mishra A. Study of clinical profile of hypothyroidism in a tertiary care hospital, Central India. Int J Health Sci (Qassim). 2022;8(7):2594–601. Song B, Lu C, Teng D, Shan Z, Teng W. Association between different metabolic phenotypes of obesity and thyroid disorders among Chinese adults: a nationwide cross-sectional study. Front Endocrinol (Lausanne). 2023;14(April). Kim D, Kim W, Joo SK, Bae JM, Kim JH, Ahmed A. Subclinical Hypothyroidism and Low-Normal Thyroid Function Are Associated With Nonalcoholic Steatohepatitis and Fibrosis. Clin Gastroenterol Hepatol [Internet]. 2018;16(1):123-131.e1. Available from: https://doi.org/10.1016/j.cgh.2017.08.014 Gyamfi D, Wiafe YA, Ofori Awuah E, Adu EA, Boadi EK. Goitre Prevalence and Urinary Iodine Concentration in School-Aged Children in the Ashanti Region of Ghana. Int J Endocrinol. 2020;2020. Ruíz-Pacheco MG, Hernández I, Hernández-Estrella G, Basurto L, Vargas-Ortega G, González-Virla B, et al. Severity of Fatigue and Its Relationship with TSH before and after Levothyroxine Replacement Therapy in Patients with Primary Hypothyroidism. Biomedicines. 2023;11(3). Kaudha G, Piloya T, Musiime V, Kuteesa MG, Namugerwa S, Owomugisha G, et al. Prevalence and factors associated with hypothyroidism in children with sickle cell anemia aged 6 months − 17 years attending the Sickle Cell Clinic, Mulago Hospital, Uganda; a cross-sectional study. BMC Endocr Disord. 2023;23(1):1–9. Stone MB, Wallace RB. Medicare Coverage of Routine Screening for Thyroid Dysfunction. Medicare Coverage of Routine Screening for Thyroid Dysfunction. 2003. Güngör Semiz G, Hekimsoy Z. Menstrual Cycle Characteristics in Women With and Without Thyroid Disease. Cureus. 2024;16(December 2013). Ma B-J. Excessive Uterine Bleeding in a Non-Compliant Patient With Profound Hypothyroidism: A Case Report and Review of the Literatures. J Med Cases. 2016;7(6):234–8. Zhang Z, Boelen A, Kalsbeek A, Fliers E. TRH Neurons and Thyroid Hormone Coordinate the Hypothalamic Response to Cold. Eur Thyroid J. 2018;7(6):279–88. LY a, 1 GP a, 1 ZL c, A LL, A SG, A FL, et al. Impaired sensitivity to thyroid hormones is associated with different grades of hypertension: A multicenter cross-sectional study. Nutr Metab Cardiovasc Dis. 2024;34:1581–9. Popoveniuc G, Jonklaas J. Thyroid Nodules. Med Clin North Am [Internet]. 2012;96(2):329–49. Available from: http://dx.doi.org/10.1016/j.mcna.2012.02.002 Dauksiene D, Petkeviciene J, Klumbiene J, Verkauskiene R, Vainikonyte-Kristapone J, Seibokaite A, et al. Factors Associated with the Prevalence of Thyroid Nodules and Goiter in Middle-Aged Euthyroid Subjects. Int J Endocrinol. 2017;2017. Blanc E, Ponce C, Brodschi D, Nepote A, Barreto A, Schnitman M, et al. Association between worse metabolic control and increased thyroid volume and nodular disease in elderly adults with metabolic syndrome. Metab Syndr Relat Disord. 2015;13(5):221–6. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Apr, 2025 Read the published version in BMC Endocrine Disorders → Version 1 posted Editorial decision: Revision requested 08 Apr, 2025 Submission checks completed at journal 06 Apr, 2025 First submitted to journal 06 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5705599","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":439193955,"identity":"c8cf3927-033e-446f-b8a2-1d82027be03f","order_by":0,"name":"Samuel Ametepe","email":"","orcid":"","institution":"Koforidua Technical University","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Ametepe","suffix":""},{"id":439193957,"identity":"df4ca973-38cc-4ddd-9bb9-ec0f5a818c25","order_by":1,"name":"Brian Yaw Entsiey Nyarko","email":"","orcid":"","institution":"University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Brian","middleName":"Yaw Entsiey","lastName":"Nyarko","suffix":""},{"id":439193958,"identity":"8ed2f013-f2d1-4190-b4b5-c5f4c8b82b60","order_by":2,"name":"Isaac Wormekpor","email":"","orcid":"","institution":"University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Wormekpor","suffix":""},{"id":439193959,"identity":"77dede97-4154-4e14-b13d-fd8e206ccc3e","order_by":3,"name":"Bright Kantah","email":"","orcid":"","institution":"University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Bright","middleName":"","lastName":"Kantah","suffix":""},{"id":439193960,"identity":"a9c4d06d-de0b-4039-94b0-ff54e0ac3e09","order_by":4,"name":"Michael Appiah","email":"","orcid":"","institution":"Accra Technical 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Technology","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Obirikorang","suffix":""},{"id":439193964,"identity":"377e8f1e-db0c-4256-b716-a61c656174f6","order_by":8,"name":"Abigail Ibrahim","email":"","orcid":"","institution":"Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Abigail","middleName":"","lastName":"Ibrahim","suffix":""},{"id":439193965,"identity":"38682e2d-9d7d-469c-b264-55bdb34f579d","order_by":9,"name":"Belinda Ampomah Kwarteng","email":"","orcid":"","institution":"Koforidua Technical University Clinic","correspondingAuthor":false,"prefix":"","firstName":"Belinda","middleName":"Ampomah","lastName":"Kwarteng","suffix":""},{"id":439193966,"identity":"e83e607c-203a-489e-bbe2-546fb96750bb","order_by":10,"name":"Eric NY Nyarko","email":"","orcid":"","institution":"University of Ghana Medical 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Lokpo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYFAC5gY4k/EDjw2IajyAXwsjSIsBRLeETBpYhHgtDDw2h8E0Xi3yMxLbJD78+SNnPiP54QOJnPN2a9sPA22psYnGpcXgRmKb5Mw2A2OZG2nGBgVnbidvO5MI1HIsLbcBlxaJxGZj3gaDxBkSCWYSkj23k80OALUwNhzGqQXosGbjP38M6mdIpH+T4P13Ltns/EP8WhhuJDY+ZmAzSJCQyDGT4OE5YGd2g4AtBmceNj7sbTM2nMHzpthYgic5wewG0JYEPH6Rb08+cODHHzl5Cfb0jQ8/8NjZm51Pf/jgQ40NbocJJKAyEsEqE7AphQH+A6gMe3yKR8EoGAWjYGQCAOs1ZN19/F27AAAAAElFTkSuQmCC","orcid":"","institution":"University of Health and Allied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Sylvester","middleName":"Yao","lastName":"Lokpo","suffix":""}],"badges":[],"createdAt":"2024-12-24 10:38:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5705599/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5705599/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12902-025-01934-z","type":"published","date":"2025-04-22T15:57:40+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80224432,"identity":"00e91833-10c0-486c-bcdf-5a96bd083ebf","added_by":"auto","created_at":"2025-04-09 11:27:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20328,"visible":true,"origin":"","legend":"\u003cp\u003eHypothyroidism phenotypes and sonographic characteristics of the thyroid gland.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5705599/v1/c85697327c342a4bf1cb70a6.png"},{"id":81569871,"identity":"73acbe0d-5c35-40a6-ac46-77db0cfd3efc","added_by":"auto","created_at":"2025-04-28 16:12:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1474370,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5705599/v1/0ef3a2aa-7516-4a60-b217-64eb75ad3f79.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hypothyroidism phenotypes, clinical characteristics and factors associated with nodular thyroid disease in patients with hypothyroidism in southern Ghana: A 6-year retrospective study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHypothyroidism (underactive thyroid disease) is a common thyroid disorder in which the thyroid gland fails to produce enough hormones. Hormones released by the thyroid gland are transported through the bloodstream, where they exert their physiological effect in nearly every part of the body. Thyroid hormones control cellular metabolism that produces the body\u0026rsquo;s energy needs and thus affects the heartbeat and the body\u0026rsquo;s temperature (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHypothyroidism affects up to approximately 5% of the general population, with an estimated 5% undiagnosed. In comparison, more than 99% of patients with hypothyroidism present with the primary phenotype (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Data derived from the National Health and Nutrition Examination Survey suggest that about one in 300 persons in the United States has hypothyroidism, while autoimmune thyroid disease is the most common etiology of hypothyroidism (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A study by Yang et al.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) also indicates that the prevalence of hypothyroidism increases with age and is higher in females than in males.\u003c/p\u003e \u003cp\u003eMoreover, previous studies have shown an association between hypothyroidism and pregnancy. Nicolaou et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) found that hypothyroidism was present in 2.3\u0026ndash;3.5% of pregnancies, with overt hypothyroidism accounting for 0.3\u0026ndash;0.5% and subclinical hypothyroidism accounting for 2\u0026ndash;3% in iodine-sufficient areas. Meanwhile, worldwide, environmental iodine deficiency is the most common cause of thyroid disorders, including hypothyroidism, but in areas of iodine sufficiency, Hashimoto\u0026rsquo;s disease (chronic autoimmune thyroiditis) is the most common cause of thyroid failure (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe symptoms of hypothyroidism are non-specific, including mild to moderate weight gain, fatigue, poor concentration, depression, and menstrual irregularities, while the consequences of untreated or under-treated hypothyroidism may lead to cardiovascular disease and increased mortality (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Also, untreated hypothyroidism can contribute to dyslipidaemia, infertility, cognitive impairment, and neuromuscular dysfunction (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In severe hypothyroidism, various comorbidities, including congestive heart failure, pericarditis, pleural effusion, intestinal obstruction, and pseudo-obstruction, as well as coagulation disorders, have been reported (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), and these could increase the risk of mortality.\u003c/p\u003e \u003cp\u003eIn sub-Saharan African countries, including Ghana, very little data on thyroid disease exists in the literature. However, a prevalence of 13.1% thyroid disorders was reported in a five-year retrospective analysis to ascertain the spectrum of endocrine disorders in Central Ghana (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). A recent work by Aidoo et al, (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) found that primary hypothyroidism (22.3%), euthyroid sick syndrome (6.5%), and subclinical hypothyroidism (4.6%) were among the most frequently reported thyroid disorders. In addition, the frequency of asymptomatic thyroid nodules in a study conducted among six communities in the Assin North District was 11.3% (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) while 7.7% of hospital admissions from a 9-year review study in a leading tertiary hospital were attributed to thyroid disorders (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo reduce endemic iodine deficiency and its consequent disorders among Ghanaians, the universal salt iodization program was instituted in 1996 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, the program was riddled with poor coverage that resulted from a lack of proper monitoring and coordination of activities. To ascertain its effectiveness, a study that sought to compare the prevalence of thyroid disorders pre- and post-intervention suggests higher rates post-intervention (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) The outcome, therefore, indicates that the quest to achieve the elimination of iodine deficiency disorders by the World Health Organization (WHO) on the African continent (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) had suffered a setback.\u003c/p\u003e \u003cp\u003eMoreover, despite the high risk of thyroid disorders, research work focusing on examining the burden of hypothyroidism and its phenotypes, clinical presentations, and factors contributing to the prevalence of thyroid nodular disease remains underexplored in sub-Saharan countries, including Ghana. To bridge this knowledge gap, the current study was designed to describe the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid disease in patients who presented with hypothyroidism in Accra, southern Ghana.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Study Site\u003c/h2\u003e \u003cp\u003eThe research was a retrospective study spanning a 6-year (2015\u0026ndash;2020) review of electronic records of patients diagnosed with hypothyroidism at the University of Ghana Hospital in southern Ghana. The University of Ghana Hospital, also referred to as Legon Hospital, was established and inaugurated in 1957, and the University of Ghana formally owns it. The hospital is located approximately 12.6 kilometers (about 7.83 miles) from the main Accra\u0026ndash;Aburi road. The hospital is a quasi-government hospital with a bed capacity of 130, which includes general wards, maternity, casualty and emergency wards, pediatric and dental units, a pharmacy, as well as an operating theatre and laboratory. The hospital was first founded to address the healthcare requirements of the student body, staff, and their dependents, but its services are now open to the public.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Population and Sampling Technique\u003c/h2\u003e \u003cp\u003eThe study population included conveniently sampled patients who were clinically diagnosed with hypothyroidism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.3 Inclusion and Exclusion Criteria\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eData on 228 patients with hypothyroidism were initially extracted from the electronic record of the Hospital. Seven out of 228 patients did not meet the definition of hypothyroidism based on the serum thyroid biomarker levels; hence, these were excluded from the study. The resulting 221 patients were finally included in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Sample Size Determination\u003c/h2\u003e \u003cp\u003eSince information on the prevalence of hypothyroidism in Ghana is scanty from existing literature, we could not calculate the sample size for this study hence, the sample size of 221 patients was based on all individuals with hypothyroidism who met the inclusion criteria between 2015 and 2020.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data Collection Technique\u003c/h2\u003e \u003cp\u003eThe checklist was designed to capture socio-demography (age, gender, marital status, area of residence, and educational level) lifestyle variables (anthropometry, smoking status, and alcohol intake), and clinical details (signs and symptoms, and co-morbid conditions such as hypertension, diabetes mellitus, renal failure, sickle cell disease, HIV infection, etc.) as well as ultrasound imaging findings (multi nodules, single nodule, and diffused type) and laboratory findings (including hormonal profiles and lipid profiles) from the hospital\u0026rsquo;s electronic database.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.5.1 Biochemical Investigation\u003c/h2\u003e \u003cp\u003eThyroid function profiles (TSH, FT3, and FT4) available were performed based on the sandwich ELISA (Enzyme-Linked Immunosorbent Assay) method on a microplate reader using reagents from the manufacturers (Human Diagnostics, Germany). Briefly, the sandwich ELISA is an antibody-based technique that quantifies the amount of protein, hormone, or analyte of interest in a sample. Capture and detection antibodies bind to nonoverlapping epitopes on the protein to sandwich the protein, hence the name, Sandwich ELISA. Following the addition of the detection antibody, a chemical substrate is added to produce a colorimetric signal that an ELISA plate reader can read. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The following were the reference ranges of each biomarker based on those provided by the reagent manufacturer;\u003c/p\u003e \u003cp\u003eThyroid-stimulating hormone (TSH) --- 0.3\u0026ndash;4.0 mIU/L\u003c/p\u003e \u003cp\u003eFree triiodothyronine (FT3) ----------------- 1.4\u0026ndash;4.2 pg/ml\u003c/p\u003e \u003cp\u003eFree tetraiodothyronine (FT4) ----------- 0.8\u0026ndash;2.0 ng/dl\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Definition of Hypothyroidism Phenotypes, Dyslipidaemia and Obesity\u003c/h2\u003e \u003cp\u003eSubclinical hypothyroidism was defined as low TSH, normal FT4, and FT3 levels. Primary hypothyroidism was defined as elevated TSH, low FT4 and FT3 levels, while secondary hypothyroidism was defined as low TSH, low FT4 and FT3 levels. Dyslipidaemia was defined according to the National Cholesterol Education Program-Adult Treatment Panel (NCEP-ATP) III (TC\u0026thinsp;\u0026gt;\u0026thinsp;5.17 mmol/l or TG\u0026thinsp;\u0026gt;\u0026thinsp;1.7 mmol/l or HDL-c\u0026thinsp;\u0026lt;\u0026thinsp;1.03 mmol/l in men, and HDL-c\u0026thinsp;\u0026lt;\u0026thinsp;1.29 mmol/l in women or LDL-c\u0026thinsp;\u0026gt;\u0026thinsp;4.1 mmol/l) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Overweight and obesity were defined as BMI between 25.00 and 29.9 kg/m\u003csup\u003e2\u003c/sup\u003e and \u0026ge;\u0026thinsp;30.00 kg/m\u003csup\u003e2\u003c/sup\u003e according to the WHO criteria (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Data Analysis\u003c/h2\u003e \u003cp\u003eData on the hospital\u0026rsquo;s database, which was based on an Excel Spreadsheet, was extracted, cleaned, and exported to the Statistical Package for Social Sciences (SPSS) software version 22 for analysis. Continuous variables were presented as mean and standard deviation, while categorical variables were presented as frequency and their corresponding proportion. Bivariate and multivariate logistic regression analyses were performed to determine the crude and adjusted odds ratios of factors associated with nodular thyroid. The parameters included in the regression models were age, gender, marital status, educational level, residential status, blood pressure levels, body mass index, dyslipidemia, the presence of chronic conditions, smoking, and alcohol intake statuses.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThis study included 221 eligible patients with hypothyroidism. The majority were females [160 (72.4%)], 143 (64.7%) married, 86 (38.9%) were within the 31\u0026ndash;50 years age category while 183(60.2%) were residents within the Accra Metropolis, and 90 (40.7%) had attained a tertiary level of education at the time of this study. The history of current and past smoking statuses were 16/221 (7.2%) and 8/205 (3.9%), respectively, whereas current and past alcohol consumptions were 455/211 (20.4%) and 14/176 (8.0%), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral demographic and behavioral characteristics of the study participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e221\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eArea of Residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin-Accra Metropolis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutside-Accra Metropolis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody Mass Index*(Total\u0026thinsp;=\u0026thinsp;57)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight \u0026amp; Obesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent Smoking Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePast Smoking Status (Total\u0026thinsp;=\u0026thinsp;205)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent Alcohol Intake\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePast Alcohol Intake (Total\u0026thinsp;=\u0026thinsp;176)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData presented as frequency and the corresponding proportion\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical presentations at diagnosis among patients with hypothyroidism\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFatigue was the most predominant symptom [120(54.3%)], followed by heavy menstrual period [54/160(33.8%)], cold intolerance (33.0%), weight gain (27.6%), constipation (16.7%), and other less frequent symptoms (below 2%). The most frequently observed signs were slow pulse rate (28.1%), heavy hair loss (10.0%), miscarriages 15/160 (9.4%), and tremor (5.9%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical presentation at diagnosis among patients with hypothyroidism.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e221\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy Menstrual Period (Total\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCold Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight Gain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstipation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular Menstrual period (Total\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalpitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeat Intolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSigns\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlow Pulse Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy Hair Loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiscarriages (Total\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRapid Pulse Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEyes and Face Swelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcessive Sweating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eData presented as frequency and the corresponding proportion\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePrevalence of comorbid conditions among patients with hypothyroidism.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThirty-four (34) out of 221 patients reported with chronic conditions. Of these, 7(20.6%) had hypertension, 5 had sickle cell disease (14.7%), and 11.8% each had diabetes mellitus and hepatitis B virus (HBV) infection. Also, 54/57 (94.7%) were overweight/obese, whereas 23/32 (71.9%) had dyslipidaemia (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of comorbid conditions among patients with hypothyroidism.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSickle Cell Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBV infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlzheimer's disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical neoplasm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCV infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypotension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProstate cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight \u0026amp; Obesity (Total\u0026thinsp;=\u0026thinsp;57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidaemia (Total\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData presented as frequency and the corresponding proportion\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePrevalence of hypothyroidism phenotypes and ultrasound imaging characteristics of the thyroid among patients with hypothyroidism\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe most frequent hypothyroidism phenotype was primary hypothyroidism [180 (81.4%)], followed by subclinical hypothyroidism (16.3%). Concerning ultrasound imaging characteristics of the thyroid, 49(22.2%) had multinodules, 30(13.6%) and 28 (12.7%0) had diffuse type and single-nodule, respectively. However, the majority [114(51.6%)] of hypothyroid patients presented with normal thyroid (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors associated with abnormal thyroid based on ultrasound imaging among study participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe univariate analysis did not reveal any statistically significant association between abnormal thyroid and sociodemographic, lifestyle, and clinical variables of interest. However, upon adjusting for potential confounders in the multivariate analysis, the odds of developing nodular thyroid disease were 2.11 times higher (95% CI: 1.07\u0026ndash;4.17; p\u0026thinsp;=\u0026thinsp;0.032) in males than in females (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with nodular thyroid based on ultrasound imaging findings among patients with hypothyroidism\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eThyroid type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003en(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNodular\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003en(%)[95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003en(%)[95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ecOR[95% CI]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eaOR[95% CI]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107(48.4)[41.8\u0026ndash;55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114(51.6)[45\u0026ndash;58.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(51.2)[40.5\u0026ndash;61.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41(48.8)[38.1\u0026ndash;59.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86(38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(50.0)[39.4\u0026ndash;60.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(50.0)[39.4\u0026ndash;60.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95[0.52\u0026ndash;1.74]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.34[0.55\u0026ndash;3.27]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40(18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(47.5)[32.0\u0026ndash;63.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(52.5)[37.0\u0026ndash;68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86[0.41\u0026ndash;1.83]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.24[0.43\u0026ndash;3.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(18.2)[-4.6\u0026ndash;41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(81.8)[59.0\u0026ndash;104.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21[0.04\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.26[0.04\u0026ndash;1.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61(27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(57.4)[45.0\u0026ndash;69.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(42.6)[30.2\u0026ndash;55.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49[0.10\u0026ndash;1.08]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.11[1.07\u0026ndash;4.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160(72.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72(45.0)[37.3\u0026ndash;52.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88(55.0)[47.3\u0026ndash;62.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78(35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(52.6)[41.5\u0026ndash;63.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(47.4)[36.4\u0026ndash;58.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143(64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(46.2)[38\u0026ndash;54.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77(53.8)[45.7\u0026ndash;62.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77[0.45\u0026ndash;1.34]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.73[0.31\u0026ndash;1.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90(40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38(42.2)[32.0\u0026ndash;52.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52(57.8)[47.6\u0026ndash;68.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57(25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(52.6)[39.7\u0026ndash;65.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(47.4)[34.4\u0026ndash;60.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.52[0.78\u0026ndash;2.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.59[0.79\u0026ndash;3.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38(17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(47.4)[31.5\u0026ndash;63.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(52.6)[36.8\u0026ndash;68.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23[0.57\u0026ndash;2.64]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.36[0.61\u0026ndash;3.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(58.3)[42.2\u0026ndash;74.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(41.7)[25.6\u0026ndash;57.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.92[0.88\u0026ndash;4.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.21[0.96\u0026ndash;5.08]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidential Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin Accra Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133(60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60(45.1)[36.7\u0026ndash;53.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73(54.9)[46.4\u0026ndash;63.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutside Accra Metro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88(39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(0.032]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41(46.6)[36.2\u0026ndash;57.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.39[0.81\u0026ndash;2.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.52[0.86\u0026ndash;2.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood Pressure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow/Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187(84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(46.5)[39.4\u0026ndash;53.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100(53.5)[46.3\u0026ndash;60.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(58.8)[42.3\u0026ndash;75.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(41.2)[24.6\u0026ndash;57.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.64[0.78\u0026ndash;3.44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.84[0.84\u0026ndash;4.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody Mass Index*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(66.7)[13.3\u0026ndash;120.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(33.3)[-20.0\u0026ndash;86.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight/Obesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54(94.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(48.1)[34.8\u0026ndash;61.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(51.9)[38.5\u0026ndash;65.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46[0.04\u0026ndash;5.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57(25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(49.1)[36.1\u0026ndash;62.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(50.9)[37.9\u0026ndash;63.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDyslipidaemia \u0026yen;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(77.8)[50.6\u0026ndash;104.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(22.2)[-4.9\u0026ndash;49.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23(71.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(56.5)[36.3\u0026ndash;76.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(43.5)[23.2\u0026ndash;63.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37[0.06\u0026ndash;2.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(62.5)[45.7\u0026ndash;79.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(37.5)[20.7\u0026ndash;54.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic Condition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187(84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(49.2)[42.0\u0026ndash;56.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95(50.8)[43.6\u0026ndash;58.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(44.1)[27.4\u0026ndash;60.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(55.9)[39.2\u0026ndash;72.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91[0.41\u0026ndash;2.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.96[0.41\u0026ndash;2.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePast/current smoker\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197(89.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95(48.2)[41.2\u0026ndash;55.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102(51.8)[44.8\u0026ndash;58.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(50.0)[30.0\u0026ndash;70.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(50.0)[30.0\u0026ndash;70.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07[0.46\u0026ndash;2.51]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.69[0.27\u0026ndash;1.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePast/current drinker\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162(73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81(50.0)[42.3\u0026ndash;57.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81(50.0)[42.3\u0026ndash;57.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(44.1)[31.4\u0026ndash;56.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(55.9)[43.3\u0026ndash;68.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79[0.43\u0026ndash;1.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.77[0.40\u0026ndash;1.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e- Observations too small for logistics regression\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e* Reported for participants whose weight and height measurements were available to calculate BMI\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u0026yen; Reported for participants whose lipid profile measurements were available to diagnose dyslipidaemia\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we investigated the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid disease among patients with hypothyroidism based on a retrospective data extracted at a single-center facility in southern Ghana during a 6-year period (2015\u0026ndash;2020).\u003c/p\u003e \u003cp\u003eWe found that primary hypothyroidism was the most frequently reported phenotype of hypothyroidism, followed by subclinical hypothyroidism and secondary or central hypothyroidism based on biochemical findings. Fatigue, heavy menstrual period, and cold intolerance were predominant symptoms, while overweight/obesity, dyslipidaemia, and hypertension were commonly reported co-morbid conditions. The odds of nodular thyroid based on ultrasound findings were significantly higher in males compared to females.\u003c/p\u003e \u003cp\u003eAccording to Chiovato et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), over 99% of hypothyroid patients suffer from primary hypothyroidism. Jain et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) also reported that primary hypothyroidism is the most frequent phenotype among Indian patients with hypothyroidism. These findings are consistent with the high frequency of primary hypothyroidism (81.4%), although lower compared to Chiovato et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), which may be attributed to differences in population characteristics. Conversely, the frequency of subclinical hypothyroidism in our study (16.3%) is moderately higher than the overall prevalence of subclinical hypothyroidism (12.9%) reported in China (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) but approximately four-fold higher than what was reported in Korea (3.1%) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The difference in the results may be due to the difference in the hospital-based study design adopted for our study as opposed to the population-based nationwide study employed in the Asian studies.\u003c/p\u003e \u003cp\u003eIt is suggested that iodine deficiency is the most common cause of hypothyroidism globally, underscoring the critical role of iodine in thyroid hormone metabolism, whereas autoimmune thyroiditis (Hashimoto\u0026rsquo;s disease) is the most common cause of primary hypothyroidism in iodine-replete areas (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In Ghana, the 2014 Annual Health Report indicated that iodine deficiency disorders were still high despite the introduction of the mandatory iodization of salt program in 1996 (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Sarfo-Kantanka et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), who compared the prevalence of thyroid disorders before and after the introduction of the program, also found a progressive increase in the prevalence of autoimmune thyroid disorders. Thus, the apparent failure of the iodization intervention program reinforces the need to intensify health education programs aimed at promoting regular consumption of iodine-fortified diets. Screening the healthy population regularly to identify antibodies to the thyroid could help initiate early treatment and management to prevent the development of overt hypothyroidism.\u003c/p\u003e \u003cp\u003eFatigue [120(54.3%)], heavy menstrual loss [54/160(33.8%)], and cold intolerance [73(33.0%)], were predominant in our study participants. The findings in relation to fatigue were corroborated by Ruiz-Pacheco et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), who reported that 63% of patients with primary hypothyroidism presented with asthenia. Kaudha et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) also found that fatigue or exercise intolerance was among the prominent symptoms in hypothyroid children with underlying sickle cell anemia, which is in tandem with our findings. In hypothyroidism, the underactive thyroid slows down the body\u0026rsquo;s metabolism, often leading to many symptoms, including lethargy and fatigue (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The frequency of menorrhagia found in this study aligns with a previous study (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), and it is postulated to be due to complex mechanisms that impair hemostasis in the coagulation cascade and neuro-endocrine dysfunction leading to dysfunctional uterine bleeding (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Cold intolerance is associated with hypothyroidism due to the hypoactivity of the thyroid hormones, which are responsible for the regulation of body temperature (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The presence of metabolic syndrome or its components, namely, hypertension, insulin resistance, abdominal obesity, and dyslipidemia, is a prominent feature of hypothyroidism, which increases the risk of cardiovascular disease (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Consistent with this study's findings, 94.7% of the hypothyroid patients were overweight/obese, 71.9% had dyslipidemia, and 20.6% had hypertension.\u003c/p\u003e \u003cp\u003eWith regard to nodular thyroid abnormalities, 22.2% had multinodular thyroid glands while 13.6% and 12.7% had diffuse type and single-nodular thyroid gland, respectively, indicating that overall, at least two out of five patients were positive for thyroid gland abnormality upon ultrasound examination. Moreover, the multivariate regression analysis showed that gender is an independent predictor of nodular thyroid. Thus, the odds of developing nodular thyroid disease in males were approximately twice (aOR\u0026thinsp;=\u0026thinsp;2.11; 95% CI: 1.07\u0026ndash;4.17; p\u0026thinsp;=\u0026thinsp;0.032) higher compared to their female counterparts. The reason for the male preponderance to nodular thyroid disease cannot be inferred directly from our study. However, advancing age and iodine deficiency have been shown to be strongly linked to nodular thyroid disease (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) which was not assessed in the current study, hence could not be verified. Our findings also highlight the need for thorough clinical assessment and management of nodular thyroid disease among males with hypothyroidism.\u003c/p\u003e \u003cp\u003eIn contrast, Dauksiene et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) found that female gender was an independent risk factor for the presence of both goiter and thyroid nodules in euthyroid subjects. Moreover, our study findings contradict the lack of association found between gender and thyroid volume, or nodularity, among type 2 diabetic patients and non-diabetics (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Hence, it could also be speculated that differences in the association between gender and nodular thyroid disease may stem from the differences in the sample characteristics.\u003c/p\u003e \u003cp\u003eDespite the important findings presented in the current study, some limitations are acknowledged. The retrospective study design did not allow for the collection of comprehensive data, including dietary patterns, which are known to be involved in the pathogenesis of thyroid disorders. The cross-sectional design also limits the interpretation of any causality between the study variables and the outcome. Since this is a hospital-based study, the generalization of the findings is also limited. The adoption of a convenient sampling technique could potentially introduce selection bias, while the classification of nodular thyroid disease was based on imaging findings rather than histological findings, which is widely regarded as the gold standard. Moreover, the findings related to obesity and dyslipidaemia should be interpreted within the context that data were available for only 57 and 32 participants, respectively, whereas a larger part of the electronic records reviewed had missing data.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur results provide insight into the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid disease, emphasizing the male gender as an independent predictor of nodular thyroid disease. Our findings also emphasize the need for adjustment in lifestyle practices as a mitigating strategy for the management of hypothyroidism. However, prospective studies are required to confirm the findings or investigate the histological characteristics of thyroid nodules in patients with hypothyroidism.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHIV: Human immune deficiency virus\u003c/p\u003e\n\u003cp\u003eTSH: Thyroid stimulating hormone\u003c/p\u003e\n\u003cp\u003eFT3:\u0026nbsp;Free triiodothyronine\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFT4: Free tetraiodothyronine (FT4)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eELISA: Enzyme-linked immunosorbent assay\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e\n\u003cp\u003eSPSS: Statistical Package for the Social Sciences\u003c/p\u003e\n\u003cp\u003eTG: Triglycerides\u003c/p\u003e\n\u003cp\u003eHDL- High-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003eNCEP-ATP III- National Cholesterol Education Programme and Adult Treatment Panel III\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Research and Ethical Review Committee of the Department of Medical Laboratory Technology, Accra Technical University, with protocol number ATU/MLT/ET/01200009B/2020-2021.\u0026nbsp;The management of the University of Ghana Hospital also gave permission to carry out this study. However, due to the retrospective study design, obtaining consent from participants to participate in this study was not plausible, so this was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on request\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no competing interests to declare.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e: Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSA, SYL, CO, BYEN, IW, and, BK\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eConceptualised and designed the experiments; Carried out the experiments; Provided reagents, logistics, analysis tools, or data; wrote the paper. PKK, ENA, and JOY: Carried out the experiments; Analysed and interpreted the data; wrote the paper. AI, ENYN, BAK, and MA: Provided reagents, logistics, carried out the experiments, analysis tools, or data; wrote the paper.\u0026nbsp;All authors of this paper have read and approved the final version submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our appreciation to the management of the University of Ghana Hospital for permitting us to carry out this investigation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChawda N, Jain S, Solanki B. Open Access A study of cardiovascular manifestations in hypothyroidism A Study of Cardiovascular Manifestations in Hypothyroidism. Orig Res Ser Endocrinol. 2022;4(3):68\u0026ndash;77. \u003c/li\u003e\n\u003cli\u003eChiovato L, Magri F, Carl\u0026eacute; A. Hypothyroidism in Context: Where We\u0026rsquo;ve Been and Where We\u0026rsquo;re Going. Adv Ther. 2019;36:47\u0026ndash;58. \u003c/li\u003e\n\u003cli\u003eGaitonde DY, Rowley KD, Sweeney LB. Hypothyroidism: An update. Am Fam Physician. 2012;86(3):244\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eYang M, Cao S. Gender and Age-Specific Differences in the Association of Thyroid Function and Hyperuricemia in Chinese: A Cross-Sectional Study. Int J Endocrinol. 2022;2022. \u003c/li\u003e\n\u003cli\u003eNicolaou V, Droste C, Huddle KRL, Dickens C, Menezes CN, Shires R. A retrospective analysis of thyroid disease in pregnancy at chris hani baragwanath academic hospital, Soweto, South Africa. S Afr J Obstet Gynaecol. 2017;23(3):85\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eVanderpump MPJ. The epidemiology of thyroid disease. Br Med Bull. 2011;99(1):39\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eDevaraj T V., Salina S. Prevalence of hypothyroidism in Kannur; a coastal district in Kerala. 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Available from: http://dx.doi.org/10.1371/journal.pone.0263365\u003c/li\u003e\n\u003cli\u003eSarfo-Kantanka O, Ansah EO, Kyei I, Barnes NA. Causes and predictors of mortality among Ghanaians hospitalised with endocrine disorders. Int Health. 2019;12(2):107\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eNyumuah RO, Hoang TCC, Amoaful EF, Agble R, Meyer M, Wirth JP, et al. Implementing large-scale food fortification in Ghana: lessons learned. Food Nutr Bull. 2012;33(4 Suppl):293\u0026ndash;300. \u003c/li\u003e\n\u003cli\u003eElizabeth N. Pearce, Maria Andersson and MBZ. Global iodine nutrition: where do we stand in 2013? Thyroid Res Pract. 2013;Vol. 23, N. \u003c/li\u003e\n\u003cli\u003eOgbera A, Kuku S. Epidemiology of thyroid diseases in Africa. Indian J Endocrinol Metab. 2011;15(6):82. \u003c/li\u003e\n\u003cli\u003eAdesunkanmi ARK, Makinde ON. Goitre prevalence in pregnant women attending antenatal clinic in a teaching hospital. J Obstet Gynaecol (Lahore). 2003;23(2):156\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eFisher T. Elisa Guide ThermoFisher. Kit Man. 2014;597(815):421\u0026ndash;4. \u003c/li\u003e\n\u003cli\u003eRezaianzadeh A, Namayandeh SM, Sadr SM. National Cholesterol Education Program Adult Treatment Panel III versus International Diabetic Federation definition of metabolic syndrome, which one is associated with diabetes mellitus and coronary artery disease? Int J Prev Med. 2012;3(8):552\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eKanazawa M, Yoshiike N, Osaka T, Numba Y, Zimmet P, Inoue S. Criteria and classification of obesity in Japan and Asia-Oceania. World Rev Nutr Diet. 2005;94:1\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003eJain HK, Sharma AK, Mishra A. Study of clinical profile of hypothyroidism in a tertiary care hospital, Central India. Int J Health Sci (Qassim). 2022;8(7):2594\u0026ndash;601. \u003c/li\u003e\n\u003cli\u003eSong B, Lu C, Teng D, Shan Z, Teng W. Association between different metabolic phenotypes of obesity and thyroid disorders among Chinese adults: a nationwide cross-sectional study. Front Endocrinol (Lausanne). 2023;14(April). \u003c/li\u003e\n\u003cli\u003eKim D, Kim W, Joo SK, Bae JM, Kim JH, Ahmed A. Subclinical Hypothyroidism and Low-Normal Thyroid Function Are Associated With Nonalcoholic Steatohepatitis and Fibrosis. Clin Gastroenterol Hepatol [Internet]. 2018;16(1):123-131.e1. Available from: https://doi.org/10.1016/j.cgh.2017.08.014\u003c/li\u003e\n\u003cli\u003eGyamfi D, Wiafe YA, Ofori Awuah E, Adu EA, Boadi EK. Goitre Prevalence and Urinary Iodine Concentration in School-Aged Children in the Ashanti Region of Ghana. Int J Endocrinol. 2020;2020. \u003c/li\u003e\n\u003cli\u003eRu\u0026iacute;z-Pacheco MG, Hern\u0026aacute;ndez I, Hern\u0026aacute;ndez-Estrella G, Basurto L, Vargas-Ortega G, Gonz\u0026aacute;lez-Virla B, et al. Severity of Fatigue and Its Relationship with TSH before and after Levothyroxine Replacement Therapy in Patients with Primary Hypothyroidism. Biomedicines. 2023;11(3). \u003c/li\u003e\n\u003cli\u003eKaudha G, Piloya T, Musiime V, Kuteesa MG, Namugerwa S, Owomugisha G, et al. Prevalence and factors associated with hypothyroidism in children with sickle cell anemia aged 6 months \u0026minus; 17 years attending the Sickle Cell Clinic, Mulago Hospital, Uganda; a cross-sectional study. BMC Endocr Disord. 2023;23(1):1\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eStone MB, Wallace RB. Medicare Coverage of Routine Screening for Thyroid Dysfunction. Medicare Coverage of Routine Screening for Thyroid Dysfunction. 2003. \u003c/li\u003e\n\u003cli\u003eG\u0026uuml;ng\u0026ouml;r Semiz G, Hekimsoy Z. Menstrual Cycle Characteristics in Women With and Without Thyroid Disease. Cureus. 2024;16(December 2013). \u003c/li\u003e\n\u003cli\u003eMa B-J. Excessive Uterine Bleeding in a Non-Compliant Patient With Profound Hypothyroidism: A Case Report and Review of the Literatures. J Med Cases. 2016;7(6):234\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eZhang Z, Boelen A, Kalsbeek A, Fliers E. TRH Neurons and Thyroid Hormone Coordinate the Hypothalamic Response to Cold. Eur Thyroid J. 2018;7(6):279\u0026ndash;88. \u003c/li\u003e\n\u003cli\u003eLY a, 1 GP a, 1 ZL c, A LL, A SG, A FL, et al. Impaired sensitivity to thyroid hormones is associated with different grades of hypertension: A multicenter cross-sectional study. Nutr Metab Cardiovasc Dis. 2024;34:1581\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003ePopoveniuc G, Jonklaas J. Thyroid Nodules. Med Clin North Am [Internet]. 2012;96(2):329\u0026ndash;49. Available from: http://dx.doi.org/10.1016/j.mcna.2012.02.002\u003c/li\u003e\n\u003cli\u003eDauksiene D, Petkeviciene J, Klumbiene J, Verkauskiene R, Vainikonyte-Kristapone J, Seibokaite A, et al. Factors Associated with the Prevalence of Thyroid Nodules and Goiter in Middle-Aged Euthyroid Subjects. Int J Endocrinol. 2017;2017. \u003c/li\u003e\n\u003cli\u003eBlanc E, Ponce C, Brodschi D, Nepote A, Barreto A, Schnitman M, et al. Association between worse metabolic control and increased thyroid volume and nodular disease in elderly adults with metabolic syndrome. Metab Syndr Relat Disord. 2015;13(5):221\u0026ndash;6. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hypothyroidism phenotypes, clinical characteristics, nodular thyroid, hypothyroidism","lastPublishedDoi":"10.21203/rs.3.rs-5705599/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5705599/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aimed to describe the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid among hypothyroid patients at the University of Ghana Hospital in southern Ghana.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study was a 6-year hospital-based retrospective study that extracted data from 221 patients with hypothyroidism from the archival records of the University of Ghana Hospital using a checklist. These include socio-demography (age, gender, marital status, residential status, educational level), lifestyle variables (anthropometry, smoking status, alcohol intake), and co-morbidities, as well as ultrasound imaging findings of the thyroid. Serum thyroid hormone levels were used to classify hypothyroidism phenotypes. Bivariate and multivariate logistic regression analyses were performed to identify factors associated with nodular thyroid disease.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe frequency of primary, subclinical, and secondary hypothyroidism was 81.4%, 16.3%, and 2.3%, respectively. Fatigue [120(54.3%)], heavy menstrual loss [54/160(33.8%)], and cold intolerance [73(33.0%)], were predominant symptoms while 54/57 (94.7%) were overweight/obese, 23/32 (71.9%) had dyslipidaemia whereas 7/34 (20.6%) had hypertension. The odds of developing nodular thyroid disease were 2.11 times higher (95% CI: 1.07\u0026ndash;4.17; p\u0026thinsp;=\u0026thinsp;0.032) in males than in females.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur results provide insight into the frequency of hypothyroidism phenotypes, clinical characteristics, and factors associated with nodular thyroid, emphasizing male gender as an independent predictor of nodular thyroid disease. Our findings also emphasize the need for lifestyle adjustment as a mitigating strategy in the management of hypothyroidism. However, prospective studies are required to confirm the findings or investigate the histological characteristics of thyroid nodules in patients with hypothyroidism.\u003c/p\u003e","manuscriptTitle":"Hypothyroidism phenotypes, clinical characteristics and factors associated with nodular thyroid disease in patients with hypothyroidism in southern Ghana: A 6-year retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-09 11:27:34","doi":"10.21203/rs.3.rs-5705599/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-08T08:38:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-07T02:01:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Endocrine Disorders","date":"2025-04-06T21:56:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c2eff7e0-ff7d-4bb0-b52f-bc6055f07027","owner":[],"postedDate":"April 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T16:05:51+00:00","versionOfRecord":{"articleIdentity":"rs-5705599","link":"https://doi.org/10.1186/s12902-025-01934-z","journal":{"identity":"bmc-endocrine-disorders","isVorOnly":false,"title":"BMC Endocrine Disorders"},"publishedOn":"2025-04-22 15:57:40","publishedOnDateReadable":"April 22nd, 2025"},"versionCreatedAt":"2025-04-09 11:27:34","video":"","vorDoi":"10.1186/s12902-025-01934-z","vorDoiUrl":"https://doi.org/10.1186/s12902-025-01934-z","workflowStages":[]},"version":"v1","identity":"rs-5705599","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5705599","identity":"rs-5705599","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}