Dyslipidemia and its associated factors among Helicobacter Pylori-infected Patients Attending at University of Gondar Comprehensive Specialized Hospital, Gondar, North- West Ethiopia: A Comparative Cross-Sectional Study

Dyslipidemia and its associated factors among Helicobacter Pylori-infected Patients Attending at University of Gondar Comprehensive Specialized Hospital, Gondar, North- West Ethiopia: A Comparative Cross-Sectional 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 Dyslipidemia and its associated factors among Helicobacter Pylori-infected Patients Attending at University of Gondar Comprehensive Specialized Hospital, Gondar, North- West Ethiopia: A Comparative Cross-Sectional Study Abebaw Worede, Marye Nigatie, Tadele Melak, Daniel Asmelash This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1489416/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Dyslipidemia refers to a lipid profile disturbance due to decreased high-density lipoprotein cholesterol and elevated low-density lipoprotein cholesterol, triglycerides, and total cholesterol. H. pylori infection can lead to some appetite-related disorders and significant changes in body weight. For this reason, H. pylori infection may cause deregulated absorption of nutrients in the digestive system, contributing to changes in serum lipids. The purpose of this study is to assess dyslipidemia and its associated factors among Helicobacter Pylori infected patients attending at University of Gondar Comprehensive specialized hospital. Methods: A comparative cross-sectional study was conducted on 231 H. pylori positive and control groups which were included by the convenience sampling technique from March to May 2021 at University of Gondar specialized hospital. Sociodemographic and behavioral characteristic data were collected using a pretested semi structured questionnaire. About 5ml of venous blood were used to determine the lipid profiles using DxC 700 AU chemistry auto analyzer ( Beckman Coulter, USA). The data were entered into Epi-data version 4.6 and analyzed using SPSS version 25. Mann-Whitney U test was used to compare the median of the continuous variables. Multivariable logistic regression analysis was done to determine the associated factors of dyslipidemia. P-value <0.05 is considered statistically significant. Results : The magnitude of dyslipidemia among Helicobacter pylori -infected patients was 71.8% (95% CI: 62.7-79.7). There was a statistically significant difference in lipid profiles between Helicobacter pylori -infected patients and control groups. The median (IQR) of lipid profiles in Helicobacter pylori- positive patients and control groups were for low-density lipoprotein: 108 (89.8, 145.5) vs 95 (79.45, 115.8, P<0.001), for triglycerides: 93 (65,117) vs 83 (58.5, 102, P=0.031), and cholesterol: 143 (119.5, 169,) vs 125 (110,143, P<0.001) mg/dl respectively. Helicobacter pylori infection (95%CI: 1.637-6.966), alcohol drinking (95%CI: 2.616-36.467), unable to read and write (95%CI: 1.384-14.077)), primary school (95%CI: 1.026-9.170), and secondary school (95%CI: 2.167-10.571) were a significant associated variables with dyslipidemia (P<0.05). Conclusion: There was a median lipid profile statistically significant difference between H. pylori positive and control groups. H. pylori infection, educational status, and alcohol drinking habit had statistically significant association of dyslipidemia. Associated factors Dyslipidemia H. pylori Background Dyslipidemia refers to a lipid profile disturbance, including both hyperlipidemia and hypolipidemia ( 3 ). Dyslipidemia can be a metabolically linked category of plasma lipid and lipoprotein deviations from the normal range and is categorized by decreased high-density lipoprotein cholesterol (HDL-C) and elevated low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), and total cholesterol (TC) ( 4 ). The invading of the stomach by H.pylori causes reliable disturbance of the stomach which can affect some biochemical parameters(lipid profiles) in the patient ( 7 ). The underlying possible mechanisms for these conditions are chronic low-grade activation of the coagulation cascade, accelerating atherosclerosis, and antigenic mimicry between H. pylori and host epitopes leading to autoimmune disorders and lipid metabolism abnormality ( 8 ). Scientific facts indicate that H. pylori infection can lead to some appetite-related disorders and significant changes in body weight. Dysregulated absorption of nutrients and the effects of the inflammatory response system caused by H. pylori infection contribute to changes in serum lipids. The change of lipid profiles may also be due to. Several lines of evidence indicate that the secretion of inflammatory cytokines by cells induced by chronic infection of gram-negative bacteria is related to the change of lipid profiles ( 13 ). An experimental investigation indicated that interleukin-8, which is overexpressed in H. pylori -infection, increases the recruitment of T lymphocytes and smooth muscle cells, contributing to atherosclerosis ( 14 ). In addition to this, lipopolysaccharide (LPS) affects circulating macrophages and increases free radical production. It is known that free radicals oxidize LDL, the result of which (oxidized LDL) transforms macrophages into foam cells that are known to be essential in atherosclerosis pathogenesis ( 15 ). With the presence of LPS present in the cell walls of H. pylori , there is the stimulation of large quantities of cytokines (TNF-α, and IL-6) which inhibit lipoprotein lipase activity. The consequence being mobilization of lipid in the tissue through an increase in serum TG level and in contrast, a decrease in serum HDL cholesterol level ( 16 , 17 ). The predominance of dyslipidemia varies from country to country. In USA, 52% of adults had lipid abnormality ( 23 ). In Chinese from study individuals, the predominance of at slightest one sort of unusual lipid concentration was 64.4% ( 24 ). In Nigeria, the prevalence of dyslipidemia extended from 60% among clearly healthy Nigerians ( 25 ). The commitment of dyslipidemia to cardiovascular diseases (CVDs) is apparent from several longitudinal considers which have outlined the affiliation of high levels of LDL-C, TC, TG, and low levels of HDL-C with CVD ( 26 – 28 ). Dyslipidemia is a class of TC and TG metabolism disorders that have consequences for the cardiovascular system, causing pathologies such as vascular coronary disease and atherosclerosis. An increase of TC, LDL-C, and decrease in HDL-C levels in H. pylori -infected people creates an atherogenic lipid profile which could promote atherosclerosis with its complications, myocardial infarction, stroke, and peripheral vascular disease ( 29 ). Different studies have reported different findings regarding the relationship of H. pylori disease and its relation to changes in serum lipid profile. Several studies yield various and sometimes contradictory results; increased, normal, and decreased levels of lipids ( 30 – 33 ). In H. pylori patients, observational studies have found a strong correlation between rising levels of LDL-C or decreasing levels of HDL-C and increased risk of coronary artery disease (CAD) events ( 34 ). Other studies show that H. Pylori could play a role in the development of ischemic heart disease through various means, such as endothelial cell colonization, lipid profile changes, hypercoagulation, platelet aggregation, molecular mimicry mechanism induction, and low-grade systemic inflammation progression ( 35 ). A study in Ethiopia showed that around 87.2% of H. pylori- infected individuals had dyslipidemia in at least one of the four lipid profiles. The distribution of abnormal lipid profile among H. pylori -infected individuals was 51.4%, 67.05%, 38.1%, and 39.3% by serum TC, TG, LDL-C, and HDL-C respectively, whereas the prevalence of dyslipidemia among H. pylori- negative individuals were 20.9%, 40.8%, 16.8% and 43.8% by serum TC, TG, LDL-C, and HDL-C respectively ( 39 ). Dyslipidemia is the most part asymptomatic and is analyzed incidentally or through screening. However, in serious cases, the patient can show one of the indications of the complications (either coronary or peripheral artery illness) such as leg pain, chest pain, dizziness, palpitations, swelling of lower limb or veins (e.g.in neck, or stomach), and blacking out ( 42 ). The effects of H. pylori infection on lipid profiles are still unknown. Several studies have shown varying and occasionally contradictory results, including raised, normal, and decreased lipid levels, all of which have been reported. The study will be used as a source of information about lipid profiles of H. pylori infected patients for the physicians for early detection, treatment, and prevention of lipid abnormalities. This study will also be used to provide supportive evidence for policymakers and evidence-based information to the scientific community about the lipid profiles among H. pylori infected patients. Additionally, this study will serve as baseline information for other researchers in the study area. Therefore aim of this study is assessing dyslipidemia and its associated factors among H. pylori- infected patients attending at University of Gondar comprehensive specialized Hospital from March 10/2021 to May 10/2021, Gondar, North-West Ethiopia Materials And Methods Study population, area, design and period A Hospital-based comparative cross-sectional study design was conducted among H. pylori- infected patients attending the outpatient department of University of Gondar Comprehensive Specialized Hospital (UGCSH) which is located in Gondar town, Amhara Region, North-West Ethiopia. Gondar is found in the North-West of Ethiopia at about 727 Km and 180 Km away from the capital city Addis Ababa and Bahirdar respectively. It is at 12 0 3′ N latitude and 37 0 28′E ( 52 ). The current population of Gondar city is 378,000 and has a total area of 192.3 km 2 with undulating mountainous topography ( 53 ). Currently, the hospital has a catchment population of over 7 million and serving as a referral hospital for all populations in the Central Gondar zone and neighboring district areas. All H. pylori- infected patients attending at UGCSH during the study period and who can participate the study were in the study population. Age matched healthy H. pylori negative adults who were come to Gondar Blood Bank during the study period for controls during the study period. Eligibility criteria Inclusion criteria The inclusion criteria were all H. pylori- infected adult patients aged greater than or equal to 18 years and who were willing to voluntarily participate in the study. All adult healthy H. pylori negative individuals aged greater than or equal to 18years and who were willing to voluntarily participate in the study were included in the control groups. Exclusion criteria Those study participants having TB drug users, antiretroviral treatment users, participants who have hypertension and diabetes mellitus (DM) were excluded by screening and reviewing their medical records. Patients who were severely ill were excluded from the study. Sample size determination and sampling techniques The sample size was determined by using open Epi, version-3 software by considering the following assumptions; mean difference of TG on a study done at the United States of America (USA) ( 51 ), sample 1 mean = 177.2, SD1 = 87.5, sample 2 mean = 148, SD2 = 68.2, 95% Confidence level, and 80% power(0.84) (power approach two mean difference formula). This gives a total of 228 (114 confirmed H. pylori patients and 114 healthy H. pylori negative control groups) study units. A convenience sampling technique was employed to select study participants at UGCSH and adult healthy controls from the Gondar blood bank. When the study participants coming to the medical OPD with complain of gastritis, these patients tested for H. pylori . As the patients have become positive for H. pylori , they were asked to fill written consent for their participation conveniently in this study. Operational definition Dyslipidemia was considered when total cholesterol > 200 mg/dl and/or triglycerides > 150 mg/dl and/or LDL-C > 130 mg/dl and/or, HDL-C < 40 mg/dl; male and/or, HDL-C < 50 mg/dl; female ( 54 ). Alcohol intake was defined as people who never drink any alcohol and people who don't drink alcohol now but did in the past (non-drinkers),and people who drink alcohol one or more days per week (regular drinkers), and (past drinkers) (ex-drinker) ( 55 ). Cigarette Smoking was also defined as None-smoker (individuals who never smoke, and those who smoke before but not current), smoker ( individuals who are currently smoking) ( 55 ). The WHO definition of obesity is based on various categorical cut-points based on the body mass index (BMI) of weight-for-height: underweight (< 18.5 kg/m 2 ), normal weight (18.5–24.9 kg/m 2 ), overweight (25.0–29.9 kg/m 2 ), and obesity (≥ 30 kg/m 2 ) ( 56 ). Physical exercise was considered when a study subject has experience of doing the physical exercise once per day for 20–30 minutes as a continuous activity ( 57 ). Data collection and laboratory methods The socio-demographic characteristics of study participants were collected by using a questionnaire prepared for this study. The questionnaire consisted of the study participant's age, sex, ethnicity, religion, marital status, residence, occupation, educational status, income, and behavioral characteristics such as the habit of physical exercise, smoking habit, and a habit of alcohol drinking, and cigarette smoking. Data for these characteristics were collected by trained nurse through a face-to-face interview. The study participants were interviewed after written informed consent was taken. Height was measured using a height measure scale. Participants stood erect on the stadiometer's floorboard with their backs to the stadiometer's vertical backboard. Both heels of the feet were placed together on the vertical board, with both heels touching the base. The feet were at a 60-degree angle, slightly outward. The participant's shoes and hats were removed during the height assessment. The height measurement was recorded to the nearest 0.1 cm ( 58 ). Before weighing the study subjects, the weight scale was turn to zero. Then participants were asked to remove extra layers of clothing, shoes, jewelers, and any items in their pockets. Then after the participant were asked to step on the scale backward (for confidentiality) body weight was recorded to the nearest 0.1 kg (100 gm) ( 58 ). The waist circumference was measured using a tape measure at the level of the iliac processes and the umbilicus to assess abdominal(central) obesity ( 59 ). The spatial distance between each corresponding hipbone in proportion to the buttocks was determined by measuring the hips with a tape measure ( 60 ). After receiving informed consent from the study participants, 8–12 hours fasting 5 ml of venous blood was collected preferably at the antecubital area by applying a tourniquet. Before collecting the sample, the puncture area of the vein was disinfected by using 70% alcohol. The serum was collected using a serum separator tube at the medical ward department of UGCSH. After collection, specimens were transported to the clinical chemistry unit of the UGCSH laboratory for analysis. The collected blood sample was left for 30 minutes at room temperature. Then the blood samples were centrifuged for 5 minutes at 3500 revolutions per minute (rpm) to separate serum from formed elements. All these procedures were done by the laboratory technologist and principal investigator by applying standard operating procedures (SOPs). The HDL-C, LDL-C, TG, and TC were analyzed by DxC 700 AU auto analyzer (Beckman Coulter, USA). The stool antigen H. pylori RapiCard™ Insta tests were performed for the recruitment of study participants. Data quality assurance and management The questionnaire was prepared both in English and in Amharic, the local language. Five percent ( 12 ) of the sample size was pre-tested at Poly health center. Data collectors were given training in data collection to eliminate technical and observer bias. After completion of each questionnaire, cross-checking was done between the data collector and principal investigator to assure the completeness of the data collected. The label on the test tube and the study participants' unique identification number on the questionnaire were checked. Before patient sample processing, quality controls (normal and pathological) were performed and the study participants’ result was taken after confirmation of the controls were okay. Data analysis and interpretation The results were organized and summarized using frequency, and percentage for categorical variables, median (inter-quartile range) for continuous variables, and using tables. The model of fit was checked by Hosmer and Lemeshow's goodness fit statistic. The Kolmogorov-Smirnov and Shapiro Wilk normality test were conducted to check the normality of continuous variables. Since the continuous variables were not normally distributed, Mann-Whitney U-tests were used to compare the median and interquartile range of these variables. Multivariable logistic regression analysis was done to control possible confounders and to determine factors statistically associated with dyslipidemia. The variables were selected by the backward selection method. The P-values less than 0.05 were considered statically significant. Results Sociodemographic characteristics of study participants This study included 117 H. pylori- infected individuals and 114 H. pylori negative healthy control groups with response rate of 100%. Among the study groups, 117 (50.65%) were females, ranging in age from 18 to 63 years, with a median (IQR) age of 31( 22 , 40 ) years. The median (IQR) age of H. pylori positive and control groups was 32( 22 , 42.5), and 31( 20 , 38 ) years respectively. The urban residence of study participants was 155(67.10%), and 121(52.38%) were married. Based on educational status, 67(29.00%) study participants were from secondary schools, 77(33.33%) of occupation status were students (Table 1 ). Table 1 Sociodemographic characteristics of study subjects (N = 231, UGCSH, Gondar, 2021) Variables. Category H. pylori positive, N = 117 No (%) Control, N = 114 No (%) Total, N = 231 No (%) p-value Age group < 40 68 96 164 0.060 ≥ 40 49 18 67 Sex Male 53(45.3) 61(53.5) 114(49.4) Female 64(54.7) 53(46.5) 117(50.6) 0.486 Residence Rural 62(52.99) 14(12.3) 76(32.9) 0.214 Urban 55(47.01) 100(87.7) 155(67.1) Education Status Illiterate 41(35.0) 13(11.4) 54(23.4) < 0.001 Primary 30(25.6) 6(5.3)) 36(15.5) Secondary 12(10.3) 55(48.2) 67(29.0) ≥College 34(29.1) 40(35.1) 74(32.0) Occupation Student 26(22.2) 51(44.7) 77(33.3) 0.221 Farmer 23(19.7) 6(5.3) 29(12.6) Merchant 5(4.3) 10(8.8) 15(6.5) House wife 37(31.6) 15(13.2) 52(22.5) Gov’t employee 18(15.4) 24(21.0) 42(18.2) Private and others a 8(6.8) 8(7.0) 16(6.9) Marital status Single 32(27.4) 59(51.8) 91(39.4) 0.119 Married 74(63.2) 47(41.2) 121(52.4) Separated b 11(9.4) 8(7.0) 19(8.2) N.B: a = others = priest, b = separated (divorced and widowed) Behavioral and anthropometric characteristics of participants Based on the lifestyle condition of study participants, almost all of the study participants 230 (99.6%) were non-smokers, 214 (92.6%) did not drink alcohol, 229 (99.13%) did not chew Khat, and 196 (84.8%) did not have regular physical exercise. The BMI value of the study participants, 184(79.7%) had normal (18.5–25kg/m2), 17(7.4%) had overweight (≥ 25kg/ m2), and 30 (13.0%) had underweight (< 18.5kg/m2). From the study participants, 215(93.7%) had less than 94cm of waist circumference, and 206(89.2%) had less than 102 cm of the hip circumference (Table 2 ). Table 2 Behavioral and anthropometric characteristics of study participants (N = 231, UGCSH, Gondar, 2021) Pearson’s Chi-square test Variables Category H. pylori positive (117) No (%) Control (114) No (%) Total (231) No (%) P-value Physical Exercise Yes 16(13.7) 19(16.7) 35(15.2) 0.25 No 101(86.3) 95(83.3) 196(84.8) Body mass index 18.5-24.99 kg/m 2 91(77.8) 93(81.6) 184(79.7) 0.309 ≥ 25 kg/m 2 6(5.1) 11(9.6) 17(7.4) < 18.5kg/m 2 20(17.1) 10(8.8) 30(13.0) Alcohol drinking Yes 10(8.5) 7(6.10 17(7.4) < 0.001 No 107(91.5) 107(93.9) 214(92.6) Waist circumference < 94cm 106(90.6) 109(95.6) 215(93.7) 0.113 ≥ 94cm 11(9.4) 5(4.4) 16(6.3) Hip circumference < 102cm 97(82.9) 109(95.6) 206(89.2) 0.020 ≥ 102cm 20(17.1) 5(4.4) 25(10.8) Cigarette smoking Yes 1(0.9) 0 1(0.4) 0.440 No 116(99.1) 114(100) 230(99.6) Khat chewing Yes 0 2(1.8) 2(0.9) 0.065 No 117(100) 112(98.2) 229(99.1) HDL = high density lipoprotein, LDL = low density lipoprotein The magnitude of dyslipidemia among study participants The overall prevalence of dyslipidemia in either of the four lipid profile parameters was 145(62.8%) (95% CI: 56.2–69%). From H. pylori infected patients, the prevalence of dyslipidemia in at least one of the parameters among the four lipid profiles were 71.8% (84/117), (95% CI: 62.7–79.7%, and 53.5% (61/114) (95% CI: 43.9–62.9%) were from control groups (Table 3 ). Table 3 Dyslipidemia among H. pylori positive patients and control groups (N = 231 at UGCSH, Gondar, 2021) Lipid profiles H. pylori status Total Positive Control No (%) 95% CI No (%) 95% CI No (%) 95% CI Decreased HDL-C 53(45.3%) 36.1–54.8 54(47.4) 37.9–56.9 107(46.3) 39.8–53 Increased LDL-C 41(35) 26.5–44.4 11(9.6) 4.9–16.6 52(22.5) 17.3–29.4 Hypercholesterolemia 12(10.3) 3.4–11.2 9(7.9) 0-4.8 21(9.1) 3.0-9.4 Hypertriglyceridemia 12(10.3) 3.4–11.2 1(0.9) 3.1–13.4 13(5.6) 5.4–13.1 Total dyslipidemia 84(71.8) 62.7–79.7 61(53.5) 43.9–62.9 145(62.8) 56.2–69 The serum level of abnormal lipid profile among H. pylori- positive individuals were 53 (45.3%) HDL-C, 41(35%) LDL-C, 12(10.3%) TC, and 12(10.3%) TG, whereas the prevalence of dyslipidemia among control groups were 54 (47.37%), 11 (9.6%), 9(7.9%), and 1(0.9%) of serum HDL-C, LDL-C, TC, and TG respectively (Table 3 ). Associated factors of dyslipidemia among study individuals In bivariable analysis, age, education status, H. pylori infection, alcohol drinking habits, and hip circumference were statistically significant associations with dyslipidemia (P < 0.05). In multivariable analysis, there was a significant association between dyslipidemia with educational status (p = 0.001), alcohol drinking habits (p = 0.001), and H. pylori infection (p = 0.001) (Table 4 ). Table 4 Associated factors of dyslipidemia among study participants (N = 231, Gondar, 2021) Variables Dyslipidemia COR (95% CI) AOR (95% CI) p-value Yes No Age < 40 93 71 1 1 ≥ 40 52 15 2.647 (1.379–5.081) ** 1.6779(0.692–4.063) 0.081 Sex Male 69 45 1 1 1 Female 76 41 1.209(0.709–2.602) 0.860(0.364–2.033) 0.409 Marital status Single 50 41 1 1 1 Married 81 40 1.660(0.948–2.908) 1.328(0.611–2.887) 0.097 Separated 14 5 2.296(0.763–6.908) 1.329(0.360–4.906) 0.099 Residence Rural 52 24 1 1 1 Urban 93 62 0.692(0.387–1.237) 2.308(0.869–6.128) 0.050 Education status Unable to read &write 41 13 4.139(1.907–8.985) *** 4.413(1.384–14.077) ** 0.012* Primary 26 10 3.412(1.441–8.082) ** 3.607(1.026–9.170) 0.045* Secondary 46 21 2.875(1.440–5.740) ** 4.787(2.167–10.571) < 0.001*** College and above 32 42 1 1 1 Occupation status Student 48 29 1 1 1 Farmer 20 9 1.343(0.539–3.341) 0.269(0.039–1.874) 0.331 Merchant 10 5 1.208(0.376–3.887) 0.233(0.034–1.582) 0.124 House wife 38 14 1.640(0.762–3.530) 0.229(0.038–1.373) 0.141 Gov’t employee 21 21 0.604(0.282–1.293) 0.360(0.070–1.841) 0.339 Private 8 8 0.604(0.205–1.784) 0.082(0.011–0.621) 0.019 Alcohol drinking Yes 3 14 9.204(2.562–33.062) ** 9.767(2.616–36.467) ** 0.001** No 142 72 1 1 1 BMI 18.5-24.99kg/m2 111 73 1 1 1 > 24.99kg/m2 12 5 1.578 (.534-4.668) 2.286(0.614–8.505) 0.119 < 18.5 22 8 1.809(.764 − 4.280) 1.869(0.679–5.139) 0.410 Exercise Yes 25 10 1 1 No 120 76 1.583(0.720–3.480) 1.734(0.652–4.614) 0.221 H. pylori status Negative 61 53 1 1 1 Positive 84 33 2.212(1.282–3.816) ** 3.377(1.637–6.966) ** 0.001** WC < 94cm 132 83 1 1 1 ≥ 94cm 13 3 2.725(0.754–9.850) 1.354(0.126–14.533) 0.858 HC < 102cm 124 82 1 1 1 ≥ 102cm 21 4 3.472(1.150-10.483) * 2.123(0.517–8.7140 0.128 *=p < 0.05, **=p < 0.01, ***=p < 0.001, AOR = adjusted odds ratio, BMI = body mass index, COR = crude odds ratio, CI = confidence interval, HC = Hip circumference, WC = waist circumference Comparison of lipid profiles among study participants The median level of serum HDL-C was not statistically significant difference with H. pylori positive and control groups (p = 0.376). But the median serum level of LDL-C, TG, and TC was a statistically significant difference between H. pylori positive and control groups (p < 0.05) (Table 5 ). Table 5 Comparison of lipid profiles among cases and controls (Cases, N = 117, Control-N = 114, Gondar, Ethiopia, 2021) (Mann-whitely U test) Variables H. pylori status P-value positive, median (IQR) Control, median (IQR) age 32(22, 42.5) 31(20, 38) 0.060 HDL-C 41(35, 47) 40(33.75, 44) 0.376 LDL-C 108(89.8, 145.5) 95(79.45, 115.8) < 0.001 TG 93(65, 117) 83(58.5, 102) 0.031 TC 143(119.5, 169) 125(110, 143) < 0.001 HC 89(82.5, 92) 88 (81.75, 93) 0.159 WC 75(69, 86) 77(70.75, 77) 0.837 HDL = High-density lipoprotein, HC = Hip circumference, LDL = low-density lipoprotein, TC = total cholesterol, TG = triglycerides, WC = Waist circumference, P < 0.05 = statistically significant value Discussion The prevalence of dyslipidemia among H.pylori patients in either of the four lipid profiles was 71.8% (95% CI: 62.7–79.7), which was higher than a study conducted in Iran (60.4%) ( 45 ). Our findings, however, were lower than a study done in Ethiopia, which found that 87.2% of H.pylori patients had dyslipidemia ( 39 ). The reason for the variation is most likely related to differences in lifestyle, study design, and sample size. In our finding, the odds of dyslipidemia among peoples unable to read and write were 4.413 times higher (AOR: 4.413; 95% CI: 1.384–14.077, P = 0.012), the odds of dyslipidemia being primary school education status were 3.067 times higher (AOR: 3.067; 95% CI: 1.026–9.170; P = 0.045), and the odds of dyslipidemia among secondary school education status were 4.787 times higher (AOR: 4.787, 95% CI; 2.167–10.571, P < 0.001) compared to higher educational status. Most cardiovascular risk factors were more common at lower educational levels in the most recent National Health Survey, indicating a trend toward better health outcomes as education levels increase ( 61 ). People having a lower level of education are more likely to develop unhealthy eating habits and lifestyles, which can be worsened if their income rises without their level of education ( 62 ). Dyslipidemia was 9.767 times more common in alcoholics than non-alcoholics (AOR: 9.767, 95% CI: 2.616–36.467, P = 0.001) which was consistent with the study done in Korea ( 49 ). This is due to the impact of chronic ethanol drinks on cardiovascular health is through the effect on lipid metabolism ( 63 ). The odds of dyslipidemia with H. pylori infection were 3.377 times higher than control groups (AOR: 3.377; 95% CI; 1.637–6.966, P = 0.001). This finding was agreed with studies done in Ethiopia and Iran ( 39 , 45 ). In our finding, the lipid profiles showed that H. pylori infected individuals have a statistically significant difference in LDL-C, TG, and TC compared with control groups. The HDL-C levels of H. pylori positive and control study participants, however, did not differ significantly. This finding was consistent with a study done in Ethiopia and Iran ( 39 , 45 ). This may be due to the impact of H. pylori infection on lipid metabolism ( 64 ). The current study was consistent with studies conducted in other areas, indicating that H. pylori infection may alter serum lipid concentrations, potentially increasing the risk of CHD. H. pylori positive individuals had a statistically significant higher concentration of LDL-C than those control groups (p < 0.05) ( 30 , 39 , 47 , 50 , 51 ). Our finding shows that the median (IQR) of lipid profiles in H. pylori -positive individuals was significantly greater than in control groups for LDL-C: 108 (89.8, 145.5) vs 95 (79.45, 115.8), for TG: 93 (65, 117) vs 83 (58.5, 102), and TC:143 (119.5, 169) vs 125 (110, 143) mg/dl respectively with P value less than 0.05. This finding was comparable with a study conducted in Iraq ( 65 ) and Japan ( 33 ) that H.pylori infection was associated with an increase in serum cholesterol, TG, and LDL-C. Our findings were also in line with those of a Turkish study on H. pylori -infected patients' serum cholesterol which was considerably higher (189.32 ± 45.15 vs 179.41 ± 36.37) mg/dl (p < 0.05) when compared to the control study participants. The patient's group also had significantly higher serum TG and TC/HDL-c values compared to control groups (169.46 ± 68.53 vs 135.67 ± 94.35) mg/dl (p < 0.05) and 3.93 ± 1.23 vs 3.51 ± 1.62, (p < 0.05) respectively ( 46 ). Our results were comparable with a study done in Ethiopia, the serum LDL-C concentration was higher in H.pylori positive patients than H.pylori negative groups 122 ± 37 vs 104.27 ± 34.71 mg/dl (p < 0.001), serum TG (185.61 ± 74.82 vs 138.18 ± 60.17 mg/dl ( p < 0.001), and, serum TC(200.8 ± 43.48 vs 173.67 ± 42.41 mg/dl (p < 0.001) respectively ( 39 ). Our findings also supported by those of a study conducted in Sudan ( 47 ), the United States ( 51 ), China ( 30 ), and Korea ( 50 ), which found a statistical difference between patients and controls with TC, TG, and LDL-C values with a p-value of < 0.05. Our findings showed that H. pylori infection increased TC, LDL-C, and TG levels in infected participants when compared to control groups. This finding was in line with a Korean study that found H.pylori is associated with higher levels of TC and LDL-C ( 29 ). This is due to a disturbance in food absorption in the digestive system, which causes alterations in serum lipids. The effects of the inflammatory response system caused by H. pylori infection may potentially be responsible for the alteration in lipid profiles ( 13 ). Because of the presence of LPS in the cell walls of gram-negative bacteria like H. pylori , high amounts of cytokines (TNF-α, and IL-6) are released, inhibiting lipoprotein lipase action. The consequence being the mobilization of fat from tissues to blood is responsible for an increase in serum lipid levels ( 16 , 66 ). In contrast, our result was not comparable in a study done in Finland indicate that H. pylori infection was no significant difference in H. pylori positive and control groups with serum TC, LDL-C, and TG. The serum HDL-C concentration in H.pylori positive patients had a significant difference than in control groups (p < 0.001) ( 31 ). Whereas, in our finding LDL-C, TG, and TC concentration was a statistical difference between cases and controls but not in HDL-C. Our findings also not supported by a study done in Iran shows that the value of TG, LDL-C were high and HDL-C was low in H. pylori positive than control groups. But these findings were not a statistical difference between H.pylori positive and control groups ( 32 ). A study was done in China also shows that the value of TG and LDL-C was not statistically different between H.pylori positive and control groups ( 48 ). This is due to differences in the study design, source population, study participants they use, and the way they define dyslipidemia. Conclusion Based on our findings, we conclude that H. pylori patients have more likely to develop dyslipidemia than control (healthy) groups. There is a statistically significant association between H. pylori infection with cardiac and coronary risk factors like a high concentration of LDL-C, TG, and TC. Alcohol drinking habits, and education status were statistically significantly associated with dyslipidemia. For health professionals, monitoring and assessment of serum lipid profiles are important for the management of dyslipidemia. So, patients who had H. pylori infection should be assessed for their serum lipid profiles. Abbreviations AOR: Adjusted Odds Ratio; BP: Blood Pressure; BMI: Body Mass Index; CVDs: Cardio Vascular Diseases; CAD: Coronary Artery Disease; COR: Crude Odds Ratio; DBP: Diastolic Blood Pressure; H. pylori: Helicobacter Pylori; HDL-C: High-Density Lipoprotein Cholesterol; IL: Interleukin; IQR: Inter Quartile Range; LPS: Lipopolysaccharide; LDL-C: Low-density lipoprotein cholesterol; NCDs: Non-Communicable Diseases; SST: Serum Separator Tube; SOPs: Standard Operating Procedures; SPSS: statistical package for Social Science; TGs: Triglycerides; TC: Total Cholesterol; WHO: World Health Organization Declarations Ethics approval and consent to participate Ethical approval was obtained from the Research and Ethical Committee of the School of Biomedical and Laboratory Sciences, the University of Gondar with the reference number of SBLS 2762 on March 08/2021. Data collectors explained the purpose, confidentiality, and discomfort related to the study to each participant and obtained a fully informed written consent. The privacy of information was kept up during and after an interview in which coding was utilized for all the information collected and those who had lipid abnormalities were advised to visit the UGCSH Medical OPD for further diagnosis and treatment. Consent for publication Not applicable Availability of data and materials All the primary data are available and if anyone has a reasonable interest to find the data, he can contact the corresponding author Competing interests The authors declare that they have no competing interests Funding I declared that data collection and laboratory diagnosis were funded by University of Gondar Authors' contributions MN, designed the study, performed the laboratory activity, data analysis and interpretation, AW, developed the manuscript, AW, TM and DA assisted in the design, analysis and interpretation of data and critically evaluated the manuscript. All authors read and approved the fnal manuscript. Acknowledgements We would like to thank study participants, University of Gondar, and data collectors for their cooperation and financial, material, and reagent support References Kim HC, Oh SM. Noncommunicable diseases: current status of major modifiable risk factors in Korea. Journal of preventive medicine and public health. 2013;46(4):165. Bhandari GP, Angdembe MR, Dhimal M, Neupane S, Bhusal C. State of non-communicable diseases in Nepal. BMC public health. 2014;14(1):1-9. Welty FK. Hypobetalipoproteinemia and abetalipoproteinemia. Current opinion in lipidology. 2014;25(3):161. Bays HE, Toth PP, Kris-Etherton PM, Abate N, Aronne LJ, Brown WV, et al. Obesity, adiposity, and dyslipidemia: a consensus statement from the National Lipid Association. Journal of clinical lipidology. 2013;7(4):304-83. Blaser MJ, Atherton JCJTJoci. Helicobacter pylori persistence: biology and disease. 2004;113(3):321-33. de Korwin JD, Ianiro G, Gibiino G, Gasbarrini A. Helicobacter pylori infection and extragastric diseases in 2017. Helicobacter. 2017;22:e12411. Ndebi M, Guimtsop Y, Tamokou JJIJoRiMS. The assessment of risk factors, lipid profile, uric acid and alanine aminotransferase in Helicobacter pylori-positive subjects. 2018;6(9):2889. Kusters JG, Van Vliet AH, Kuipers EJ. Pathogenesis of Helicobacter pylori infection. Clinical microbiology reviews. 2006;19(3):449-90. Klok MD, Jakobsdottir S, Drent ML. The role of leptin and ghrelin in the regulation of food intake and body weight in humans: a review. Obes Rev. 2007;8(1):21-34. Kalra SP, Ueno N, Kalra PS. Stimulation of appetite by ghrelin is regulated by leptin restraint: peripheral and central sites of action. The Journal of nutrition. 2005;135(5):1331-5. Roper J, Francois F, Shue PL, Mourad MS, Pei Z, Olivares de Perez AZ, et al. Leptin and ghrelin in relation to Helicobacter pylori status in adult males. J Clin Endocrinol Metab. 2008;93(6):2350-7. Osawa H, Nakazato M, Date Y, Kita H, Ohnishi H, Ueno H, et al. Impaired production of gastric ghrelin in chronic gastritis associated with Helicobacter pylori. The Journal of Clinical Endocrinology & Metabolism. 2005;90(1):10-6. Khovidhunkit W, Kim M-S, Memon RA, Shigenaga JK, Moser AH, Feingold KR, et al. Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host. The Journal of Lipid Research. 2004;45(7):1169-96. Buzás GM. Metabolic consequences of Helicobacter pylori infection and eradication. World journal of gastroenterology: WJG. 2014;20(18):5226. Ellis R. Infection and coronary heart disease. Journal of Medical Microbiology. 1997;46(7):535-9. Sung KC, Rhee EJ, Ryu SH, Beck S-H. Prevalence of Helicobacter pylori infection and its association with cardiovascular risk factors in Korean adults. International journal of cardiology. 2005;102(3):411-7. Feingold KR, Grunfeld C. Lipids: a key player in the battle between the host and microorganisms. Journal of lipid research. 2012;53(12):2487-9. Aimo A, Borrelli C, Giannoni A, Pastormerlo LE, Barison A, Mirizzi G, et al. Cardioprotection by remote ischemic conditioning: mechanisms and clinical evidences. World journal of cardiology. 2015;7(10):621. Organization WH. Noncommunicable diseases country profiles 2018. 2018. Organization WH. Noncommunicable diseases. Fact sheet. World Health Organisation, Geneva http://www who int/mediacentre/factsheets/fs355/en/ Accessed. 2017;23. Overweight WHO. Global health observatory:Deaths from NCDs. Organization. WH. Global Health Observatory:. World Health Organization. 13 December Tóth PP, Potter D, Ming EE. Prevalence of lipid abnormalities in the United States: the National Health and Nutrition Examination Survey 2003-2006. Journal of clinical lipidology. 2012;6(4):325-30. Sun G-Z, Guo L, Wang X-Z, Song H-J, Li Z, Wang J, et al. Prevalence of atrial fibrillation and its risk factors in rural China: a cross-sectional study. International journal of cardiology. 2015;182:13-7. Oguejiofor O, Onwukwe C, Odenigbo C. Dyslipidemia in Nigeria: prevalence and pattern. Annals of African medicine. 2012;11(4):197. Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. Jama. 2007;298(3):309-16. D'Agostino Sr RB, Pencina MJ, Massaro JM, Coady S. Cardiovascular disease risk assessment: insights from Framingham. Global heart. 2013;8(1):11-23. Reinikainen J, Laatikainen T, Karvanen J, Tolonen H. Lifetime cumulative risk factors predict cardiovascular disease mortality in a 50-year follow-up study in Finland. International Journal of Epidemiology. 2015;44(1):108-16. Kim H-L, Jeon HH, Park IY, Choi JM, Kang JS, Min K-W. Helicobacter pylori infection is associated with elevated low density lipoprotein cholesterol levels in elderly Koreans. Journal of Korean medical science. 2011;26(5):654. Gong Y, Wei W, Jingwei L, Nannan D, Yuan Y. Helicobacter pylori infection status correlates with serum parameter levels responding to multi-organ functions. Digestive diseases and sciences. 2015;60(6):1748-54. Pohjanen V-M, Koivurova O-P, Niemelä SE, Karttunen RA, Karttunen TJ. Role of Helicobacter pylori and interleukin 6-174 gene polymorphism in dyslipidemia: a case–control study. BMJ open. 2016;6(1). Haeri M, Parham M, Habibi N, Vafaeimanesh J. Effect of Helicobacter pylori infection on serum lipid profile. Journal of lipids. 2018;2018. Shimamoto T, Yamamichi N, Gondo K, Takahashi Y, Takeuchi C, Wada R, et al. The association of Helicobacter pylori infection with serum lipid profiles: An evaluation based on a combination of meta-analysis and a propensity score-based observational approach. PloS one. 2020;15(6):e0234433. Kopin L, Lowenstein C. In the clinic. Dyslipidemia. Annals of internal medicine. 2010;153(3):Itc21. Azizian R, Khosravi A, Azizian M. The association of the human leukocyte antigen (HLA) with the pathogenesis of Helicobacter pylori. J Pure Appl Microbiol. 2013;7(3):2183-9. Atherton JC. The pathogenesis of Helicobacter pylori–induced gastro-duodenal diseases. Annu Rev Pathol Mech Dis. 2006;1:63-96. Satoh H, Saijo Y, Yoshioka E, Tsutsui H. Helicobacter Pylori infection is a significant risk for modified lipid profile in Japanese male subjects. Journal of atherosclerosis and thrombosis. 2010:1007010255-. Tarchalski J, Guzik P, Wysocki H. Correlation between the extent of coronary atherosclerosis and lipid profile. Vascular biochemistry: Springer; 2003. p. 25-30. Abdu A, Cheneke W, Adem M, Belete R, Getachew A. Dyslipidemia and Associated Factors Among Patients Suspected to Have Helicobacter pylori Infection at Jimma University Medical Center, Jimma, Ethiopia. International Journal of General Medicine. 2020;13:311. Hooi JK, Lai WY, Ng WK, Suen MM, Underwood FE, Tanyingoh D, et al. Grant Support: Nil. 2017. Hailu G, Desta K, Tadesse F. Prevalence and Risk Factors of Helicobacter pylori among Adults at Jinka Zonal Hospital, Debub Omo Zone, Southwest Ethiopia. Autoimmune Infect Dis. 2016;2:2. Rhee E-J, Kim HC, Kim JH, Lee EY, Kim BJ, Kim EM, et al. 2018 Guidelines for the management of dyslipidemia in Korea. Journal of Lipid and Atherosclerosis. 2019;8(2):78-131. Baigent C. Cholesterol Treatment Trialists'(CTT) Collaborators: Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet (London, England). 2005;366:1267-78. Garber AJ, Abrahamson MJ, Barzilay JI, Blonde L, Bloomgarden ZT, Bush MA, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm–2018 executive summary. Endocrine practice. 2018;24(1):91-120. Karim I, Zardari AK, Shaikh MK, Baloch ZAQ, Shah SZA. DYSLIPIDEMIA. The Professional Medical Journal. 2014;21(05):956-9. Al-Fawaeir S, Zaid MA, Awad AA, Alabedallat B. Serum lipid profile in Helicobacter pylori infected patients. American Journal of Physiology, Biochemistry and Pharmacology. 2013;2(2):1-4. Ali MAE. Assessment of Serum High Sensitivity C-Reactive Protein, Lipid Profile and Magnesium among Sudanese Patients with H. Pylori Infection.(In Khartoum State): Sudan University of Science & Technology; 2019. Jia E-Z, Zhao F-J, Hao B, Zhu T-B, Wang L-S, Chen B, et al. Helicobacter pylori infection is associated with decreased serum levels of high density lipoprotein, but not with the severity of coronary atherosclerosis. Lipids in Health and Disease. 2009;8(1):1-7. Kim D-H, Son BK, Min K-W, Han SK, Na JU, Choi PC, et al. Chronic Gastritis Is Associated with a Decreased High-Density Lipid Level: Histological Features of Gastritis Based on the Updated Sydney System. Journal of clinical medicine. 2020;9(6):1856. Kim TJ, Lee H, Kang M, Kim JE, Choi Y-H, Min YW, et al. Helicobacter pylori is associated with dyslipidemia but not with other risk factors of cardiovascular disease. Scientific reports. 2016;6(1):1-8. Tang DM, Chascsa DM, Chou JY, Ho N, Auh S, Wank SA, et al. Helicobacter pylori infection is strongly associated with metabolic syndrome, and weakly associated with non‐alcoholic fatty liver disease, in a US Hispanic population. GastroHep. 2019;1(6):325-31. Atsede D. Tegegne MAN, Meseret K. Desta,, Kumela G. Nedessa HMB. CITY PROFILE GONDAR. SES Social Inclusion and Energy Management for Informal Urban Settlements. Gondar, Ethiopia Metro Area Population 1950-2021. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation. 2009;120(16):1640-5. Megerssa Y, Gebre M, Birru S, Goshu A, Tesfaye D. Prevalence of undiagnosed diabetes mellitus and its risk factors in selected institutions at Bishoftu Town, East Shoa. Ethiopia J Diabetes Metab. 2013. These include industries, research centers, schools, health sectors and…; 2013. NHANES C. Anthropometry procedures manual. Atlanta (GA): CDC. 2007. Corbridge SJ, Nyenhuis SM. Promoting physical activity and exercise in patients with asthma and chronic obstructive pulmonary disease. The Journal for Nurse Practitioners. 2017;13(1):41-6. Zaret B, Battler A, Berger H, Bodenheimer M, Borer J, Brochier M, et al. Report of the joint international society and federation of cardiology/world health organization task force on nuclear cardiology. European heart journal. 1984;5(10):850-63. Bayram F, Kocer D, Gundogan K, Kaya A, Demir O, Coskun R, et al. Prevalence of dyslipidemia and associated risk factors in Turkish adults. Journal of clinical lipidology. 2014;8(2):206-16. Cameron N, Schell L. Human growth and development: Academic Press; 2012. Health. Mo. National Health Survey ENS Chile 2009–2010. http://webminsalcl/portal/url/item/ bcb03d7bc28b64dfe040010165012d23pdf. Santiago; 2010;Accessed 03 Mar 2017. Egerter S, Braveman P, Sadegh-Nobari T, Grossman-Kahn R, Dekker M. Issue brief 6: education and health. Princeton, NJ: Robert Wood Johnson Foundation. 2009. Brinton EA. Effects of ethanol intake on lipoproteins and atherosclerosis. Current opinion in lipidology. 2010;21(4):346-51. Murray LJ, Bamford KB, O'Reilly D, McCrum EE, Evans AE. Helicobacter pylori infection: relation with cardiovascular risk factors, ischaemic heart disease, and social class. Heart. 1995;74(5):497-501. Moutar F, Alsamarai A, Ibrahim F. Lipid profile in patients with gastritis. World J Pharm Pharm Sci. 2016;5(7):74-90. Grunfeld C, Gulli R, Moser A, Gavin L, Feingold K. Effect of tumor necrosis factor administration in vivo on lipoprotein lipase activity in various tissues of the rat. Journal of Lipid Research. 1989;30(4):579-85. 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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-1489416","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":94356967,"identity":"d953d586-d1f3-4cb8-9451-008c084b7697","order_by":0,"name":"Abebaw Worede","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYLACHgaGBAYJIOMDiEGSFsYZJGth5iFGi8Hx3ocP3lTY5fFLNz+Ttm0DMtgbGD98zMGj5cxxY8M5Z5KLJeccM5PObQMyeg4wS87chluL2Y00NmneNubEDTcSzG7nQhhszLz4tbD/5v1Xn7j/Rvq325Zt9URpASpoOJy4QSLH7DZj22HCWuzPHGMGeuN4scSdM+U/e84dT5zZc7AZr18k29sYP7ypqc7jn92+2eBHWXViP3vzwQ8f8WhBBYxsYLKBWPUg8IcUxaNgFIyCUTBSAACUj1cRip/GIAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Gondar","correspondingAuthor":true,"prefix":"","firstName":"Abebaw","middleName":"","lastName":"Worede","suffix":""},{"id":94356962,"identity":"83f24832-b3b1-4a46-8e15-6bc1dc167d3f","order_by":1,"name":"Marye Nigatie","email":"","orcid":"","institution":"Weldia University","correspondingAuthor":false,"prefix":"","firstName":"Marye","middleName":"","lastName":"Nigatie","suffix":""},{"id":94356965,"identity":"6ed76669-9a1e-42ee-8444-26839cf64c31","order_by":2,"name":"Tadele Melak","email":"","orcid":"","institution":"University of Gondar","correspondingAuthor":false,"prefix":"","firstName":"Tadele","middleName":"","lastName":"Melak","suffix":""},{"id":94356966,"identity":"ca51af9e-e952-4b35-a225-e387f0e94e8f","order_by":3,"name":"Daniel Asmelash","email":"","orcid":"","institution":"University of Gondar","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Asmelash","suffix":""}],"badges":[],"createdAt":"2022-03-25 13:44:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1489416/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1489416/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19795395,"identity":"0a156586-dcf0-46c9-8d11-c2883acf7f21","added_by":"auto","created_at":"2022-03-30 20:10:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":530151,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1489416/v1/3160a517-5074-4527-b39e-5e524cde9142.pdf"},{"id":19795394,"identity":"1ddf8a42-5fba-41ca-83e1-163c94e2557a","added_by":"auto","created_at":"2022-03-30 20:10:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":530151,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1489416/v1/a7a67e7d-d423-425f-9234-e2895461e95d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dyslipidemia and its associated factors among Helicobacter Pylori-infected Patients Attending at University of Gondar Comprehensive Specialized Hospital, Gondar, North- West Ethiopia: A Comparative Cross-Sectional Study","fulltext":[{"header":"Background","content":"\u003cp\u003eDyslipidemia refers to a lipid profile disturbance, including both hyperlipidemia and hypolipidemia (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Dyslipidemia can be a metabolically linked category of plasma lipid and lipoprotein deviations from the normal range and is categorized by decreased high-density lipoprotein cholesterol (HDL-C) and elevated low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), and total cholesterol (TC) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe invading of the stomach by \u003cem\u003eH.pylori\u003c/em\u003e causes reliable disturbance of the stomach which can affect some biochemical parameters(lipid profiles) in the patient (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The underlying possible mechanisms for these conditions are chronic low-grade activation of the coagulation cascade, accelerating atherosclerosis, and antigenic mimicry between \u003cem\u003eH. pylori\u003c/em\u003e and host epitopes leading to autoimmune disorders and lipid metabolism abnormality (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Scientific facts indicate that \u003cem\u003eH. pylori\u003c/em\u003e infection can lead to some appetite-related disorders and significant changes in body weight. Dysregulated absorption of nutrients and the effects of the inflammatory response system caused by \u003cem\u003eH. pylori\u003c/em\u003e infection contribute to changes in serum lipids. The change of lipid profiles may also be due to. Several lines of evidence indicate that the secretion of inflammatory cytokines by cells induced by chronic infection of gram-negative bacteria is related to the change of lipid profiles (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAn experimental investigation indicated that interleukin-8, which is overexpressed in \u003cem\u003eH. pylori\u003c/em\u003e-infection, increases the recruitment of T lymphocytes and smooth muscle cells, contributing to atherosclerosis (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In addition to this, lipopolysaccharide (LPS) affects circulating macrophages and increases free radical production. It is known that free radicals oxidize LDL, the result of which (oxidized LDL) transforms macrophages into foam cells that are known to be essential in atherosclerosis pathogenesis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). With the presence of LPS present in the cell walls of \u003cem\u003eH. pylori\u003c/em\u003e, there is the stimulation of large quantities of cytokines (TNF-α, and IL-6) which inhibit lipoprotein lipase activity. The consequence being mobilization of lipid in the tissue through an increase in serum TG level and in contrast, a decrease in serum HDL cholesterol level (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe predominance of dyslipidemia varies from country to country. In USA, 52% of adults had lipid abnormality (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In Chinese from study individuals, the predominance of at slightest one sort of unusual lipid concentration was 64.4% (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In Nigeria, the prevalence of dyslipidemia extended from 60% among clearly healthy Nigerians (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The commitment of dyslipidemia to cardiovascular diseases (CVDs) is apparent from several longitudinal considers which have outlined the affiliation of high levels of LDL-C, TC, TG, and low levels of HDL-C with CVD (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Dyslipidemia is a class of TC and TG metabolism disorders that have consequences for the cardiovascular system, causing pathologies such as vascular coronary disease and atherosclerosis. An increase of TC, LDL-C, and decrease in HDL-C levels in \u003cem\u003eH. pylori\u003c/em\u003e-infected people creates an atherogenic lipid profile which could promote atherosclerosis with its complications, myocardial infarction, stroke, and peripheral vascular disease (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferent studies have reported different findings regarding the relationship of \u003cem\u003eH. pylori\u003c/em\u003e disease and its relation to changes in serum lipid profile. Several studies yield various and sometimes contradictory results; increased, normal, and decreased levels of lipids (\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In \u003cem\u003eH. pylori\u003c/em\u003e patients, observational studies have found a strong correlation between rising levels of LDL-C or decreasing levels of HDL-C and increased risk of coronary artery disease (CAD) events (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Other studies show that \u003cem\u003eH. Pylori\u003c/em\u003e could play a role in the development of ischemic heart disease through various means, such as endothelial cell colonization, lipid profile changes, hypercoagulation, platelet aggregation, molecular mimicry mechanism induction, and low-grade systemic inflammation progression (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA study in Ethiopia showed that around 87.2% of \u003cem\u003eH. pylori-\u003c/em\u003einfected individuals had dyslipidemia in at least one of the four lipid profiles. The distribution of abnormal lipid profile among \u003cem\u003eH. pylori\u003c/em\u003e-infected individuals was 51.4%, 67.05%, 38.1%, and 39.3% by serum TC, TG, LDL-C, and HDL-C respectively, whereas the prevalence of dyslipidemia among \u003cem\u003eH. pylori-\u003c/em\u003enegative individuals were 20.9%, 40.8%, 16.8% and 43.8% by serum TC, TG, LDL-C, and HDL-C respectively (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDyslipidemia is the most part asymptomatic and is analyzed incidentally or through screening. However, in serious cases, the patient can show one of the indications of the complications (either coronary or peripheral artery illness) such as leg pain, chest pain, dizziness, palpitations, swelling of lower limb or veins (e.g.in neck, or stomach), and blacking out (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effects of \u003cem\u003eH. pylori\u003c/em\u003e infection on lipid profiles are still unknown. Several studies have shown varying and occasionally contradictory results, including raised, normal, and decreased lipid levels, all of which have been reported. The study will be used as a source of information about lipid profiles of \u003cem\u003eH. pylori\u003c/em\u003e infected patients for the physicians for early detection, treatment, and prevention of lipid abnormalities. This study will also be used to provide supportive evidence for policymakers and evidence-based information to the scientific community about the lipid profiles among \u003cem\u003eH. pylori\u003c/em\u003e infected patients. Additionally, this study will serve as baseline information for other researchers in the study area. Therefore aim of this study is assessing dyslipidemia and its associated factors among \u003cem\u003eH. pylori-\u003c/em\u003einfected patients attending at University of Gondar comprehensive specialized Hospital from March 10/2021 to May 10/2021, Gondar, North-West Ethiopia\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population, area, design and period\u003c/h2\u003e \u003cp\u003eA Hospital-based comparative cross-sectional study design was conducted among \u003cem\u003eH. pylori-\u003c/em\u003einfected patients attending the outpatient department of University of Gondar Comprehensive Specialized Hospital (UGCSH) which is located in Gondar town, Amhara Region, North-West Ethiopia. Gondar is found in the North-West of Ethiopia at about 727 Km and 180 Km away from the capital city Addis Ababa and Bahirdar respectively. It is at 12\u003csup\u003e0\u003c/sup\u003e 3\u0026prime; N latitude and 37\u003csup\u003e0\u003c/sup\u003e 28\u0026prime;E (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). The current population of Gondar city is 378,000 and has a total area of 192.3 km\u003csup\u003e2\u003c/sup\u003e with undulating mountainous topography (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Currently, the hospital has a catchment population of over 7\u0026nbsp;million and serving as a referral hospital for all populations in the Central Gondar zone and neighboring district areas. All \u003cem\u003eH. pylori-\u003c/em\u003einfected patients attending at UGCSH during the study period and who can participate the study were in the study population. Age matched healthy \u003cem\u003eH. pylori\u003c/em\u003e negative adults who were come to Gondar Blood Bank during the study period for controls during the study period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEligibility criteria\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eInclusion criteria\u003c/h2\u003e \u003cp\u003eThe inclusion criteria were all \u003cem\u003eH. pylori-\u003c/em\u003einfected adult patients aged greater than or equal to 18 years and who were willing to voluntarily participate in the study. All adult healthy \u003cem\u003eH. pylori\u003c/em\u003e negative individuals aged greater than or equal to 18years and who were willing to voluntarily participate in the study were included in the control groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eExclusion criteria\u003c/h2\u003e \u003cp\u003eThose study participants having TB drug users, antiretroviral treatment users, participants who have hypertension and diabetes mellitus (DM) were excluded by screening and reviewing their medical records. Patients who were severely ill were excluded from the study.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSample size determination and sampling techniques\u003c/h2\u003e \u003cp\u003eThe sample size was determined by using open Epi, version-3 software by considering the following assumptions; mean difference of TG on a study done at the United States of America (USA) (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), sample 1 mean\u0026thinsp;=\u0026thinsp;177.2, SD1\u0026thinsp;=\u0026thinsp;87.5, sample 2 mean\u0026thinsp;=\u0026thinsp;148, SD2\u0026thinsp;=\u0026thinsp;68.2, 95% Confidence level, and 80% power(0.84) (power approach two mean difference formula). This gives a total of 228 (114 confirmed \u003cem\u003eH. pylori\u003c/em\u003e patients and 114 healthy \u003cem\u003eH. pylori\u003c/em\u003e negative control groups) study units. A convenience sampling technique was employed to select study participants at UGCSH and adult healthy controls from the Gondar blood bank. When the study participants coming to the medical OPD with complain of gastritis, these patients tested for \u003cem\u003eH. pylori\u003c/em\u003e. As the patients have become positive for \u003cem\u003eH. pylori\u003c/em\u003e, they were asked to fill written consent for their participation conveniently in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOperational definition\u003c/h2\u003e \u003cp\u003e \u003cb\u003eDyslipidemia\u003c/b\u003e was considered when total cholesterol\u0026thinsp;\u003cem\u003e\u0026gt;\u003c/em\u003e\u0026thinsp;200 mg/dl and/or triglycerides\u0026thinsp;\u003cem\u003e\u0026gt;\u003c/em\u003e\u0026thinsp;150 mg/dl and/or LDL-C\u0026thinsp;\u003cem\u003e\u0026gt;\u003c/em\u003e\u0026thinsp;130 mg/dl and/or, HDL-C\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;40 mg/dl; male and/or, HDL-C\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;50 mg/dl; female (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). \u003cb\u003eAlcohol intake\u003c/b\u003e was defined as people who never drink any alcohol and people who don't drink alcohol now but did in the past (non-drinkers),and people who drink alcohol one or more days per week (regular drinkers), and (past drinkers) (ex-drinker) (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). \u003cb\u003eCigarette Smoking\u003c/b\u003e was also defined as None-smoker (individuals who never smoke, and those who smoke before but not current), smoker ( individuals who are currently smoking) (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). The WHO definition of obesity is based on various categorical cut-points based on the body mass index (BMI) of weight-for-height: underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal weight (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25.0\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e), and obesity (\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). \u003cb\u003ePhysical exercise\u003c/b\u003e was considered when a study subject has experience of doing the physical exercise once per day for 20\u0026ndash;30 minutes as a continuous activity (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData collection and laboratory methods\u003c/h2\u003e \u003cp\u003eThe socio-demographic characteristics of study participants were collected by using a questionnaire prepared for this study. The questionnaire consisted of the study participant's age, sex, ethnicity, religion, marital status, residence, occupation, educational status, income, and behavioral characteristics such as the habit of physical exercise, smoking habit, and a habit of alcohol drinking, and cigarette smoking. Data for these characteristics were collected by trained nurse through a face-to-face interview. The study participants were interviewed after written informed consent was taken.\u003c/p\u003e \u003cp\u003eHeight was measured using a height measure scale. Participants stood erect on the stadiometer's floorboard with their backs to the stadiometer's vertical backboard. Both heels of the feet were placed together on the vertical board, with both heels touching the base. The feet were at a 60-degree angle, slightly outward. The participant's shoes and hats were removed during the height assessment. The height measurement was recorded to the nearest 0.1 cm (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Before weighing the study subjects, the weight scale was turn to zero. Then participants were asked to remove extra layers of clothing, shoes, jewelers, and any items in their pockets. Then after the participant were asked to step on the scale backward (for confidentiality) body weight was recorded to the nearest 0.1 kg (100 gm) (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). The waist circumference was measured using a tape measure at the level of the iliac processes and the umbilicus to assess abdominal(central) obesity (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). The spatial distance between each corresponding hipbone in proportion to the buttocks was determined by measuring the hips with a tape measure (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter receiving informed consent from the study participants, 8\u0026ndash;12 hours fasting 5 ml of venous blood was collected preferably at the antecubital area by applying a tourniquet. Before collecting the sample, the puncture area of the vein was disinfected by using 70% alcohol. The serum was collected using a serum separator tube at the medical ward department of UGCSH. After collection, specimens were transported to the clinical chemistry unit of the UGCSH laboratory for analysis. The collected blood sample was left for 30 minutes at room temperature. Then the blood samples were centrifuged for 5 minutes at 3500 revolutions per minute (rpm) to separate serum from formed elements. All these procedures were done by the laboratory technologist and principal investigator by applying standard operating procedures (SOPs). The HDL-C, LDL-C, TG, and TC were analyzed by DxC 700 AU auto analyzer (Beckman Coulter, USA). The stool antigen \u003cem\u003eH. pylori\u003c/em\u003e RapiCard\u0026trade; Insta tests were performed for the recruitment of study participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData quality assurance and management\u003c/h2\u003e \u003cp\u003eThe questionnaire was prepared both in English and in Amharic, the local language. Five percent (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) of the sample size was pre-tested at Poly health center. Data collectors were given training in data collection to eliminate technical and observer bias. After completion of each questionnaire, cross-checking was done between the data collector and principal investigator to assure the completeness of the data collected. The label on the test tube and the study participants' unique identification number on the questionnaire were checked. Before patient sample processing, quality controls (normal and pathological) were performed and the study participants\u0026rsquo; result was taken after confirmation of the controls were okay.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData analysis and interpretation\u003c/h2\u003e \u003cp\u003eThe results were organized and summarized using frequency, and percentage for categorical variables, median (inter-quartile range) for continuous variables, and using tables. The model of fit was checked by Hosmer and Lemeshow's goodness fit statistic. The Kolmogorov-Smirnov and Shapiro Wilk normality test were conducted to check the normality of continuous variables. Since the continuous variables were not normally distributed, Mann-Whitney U-tests were used to compare the median and interquartile range of these variables. Multivariable logistic regression analysis was done to control possible confounders and to determine factors statistically associated with dyslipidemia. The variables were selected by the backward selection method. The P-values less than 0.05 were considered statically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic characteristics of study participants\u003c/h2\u003e \u003cp\u003eThis study included 117 \u003cem\u003eH. pylori-\u003c/em\u003einfected individuals and 114 \u003cem\u003eH. pylori\u003c/em\u003e negative healthy control groups with response rate of 100%. Among the study groups, 117 (50.65%) were females, ranging in age from 18 to 63 years, with a median (IQR) age of 31(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) years. The median (IQR) age of \u003cem\u003eH. pylori\u003c/em\u003e positive and control groups was 32(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, 42.5), and 31(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) years respectively. The urban residence of study participants was 155(67.10%), and 121(52.38%) were married. Based on educational status, 67(29.00%) study participants were from secondary schools, 77(33.33%) of occupation status were students (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\u003eSociodemographic characteristics of study subjects (N\u0026thinsp;=\u0026thinsp;231, UGCSH, Gondar, 2021)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e positive, N\u0026thinsp;=\u0026thinsp;117\u003c/p\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl, N\u0026thinsp;=\u0026thinsp;114\u003c/p\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal, N\u0026thinsp;=\u0026thinsp;231\u003c/p\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61(53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e114(49.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64(54.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53(46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117(50.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62(52.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76(32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55(47.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100(87.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155(67.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(5.3))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36(15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55(48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67(29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40(35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74(32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29(12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerchant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHouse wife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52(22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGov\u0026rsquo;t employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate and others \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16(6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59(51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91(39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74(63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47(41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121(52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeparated \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19(8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eN.B: a\u0026thinsp;=\u0026thinsp;others\u0026thinsp;=\u0026thinsp;priest, b\u0026thinsp;=\u0026thinsp;separated (divorced and widowed)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eBehavioral and anthropometric characteristics of participants\u003c/h2\u003e \u003cp\u003eBased on the lifestyle condition of study participants, almost all of the study participants 230 (99.6%) were non-smokers, 214 (92.6%) did not drink alcohol, 229 (99.13%) did not chew Khat, and 196 (84.8%) did not have regular physical exercise. The BMI value of the study participants, 184(79.7%) had normal (18.5\u0026ndash;25kg/m2), 17(7.4%) had overweight (\u0026ge;\u0026thinsp;25kg/ m2), and 30 (13.0%) had underweight (\u0026lt;\u0026thinsp;18.5kg/m2). From the study participants, 215(93.7%) had less than 94cm of waist circumference, and 206(89.2%) had less than 102 cm of the hip circumference (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\u003eBehavioral and anthropometric characteristics of study participants (N\u0026thinsp;=\u0026thinsp;231, UGCSH, Gondar, 2021) Pearson\u0026rsquo;s Chi-square test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e positive (117)\u003c/p\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl (114)\u003c/p\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal (231)\u003c/p\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhysical Exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35(15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101(86.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95(83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e196(84.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBody mass index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.5-24.99 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91(77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93(81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e184(79.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30(13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlcohol drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(6.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107(91.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107(93.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e214(92.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;94cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106(90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109(95.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e215(93.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;94cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16(6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;102cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97(82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109(95.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e206(89.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;102cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25(10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCigarette smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116(99.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e230(99.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKhat chewing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112(98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e229(99.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHDL\u0026thinsp;=\u0026thinsp;high density lipoprotein, LDL\u0026thinsp;=\u0026thinsp;low density lipoprotein\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe magnitude of dyslipidemia among study participants\u003c/h2\u003e \u003cp\u003eThe overall prevalence of dyslipidemia in either of the four lipid profile parameters was 145(62.8%) (95% CI: 56.2\u0026ndash;69%). From \u003cem\u003eH. pylori\u003c/em\u003e infected patients, the prevalence of dyslipidemia in at least one of the parameters among the four lipid profiles were 71.8% (84/117), (95% CI: 62.7\u0026ndash;79.7%, and 53.5% (61/114) (95% CI: 43.9\u0026ndash;62.9%) were from control groups (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\u003eDyslipidemia among \u003cem\u003eH. pylori\u003c/em\u003e positive patients and control groups (N\u0026thinsp;=\u0026thinsp;231 at UGCSH, Gondar, 2021)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLipid profiles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c7\" namest=\"c6\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecreased HDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53(45.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.1\u0026ndash;54.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54(47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.9\u0026ndash;56.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e107(46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39.8\u0026ndash;53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncreased LDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41(35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.5\u0026ndash;44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11(9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.9\u0026ndash;16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52(22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17.3\u0026ndash;29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypercholesterolemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.4\u0026ndash;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9(7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0-4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21(9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.0-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertriglyceridemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.4\u0026ndash;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.1\u0026ndash;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13(5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.4\u0026ndash;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal dyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.7\u0026ndash;79.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61(53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.9\u0026ndash;62.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e145(62.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e56.2\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe serum level of abnormal lipid profile among \u003cem\u003eH. pylori-\u003c/em\u003epositive individuals were 53 (45.3%) HDL-C, 41(35%) LDL-C, 12(10.3%) TC, and 12(10.3%) TG, whereas the prevalence of dyslipidemia among control groups were 54 (47.37%), 11 (9.6%), 9(7.9%), and 1(0.9%) of serum HDL-C, LDL-C, TC, and TG respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAssociated factors of dyslipidemia among study individuals\u003c/h2\u003e \u003cp\u003eIn bivariable analysis, age, education status, \u003cem\u003eH. pylori\u003c/em\u003e infection, alcohol drinking habits, and hip circumference were statistically significant associations with dyslipidemia (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In multivariable analysis, there was a significant association between dyslipidemia with educational status (p\u0026thinsp;=\u0026thinsp;0.001), alcohol drinking habits (p\u0026thinsp;=\u0026thinsp;0.001), and \u003cem\u003eH. pylori\u003c/em\u003e infection (p\u0026thinsp;=\u0026thinsp;0.001) (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\u003eAssociated factors of dyslipidemia among study participants (N\u0026thinsp;=\u0026thinsp;231, Gondar, 2021)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.647 (1.379\u0026ndash;5.081) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6779(0.692\u0026ndash;4.063)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.209(0.709\u0026ndash;2.602)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.860(0.364\u0026ndash;2.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.660(0.948\u0026ndash;2.908)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.328(0.611\u0026ndash;2.887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.296(0.763\u0026ndash;6.908)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.329(0.360\u0026ndash;4.906)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.692(0.387\u0026ndash;1.237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.308(0.869\u0026ndash;6.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnable to read \u0026amp;write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.139(1.907\u0026ndash;8.985) ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.413(1.384\u0026ndash;14.077) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.412(1.441\u0026ndash;8.082) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.607(1.026\u0026ndash;9.170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.875(1.440\u0026ndash;5.740) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.787(2.167\u0026ndash;10.571)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eOccupation status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.343(0.539\u0026ndash;3.341)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.269(0.039\u0026ndash;1.874)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerchant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.208(0.376\u0026ndash;3.887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.233(0.034\u0026ndash;1.582)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHouse wife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.640(0.762\u0026ndash;3.530)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.229(0.038\u0026ndash;1.373)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGov\u0026rsquo;t employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.604(0.282\u0026ndash;1.293)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.360(0.070\u0026ndash;1.841)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.604(0.205\u0026ndash;1.784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.082(0.011\u0026ndash;0.621)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlcohol drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.204(2.562\u0026ndash;33.062) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.767(2.616\u0026ndash;36.467) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.5-24.99kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;24.99kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.578 (.534-4.668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.286(0.614\u0026ndash;8.505)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.809(.764\u0026thinsp;\u0026minus;\u0026thinsp;4.280)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.869(0.679\u0026ndash;5.139)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.583(0.720\u0026ndash;3.480)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.734(0.652\u0026ndash;4.614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.212(1.282\u0026ndash;3.816) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.377(1.637\u0026ndash;6.966) **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;94cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;94cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.725(0.754\u0026ndash;9.850)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.354(0.126\u0026ndash;14.533)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;102cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;102cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.472(1.150-10.483) *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.123(0.517\u0026ndash;8.7140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*=p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **=p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***=p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, AOR\u0026thinsp;=\u0026thinsp;adjusted odds ratio, BMI\u0026thinsp;=\u0026thinsp;body mass index, COR\u0026thinsp;=\u0026thinsp;crude odds ratio, CI\u0026thinsp;=\u0026thinsp;confidence interval, HC\u0026thinsp;=\u0026thinsp;Hip circumference, WC\u0026thinsp;=\u0026thinsp;waist circumference\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eComparison of lipid profiles among study participants\u003c/h2\u003e \u003cp\u003eThe median level of serum HDL-C was not statistically significant difference with \u003cem\u003eH. pylori\u003c/em\u003e positive and control groups (p\u0026thinsp;=\u0026thinsp;0.376). But the median serum level of LDL-C, TG, and TC was a statistically significant difference between \u003cem\u003eH. pylori\u003c/em\u003e positive and control groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of lipid profiles among cases and controls (Cases, N\u0026thinsp;=\u0026thinsp;117, Control-N\u0026thinsp;=\u0026thinsp;114, Gondar, Ethiopia, 2021) (Mann-whitely U test)\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=\"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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epositive, median (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl, median (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32(22, 42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(20, 38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41(35, 47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(33.75, 44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108(89.8, 145.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95(79.45, 115.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93(65, 117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83(58.5, 102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143(119.5, 169)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125(110, 143)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89(82.5, 92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (81.75, 93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75(69, 86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77(70.75, 77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHDL\u0026thinsp;=\u0026thinsp;High-density lipoprotein, HC\u0026thinsp;=\u0026thinsp;Hip circumference, LDL\u0026thinsp;=\u0026thinsp;low-density lipoprotein, TC\u0026thinsp;=\u0026thinsp;total cholesterol, TG\u0026thinsp;=\u0026thinsp;triglycerides, WC\u0026thinsp;=\u0026thinsp;Waist circumference, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u0026thinsp;=\u0026thinsp;statistically significant value\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe prevalence of dyslipidemia among \u003cem\u003eH.pylori\u003c/em\u003e patients in either of the four lipid profiles was 71.8% (95% CI: 62.7\u0026ndash;79.7), which was higher than a study conducted in Iran (60.4%) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Our findings, however, were lower than a study done in Ethiopia, which found that 87.2% of \u003cem\u003eH.pylori\u003c/em\u003e patients had dyslipidemia (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). The reason for the variation is most likely related to differences in lifestyle, study design, and sample size.\u003c/p\u003e \u003cp\u003eIn our finding, the odds of dyslipidemia among peoples unable to read and write were 4.413 times higher (AOR: 4.413; 95% CI: 1.384\u0026ndash;14.077, P\u0026thinsp;=\u0026thinsp;0.012), the odds of dyslipidemia being primary school education status were 3.067 times higher (AOR: 3.067; 95% CI: 1.026\u0026ndash;9.170; P\u0026thinsp;=\u0026thinsp;0.045), and the odds of dyslipidemia among secondary school education status were 4.787 times higher (AOR: 4.787, 95% CI; 2.167\u0026ndash;10.571, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to higher educational status. Most cardiovascular risk factors were more common at lower educational levels in the most recent National Health Survey, indicating a trend toward better health outcomes as education levels increase (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). People having a lower level of education are more likely to develop unhealthy eating habits and lifestyles, which can be worsened if their income rises without their level of education (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDyslipidemia was 9.767 times more common in alcoholics than non-alcoholics (AOR: 9.767, 95% CI: 2.616\u0026ndash;36.467, P\u0026thinsp;=\u0026thinsp;0.001) which was consistent with the study done in Korea (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). This is due to the impact of chronic ethanol drinks on cardiovascular health is through the effect on lipid metabolism (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). The odds of dyslipidemia with \u003cem\u003eH. pylori\u003c/em\u003e infection were 3.377 times higher than control groups (AOR: 3.377; 95% CI; 1.637\u0026ndash;6.966, P\u0026thinsp;=\u0026thinsp;0.001). This finding was agreed with studies done in Ethiopia and Iran (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our finding, the lipid profiles showed that \u003cem\u003eH. pylori\u003c/em\u003e infected individuals have a statistically significant difference in LDL-C, TG, and TC compared with control groups. The HDL-C levels of \u003cem\u003eH. pylori\u003c/em\u003e positive and control study participants, however, did not differ significantly. This finding was consistent with a study done in Ethiopia and Iran (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). This may be due to the impact of \u003cem\u003eH. pylori\u003c/em\u003e infection on lipid metabolism (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). The current study was consistent with studies conducted in other areas, indicating that \u003cem\u003eH. pylori\u003c/em\u003e infection may alter serum lipid concentrations, potentially increasing the risk of CHD. \u003cem\u003eH. pylori\u003c/em\u003e positive individuals had a statistically significant higher concentration of LDL-C than those control groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur finding shows that the median (IQR) of lipid profiles in \u003cem\u003eH. pylori\u003c/em\u003e-positive individuals was significantly greater than in control groups for LDL-C: 108 (89.8, 145.5) vs 95 (79.45, 115.8), for TG: 93 (65, 117) vs 83 (58.5, 102), and TC:143 (119.5, 169) vs 125 (110, 143) mg/dl respectively with P value less than 0.05. This finding was comparable with a study conducted in Iraq (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e) and Japan (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) that \u003cem\u003eH.pylori\u003c/em\u003e infection was associated with an increase in serum cholesterol, TG, and LDL-C. Our findings were also in line with those of a Turkish study on \u003cem\u003eH. pylori\u003c/em\u003e-infected patients' serum cholesterol which was considerably higher (189.32\u0026thinsp;\u0026plusmn;\u0026thinsp;45.15 vs 179.41\u0026thinsp;\u0026plusmn;\u0026thinsp;36.37) mg/dl (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) when compared to the control study participants. The patient's group also had significantly higher serum TG and TC/HDL-c values compared to control groups (169.46\u0026thinsp;\u0026plusmn;\u0026thinsp;68.53 vs 135.67\u0026thinsp;\u0026plusmn;\u0026thinsp;94.35) mg/dl (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and 3.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23 vs 3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62, (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) respectively (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur results were comparable with a study done in Ethiopia, the serum LDL-C concentration was higher in \u003cem\u003eH.pylori\u003c/em\u003e positive patients than \u003cem\u003eH.pylori\u003c/em\u003e negative groups 122\u0026thinsp;\u0026plusmn;\u0026thinsp;37 vs 104.27\u0026thinsp;\u0026plusmn;\u0026thinsp;34.71 mg/dl (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), serum TG (185.61\u0026thinsp;\u0026plusmn;\u0026thinsp;74.82 vs 138.18\u0026thinsp;\u0026plusmn;\u0026thinsp;60.17 mg/dl ( p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and, serum TC(200.8\u0026thinsp;\u0026plusmn;\u0026thinsp;43.48 vs 173.67\u0026thinsp;\u0026plusmn;\u0026thinsp;42.41 mg/dl (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) respectively (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Our findings also supported by those of a study conducted in Sudan (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), the United States (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), China (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), and Korea (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e), which found a statistical difference between patients and controls with TC, TG, and LDL-C values with a p-value of \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eOur findings showed that \u003cem\u003eH. pylori\u003c/em\u003e infection increased TC, LDL-C, and TG levels in infected participants when compared to control groups. This finding was in line with a Korean study that found \u003cem\u003eH.pylori\u003c/em\u003e is associated with higher levels of TC and LDL-C (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). This is due to a disturbance in food absorption in the digestive system, which causes alterations in serum lipids. The effects of the inflammatory response system caused by \u003cem\u003eH. pylori\u003c/em\u003e infection may potentially be responsible for the alteration in lipid profiles (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Because of the presence of LPS in the cell walls of gram-negative bacteria like \u003cem\u003eH. pylori\u003c/em\u003e, high amounts of cytokines (TNF-α, and IL-6) are released, inhibiting lipoprotein lipase action. The consequence being the mobilization of fat from tissues to blood is responsible for an increase in serum lipid levels (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, our result was not comparable in a study done in Finland indicate that \u003cem\u003eH. pylori\u003c/em\u003e infection was no significant difference in \u003cem\u003eH. pylori\u003c/em\u003e positive and control groups with serum TC, LDL-C, and TG. The serum HDL-C concentration in \u003cem\u003eH.pylori\u003c/em\u003e positive patients had a significant difference than in control groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Whereas, in our finding LDL-C, TG, and TC concentration was a statistical difference between cases and controls but not in HDL-C. Our findings also not supported by a study done in Iran shows that the value of TG, LDL-C were high and HDL-C was low in \u003cem\u003eH. pylori\u003c/em\u003e positive than control groups. But these findings were not a statistical difference between \u003cem\u003eH.pylori\u003c/em\u003e positive and control groups (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). A study was done in China also shows that the value of TG and LDL-C was not statistically different between \u003cem\u003eH.pylori\u003c/em\u003e positive and control groups (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). This is due to differences in the study design, source population, study participants they use, and the way they define dyslipidemia.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on our findings, we conclude that \u003cem\u003eH. pylori\u003c/em\u003e patients have more likely to develop dyslipidemia than control (healthy) groups. There is a statistically significant association between \u003cem\u003eH. pylori\u003c/em\u003e infection with cardiac and coronary risk factors like a high concentration of LDL-C, TG, and TC. Alcohol drinking habits, and education status were statistically significantly associated with dyslipidemia. For health professionals, monitoring and assessment of serum lipid profiles are important for the management of dyslipidemia. So, patients who had \u003cem\u003eH. pylori\u003c/em\u003e infection should be assessed for their serum lipid profiles.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOR: Adjusted Odds Ratio; BP: Blood Pressure; BMI: Body Mass Index; CVDs: Cardio Vascular Diseases; CAD: Coronary Artery Disease; COR: Crude Odds Ratio; DBP: Diastolic Blood Pressure; H. pylori: Helicobacter Pylori; HDL-C: High-Density Lipoprotein Cholesterol; IL: Interleukin; IQR: Inter Quartile Range; LPS: Lipopolysaccharide; LDL-C: Low-density lipoprotein cholesterol; NCDs: Non-Communicable Diseases; SST: Serum Separator Tube; SOPs: Standard Operating Procedures; SPSS: statistical package for Social Science; TGs: Triglycerides; TC: Total Cholesterol; WHO: World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Research and Ethical Committee of the School of Biomedical and Laboratory Sciences, the University of Gondar\u0026nbsp;with the reference number of SBLS 2762 on March 08/2021. Data collectors explained the purpose, confidentiality, and discomfort related to the study to each participant and obtained a fully informed written consent.\u0026nbsp;The privacy of information was kept up during and after an interview in which coding was utilized for all the information collected and\u0026nbsp;those who had lipid abnormalities were advised to\u0026nbsp;visit\u0026nbsp;the UGCSH Medical OPD for further diagnosis and treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the primary data are available and if anyone has a reasonable interest to find the data, he can contact the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI declared that data collection and laboratory diagnosis were funded by University of Gondar\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMN, designed the study, performed the laboratory activity, data analysis and\u003cbr\u003e\u0026nbsp;interpretation, AW, developed the manuscript, AW, TM and DA assisted in the\u003cbr\u003e\u0026nbsp;design, analysis and interpretation of data and critically evaluated the manuscript. All authors read and approved the fnal manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank study participants, University of Gondar, and data collectors for their cooperation and financial, material, and reagent support\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e Kim HC, Oh SM. Noncommunicable diseases: current status of major modifiable risk factors in Korea. Journal of preventive medicine and public health. 2013;46(4):165.\u003c/li\u003e\n \u003cli\u003e Bhandari GP, Angdembe MR, Dhimal M, Neupane S, Bhusal C. State of non-communicable diseases in Nepal. BMC public health. 2014;14(1):1-9.\u003c/li\u003e\n \u003cli\u003e Welty FK. Hypobetalipoproteinemia and abetalipoproteinemia. Current opinion in lipidology. 2014;25(3):161.\u003c/li\u003e\n \u003cli\u003e Bays HE, Toth PP, Kris-Etherton PM, Abate N, Aronne LJ, Brown WV, et al. Obesity, adiposity, and dyslipidemia: a consensus statement from the National Lipid Association. Journal of clinical lipidology. 2013;7(4):304-83.\u003c/li\u003e\n \u003cli\u003e Blaser MJ, Atherton JCJTJoci. Helicobacter pylori persistence: biology and disease. 2004;113(3):321-33.\u003c/li\u003e\n \u003cli\u003e de Korwin JD, Ianiro G, Gibiino G, Gasbarrini A. Helicobacter pylori infection and extragastric diseases in 2017. Helicobacter. 2017;22:e12411.\u003c/li\u003e\n \u003cli\u003e Ndebi M, Guimtsop Y, Tamokou JJIJoRiMS. The assessment of risk factors, lipid profile, uric acid and alanine aminotransferase in Helicobacter pylori-positive subjects. 2018;6(9):2889.\u003c/li\u003e\n \u003cli\u003e Kusters JG, Van Vliet AH, Kuipers EJ. Pathogenesis of Helicobacter pylori infection. Clinical microbiology reviews. 2006;19(3):449-90.\u003c/li\u003e\n \u003cli\u003e Klok MD, Jakobsdottir S, Drent ML. The role of leptin and ghrelin in the regulation of food intake and body weight in humans: a review. Obes Rev. 2007;8(1):21-34.\u003c/li\u003e\n \u003cli\u003e Kalra SP, Ueno N, Kalra PS. Stimulation of appetite by ghrelin is regulated by leptin restraint: peripheral and central sites of action. The Journal of nutrition. 2005;135(5):1331-5.\u003c/li\u003e\n \u003cli\u003e Roper J, Francois F, Shue PL, Mourad MS, Pei Z, Olivares de Perez AZ, et al. Leptin and ghrelin in relation to Helicobacter pylori status in adult males. J Clin Endocrinol Metab. 2008;93(6):2350-7.\u003c/li\u003e\n \u003cli\u003e Osawa H, Nakazato M, Date Y, Kita H, Ohnishi H, Ueno H, et al. Impaired production of gastric ghrelin in chronic gastritis associated with Helicobacter pylori. The Journal of Clinical Endocrinology \u0026amp; Metabolism. 2005;90(1):10-6.\u003c/li\u003e\n \u003cli\u003e Khovidhunkit W, Kim M-S, Memon RA, Shigenaga JK, Moser AH, Feingold KR, et al. Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host. The Journal of Lipid Research. 2004;45(7):1169-96.\u003c/li\u003e\n \u003cli\u003e Buz\u0026aacute;s GM. Metabolic consequences of Helicobacter pylori infection and eradication. World journal of gastroenterology: WJG. 2014;20(18):5226.\u003c/li\u003e\n \u003cli\u003e Ellis R. Infection and coronary heart disease. Journal of Medical Microbiology. 1997;46(7):535-9.\u003c/li\u003e\n \u003cli\u003e Sung KC, Rhee EJ, Ryu SH, Beck S-H. Prevalence of Helicobacter pylori infection and its association with cardiovascular risk factors in Korean adults. International journal of cardiology. 2005;102(3):411-7.\u003c/li\u003e\n \u003cli\u003e Feingold KR, Grunfeld C. Lipids: a key player in the battle between the host and microorganisms. Journal of lipid research. 2012;53(12):2487-9.\u003c/li\u003e\n \u003cli\u003e Aimo A, Borrelli C, Giannoni A, Pastormerlo LE, Barison A, Mirizzi G, et al. Cardioprotection by remote ischemic conditioning: mechanisms and clinical evidences. World journal of cardiology. 2015;7(10):621.\u003c/li\u003e\n \u003cli\u003e Organization WH. Noncommunicable diseases country profiles 2018. 2018.\u003c/li\u003e\n \u003cli\u003e Organization WH. Noncommunicable diseases. Fact sheet. World Health Organisation, Geneva\u003ca href=\"http://www\"\u003ehttp://www\u003c/a\u003e who int/mediacentre/factsheets/fs355/en/ Accessed. 2017;23.\u003c/li\u003e\n \u003cli\u003e Overweight WHO. Global health observatory:Deaths from NCDs.\u003c/li\u003e\n \u003cli\u003e Organization. WH. Global Health Observatory:. World Health Organization. 13 December\u003c/li\u003e\n \u003cli\u003e T\u0026oacute;th PP, Potter D, Ming EE. Prevalence of lipid abnormalities in the United States: the National Health and Nutrition Examination Survey 2003-2006. Journal of clinical lipidology. 2012;6(4):325-30.\u003c/li\u003e\n \u003cli\u003e Sun G-Z, Guo L, Wang X-Z, Song H-J, Li Z, Wang J, et al. Prevalence of atrial fibrillation and its risk factors in rural China: a cross-sectional study. International journal of cardiology. 2015;182:13-7.\u003c/li\u003e\n \u003cli\u003e Oguejiofor O, Onwukwe C, Odenigbo C. Dyslipidemia in Nigeria: prevalence and pattern. Annals of African medicine. 2012;11(4):197.\u003c/li\u003e\n \u003cli\u003e Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. Jama. 2007;298(3):309-16.\u003c/li\u003e\n \u003cli\u003e D\u0026apos;Agostino Sr RB, Pencina MJ, Massaro JM, Coady S. Cardiovascular disease risk assessment: insights from Framingham. Global heart. 2013;8(1):11-23.\u003c/li\u003e\n \u003cli\u003e Reinikainen J, Laatikainen T, Karvanen J, Tolonen H. Lifetime cumulative risk factors predict cardiovascular disease mortality in a 50-year follow-up study in Finland. International Journal of Epidemiology. 2015;44(1):108-16.\u003c/li\u003e\n \u003cli\u003e Kim H-L, Jeon HH, Park IY, Choi JM, Kang JS, Min K-W. Helicobacter pylori infection is associated with elevated low density lipoprotein cholesterol levels in elderly Koreans. Journal of Korean medical science. 2011;26(5):654.\u003c/li\u003e\n \u003cli\u003e Gong Y, Wei W, Jingwei L, Nannan D, Yuan Y. Helicobacter pylori infection status correlates with serum parameter levels responding to multi-organ functions. Digestive diseases and sciences. 2015;60(6):1748-54.\u003c/li\u003e\n \u003cli\u003e Pohjanen V-M, Koivurova O-P, Niemel\u0026auml; SE, Karttunen RA, Karttunen TJ. Role of Helicobacter pylori and interleukin 6-174 gene polymorphism in dyslipidemia: a case\u0026ndash;control study. BMJ open. 2016;6(1).\u003c/li\u003e\n \u003cli\u003e Haeri M, Parham M, Habibi N, Vafaeimanesh J. Effect of Helicobacter pylori infection on serum lipid profile. Journal of lipids. 2018;2018.\u003c/li\u003e\n \u003cli\u003e Shimamoto T, Yamamichi N, Gondo K, Takahashi Y, Takeuchi C, Wada R, et al. The association of Helicobacter pylori infection with serum lipid profiles: An evaluation based on a combination of meta-analysis and a propensity score-based observational approach. PloS one. 2020;15(6):e0234433.\u003c/li\u003e\n \u003cli\u003e Kopin L, Lowenstein C. In the clinic. Dyslipidemia. Annals of internal medicine. 2010;153(3):Itc21.\u003c/li\u003e\n \u003cli\u003e Azizian R, Khosravi A, Azizian M. The association of the human leukocyte antigen (HLA) with the pathogenesis of Helicobacter pylori. J Pure Appl Microbiol. 2013;7(3):2183-9.\u003c/li\u003e\n \u003cli\u003e Atherton JC. The pathogenesis of Helicobacter pylori\u0026ndash;induced gastro-duodenal diseases. Annu Rev Pathol Mech Dis. 2006;1:63-96.\u003c/li\u003e\n \u003cli\u003e Satoh H, Saijo Y, Yoshioka E, Tsutsui H. Helicobacter Pylori infection is a significant risk for modified lipid profile in Japanese male subjects. Journal of atherosclerosis and thrombosis. 2010:1007010255-.\u003c/li\u003e\n \u003cli\u003e Tarchalski J, Guzik P, Wysocki H. Correlation between the extent of coronary atherosclerosis and lipid profile. Vascular biochemistry: Springer; 2003. p. 25-30.\u003c/li\u003e\n \u003cli\u003e Abdu A, Cheneke W, Adem M, Belete R, Getachew A. Dyslipidemia and Associated Factors Among Patients Suspected to Have Helicobacter pylori Infection at Jimma University Medical Center, Jimma, Ethiopia. International Journal of General Medicine. 2020;13:311.\u003c/li\u003e\n \u003cli\u003e Hooi JK, Lai WY, Ng WK, Suen MM, Underwood FE, Tanyingoh D, et al. Grant Support: Nil. 2017.\u003c/li\u003e\n \u003cli\u003e Hailu G, Desta K, Tadesse F. Prevalence and Risk Factors of Helicobacter pylori among Adults at Jinka Zonal Hospital, Debub Omo Zone, Southwest Ethiopia. Autoimmune Infect Dis. 2016;2:2.\u003c/li\u003e\n \u003cli\u003e Rhee E-J, Kim HC, Kim JH, Lee EY, Kim BJ, Kim EM, et al. 2018 Guidelines for the management of dyslipidemia in Korea. Journal of Lipid and Atherosclerosis. 2019;8(2):78-131.\u003c/li\u003e\n \u003cli\u003e Baigent C. Cholesterol Treatment Trialists\u0026apos;(CTT) Collaborators: Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet (London, England). 2005;366:1267-78.\u003c/li\u003e\n \u003cli\u003e Garber AJ, Abrahamson MJ, Barzilay JI, Blonde L, Bloomgarden ZT, Bush MA, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm\u0026ndash;2018 executive summary. Endocrine practice. 2018;24(1):91-120.\u003c/li\u003e\n \u003cli\u003e Karim I, Zardari AK, Shaikh MK, Baloch ZAQ, Shah SZA. DYSLIPIDEMIA. The Professional Medical Journal. 2014;21(05):956-9.\u003c/li\u003e\n \u003cli\u003e Al-Fawaeir S, Zaid MA, Awad AA, Alabedallat B. Serum lipid profile in Helicobacter pylori infected patients. American Journal of Physiology, Biochemistry and Pharmacology. 2013;2(2):1-4.\u003c/li\u003e\n \u003cli\u003e Ali MAE. Assessment of Serum High Sensitivity C-Reactive Protein, Lipid Profile and Magnesium among Sudanese Patients with H. Pylori Infection.(In Khartoum State): Sudan University of Science \u0026amp; Technology; 2019.\u003c/li\u003e\n \u003cli\u003e Jia E-Z, Zhao F-J, Hao B, Zhu T-B, Wang L-S, Chen B, et al. Helicobacter pylori infection is associated with decreased serum levels of high density lipoprotein, but not with the severity of coronary atherosclerosis. Lipids in Health and Disease. 2009;8(1):1-7.\u003c/li\u003e\n \u003cli\u003e Kim D-H, Son BK, Min K-W, Han SK, Na JU, Choi PC, et al. Chronic Gastritis Is Associated with a Decreased High-Density Lipid Level: Histological Features of Gastritis Based on the Updated Sydney System. Journal of clinical medicine. 2020;9(6):1856.\u003c/li\u003e\n \u003cli\u003e Kim TJ, Lee H, Kang M, Kim JE, Choi Y-H, Min YW, et al. Helicobacter pylori is associated with dyslipidemia but not with other risk factors of cardiovascular disease. Scientific reports. 2016;6(1):1-8.\u003c/li\u003e\n \u003cli\u003e Tang DM, Chascsa DM, Chou JY, Ho N, Auh S, Wank SA, et al. Helicobacter pylori infection is strongly associated with metabolic syndrome, and weakly associated with non‐alcoholic fatty liver disease, in a US Hispanic population. GastroHep. 2019;1(6):325-31.\u003c/li\u003e\n \u003cli\u003e Atsede D. Tegegne MAN, Meseret K. Desta,, Kumela G. Nedessa HMB. CITY PROFILE GONDAR. SES Social Inclusion and Energy Management for Informal Urban Settlements.\u003c/li\u003e\n \u003cli\u003e Gondar, Ethiopia Metro Area Population 1950-2021.\u003c/li\u003e\n \u003cli\u003e Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation. 2009;120(16):1640-5.\u003c/li\u003e\n \u003cli\u003e Megerssa Y, Gebre M, Birru S, Goshu A, Tesfaye D. Prevalence of undiagnosed diabetes mellitus and its risk factors in selected institutions at Bishoftu Town, East Shoa. Ethiopia J Diabetes Metab. 2013. These include industries, research centers, schools, health sectors and\u0026hellip;; 2013.\u003c/li\u003e\n \u003cli\u003e NHANES C. Anthropometry procedures manual. Atlanta (GA): CDC. 2007.\u003c/li\u003e\n \u003cli\u003e Corbridge SJ, Nyenhuis SM. Promoting physical activity and exercise in patients with asthma and chronic obstructive pulmonary disease. The Journal for Nurse Practitioners. 2017;13(1):41-6.\u003c/li\u003e\n \u003cli\u003e Zaret B, Battler A, Berger H, Bodenheimer M, Borer J, Brochier M, et al. Report of the joint international society and federation of cardiology/world health organization task force on nuclear cardiology. European heart journal. 1984;5(10):850-63.\u003c/li\u003e\n \u003cli\u003e Bayram F, Kocer D, Gundogan K, Kaya A, Demir O, Coskun R, et al. Prevalence of dyslipidemia and associated risk factors in Turkish adults. Journal of clinical lipidology. 2014;8(2):206-16.\u003c/li\u003e\n \u003cli\u003e Cameron N, Schell L. Human growth and development: Academic Press; 2012.\u003c/li\u003e\n \u003cli\u003e Health. Mo. National Health Survey ENS Chile 2009\u0026ndash;2010.\u003ca href=\"http://webminsalcl/portal/url/item/\"\u003ehttp://webminsalcl/portal/url/item/\u003c/a\u003e bcb03d7bc28b64dfe040010165012d23pdf. Santiago; 2010;Accessed 03 Mar 2017.\u003c/li\u003e\n \u003cli\u003e Egerter S, Braveman P, Sadegh-Nobari T, Grossman-Kahn R, Dekker M. Issue brief 6: education and health. Princeton, NJ: Robert Wood Johnson Foundation. 2009.\u003c/li\u003e\n \u003cli\u003e Brinton EA. Effects of ethanol intake on lipoproteins and atherosclerosis. Current opinion in lipidology. 2010;21(4):346-51.\u003c/li\u003e\n \u003cli\u003e Murray LJ, Bamford KB, O\u0026apos;Reilly D, McCrum EE, Evans AE. Helicobacter pylori infection: relation with cardiovascular risk factors, ischaemic heart disease, and social class. Heart. 1995;74(5):497-501.\u003c/li\u003e\n \u003cli\u003e Moutar F, Alsamarai A, Ibrahim F. Lipid profile in patients with gastritis. World J Pharm Pharm Sci. 2016;5(7):74-90.\u003c/li\u003e\n \u003cli\u003e Grunfeld C, Gulli R, Moser A, Gavin L, Feingold K. Effect of tumor necrosis factor administration in vivo on lipoprotein lipase activity in various tissues of the rat. Journal of Lipid Research. 1989;30(4):579-85.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Associated factors, Dyslipidemia, H. pylori","lastPublishedDoi":"10.21203/rs.3.rs-1489416/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1489416/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBackground:\u003c/em\u003e\u003c/strong\u003e Dyslipidemia refers to a lipid profile disturbance due to decreased high-density lipoprotein cholesterol and elevated low-density lipoprotein cholesterol, triglycerides, and total cholesterol. H. pylori infection can lead to some appetite-related disorders and significant changes in body weight. For this reason, H. pylori infection may cause deregulated absorption of nutrients in the digestive system, contributing to changes in serum lipids. The purpose of this study is to assess dyslipidemia and its associated factors among \u003cem\u003eHelicobacter Pylori\u003c/em\u003e infected patients attending at University of Gondar Comprehensive specialized hospital.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMethods:\u003c/em\u003e \u003c/strong\u003eA comparative cross-sectional study was conducted on 231 \u003cem\u003eH. pylori\u003c/em\u003e positive and control groups which were included by the convenience sampling technique from March to May 2021 at University of Gondar specialized hospital. Sociodemographic and behavioral characteristic data were collected using a pretested semi structured questionnaire. About 5ml of venous blood were used to determine the lipid profiles using DxC 700 AU chemistry auto analyzer\u003cstrong\u003e (\u003c/strong\u003eBeckman Coulter, USA). The data were entered into Epi-data version 4.6 and analyzed using SPSS version 25. Mann-Whitney U test was used to compare the median of the continuous variables. Multivariable logistic regression analysis was done to determine the associated factors of dyslipidemia. P-value \u0026lt;0.05 is considered statistically significant.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResults\u003c/em\u003e:\u003c/strong\u003e The magnitude of dyslipidemia among \u003cem\u003eHelicobacter pylori\u003c/em\u003e-infected patients was 71.8% (95% CI: 62.7-79.7). There was a statistically significant difference in lipid profiles between \u003cem\u003eHelicobacter pylori\u003c/em\u003e-infected patients and control groups. The median (IQR) of lipid profiles in \u003cem\u003eHelicobacter pylori-\u003c/em\u003epositive patients and control groups were for low-density lipoprotein: 108 (89.8, 145.5) vs 95 (79.45, 115.8, P\u0026lt;0.001), for triglycerides: 93 (65,117) vs 83 (58.5, 102, P=0.031), and cholesterol: 143 (119.5, 169,) vs 125 (110,143, P\u0026lt;0.001) mg/dl respectively. \u003cem\u003eHelicobacter pylori\u003c/em\u003e infection (95%CI: 1.637-6.966), alcohol drinking (95%CI: 2.616-36.467), unable to read and write (95%CI: 1.384-14.077)), primary school (95%CI: 1.026-9.170), and secondary school (95%CI: 2.167-10.571) were a significant associated variables with dyslipidemia (P\u0026lt;0.05).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConclusion:\u003c/em\u003e \u003c/strong\u003eThere was a median lipid profile statistically significant difference between \u003cem\u003eH. pylori\u003c/em\u003e positive and control groups. \u003cem\u003eH. pylori\u003c/em\u003e infection, educational status, and alcohol drinking habit had statistically significant association of dyslipidemia.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","manuscriptTitle":"Dyslipidemia and its associated factors among Helicobacter Pylori-infected Patients Attending at University of Gondar Comprehensive Specialized Hospital, Gondar, North- West Ethiopia: A Comparative Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-30 20:10:47","doi":"10.21203/rs.3.rs-1489416/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b988fb01-744b-4a0c-b8fb-465b145fa86e","owner":[],"postedDate":"March 30th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-03-30T20:10:49+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-30 20:10:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1489416","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1489416","identity":"rs-1489416","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}