Abnormal Serum Levels of Liver Enzyme Markers and Related Risk Factors in Type 2 Diabetes Mellitus Patients Attending the Buea Regional Hospital, Cameroon

Abnormal Serum Levels of Liver Enzyme Markers and Related Risk Factors in Type 2 Diabetes Mellitus Patients Attending the Buea Regional Hospital, Cameroon | 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 Abnormal Serum Levels of Liver Enzyme Markers and Related Risk Factors in Type 2 Diabetes Mellitus Patients Attending the Buea Regional Hospital, Cameroon Arnaud Fondjo Kouam, Saturine Mengwe Mofor, Madeleine Yvanna Nyangono Essam, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6388673/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 Objectives: The prevalence of type 2 Diabetes Mellitus (T2DM) is increasing globally, leading to complications, including liver damage. This study aims to examine serum biomarkers of liver injury and the related risk factors in T2DM patients at the Buea Regional Hospital, Cameroon Methods: The sociodemographic, clinical, and behavioral characteristics of patients with T2DM were captured using a structured questionnaire. Anthropometric parameters were measured, and the Body Mass Index was calculated. Blood samples were analyzed for biomarkers of liver damage (ALT, AST, GGT, and ALP), considering a liver enzyme profile abnormal if it had more than 2 abnormally elevated values. Bivariate and multivariate logistic regressions analysis were used to identify risk factors, with significance set at P<0.05. Results: Among the 170 participants recruited, 75.9% were female. The median age was 62 years. Over half (52.9%) were married, 64.7% attended primary school, and 55.3% were retired. Also, 59.4% had diabetes for over five years, and all reported knowledge of diabetes care. About 73.3% adhered to their medication, 64.7% consumed alcohol, 28.8% smoked tobacco, with 22.4% engaged in physical activity, and 77.6% with comorbidities. Blood sugar monitoring was practiced by 80%, with 66.5% having high blood pressure. Healthy weight individuals were 31.2%, while 41.2% were obese and 56.5% had abnormal liver enzyme profiles. Five factors: duration of illness, physical inactivity, tobacco smoking, comorbidities, and overweight/obesity were significantly (P<0.05) associated with abnormal liver enzyme profile. Conclusion: Our findings identify risk factors linked to elevated liver enzyme markers indicating liver injury in T2DM patients. Diabetic patients Liver injury Serum biomarkers Abnormal level Risk factors Figures Figure 1 1. Introduction Diabetes Mellitus (DM) ranks among the most prevalent non-communicable diseases, rising at an alarming pace and impacting a considerable number of individuals. This disease has quickly become a global health issue, largely due to high calorie intake, lack of physical activity, inadequate diagnosis, and poor management [ 1 , 2 ]; it is now posing a risk of reaching endemic status by 2030, particularly in developing nations [ 3 , 4 ]. Moreover, it is a metabolic disorder characterized by sustained high blood sugar levels with the disturbance of the metabolism of proteins, lipids, and carbohydrates as a result of a deficiency in insulin secretion and/or action [ 5 ]. Globally, around 1 in 11 adults experience DM, with type 2 DM (T2DM) representing approximately 90% of cases [ 4 ]. T2DM arises from dysfunctional pancreatic β-cell activity and an inability to produce enough insulin, coupled with insulin resistance characterized by decreased sensitivity to insulin in target tissues such as muscles and the liver [ 6 ]. T2DM negatively impacts various systems and organs in the body, including the liver, which is crucial in the detoxification process, glycaemia regulation, and the metabolism of lipids, proteins, and carbohydrates [ 7 – 9 ]. Indeed, liver impairment, characterized by abnormally elevated serum levels of liver enzymes such as transaminases: alanine aminotransferase (ALT) and aspartate aminotransferase (AST); alkaline phosphatase (ALP) and γ-glutamyl-transferase (GGT), is commonly observed in about 70% of diabetic patients and accounts for roughly 2–4% of fatalities in T2DM [ 10 , 11 ]. Although T2DM represents a significant public health issue in Cameroon, there is a paucity of knowledge regarding the relationship between T2DM and liver injury or dysfunction, which further raises morbidity and mortality among Cameroonian diabetic patients. Accordingly, continuous monitoring of serum liver enzymes and identification of potential risk factors associated with their abnormal levels in T2DM patients are necessary to detect early signs of hepatic injury that may prompt medical intervention to prevent further detrimental complications for the patients. Therefore, the purpose of this study was to assess the serum levels of liver enzyme markers and identify the potential risk factors related to their abnormal levels in T2DM patients attending the Buea Regional Hospital, South-West Region, Cameroon. 2. Material and methods 2.1 Study design and settings This descriptive cross-sectional study followed by laboratory analysis took place at the Diabetes Unit of the Buea Regional Hospital, from June to September 2024. The city of Buea serves as the Headquarters of the South-West Region of Cameroon. It is located on the eastern slope of Mount Cameroon. It has coordinates 4°10ˈ0″N994ˈ0″E ⁄ 4.16667°N9.23333°E with an elevation of 896 m above sea level. The Buea Regional Hospital is classified as a secondary health institution, that delivers both outpatient and inpatient services for various diseases, including chronic conditions such as hypertension, stroke, kidney and cardiac diseases, and DM. 2.2 Target population, sampling technique and sample size estimation The target population was adults aged over 21 years suffering from T2DM who were on anti-diabetic medications for at least 6 months. Diabetic patients with a history of liver diseases, clinical symptoms of acute hepatitis, infected with hepatitis C or B virus, or taking hepatotoxic drugs were excluded from the study. A convenient random sampling technique was used for participant recruitment. After approaching a potential participant, the goals of the investigation, as well as the potential risks and benefits, were clearly explained, and only those who gave their consent by signing the informed consent form were enrolled in the study. The estimated sample size was calculated using the Lorentz formula (1). (1): \(\:N=\frac{{Z}^{2}\times\:p(1-p)}{{d}^{2}}\) Where: N is the calculated sample size; Z = 1.96 is the typical value of the degree of confidence at 95%; p = 7.1% is the prevalence of diabetes among adults living in Cameroon [ 12 ]. d = 5% is the margin error permitted. After calculation, N ≈ 102. For a better representation of the population, 20% of N was added. Therefore, the minimum number of diabetic patients to be enrolled in this study was estimated at 123 participants. 2.3 Ethical consideration The study was conducted in accordance with guidelines from the declarations of Helsinki. Ethical Clearance for this study was obtained from the Institutional Review Board of the Faculty of Health Sciences, University of Buea (Ref N°: 2024/2484-03/UB/SG/IRB/FHS) (Online Resources S1_file). In addition, an Administrative Authorizations were issued by the Regional Health Office of the South-West Region, Ministry of Public Health, Cameroon (Ref N°: P42/MINSANTE/SWR/RDPH/CB.PT/183/293) and from the director of the Buea Regional Hospital (Ref N°: 22/05/2024/MPH/SWRDPH/BRH/IRB), respectively. The information collected during the interview was not disclosed, and the participant’s names were replaced with codes during the data collection. 2.4 Data collection procedure 2.4.1 General characteristic of diabetic patients enrolled in the study An overview of the characteristics of diabetic patients recruited for this investigation was captured through a structured questionnaire (Online Resources S_2 file) administered in person. The questionnaire allowed for gathering information regarding socio-demographic data, the history and monitoring of illness, eating habits and physical activity practices, alcohol consumption, and the use of tobacco products. In addition, blood pressure and anthropometric parameters including height and weight were measured, and the Body Mass Index (BMI) was subsequently calculated; each participant was classified as underweight, normal weight, overweight, or obese based on a BMI of 30, respectively. At the end of the interview, 5 mL of blood was collected via venipuncture into a tube free of anticoagulant and centrifuged (3000×g, 10 min, 4°C). The serum obtained was used to measure liver enzyme markers. 2.4.2 Evaluation of some biochemical markers of liver injury in diabetic patients The biochemical markers of liver injury were assessed by measuring the serum activity of some liver enzymes, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and γ-glutamyl-transferase (GGT) using commercial assay kits (Catalog N° REF_80227, Catalog N° REF_80225, Catalog N° REF_80014 and Catalog N° REF_4110 respectively for ALT, AST, ALP, and GGT) purchased from BIOLABO, Les Hautes Rives, Maizy, France. The assays were performed in accordance with the manufacturer's instructions using a semi-automatic spectrophotometer. 2.4.3 Estimation of the alteration of serum liver enzyme markers The level of alteration of the serum liver enzyme activity was estimated by considering the normal range of values (reference values) for each enzyme assessed. These reference values are: from 10 to 42 IU/L, from 8 to 39 IU/L, from 40 to 129 IU/L, and from 11 to 50 IU/L respectively for ALT, AST, ALP, and GGT, as indicated in the manufacturer's instructions. Accordingly, any value found within its normal range or higher than upper limit of the normal range of values (ULN) was considered normal or high, respectively. Similarly, any patient with more than 2 high values was considered to have an abnormal status of liver enzyme profile. 2.5 Data management and statistical analysis After checking that all sections of the questionnaire had been completed, the data collected and the results of the laboratory analyses for each participant were saved in Excel 2013 (Microsoft Corporation, USA) (Online Resources S3_file), and then exported to the statistical analysis software SPSS (Statistical Package for Social Sciences) version 25.0 (SPSS Inc., USA) or GraphPad Prism version 8.0.2. Descriptive statistics were performed using SPSS software. Qualitative variables were presented as frequency and percentage (%). Quantitative variables were first tested for normality using the Kolmogorov-Smirnov test. Variables that followed a normal distribution and those that did not pass the test were expressed as mean ± standard deviation or median and interquartile range respectively. Comparison of median values between two categories was done by the non-parametric Mann Whitney U test. Risk factors associated with the abnormal status of liver enzyme profile were determined through bivariate and multivariate logistic regression analysis. The significance threshold was declared at P < 0.05. 3. Results 3.1 Socio-demographic characteristics of the enrolled T2DM patients A total of 170 patients were recruited for the study. The gender ratio was 3.15, favoring females, who made up 75.9% (129/170) of the participants. The median age of the participants was 62 years, with an interquartile range of 55 to 70 years for the 25% and 75% percentiles, respectively. A significant portion of the participants, 66.5% (113/170), were over 60 years old. Additionally, more than half of the participants were married (52.9%; 90/170), and 64.7% (110/170) attended primary school. In terms of occupation, 55.3% (94/170) of the enrolled patients were retired (Table 1 ). Table 1 Socio-demographic characteristics of diabetic patients attending the Buea Regional Hospital Socio-demographic characteristics Categories Frequency (n) Percentage (%) Gender Female 129 75.9 Male 41 24.1 Total 170 100.0 Age group [21–40[ 6 3.5 [40–60] 51 30.0 > 60 113 66.5 Total 170 100.0 Marital status Married 90 52.9 Single 17 10.0 Widow(er) 63 37.1 Total 170 100.0 Education Primary 110 64.7 Secondary 36 21.2 University 24 14.1 Total 170 100.0 Occupation Civil servant 14 8.2 Employee 62 36.5 Retired 94 55.3 Total 170 100.0 3.2 Behavioral and clinical features of study participants Table 2 outlines the frequency distribution of study participants based on their behavioral and clinical characteristics. Regarding the duration of illness, 59.4% (101/170) reported being diagnosed with diabetes for over five years. All participants (100%; 170/170) indicated they had knowledge of diabetes care, while 73.3% (128/170) strictly adhered to their anti-diabetic medications. Among the participants, 64.7% (110/170) consumed alcohol, and 28.8% (49/170) were tobacco smokers. Only 22.4% (38/170) of the enrolled diabetic patients engaged in physical activity, and 77.6% (132/170) had at least one comorbidity. Systematic blood sugar monitoring was reported by 80% (136/170) of participants, while 66.5% (113/170) had high blood pressure. Based on their BMI index, those with healthy weight comprised 31.2% (33/170), whereas 27.6% (47/170) were overweight and 41.2% (70 out of 170) were obese. Abnormally high levels of serum ALT, AST, ALP, and GGT activities were observed in 61.8% (105/170), 62.4% (106/170), 37.3% (64/170), and 50% (85/170) of study participants, respectively. Consequently, the prevalence of abnormal liver enzyme profiles among the enrolled T2DM patients was estimated to be 56.5% (96/170). Table 2 Behavioral and clinical features of diabetic patients attending the Buea Regional Hospital Behavioral / Clinical features Categories Frequency (n) Percentage (%) Duration of illness ≤ 5 years 69 40.6 > 5 years 101 59.4 Total 170 100.0 Knowledge on diabetes care Yes 170 100.0 No 0 0 Total 170 100.0 Adherence to antidiabetic drugs Yes 128 73.3 No 42 24.7 Total 170 100.0 Alcohol consumption Yes 110 64.7 No 60 35.3 Total 170 100.0 Tobacco smoking Yes 49 28.8 No 121 71.2 Total 170 100.0 Practice of physical activity Yes 38 22.4 No 132 77.6 Total 170 100.0 Comorbidity Yes 132 77.6 No 38 22.4 Total 170 100.0 Blood sugar monitoring Yes 136 80.0 No 34 20.0 Total 170 100.0 Level of blood pressure High 113 66.5 Normal 57 33.5 Total 170 100.0 Interpretation of BMI Healthy weight 53 31.2 Overweight 47 27.6 Obese 70 41.2 Total 170 100.0 ALT (IU/L) High > (42) 105 61.8 Normal (39) 106 62.4 Normal (129) 64 37.6 Normal (50) 85 50.0 Normal < (50) 85 50.0 Total 170 100.0 Status of liver enzyme profile Abnormal 96 56.5 Normal 74 43.5 Total 170 100.0 BMI: Body Mass Index; ALT: Alanine amino transferase; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase; GGT: γ-glutamyl-transferase. 3.3 Association between the socio-demographic characteristics and the status of liver enzyme profile The potential socio-demographic factors associated with abnormal liver enzyme profiles were evaluated using bivariate logistic regression analysis, as summarized in Table 3 . Although a higher percentage of females (45.9%; 78 out of 129) were affected by abnormal liver enzyme profiles compared to males (10.6%; 18 out of 41), no significant association was found between gender and liver enzyme status (cOR: 1.95; CI: 0.96–3.97; P = 0.065). Additionally, the analyses indicated that age group (cOR: 0.69 and 0.71; CI: 0.13–3.55 and 0.37–1.39; P = 0.654 and 0.321), marital status (cOR: 0.72 and 1.20; CI: 0.37–1.38 and 0.39–3.68; P = 0.322 and 0.742), education level (cOR: 0.94 and 1.92; CI: 0.39–2.29 and 0.66–3.97; P = 0.898 and 0.232), and occupation (cOR: 1.12 and 0.54; CI: 0.35–3.60 and 0.96–3.97; P = 0.853 and 0.067) did not significantly influence liver enzyme status among the enrolled T2DM patients. Table 3 Bivariate logistic regression analysis for the association between the socio-demographic characteristics of diabetic patients and their status of liver enzyme profile Variables Categories Status of liver enzyme profile Bivariate logistic regression Abnormal n, (%) Normal n, (%) Total cOR [95% CI] P value Gender Female 78 (45.9) 51 (30.0) 129 (75.9) 1.95 [0.96–3.97] 0.065 Male 18 (10.6) 23 (13.5) 41 (24.1) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Age group [21–40[ 3 (1.8) 3 (1.8) 6 (3.5) 0.69 [0.13–3.55] 0.654 [40–60] 26 (15.3) 25 (14.7) 51 (30.0) 0.71 [0.37–1.39] 0.321 > 60 67 (39.4) 46 (27.1) 113 (65.5) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Marital status Married 47 (27.6) 43 (25.3) 90 (52.9) 0.72 [0.37–1.38] 0.322 Single 11 (6.5) 6 (3.5) 17 (10.0) 1.20 [0.39–3.68] 0.742 Widow(er) 38 (22.4) 25 (14.7) 63 (37.1) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Education Primary 58 (34.1) 52 (30.6) 110 (64.7) 0.94 [0.39–2.29] 0.898 Secondary 25 (14.7) 11 (6.5) 36 (21.2) 1.92 [0.66–5.61] 0.232 University 13 (7.6) 11 (6.5) 24 (14.1) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Occupation Civil servant 9 (5.3) 5 (2.9) 14 (8.2) 1.12 [0.35–3.60] 0.853 Employee 29 (17.1) 33 (19.4) 62 (36.5) 0.54 [0.96–3.97] 0.067 Retired 58 (34.1) 36 (21.2) 94 (55.3) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / cOR: Crude Odd Ratio; CI: Confidence Interval. 3.4 Relationship between the behavioral and clinical factors and the status of liver enzyme profile of study participants Table 4 summarizes the statistical associations between the behavioral and clinical factors related to an abnormal liver enzyme profile, determined through bivariate and multivariate logistic regression analysis, as indicated below. Table 4 Bivariate and multivariate logistic regression analysis for the behavioral and clinical factors associated with the abnormal liver enzyme profile in diabetic patients attending the Buea Regional Hospital Behavioral / Clinical features Categories Status of liver enzyme profile Bivariate logistic regression Multivariate logistic regression Abnormal n, (%) Normal n, (%) Total cOR [95% CI] P values aOR [95% CI] P values Duration of illness > 5 years 70 (41.2) 31 (18.2) 101 (59.4) 3.73 [1.96–7.12] < 0.0001* 6.23 [2.04–19.08] 0.001* ≤ 5 years 26 (15.3) 43 (25.3 69 (40.6) 1 / / 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / / / / Adherence to antidiabetic drugs No 22 (12.9) 20 (11.8) 42 (24.7) 0.80 [0.39–1.61] 0.538 / Yes 74 (43.5) 54 (31.8) 128 (75.3) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Alcohol consumption No 25 (14.7) 35 (20.6) 60 (35.3) 0.39 [0.21–0.75] 0.004* 0.81 [0.27–2.40] 0.703 Yes 71 (41.8) 39 (22.9) 110 (64.7) 1 / / 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / / / / Tobacco smoking No 49 (28.8) 72 (42.4) 121 (71.2) 0.029 [0.007–0.12] < 0.0001* 0.022 [0.003– 0.14] < 0.0001 Yes 47 (27.6) 2 (1.2) 49 (28.8) 1 / / 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / / / / Practice of physical activity No 88 (51.8) 44 (25.9) 132 (77.6) 7.50 [3.17–17.72] < 0.0001* 4.64 [1.34–16.07] 0.015* Yes 8 (4.7) 30 (17.6) 38 (22.4) 1 / / 1 Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Comorbidity No 13 (7.6) 25 (14.7) 38 (22.4) 0.31 [0.14–0.65] 0.002* 0.18 [0.049–0.70] 0.013* Yes 83 (48.8) 49 (28.8) 132 (77.6) 1 / / 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / / / / Blood sugar monitoring No 18 (10.6) 16 (9.4) 34 (20.0) 0.84 [0.39–1.78] 0.643 / Yes 78 (45.9) 58 (34.1) 136 (80.0) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Level of blood pressure High 67 (39.4) 48 (27.1) 113 (66.5) 1.40 [0.74–2.67] 0.297 / Normal 29 (17.1) 28 (16.5) 57 (33.5) 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / Interpretation of BMI Healthy weight 10 (5.9) 43 (25.3) 53 (31.2) 0.12 [0.048–0.30] 0.0001* 0.048 [0.011–0.21] < 0.0001* Obese 55 (32.4 15 (8.8) 70 (41.2) 1.89 [0.82–4.34] 0.132 2.55 [0.80–8.09] 0.112 Overweight 31 (18.2) 16 (9.4) (47 (27.6) 1 / / 1 / / Total 96 (56.5) 74 (43.5) 170 (100.0) / / / / / / BMI: Body Mass Index; cOR: Crude Odd Ratio; aOR: Adjusted Odd Ratio; CI: Confidence Interval; The bold cOR or aOR and P-value are indicators of a significant association. 3.4.1 Possible factors influencing the abnormal status of liver enzyme profile For the bivariate analysis, a simple logistic regression model was used at 95% confidence interval (CI) with a cut-off point p-value set at 0.05 to identify factors for multivariate analysis. The clinical and behavioral factors identified as significantly influencing the liver enzyme status were as follows: duration of illness (cOR: 3.73; CI: 1.96–7.12; P < 0.0001); alcohol consumption (cOR: 0.39; CI: 0.21–0.75; P = 0.004); tobacco smoking (cOR: 0.029; CI: 0.007–0.12; P < 0.0001); comorbidity (cOR: 0.31; CI: 0.14–0.65; P = 0.002); practice of physical activity (cOR: 7.50; CI: 3.17–17.72; P < 0.0001); and BMI index (cOR: 0.12; CI: 0.048–0.30; P < 0.0001). 3.4.2 Factors associated with abnormal liver enzyme profile Following the bivariate analysis, a multivariate logistic regression analysis was performed in the same conditions to determine the factors associated with abnormal liver enzyme profile among those identified as influencing the liver enzyme status. Five factors were found to be significantly associated with abnormal levels of liver enzyme among the enrolled T2DM patients. These factors were: duration of illness (aOR: 6.23; CI: 2.04–19.08; P = 0.001); tobacco smoking (aOR: 0.022; CI: 0.003–0.14; P < 0.0001); practice of physical activity (aOR: 4.64; CI: 1.34–16.07; P = 0. 015); comorbidity (aOR: 0.18; CI: 0.049–0.70; P = 0.013); and BMI (aOR: 0.048; CI: 0.011–0.21; P < 0.0001). This means that the enrolled T2DM participants with a duration of illness greater than 5 years (aOR: 6.23) and those not engaged in physical activity (aOR: 4.64) were significantly (P < 0.05) at higher risk of presenting abnormal liver enzyme status, compared to the T2DM patients with a duration of illness less than 5 years, and those who engaged in physical activity, respectively. Similarly, T2DM patients who did not smoke (aOR: 0.022), without comorbidity (aOR: 0.18), and with healthy weight (aOR: 0.048) were significantly (P < 0.05) less at risk of having an abnormal liver enzyme profile, compared to the patients who smoked, had comorbidity, and those who are overweight or obese, respectively. 3.5 Influence of the identified risk factors on the serum levels of liver enzyme activity Figure 1 depicts the variation in liver enzyme (ALT, AST, GGT, and ALP) activity according to the risk factors associated with their abnormal profile. The median values of serum ALT, AST, and GGT activities were significantly (P < 0.05) elevated among T2DM patients with a duration of illness greater than 5 years (Fig. 1 A), those who smoked (Fig. 1 B), those who were physically inactive (Fig. 1 C), those with comorbidities (Fig. 1 D), and those who were obese or overweight (Fig. 1 E), compared to those with a duration of illness less than 5 years, non-smokers, physically active individuals, those without comorbidities, and those with a healthy weight, respectively. Regarding the median values of ALP, no significant (P > 0.05) difference was observed between patients with more than 5 years of illness duration and those with less than 5 years (Fig. 1 A), or between healthy weight and overweight patients (Fig. 1 E). In contrast, median values of ALP activity were significantly increased in T2DM patients who smoked (Fig. 1 B), were physically inactive (Fig. 1 C), had comorbidities (Fig. 1 D), and were obese (Fig. 1 E), compared to non-smokers, physically active individuals, those without comorbidities, and healthy weight patients, respectively. 4. Discussion The rising global prevalence of Type 2 Diabetes Mellitus (T2DM) poses significant health challenges and complications, including those affecting the liver, particularly in low-to-middle-income countries like Cameroon, where healthcare resources is often limited [ 10 , 13 , 14 ]. This study examining the serum levels of biomarkers of liver injury in T2DM patients attending the Buea Regional Hospital of Cameroon, provides valuable insights into the interaction between liver health and the clinical and behavioral features of this target population. Indeed, identifying the risk factors that contribute to abnormal liver enzyme levels can facilitate the development of effective intervention strategies to prevent the occurrence of liver diseases in T2DM patients. Hence, several clinical and behavioral factors related to abnormal serum liver enzyme levels were identified. These included the duration of illness, practice of physical activity, tobacco smoking, presence of comorbidities, and high Body Mass Index (BMI). Each of these factors is well known to affect liver health [ 15 – 17 ] and addressing them holistically may improve health outcomes among T2DM patients. The duration of T2DM is a fundamental factor influencing the development of liver-related complications. Indeed, chronic hyperglycemia resulting from insufficient glycemic control over time can lead to metabolic changes that predispose individuals to liver dysfunction, characterized by abnormal high level of serum liver enzyme [ 18 ]. Patients with a longer duration of diabetes are at an elevated risk of accumulating lipids into hepatic tissues, leading to inflammation and in severe cases, may progress to non-alcoholic steatohepatitis (NASH) and ultimately result in liver cirrhosis or hepatocellular carcinoma [ 9 , 19 ]. This study showed that T2DM patients with a duration of illness greater than 5 years display a significant (P < 0.05) increased serum level of ALT, AST, GGT and ALP activities and were significantly more at risk (aOR: 6.238; P = 0.001) of having abnormal liver enzyme profile, compared to those with less than 5 years history of the disease. These observations suggest a possible development of liver pathology in these old T2DM patients, which need to be confirmed by further analysis. To mitigate these risks related to the duration of the disease, it is crucial for healthcare providers to implement systematic screenings for liver function markers, especially in patients with a prolonged history of diabetes. This could help identify early signs of liver damage, allowing for timely interventions that could prevent the progression of liver disease. Also, educational programs aimed at raising awareness among T2DM patients about the potential hepatic complications related to the duration of their illness can empower them to take a more active role in their disease management. Moreso, regular physical activity is universally recognized for its beneficial effects on metabolic health, especially in managing diabetes [ 20 , 21 ]. Our findings indicate that patients who engaged in regular physical activity exhibited significant (P < 0.05) lower serum liver enzyme levels and were significantly less at risk of presenting abnormal status of liver enzyme profile, compared to physically inactive patients (aOR: 4.64; P = 0. 015). Given that physical activity is known to enhance lipid profiles and reduce systemic inflammation, creating a healthier environment for hepatic function, these findings can be attributed to beneficial effect of physical activity on lipid metabolism and improved insulin sensitivity, as reported by Cannata et al. (2020) [ 22 ]. This study also emphasizes that incorporating structured exercise regimen into diabetes management plans cannot be overstated. Accordingly, healthcare providers should consider implementing tailored exercise programs for their patients, encouraging activities that are accessible and enjoyable to foster long-term adherence. In addition, engaging patients in community-focused activities may also promote social support systems, which can further motivate sustained participation of T2DM patients in physical activities. The detrimental effects of tobacco smoking on health are well established, and the study indicates that smoking significantly correlates with elevated liver enzyme levels in T2DM patients [ 23 , 24 ]. Tobacco use has been associated with an increased risk of liver disease through mechanisms involving oxidative stress, inflammation, and metabolic dysregulation [ 24 , 25 ]. The chemicals such cadmium, present in tobacco smoke can induce hepatic oxidative injury, characterized by abnormal increased serum levels of transaminases [ 26 ]. In this study, up to 28.8% of the enrolled T2DM patients were tobacco users. These patients presented significantly (P < 0.05) increased serum levels of ALT, AST, GGT, and ALP and were at significantly (aOR: 0.022; P < 0.0001) higher risk of displaying abnormal liver enzyme profile, compared to non-smoker patients. These observations suggest that smoking can promote early development of liver complications in T2DM patients. Accordingly, healthcare interventions should prioritize smoking cessation programs tailored for T2DM patients by providing resources for cessation support, such as counseling and pharmacotherapy. Also, creating awareness campaigns that educate patients on the specific risks associated with smoking and liver health can empower individuals to make informed lifestyle choices. The presence of comorbidities, such as hypertension, obesity, cardiovascular and kidney diseases, and dyslipidemia, represents further challenges in managing the health of T2DM patients [ 27 , 28 ]. In this study, 77.6% (132/170) of participants presented at least one of these comorbid conditions and were more likely to display abnormal liver enzyme levels, when compared to patients without any comorbidity. In fact, multivariate logistic regression analysis showed that comorbidities were significantly (aOR: 0.18; P = 0.013) associated with abnormal status of liver enzyme profile. These findings highlight that effective diabetes treatment must include strategies to address all comorbid conditions simultaneously. This may include coordinated efforts among healthcare providers to ensure a cohesive treatment plan that considers managing not only glycaemia, but also blood pressure, and lipidemia. This could be helpful for better management of T2DM and its related complications, including liver damage. This study also reveals a significant (aOR: 0.048; P < 0.0001) association between elevated BMI and abnormal serum levels of liver enzyme markers in T2DM patients. Indeed, individuals with a higher BMI, particularly those categorized as overweight or obese, are more likely to exhibit elevated liver enzymes, which may indicate liver stress or damage [ 29 – 31 ]. These observations suggest that maintaining a healthy weight could potentially mitigate liver complications in diabetic patients, emphasizing the importance of weight management in this population. 5. Conclusion In summary, the findings from the present study which aimed to measure the serum levels of liver enzyme and identify the potential risk factors related to their abnormal levels in T2DM patients attending the Buea Regional Hospital-Cameroon, several clinical and behavioral factors, including the duration of illness, non-practice of physical activity, tobacco smoking, presence of comorbidities, and elevated BMI values were strongly associated with abnormal serum levels of liver enzyme, suggesting the progressive occurrence of hepatic damage. These observations pave the way for future research that will validate these associations in larger cohorts and explore the underlying mechanisms linking these risk factors to hepatic injury. Declarations Acknowledgment The authors express their gratitude to all participants involved in this study and acknowledge the laboratory staff of the Buea Regional Hospital for their technical assistance; they also appreciate the support from the trimester research modernization funding provided by the Ministry of Higher Education of Cameroon to Dr. Arnaud Fondjo Kouam. Funding The authors declare that there is no funding to report. Data availability statement. The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. Ethical statements Ethical Clearance for this study was obtained from the Institutional Review Board of the Faculty of Health Sciences, University of Buea (Ref N°: 2024/2484-03/UB/SG/IRB/FHS) Declaration of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Li D-D, Yang Y, Gao Z-Y, Zhao L-H, Yang X, Xu F, et al. Sedentary lifestyle and body composition in type 2 diabetes. Diabetol Metab Syndr. 2022;14:8. Reed J, Bain S, Kanamarlapudi V. A Review of Current Trends with Type 2 Diabetes Epidemiology, Aetiology, Pathogenesis, Treatments and Future Perspectives. Diabetes Metab Syndr Obes Targets Ther. 2021;14:3567–602. Whiting DR, Guariguata L, Weil C, Shaw J. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract. 2011;94:311–21. Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol. 2018;14:88–98. Masky B, Adjia H, Miaffo D, Aboubakar Oumarou BF, Foyet HS, Maguirgue K, et al. Antidiabetic activity of the aqueous extract of Erigeron floribundus leaves in streptozotocin-induced type 1 diabetes model in Wistar rats. Metab Open. 2024;22:100288. Pan G, Lu Y, Wei Z, Li Y, Li L, Pan X. A review on the in vitro and in vivo screening of α-glucosidase inhibitors. Heliyon. 2024;10:e37467. Baig NA, Herrine SK, Rubin R. Liver disease and diabetes mellitus. Clin Lab Med. 2001;21:193–207. Kouam AF, Njingou I, Pekam Magoudjou NJ, Ngoumbe HB, Nfombouot Njitoyap PH, Zeuko’o EM, et al. Delayed treatment with hydro-ethanolic extract of Khaya grandifoliola protects mice from acetaminophen-hepatotoxicity through inhibition of c-Jun N-terminal kinase phosphorylation and mitochondrial dysfunction. Pharm Sci Adv. 2024;2:100049. Mohamed J, Nazratun Nafizah AH, Zariyantey AH, Budin SB. Mechanisms of Diabetes-Induced Liver Damage: The role of oxidative stress and inflammation. Sultan Qaboos Univ Med J. 2016;16:e132-141. Ciardullo S, Morabito G, Rea F, Savaré L, Perseghin G, Corrao G. Time Trends in Liver-Related Mortality in People With and Without Diabetes: Results From a Population-Based Study. J Clin Endocrinol Metab. 2024;109:2513–9. Sheng X, Che H, Ji Q, Yang F, Lv J, Wang Y, et al. The Relationship Between Liver Enzymes and Insulin Resistance in Type 2 Diabetes Patients with Nonalcoholic Fatty Liver Disease. Horm Metab Res Horm Stoffwechselforschung Horm Metab. 2018;50:397–402. Bigna JJ, Nansseu JR, Katte J-C, Noubiap JJ. Prevalence of prediabetes and diabetes mellitus among adults residing in Cameroon: A systematic review and meta-analysis. Diabetes Res Clin Pract. 2018;137:109–18. He K-J, Wang H, Xu J, Gong G, Liu X, Guan H. Global burden of type 2 diabetes mellitus from 1990 to 2021, with projections of prevalence to 2044: a systematic analysis across SDI levels for the global burden of disease study 2021. Front Endocrinol [Internet]. 2024 [cited 2025 Mar 30];15. Available from: https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2024.1501690/full Khan MAB, Hashim MJ, King JK, Govender RD, Mustafa H, Al Kaabi J. Epidemiology of Type 2 Diabetes – Global Burden of Disease and Forecasted Trends. J Epidemiol Glob Health. 2020;10:107–11. Balou HA, Joukar F, Shahdkar M, Orang Goorabzarmakhi M, Maroufizadeh S, Mansour-Ghanaei F. Physical activity and elevated liver enzymes: A cross-sectional study from the PERSIAN Guilan cohort study. Casp J Intern Med. 2025;16:246–54. Jalili V, Poorahmadi Z, Hasanpour Ardekanizadeh N, Gholamalizadeh M, Ajami M, Houshiarrad A, et al. The association between obesity with serum levels of liver enzymes, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase and gamma‐glutamyl transferase in adult women. Endocrinol Diabetes Metab. 2022;5:e367. Niemelä O, Bloigu A, Bloigu R, Aalto M, Laatikainen T. Associations between Liver Enzymes, Lifestyle Risk Factors and Pre-Existing Medical Conditions in a Population-Based Cross-Sectional Sample. J Clin Med. 2023;12:4276. Sanchez L, Chen Y, Lassailly G, Qi X. Exploring the links between types 2 diabetes and liver-related complications: A comprehensive review. United Eur Gastroenterol J. 2024;12:240–51. Zhang X, Yip TC-F, Tse Y-K, Hui VW-K, Li G, Lin H, et al. Duration of type 2 diabetes and liver-related events in nonalcoholic fatty liver disease: A landmark analysis. Hepatol Baltim Md. 2023;78:1816–27. Kirwam JP, Sacks J, Nieuwoudt S. The essential role of exercise in the management of type 2 diabetes. Cleve Clin J Med. 2017;84:S15–21. Syeda USA, Battillo D, Visaria A, Malin SK. The importance of exercise for glycemic control in type 2 diabetes. Am J Med Open. 2023;9:100031. Cannata F, Vadalà G, Russo F, Papalia R, Napoli N, Pozzilli P. Beneficial Effects of Physical Activity in Diabetic Patients. J Funct Morphol Kinesiol. 2020;5:70. Marti-Aguado D, Clemente-Sanchez A, Bataller R. Cigarette smoking and liver diseases. J Hepatol. 2022;77:191–205. Rutledge SM, Asgharpour A. Smoking and Liver Disease. Gastroenterol Hepatol. 2020;16:617–25. Addissouky TA, El Sayed IET, Ali MMA, Wang Y, El Baz A, Elarabany N, et al. Oxidative stress and inflammation: elucidating mechanisms of smoking-attributable pathology for therapeutic targeting. Bull Natl Res Cent. 2024;48:16. Kouam AF, Masso M, Kouoh FE, Fifen R, Njingou I, Tchana AN, et al. Hydro-ethanolic extract of Khaya grandifoliola attenuates heavy metals-induced hepato-renal injury in rats by reducing oxidative stress and metals-bioaccumulation. Heliyon [Internet]. 2022 [cited 2025 Jan 19];8. Available from: https://www.cell.com/heliyon/abstract/S2405-8440(22)02973-5 Lou H, Jiang Y, Xu C, Dong Z-M, Liu D, Qiao C, et al. Effects of a combination of dyslipidemia and hypertension on the glycemic control of patients with type 2 diabetes mellitus: a cross-sectional study. SAGE Open Med. 2024;12:20503121241265066. Petrie JR, Guzik TJ, Touyz RM. Diabetes, Hypertension, and Cardiovascular Disease: Clinical Insights and Vascular Mechanisms. Can J Cardiol. 2018;34:575–84. El-Eshmawy MM. Impact of obesity on liver function tests: is nonalcoholic fatty liver disease the only player? A review article. Porto Biomed J. 2023;8:e228. Fabbrini E, Sullivan S, Klein S. Obesity and Nonalcoholic Fatty Liver Disease: Biochemical, Metabolic and Clinical Implications. Hepatol Baltim Md. 2010;51:679–89. Vulchi J, Suryadevara V, Mohan P, Kamalanathan S, Sahoo J, Naik D, et al. Obesity and Metabolic Dysfunction-associated Fatty Liver Disease: Understanding the Intricate Link. J Transl Gastroenterol. 2023;1:74–86. Additional Declarations No competing interests reported. Supplementary Files S1File.pdf S1_file: Ethical considerations S2File.docx S2_file: Questionnaire S3File.xlsx S3_file: Research Data Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies 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-6388673","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":439778101,"identity":"8ca6b0be-ff47-4c3b-b8b7-18a0b39a8210","order_by":0,"name":"Arnaud Fondjo Kouam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYNACtgQQyfiAgeEAlCZSC7MBRAuIJlILmwRRWvhnnz34macsTc7g+Om0ap6aO3L8DMxsH/BpkTiXlyzNcy7H2OBM7rbbPMeeGUs2MDPPwGvNGR4Dad62isQNB0Ba2A4DGfyH8eqQP8Nj/Bus5fzbbcU8/0BamJnxajE4w2MGtCUnccON3G3MvG1EaDEEarGccy7NWPLG282Sc/sOG0s2E9AiB3TYjTdlyXJ853M3fnjz7bAcP3szfi0ogIkHRJKgAZhSfpCiehSMglEwCkYMAAA6vUmk5uhDRQAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, PO Box 63, Buea, Cameroon","correspondingAuthor":true,"prefix":"","firstName":"Arnaud","middleName":"Fondjo","lastName":"Kouam","suffix":""},{"id":439778106,"identity":"657509ac-98cd-4dc3-bade-7692bcbe2da0","order_by":1,"name":"Saturine Mengwe Mofor","email":"","orcid":"","institution":"Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, PO Box 63, Buea, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Saturine","middleName":"Mengwe","lastName":"Mofor","suffix":""},{"id":439778108,"identity":"59fa1c7d-baef-47fa-9ef0-0ba9613681e6","order_by":2,"name":"Madeleine Yvanna Nyangono Essam","email":"","orcid":"","institution":"Department of Biochemistry, Faculty of Science, University of Yaoundé 1, PO Box 812, Yaoundé, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Madeleine","middleName":"Yvanna Nyangono","lastName":"Essam","suffix":""},{"id":439778110,"identity":"f0eae55e-dd24-4fc2-8697-dbaa28d8515a","order_by":3,"name":"Armelle Gaelle Kwesseu Fepa","email":"","orcid":"","institution":"Department of Biochemistry, Faculty of Science, University of Yaoundé 1, PO Box 812, Yaoundé, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Armelle","middleName":"Gaelle Kwesseu","lastName":"Fepa","suffix":""},{"id":439778112,"identity":"465beac7-55b1-4e38-a655-8ca89a23aed1","order_by":4,"name":"Elisabeth Menkem Zeuko’o","email":"","orcid":"","institution":"Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, PO Box 63, Buea, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Elisabeth","middleName":"Menkem","lastName":"Zeuko’o","suffix":""},{"id":439778116,"identity":"bb28db13-e5d9-4d06-95a1-5d55f416d90d","order_by":5,"name":"Armel Jackson Seukep","email":"","orcid":"","institution":"Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, PO Box 63, Buea, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Armel","middleName":"Jackson","lastName":"Seukep","suffix":""},{"id":439778118,"identity":"b78aa3ab-2a30-44ea-9b0d-e7e387abbf27","order_by":6,"name":"Eleonore Ngounou","email":"","orcid":"","institution":"Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, PO Box 63, Buea, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Eleonore","middleName":"","lastName":"Ngounou","suffix":""},{"id":439778119,"identity":"d2b6d169-edf0-4805-ad90-72a394e74822","order_by":7,"name":"Pascal Dieudonné Djamen Chuisseu","email":"","orcid":"","institution":"Higher Institute of Health Sciences, Université des Montagnes, P.O. Box 208, Bangangté, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Pascal","middleName":"Dieudonné Djamen","lastName":"Chuisseu","suffix":""},{"id":439778120,"identity":"480cd7a8-ba79-40ec-90be-ff93ea61e628","order_by":8,"name":"Paul Fewou Moundipa Moundipa","email":"","orcid":"","institution":"Department of Biochemistry, Faculty of Science, University of Yaoundé 1, PO Box 812, Yaoundé, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"Fewou Moundipa","lastName":"Moundipa","suffix":""},{"id":439778121,"identity":"00d9de97-b531-4f93-9384-24580d342834","order_by":9,"name":"Frédéric Nico Njayou","email":"","orcid":"","institution":"Department of Biochemistry, Faculty of Science, University of Yaoundé 1, PO Box 812, Yaoundé, Cameroon","correspondingAuthor":false,"prefix":"","firstName":"Frédéric","middleName":"Nico","lastName":"Njayou","suffix":""}],"badges":[],"createdAt":"2025-04-06 21:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6388673/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6388673/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80129912,"identity":"1d35f9b0-3695-429a-aabd-7b3d66345f2f","added_by":"auto","created_at":"2025-04-08 09:02:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":269094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVariation of liver enzyme activity according to the risk factors associated with their abnormal levels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A):\u003c/strong\u003e Effect of duration of illness; \u003cstrong\u003e(B):\u003c/strong\u003e Effect of tobacco smoking; \u003cstrong\u003e(C)\u003c/strong\u003e: Effect of physical activity; \u003cstrong\u003e(D)\u003c/strong\u003e: Effect of comorbidities; \u003cstrong\u003e(E)\u003c/strong\u003e: Effect of Body Mass Index. Comparison of median values between two categories was done by the non-parametric Mann Whitney \u003cem\u003eU\u003c/em\u003e test. \u003cstrong\u003e* \u003c/strong\u003eValues significantly different (P\u0026lt;0.05); \u003csup\u003e\u003cstrong\u003ens \u003c/strong\u003e\u003c/sup\u003eValues non-significantly different (P\u0026gt;0.05).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6388673/v1/4daa02b5872ace071f638bed.jpg"},{"id":80493918,"identity":"34e06cbe-ba46-4600-9659-40f577e9e22e","added_by":"auto","created_at":"2025-04-13 22:01:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2422996,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6388673/v1/4cc69c8b-0b31-4733-8d54-17423ecb925e.pdf"},{"id":80129922,"identity":"63bb179d-7337-43a8-a086-b702fe8144d4","added_by":"auto","created_at":"2025-04-08 09:02:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1200613,"visible":true,"origin":"","legend":"\u003cp\u003eS1_file: Ethical considerations\u003c/p\u003e","description":"","filename":"S1File.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6388673/v1/4064d81565e73d357b613f09.pdf"},{"id":80129913,"identity":"b5876389-46aa-4e3f-bf1b-32b349153d15","added_by":"auto","created_at":"2025-04-08 09:02:00","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":22223,"visible":true,"origin":"","legend":"\u003cp\u003eS2_file: Questionnaire\u003c/p\u003e","description":"","filename":"S2File.docx","url":"https://assets-eu.researchsquare.com/files/rs-6388673/v1/00d02317ea03f4e06263bfa6.docx"},{"id":80129921,"identity":"2b98175a-78d1-456f-8bfc-18c4f66a248f","added_by":"auto","created_at":"2025-04-08 09:02:00","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":41465,"visible":true,"origin":"","legend":"\u003cp\u003eS3_file: Research Data\u003c/p\u003e","description":"","filename":"S3File.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6388673/v1/e1a69cb7e487b58c59e656da.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Abnormal Serum Levels of Liver Enzyme Markers and Related Risk Factors in Type 2 Diabetes Mellitus Patients Attending the Buea Regional Hospital, Cameroon","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDiabetes Mellitus (DM) ranks among the most prevalent non-communicable diseases, rising at an alarming pace and impacting a considerable number of individuals. This disease has quickly become a global health issue, largely due to high calorie intake, lack of physical activity, inadequate diagnosis, and poor management [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]; it is now posing a risk of reaching endemic status by 2030, particularly in developing nations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, it is a metabolic disorder characterized by sustained high blood sugar levels with the disturbance of the metabolism of proteins, lipids, and carbohydrates as a result of a deficiency in insulin secretion and/or action [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Globally, around 1 in 11 adults experience DM, with type 2 DM (T2DM) representing approximately 90% of cases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. T2DM arises from dysfunctional pancreatic β-cell activity and an inability to produce enough insulin, coupled with insulin resistance characterized by decreased sensitivity to insulin in target tissues such as muscles and the liver [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eT2DM negatively impacts various systems and organs in the body, including the liver, which is crucial in the detoxification process, glycaemia regulation, and the metabolism of lipids, proteins, and carbohydrates [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Indeed, liver impairment, characterized by abnormally elevated serum levels of liver enzymes such as transaminases: alanine aminotransferase (ALT) and aspartate aminotransferase (AST); alkaline phosphatase (ALP) and γ-glutamyl-transferase (GGT), is commonly observed in about 70% of diabetic patients and accounts for roughly 2\u0026ndash;4% of fatalities in T2DM [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough T2DM represents a significant public health issue in Cameroon, there is a paucity of knowledge regarding the relationship between T2DM and liver injury or dysfunction, which further raises morbidity and mortality among Cameroonian diabetic patients. Accordingly, continuous monitoring of serum liver enzymes and identification of potential risk factors associated with their abnormal levels in T2DM patients are necessary to detect early signs of hepatic injury that may prompt medical intervention to prevent further detrimental complications for the patients. Therefore, the purpose of this study was to assess the serum levels of liver enzyme markers and identify the potential risk factors related to their abnormal levels in T2DM patients attending the Buea Regional Hospital, South-West Region, Cameroon.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and settings\u003c/h2\u003e \u003cp\u003e This descriptive cross-sectional study followed by laboratory analysis took place at the Diabetes Unit of the Buea Regional Hospital, from June to September 2024. The city of Buea serves as the Headquarters of the South-West Region of Cameroon. It is located on the eastern slope of Mount Cameroon. It has coordinates 4\u0026deg;10ˈ0\u0026Prime;N994ˈ0\u0026Prime;E \u0026frasl; 4.16667\u0026deg;N9.23333\u0026deg;E with an elevation of 896 m above sea level. The Buea Regional Hospital is classified as a secondary health institution, that delivers both outpatient and inpatient services for various diseases, including chronic conditions such as hypertension, stroke, kidney and cardiac diseases, and DM.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Target population, sampling technique and sample size estimation\u003c/h2\u003e \u003cp\u003eThe target population was adults aged over 21 years suffering from T2DM who were on anti-diabetic medications for at least 6 months. Diabetic patients with a history of liver diseases, clinical symptoms of acute hepatitis, infected with hepatitis C or B virus, or taking hepatotoxic drugs were excluded from the study. A convenient random sampling technique was used for participant recruitment. After approaching a potential participant, the goals of the investigation, as well as the potential risks and benefits, were clearly explained, and only those who gave their consent by signing the informed consent form were enrolled in the study. The estimated sample size was calculated using the Lorentz formula (1).\u003c/p\u003e \u003cp\u003e(1): \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:N=\\frac{{Z}^{2}\\times\\:p(1-p)}{{d}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eWhere: \u003cem\u003eN\u003c/em\u003e is the calculated sample size; \u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.96 is the typical value of the degree of confidence at 95%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.1% is the prevalence of diabetes among adults living in Cameroon [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5% is the margin error permitted.\u003c/p\u003e \u003cp\u003eAfter calculation, \u003cem\u003eN\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;102. For a better representation of the population, 20% of \u003cem\u003eN\u003c/em\u003e was added. Therefore, the minimum number of diabetic patients to be enrolled in this study was estimated at 123 participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Ethical consideration\u003c/h2\u003e \u003cp\u003e The study was conducted in accordance with guidelines from the declarations of Helsinki. Ethical Clearance for this study was obtained from the Institutional Review Board of the Faculty of Health Sciences, University of Buea (Ref N\u0026deg;: 2024/2484-03/UB/SG/IRB/FHS) (Online Resources S1_file). In addition, an Administrative Authorizations were issued by the Regional Health Office of the South-West Region, Ministry of Public Health, Cameroon (Ref N\u0026deg;: P42/MINSANTE/SWR/RDPH/CB.PT/183/293) and from the director of the Buea Regional Hospital (Ref N\u0026deg;: 22/05/2024/MPH/SWRDPH/BRH/IRB), respectively. The information collected during the interview was not disclosed, and the participant\u0026rsquo;s names were replaced with codes during the data collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data collection procedure\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 General characteristic of diabetic patients enrolled in the study\u003c/h2\u003e \u003cp\u003eAn overview of the characteristics of diabetic patients recruited for this investigation was captured through a structured questionnaire (Online Resources S_2 file) administered in person. The questionnaire allowed for gathering information regarding socio-demographic data, the history and monitoring of illness, eating habits and physical activity practices, alcohol consumption, and the use of tobacco products. In addition, blood pressure and anthropometric parameters including height and weight were measured, and the Body Mass Index (BMI) was subsequently calculated; each participant was classified as underweight, normal weight, overweight, or obese based on a BMI of \u0026lt;\u0026thinsp;18.5, [18.5\u0026ndash;24.9], [25-29.9], and \u0026gt;\u0026thinsp;30, respectively. At the end of the interview, 5 mL of blood was collected via venipuncture into a tube free of anticoagulant and centrifuged (3000\u0026times;g, 10 min, 4\u0026deg;C). The serum obtained was used to measure liver enzyme markers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Evaluation of some biochemical markers of liver injury in diabetic patients\u003c/h2\u003e \u003cp\u003eThe biochemical markers of liver injury were assessed by measuring the serum activity of some liver enzymes, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and γ-glutamyl-transferase (GGT) using commercial assay kits (Catalog N\u0026deg; REF_80227, Catalog N\u0026deg; REF_80225, Catalog N\u0026deg; REF_80014 and Catalog N\u0026deg; REF_4110 respectively for ALT, AST, ALP, and GGT) purchased from BIOLABO, Les Hautes Rives, Maizy, France. The assays were performed in accordance with the manufacturer's instructions using a semi-automatic spectrophotometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3 Estimation of the alteration of serum liver enzyme markers\u003c/h2\u003e \u003cp\u003eThe level of alteration of the serum liver enzyme activity was estimated by considering the normal range of values (reference values) for each enzyme assessed. These reference values are: from 10 to 42 IU/L, from 8 to 39 IU/L, from 40 to 129 IU/L, and from 11 to 50 IU/L respectively for ALT, AST, ALP, and GGT, as indicated in the manufacturer's instructions. Accordingly, any value found within its normal range or higher than upper limit of the normal range of values (ULN) was considered normal or high, respectively. Similarly, any patient with more than 2 high values was considered to have an abnormal status of liver enzyme profile.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data management and statistical analysis\u003c/h2\u003e \u003cp\u003eAfter checking that all sections of the questionnaire had been completed, the data collected and the results of the laboratory analyses for each participant were saved in Excel 2013 (Microsoft Corporation, USA) (Online Resources S3_file), and then exported to the statistical analysis software SPSS (Statistical Package for Social Sciences) version 25.0 (SPSS Inc., USA) or GraphPad Prism version 8.0.2. Descriptive statistics were performed using SPSS software. Qualitative variables were presented as frequency and percentage (%). Quantitative variables were first tested for normality using the Kolmogorov-Smirnov test. Variables that followed a normal distribution and those that did not pass the test were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median and interquartile range respectively. Comparison of median values between two categories was done by the non-parametric Mann Whitney \u003cem\u003eU\u003c/em\u003e test. Risk factors associated with the abnormal status of liver enzyme profile were determined through bivariate and multivariate logistic regression analysis. The significance threshold was declared at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Socio-demographic characteristics of the enrolled T2DM patients\u003c/h2\u003e \u003cp\u003eA total of 170 patients were recruited for the study. The gender ratio was 3.15, favoring females, who made up 75.9% (129/170) of the participants. The median age of the participants was 62 years, with an interquartile range of 55 to 70 years for the 25% and 75% percentiles, respectively. A significant portion of the participants, 66.5% (113/170), were over 60 years old. Additionally, more than half of the participants were married (52.9%; 90/170), and 64.7% (110/170) attended primary school. In terms of occupation, 55.3% (94/170) of the enrolled patients were retired (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\u003eSocio-demographic characteristics of diabetic patients attending the Buea Regional Hospital\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocio-demographic characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[21\u0026ndash;40[\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[40\u0026ndash;60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidow(er)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.7\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCivil servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Behavioral and clinical features of study participants\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e outlines the frequency distribution of study participants based on their behavioral and clinical characteristics. Regarding the duration of illness, 59.4% (101/170) reported being diagnosed with diabetes for over five years. All participants (100%; 170/170) indicated they had knowledge of diabetes care, while 73.3% (128/170) strictly adhered to their anti-diabetic medications. Among the participants, 64.7% (110/170) consumed alcohol, and 28.8% (49/170) were tobacco smokers. Only 22.4% (38/170) of the enrolled diabetic patients engaged in physical activity, and 77.6% (132/170) had at least one comorbidity. Systematic blood sugar monitoring was reported by 80% (136/170) of participants, while 66.5% (113/170) had high blood pressure. Based on their BMI index, those with healthy weight comprised 31.2% (33/170), whereas 27.6% (47/170) were overweight and 41.2% (70 out of 170) were obese. Abnormally high levels of serum ALT, AST, ALP, and GGT activities were observed in 61.8% (105/170), 62.4% (106/170), 37.3% (64/170), and 50% (85/170) of study participants, respectively. Consequently, the prevalence of abnormal liver enzyme profiles among the enrolled T2DM patients was estimated to be 56.5% (96/170).\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 clinical features of diabetic patients attending the Buea Regional Hospital\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavioral / Clinical features\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDuration of illness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eKnowledge on diabetes care\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eAdherence to antidiabetic drugs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.3\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eAlcohol consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.7\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTobacco smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.8\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePractice of physical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.4\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.6\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eBlood sugar monitoring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.0\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eLevel of blood pressure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eInterpretation of BMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eALT (IU/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh \u0026gt; (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal \u0026lt; (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eAST (IU/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh \u0026gt; (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal \u0026lt; (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eALP (IU/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh \u0026gt; (129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal \u0026lt; (129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGGT (IU/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh \u0026gt; (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal \u0026lt; (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eStatus of liver enzyme profile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI: Body Mass Index; ALT: Alanine amino transferase; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase; GGT: γ-glutamyl-transferase.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Association between the socio-demographic characteristics and the status of liver enzyme profile\u003c/h2\u003e \u003cp\u003eThe potential socio-demographic factors associated with abnormal liver enzyme profiles were evaluated using bivariate logistic regression analysis, as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Although a higher percentage of females (45.9%; 78 out of 129) were affected by abnormal liver enzyme profiles compared to males (10.6%; 18 out of 41), no significant association was found between gender and liver enzyme status (cOR: 1.95; CI: 0.96\u0026ndash;3.97; P\u0026thinsp;=\u0026thinsp;0.065). Additionally, the analyses indicated that age group (cOR: 0.69 and 0.71; CI: 0.13\u0026ndash;3.55 and 0.37\u0026ndash;1.39; P\u0026thinsp;=\u0026thinsp;0.654 and 0.321), marital status (cOR: 0.72 and 1.20; CI: 0.37\u0026ndash;1.38 and 0.39\u0026ndash;3.68; P\u0026thinsp;=\u0026thinsp;0.322 and 0.742), education level (cOR: 0.94 and 1.92; CI: 0.39\u0026ndash;2.29 and 0.66\u0026ndash;3.97; P\u0026thinsp;=\u0026thinsp;0.898 and 0.232), and occupation (cOR: 1.12 and 0.54; CI: 0.35\u0026ndash;3.60 and 0.96\u0026ndash;3.97; P\u0026thinsp;=\u0026thinsp;0.853 and 0.067) did not significantly influence liver enzyme status among the enrolled T2DM patients.\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\u003eBivariate logistic regression analysis for the association between the socio-demographic characteristics of diabetic patients and their status of liver enzyme profile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \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 \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eStatus of liver enzyme profile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eBivariate logistic regression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAbnormal n, (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal n, (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ecOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e129 (75.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.96\u0026ndash;3.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e41 (24.1)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[21\u0026ndash;40[\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e6 (3.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.13\u0026ndash;3.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[40\u0026ndash;60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e51 (30.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.37\u0026ndash;1.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e113 (65.5)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e90 (52.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.37\u0026ndash;1.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e17 (10.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.39\u0026ndash;3.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidow(er)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e63 (37.1)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e110 (64.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.39\u0026ndash;2.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.898\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\u003e25 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e36 (21.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.66\u0026ndash;5.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e24 (14.1)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCivil servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e14 (8.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.35\u0026ndash;3.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e62 (36.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.96\u0026ndash;3.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e94 (55.3)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003ecOR: Crude Odd Ratio; CI: Confidence Interval.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.4 Relationship between the behavioral and clinical factors and the status of liver enzyme profile of study participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the statistical associations between the behavioral and clinical factors related to an abnormal liver enzyme profile, determined through bivariate and multivariate logistic regression analysis, as indicated below.\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\u003eBivariate and multivariate logistic regression analysis for the behavioral and clinical factors associated with the abnormal liver enzyme profile in diabetic patients attending the Buea Regional Hospital\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBehavioral / Clinical features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eStatus of liver enzyme profile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eBivariate logistic regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eMultivariate logistic regression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAbnormal n, (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal n, (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ecOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eaOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDuration of illness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e101 (59.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.73\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[1.96\u0026ndash;7.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e6.23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[2.04\u0026ndash;19.08]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e69 (40.6)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eAdherence to antidiabetic drugs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e42 (24.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.39\u0026ndash;1.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"2\" nameend=\"c11\" namest=\"c9\" rowspan=\"3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e128 (75.3)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eAlcohol consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e60 (35.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.21\u0026ndash;0.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.004*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[0.27\u0026ndash;2.40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e110 (64.7)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTobacco smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72 (42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e121 (71.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.007\u0026ndash;0.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[0.003\u0026ndash; 0.14]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e49 (28.8)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePractice of physical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e132 (77.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e7.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[3.17\u0026ndash;17.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e4.64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[1.34\u0026ndash;16.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.015*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e38 (22.4)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e38 (22.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.14\u0026ndash;0.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.002*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[0.049\u0026ndash;0.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.013*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e132 (77.6)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eBlood sugar monitoring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e34 (20.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.39\u0026ndash;1.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"2\" nameend=\"c11\" namest=\"c9\" rowspan=\"3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e136 (80.0)\u003c/b\u003e\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eLevel of blood pressure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e113 (66.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.74\u0026ndash;2.67]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"2\" nameend=\"c11\" namest=\"c9\" rowspan=\"3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57 (33.5)\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eInterpretation of BMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.048\u0026ndash;0.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.0001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[0.011\u0026ndash;0.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (32.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70 (41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.82\u0026ndash;4.34]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e[0.80\u0026ndash;8.09]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(47 (27.6)\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\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e96 (56.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e170 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e/\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eBMI: Body Mass Index; cOR: Crude Odd Ratio; aOR: Adjusted Odd Ratio; CI: Confidence Interval; The bold cOR or aOR and P-value are indicators of a significant association.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1 Possible factors influencing the abnormal status of liver enzyme profile\u003c/h2\u003e \u003cp\u003eFor the bivariate analysis, a simple logistic regression model was used at 95% confidence interval (CI) with a cut-off point p-value set at 0.05 to identify factors for multivariate analysis. The clinical and behavioral factors identified as significantly influencing the liver enzyme status were as follows: duration of illness (cOR: 3.73; CI: 1.96\u0026ndash;7.12; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); alcohol consumption (cOR: 0.39; CI: 0.21\u0026ndash;0.75; P\u0026thinsp;=\u0026thinsp;0.004); tobacco smoking (cOR: 0.029; CI: 0.007\u0026ndash;0.12; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); comorbidity (cOR: 0.31; CI: 0.14\u0026ndash;0.65; P\u0026thinsp;=\u0026thinsp;0.002); practice of physical activity (cOR: 7.50; CI: 3.17\u0026ndash;17.72; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); and BMI index (cOR: 0.12; CI: 0.048\u0026ndash;0.30; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 Factors associated with abnormal liver enzyme profile\u003c/h2\u003e \u003cp\u003eFollowing the bivariate analysis, a multivariate logistic regression analysis was performed in the same conditions to determine the factors associated with abnormal liver enzyme profile among those identified as influencing the liver enzyme status. Five factors were found to be significantly associated with abnormal levels of liver enzyme among the enrolled T2DM patients. These factors were: duration of illness (aOR: 6.23; CI: 2.04\u0026ndash;19.08; P\u0026thinsp;=\u0026thinsp;0.001); tobacco smoking (aOR: 0.022; CI: 0.003\u0026ndash;0.14; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); practice of physical activity (aOR: 4.64; CI: 1.34\u0026ndash;16.07; P\u0026thinsp;=\u0026thinsp;0. 015); comorbidity (aOR: 0.18; CI: 0.049\u0026ndash;0.70; P\u0026thinsp;=\u0026thinsp;0.013); and BMI (aOR: 0.048; CI: 0.011\u0026ndash;0.21; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). This means that the enrolled T2DM participants with a duration of illness greater than 5 years (aOR: 6.23) and those not engaged in physical activity (aOR: 4.64) were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) at higher risk of presenting abnormal liver enzyme status, compared to the T2DM patients with a duration of illness less than 5 years, and those who engaged in physical activity, respectively. Similarly, T2DM patients who did not smoke (aOR: 0.022), without comorbidity (aOR: 0.18), and with healthy weight (aOR: 0.048) were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) less at risk of having an abnormal liver enzyme profile, compared to the patients who smoked, had comorbidity, and those who are overweight or obese, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Influence of the identified risk factors on the serum levels of liver enzyme activity\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the variation in liver enzyme (ALT, AST, GGT, and ALP) activity according to the risk factors associated with their abnormal profile. The median values of serum ALT, AST, and GGT activities were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) elevated among T2DM patients with a duration of illness greater than 5 years (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), those who smoked (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), those who were physically inactive (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), those with comorbidities (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), and those who were obese or overweight (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), compared to those with a duration of illness less than 5 years, non-smokers, physically active individuals, those without comorbidities, and those with a healthy weight, respectively. Regarding the median values of ALP, no significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) difference was observed between patients with more than 5 years of illness duration and those with less than 5 years (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), or between healthy weight and overweight patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). In contrast, median values of ALP activity were significantly increased in T2DM patients who smoked (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), were physically inactive (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), had comorbidities (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), and were obese (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), compared to non-smokers, physically active individuals, those without comorbidities, and healthy weight patients, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe rising global prevalence of Type 2 Diabetes Mellitus (T2DM) poses significant health challenges and complications, including those affecting the liver, particularly in low-to-middle-income countries like Cameroon, where healthcare resources is often limited [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This study examining the serum levels of biomarkers of liver injury in T2DM patients attending the Buea Regional Hospital of Cameroon, provides valuable insights into the interaction between liver health and the clinical and behavioral features of this target population. Indeed, identifying the risk factors that contribute to abnormal liver enzyme levels can facilitate the development of effective intervention strategies to prevent the occurrence of liver diseases in T2DM patients. Hence, several clinical and behavioral factors related to abnormal serum liver enzyme levels were identified. These included the duration of illness, practice of physical activity, tobacco smoking, presence of comorbidities, and high Body Mass Index (BMI). Each of these factors is well known to affect liver health [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and addressing them holistically may improve health outcomes among T2DM patients.\u003c/p\u003e \u003cp\u003eThe duration of T2DM is a fundamental factor influencing the development of liver-related complications. Indeed, chronic hyperglycemia resulting from insufficient glycemic control over time can lead to metabolic changes that predispose individuals to liver dysfunction, characterized by abnormal high level of serum liver enzyme [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Patients with a longer duration of diabetes are at an elevated risk of accumulating lipids into hepatic tissues, leading to inflammation and in severe cases, may progress to non-alcoholic steatohepatitis (NASH) and ultimately result in liver cirrhosis or hepatocellular carcinoma [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This study showed that T2DM patients with a duration of illness greater than 5 years display a significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) increased serum level of ALT, AST, GGT and ALP activities and were significantly more at risk (aOR: 6.238; P\u0026thinsp;=\u0026thinsp;0.001) of having abnormal liver enzyme profile, compared to those with less than 5 years history of the disease. These observations suggest a possible development of liver pathology in these old T2DM patients, which need to be confirmed by further analysis. To mitigate these risks related to the duration of the disease, it is crucial for healthcare providers to implement systematic screenings for liver function markers, especially in patients with a prolonged history of diabetes. This could help identify early signs of liver damage, allowing for timely interventions that could prevent the progression of liver disease. Also, educational programs aimed at raising awareness among T2DM patients about the potential hepatic complications related to the duration of their illness can empower them to take a more active role in their disease management.\u003c/p\u003e \u003cp\u003eMoreso, regular physical activity is universally recognized for its beneficial effects on metabolic health, especially in managing diabetes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our findings indicate that patients who engaged in regular physical activity exhibited significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) lower serum liver enzyme levels and were significantly less at risk of presenting abnormal status of liver enzyme profile, compared to physically inactive patients (aOR: 4.64; P\u0026thinsp;=\u0026thinsp;0. 015). Given that physical activity is known to enhance lipid profiles and reduce systemic inflammation, creating a healthier environment for hepatic function, these findings can be attributed to beneficial effect of physical activity on lipid metabolism and improved insulin sensitivity, as reported by Cannata et al. (2020) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This study also emphasizes that incorporating structured exercise regimen into diabetes management plans cannot be overstated. Accordingly, healthcare providers should consider implementing tailored exercise programs for their patients, encouraging activities that are accessible and enjoyable to foster long-term adherence. In addition, engaging patients in community-focused activities may also promote social support systems, which can further motivate sustained participation of T2DM patients in physical activities.\u003c/p\u003e \u003cp\u003eThe detrimental effects of tobacco smoking on health are well established, and the study indicates that smoking significantly correlates with elevated liver enzyme levels in T2DM patients [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Tobacco use has been associated with an increased risk of liver disease through mechanisms involving oxidative stress, inflammation, and metabolic dysregulation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The chemicals such cadmium, present in tobacco smoke can induce hepatic oxidative injury, characterized by abnormal increased serum levels of transaminases [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this study, up to 28.8% of the enrolled T2DM patients were tobacco users. These patients presented significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) increased serum levels of ALT, AST, GGT, and ALP and were at significantly (aOR: 0.022; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) higher risk of displaying abnormal liver enzyme profile, compared to non-smoker patients. These observations suggest that smoking can promote early development of liver complications in T2DM patients. Accordingly, healthcare interventions should prioritize smoking cessation programs tailored for T2DM patients by providing resources for cessation support, such as counseling and pharmacotherapy. Also, creating awareness campaigns that educate patients on the specific risks associated with smoking and liver health can empower individuals to make informed lifestyle choices.\u003c/p\u003e \u003cp\u003eThe presence of comorbidities, such as hypertension, obesity, cardiovascular and kidney diseases, and dyslipidemia, represents further challenges in managing the health of T2DM patients [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In this study, 77.6% (132/170) of participants presented at least one of these comorbid conditions and were more likely to display abnormal liver enzyme levels, when compared to patients without any comorbidity. In fact, multivariate logistic regression analysis showed that comorbidities were significantly (aOR: 0.18; P\u0026thinsp;=\u0026thinsp;0.013) associated with abnormal status of liver enzyme profile. These findings highlight that effective diabetes treatment must include strategies to address all comorbid conditions simultaneously. This may include coordinated efforts among healthcare providers to ensure a cohesive treatment plan that considers managing not only glycaemia, but also blood pressure, and lipidemia. This could be helpful for better management of T2DM and its related complications, including liver damage. This study also reveals a significant (aOR: 0.048; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) association between elevated BMI and abnormal serum levels of liver enzyme markers in T2DM patients. Indeed, individuals with a higher BMI, particularly those categorized as overweight or obese, are more likely to exhibit elevated liver enzymes, which may indicate liver stress or damage [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These observations suggest that maintaining a healthy weight could potentially mitigate liver complications in diabetic patients, emphasizing the importance of weight management in this population.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn summary, the findings from the present study which aimed to measure the serum levels of liver enzyme and identify the potential risk factors related to their abnormal levels in T2DM patients attending the Buea Regional Hospital-Cameroon, several clinical and behavioral factors, including the duration of illness, non-practice of physical activity, tobacco smoking, presence of comorbidities, and elevated BMI values were strongly associated with abnormal serum levels of liver enzyme, suggesting the progressive occurrence of hepatic damage. These observations pave the way for future research that will validate these associations in larger cohorts and explore the underlying mechanisms linking these risk factors to hepatic injury.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to all participants involved in this study and acknowledge the laboratory staff of the Buea Regional Hospital for their technical assistance; they also appreciate the support from the trimester research modernization funding provided by the Ministry of Higher Education of Cameroon to Dr. Arnaud Fondjo Kouam.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no funding to report.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthical statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical Clearance for this study was obtained from the Institutional Review Board of the Faculty of Health Sciences, University of Buea (Ref N\u0026deg;: 2024/2484-03/UB/SG/IRB/FHS)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLi D-D, Yang Y, Gao Z-Y, Zhao L-H, Yang X, Xu F, et al. 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Prevalence of prediabetes and diabetes mellitus among adults residing in Cameroon: A systematic review and meta-analysis. Diabetes Res Clin Pract. 2018;137:109\u0026ndash;18.\u003c/li\u003e\n \u003cli\u003eHe K-J, Wang H, Xu J, Gong G, Liu X, Guan H. Global burden of type 2 diabetes mellitus from 1990 to 2021, with projections of prevalence to 2044: a systematic analysis across SDI levels for the global burden of disease study 2021. Front Endocrinol [Internet]. 2024 [cited 2025 Mar 30];15. Available from: https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2024.1501690/full\u003c/li\u003e\n \u003cli\u003eKhan MAB, Hashim MJ, King JK, Govender RD, Mustafa H, Al Kaabi J. Epidemiology of Type 2 Diabetes \u0026ndash; Global Burden of Disease and Forecasted Trends. J Epidemiol Glob Health. 2020;10:107\u0026ndash;11.\u003c/li\u003e\n \u003cli\u003eBalou HA, Joukar F, Shahdkar M, Orang Goorabzarmakhi M, Maroufizadeh S, Mansour-Ghanaei F. Physical activity and elevated liver enzymes: A cross-sectional study from the PERSIAN Guilan cohort study. Casp J Intern Med. 2025;16:246\u0026ndash;54.\u003c/li\u003e\n \u003cli\u003eJalili V, Poorahmadi Z, Hasanpour Ardekanizadeh N, Gholamalizadeh M, Ajami M, Houshiarrad A, et al. The association between obesity with serum levels of liver enzymes, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase and gamma‐glutamyl transferase in adult women. Endocrinol Diabetes Metab. 2022;5:e367.\u003c/li\u003e\n \u003cli\u003eNiemel\u0026auml; O, Bloigu A, Bloigu R, Aalto M, Laatikainen T. Associations between Liver Enzymes, Lifestyle Risk Factors and Pre-Existing Medical Conditions in a Population-Based Cross-Sectional Sample. J Clin Med. 2023;12:4276.\u003c/li\u003e\n \u003cli\u003eSanchez L, Chen Y, Lassailly G, Qi X. Exploring the links between types 2 diabetes and liver-related complications: A comprehensive review. United Eur Gastroenterol J. 2024;12:240\u0026ndash;51.\u003c/li\u003e\n \u003cli\u003eZhang X, Yip TC-F, Tse Y-K, Hui VW-K, Li G, Lin H, et al. Duration of type 2 diabetes and liver-related events in nonalcoholic fatty liver disease: A landmark analysis. Hepatol Baltim Md. 2023;78:1816\u0026ndash;27.\u003c/li\u003e\n \u003cli\u003eKirwam JP, Sacks J, Nieuwoudt S. The essential role of exercise in the management of type 2 diabetes. Cleve Clin J Med. 2017;84:S15\u0026ndash;21.\u003c/li\u003e\n \u003cli\u003eSyeda USA, Battillo D, Visaria A, Malin SK. The importance of exercise for glycemic control in type 2 diabetes. Am J Med Open. 2023;9:100031.\u003c/li\u003e\n \u003cli\u003eCannata F, Vadal\u0026agrave; G, Russo F, Papalia R, Napoli N, Pozzilli P. Beneficial Effects of Physical Activity in Diabetic Patients. J Funct Morphol Kinesiol. 2020;5:70.\u003c/li\u003e\n \u003cli\u003eMarti-Aguado D, Clemente-Sanchez A, Bataller R. Cigarette smoking and liver diseases. J Hepatol. 2022;77:191\u0026ndash;205.\u003c/li\u003e\n \u003cli\u003eRutledge SM, Asgharpour A. Smoking and Liver Disease. Gastroenterol Hepatol. 2020;16:617\u0026ndash;25.\u003c/li\u003e\n \u003cli\u003eAddissouky TA, El Sayed IET, Ali MMA, Wang Y, El Baz A, Elarabany N, et al. Oxidative stress and inflammation: elucidating mechanisms of smoking-attributable pathology for therapeutic targeting. Bull Natl Res Cent. 2024;48:16.\u003c/li\u003e\n \u003cli\u003eKouam AF, Masso M, Kouoh FE, Fifen R, Njingou I, Tchana AN, et al. Hydro-ethanolic extract of Khaya grandifoliola attenuates heavy metals-induced hepato-renal injury in rats by reducing oxidative stress and metals-bioaccumulation. Heliyon [Internet]. 2022 [cited 2025 Jan 19];8. Available from: https://www.cell.com/heliyon/abstract/S2405-8440(22)02973-5\u003c/li\u003e\n \u003cli\u003eLou H, Jiang Y, Xu C, Dong Z-M, Liu D, Qiao C, et al. Effects of a combination of dyslipidemia and hypertension on the glycemic control of patients with type 2 diabetes mellitus: a cross-sectional study. SAGE Open Med. 2024;12:20503121241265066.\u003c/li\u003e\n \u003cli\u003ePetrie JR, Guzik TJ, Touyz RM. Diabetes, Hypertension, and Cardiovascular Disease: Clinical Insights and Vascular Mechanisms. Can J Cardiol. 2018;34:575\u0026ndash;84.\u003c/li\u003e\n \u003cli\u003eEl-Eshmawy MM. Impact of obesity on liver function tests: is nonalcoholic fatty liver disease the only player? A review article. Porto Biomed J. 2023;8:e228.\u003c/li\u003e\n \u003cli\u003eFabbrini E, Sullivan S, Klein S. Obesity and Nonalcoholic Fatty Liver Disease: Biochemical, Metabolic and Clinical Implications. Hepatol Baltim Md. 2010;51:679\u0026ndash;89.\u003c/li\u003e\n \u003cli\u003eVulchi J, Suryadevara V, Mohan P, Kamalanathan S, Sahoo J, Naik D, et al. Obesity and Metabolic Dysfunction-associated Fatty Liver Disease: Understanding the Intricate Link. J Transl Gastroenterol. 2023;1:74\u0026ndash;86.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Diabetic patients, Liver injury, Serum biomarkers, Abnormal level, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-6388673/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6388673/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e The prevalence of type 2 Diabetes Mellitus (T2DM) is increasing globally, leading to complications, including liver damage. This study aims to examine serum biomarkers of liver injury and the related risk factors in T2DM patients at the Buea Regional Hospital, Cameroon\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The sociodemographic, clinical, and behavioral characteristics of patients with T2DM were captured using a structured questionnaire. Anthropometric parameters were measured, and the Body Mass Index was calculated. Blood samples were analyzed for biomarkers of liver damage (ALT, AST, GGT, and ALP), considering a liver enzyme profile abnormal if it had more than 2 abnormally elevated values. Bivariate and multivariate logistic regressions analysis were used to identify risk factors, with significance set at P\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among the 170 participants recruited, 75.9% were female. The median age was 62 years. Over half (52.9%) were married, 64.7% attended primary school, and 55.3% were retired. Also, 59.4% had diabetes for over five years, and all reported knowledge of diabetes care. About 73.3% adhered to their medication, 64.7% consumed alcohol, 28.8% smoked tobacco, with 22.4% engaged in physical activity, and 77.6% with comorbidities. Blood sugar monitoring was practiced by 80%, with 66.5% having high blood pressure. Healthy weight individuals were 31.2%, while 41.2% were obese and 56.5% had abnormal liver enzyme profiles. Five factors: duration of illness, physical inactivity, tobacco smoking, comorbidities, and overweight/obesity were significantly (P\u0026lt;0.05) associated with abnormal liver enzyme profile.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Our findings identify risk factors linked to elevated liver enzyme markers indicating liver injury in T2DM patients.\u003c/p\u003e","manuscriptTitle":"Abnormal Serum Levels of Liver Enzyme Markers and Related Risk Factors in Type 2 Diabetes Mellitus Patients Attending the Buea Regional Hospital, Cameroon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-08 09:01:55","doi":"10.21203/rs.3.rs-6388673/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":"e1bfb611-1bc0-4be9-a6a7-6c1dfeeedac1","owner":[],"postedDate":"April 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-13T21:53:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-08 09:01:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6388673","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6388673","identity":"rs-6388673","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}