Effectiveness of Educational Interventions in Improving the Knowledge, Attitudes, and Perceptions Among Patients With Metabolic Syndrome at a Tertiary Care Hospital Setting in Palakkad District, India

Effectiveness of Educational Interventions in Improving the Knowledge, Attitudes, and Perceptions Among Patients With Metabolic Syndrome at a Tertiary Care Hospital Setting in Palakkad District, India | 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 Effectiveness of Educational Interventions in Improving the Knowledge, Attitudes, and Perceptions Among Patients With Metabolic Syndrome at a Tertiary Care Hospital Setting in Palakkad District, India AISWARYA AMBALAPPARAMBIL THANKAPPAN, ELANGO KANNAN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7923737/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Dec, 2025 Read the published version in Discover Public Health → Version 1 posted 11 You are reading this latest preprint version Abstract Objective Metabolic syndrome (MetS) is a group of metabolic abnormalities that significantly worsen several medical conditions, making it a major global health concern. Hence, a study was conducted to assess the knowledge, attitudes, and perceptions (KAP) of MetS, estimate cardiovascular risk scores, and provide educational interventions among patients with MetS. Method An interventional study was conducted among patients aged 18 years and above, diagnosed with MetS, and living in Palakkad, Kerala. A structured, validated questionnaire with 35 items was used to collect data. The intervention was provided face-to-face and online for one month, educating the patients on MetS. Results Majority of the patients were female (56%), with a mean age of 54.63 ± 10.1 years, and were obese (49%). At baseline, both the control (Median IQR = 9.5, p = 0.367) and intervention (Median IQR = 13.0, p = 0.001) group participants exhibited limited knowledge, attitudes, and perceptions toward MetS. Their 10-year cardiovascular risk assessed by Framingham Risk Score (FRS) showed that over half of the study participants in the control group (n = 34; 68%) and intervention group (n = 32; 64%) were at high risk (FRS > 20%). The educational intervention provided to the patients led to a statistically significant change in knowledge (Z=-6.5631, p < 0.001), attitudes (Z=-2.925, p < 0.001), and perceptions (Z=-4.693, p < 0.001) among the patients with MetS. Conclusion Patients in this study exhibited limited knowledge and negative attitudes towards MetS. The educational intervention provided to these patients was effective in improving KAP; hence, patient education should be encouraged at both hospital and community levels. Metabolic Syndrome Diabetes Hypertension Obesity Educational Intervention INTRODUCTION Metabolic syndrome (MetS) is a group of metabolic abnormalities that significantly worsen several medical conditions, making it a major global health concern. Abdominal obesity, high blood pressure, high fasting blood glucose, and dyslipidemia are considered the four key components of MetS. These metabolic risk factors can impact various health conditions such as cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), cerebrovascular complications, bone mineral disease (BMD), liver-related events (LRE), and gastrointestinal disorders [ 1 – 4 ]. Cardiovascular disease, characterized by heart and blood vessel problems, remains the leading cause of death globally [ 5 ]. In 2020, an estimated 244.1 million individuals worldwide were diagnosed with ischemic heart disease (IHD), with 19.1 million deaths attributed to CVDs [ 6 ]. Despite advancements in the management and treatment of non-communicable diseases (NCDs) like CVDs, T2DM, renal disease, and cerebrovascular diseases, the number of individuals with multiple NCDs continues to rise. Poor patient education plays a significant role in the rise of metabolic disorders. Many individuals lack proper knowledge about the importance of healthy lifestyle choices, such as diet and exercise, which are crucial for preventing or managing conditions like obesity, diabetes, and hypertension. Without adequate understanding, patients may not recognize the risks associated with poor eating habits, sedentary behavior, or non-compliance with prescribed treatments. Furthermore, inadequate education can lead to misunderstandings about the significance of regular monitoring, such as blood sugar or cholesterol levels, increasing the likelihood of complications. In many cases, patients may also struggle to navigate complex medical information and treatment options, leading to confusion and non-adherence to care plans. As a result, these gaps in knowledge contribute to the rising prevalence of metabolic disorders, highlighting the urgent need for healthcare systems to prioritize better patient education to prevent and manage these conditions effectively. Hence, a study was conducted to assess the Knowledge, Attitudes, and Perceptions (KAP) of MetS among patients with MetS, estimate cardiovascular risk scores, and provide educational interventions on MetS for these patients. METHODS Study design and population This interventional study was carried out among MetS patients in a private hospital setting in Palakkad, Kerala, utilizing a validated, structured study tool. This study included patients over the age of 18, regardless of gender, who had been diagnosed with MetS. Patients diagnosed with at least three metabolic abnormalities, including hypertension, diabetes mellitus, abdominal obesity, and dyslipidemia (low HDL cholesterol or hyper triglyceridemia), were eligible to participate in this study. The JIS-proposed definition of MetS - "Harmonised" criterion [ 7 ] was used to identify study participants. The following clinical indicators were utilized as diagnostic criteria for MetS in this study. Abdominal obesity is defined as a waist circumference of more than 90 cm (35 inches) for men and 80 cm (32 inches) for women [(8]. Impaired glycemic control is defined as fasting venous blood glucose levels greater than 125 mg/ dL or 7.0 m mol/L [ 9 ]. Participants with high blood pressure (≥ 130/85 mmHg) or who are taking hypertension medication [ 10 ]. Participants with high triglyceride levels (above 150 mg/dL or 1.7 mmol/L) or low fasting HDL cholesterol levels (below 40 mg/dL or 1 mmol/L for men and 50 mg/dL or 1.2 mmol/L for women) or those taking hyper triglyceridemia or low HDL cholesterol drugs [ 11 ]. Sample size estimation The sample size for the current interventional investigation was determined using the formula devised by Sathian et al., (2010)[ 12 ] for the Relevance of Sample Size Determination in Medical Research. The study used a research instrument with 35 questions, including 9 questions on demographic variables and 26 questions to assess MetS's KAP. The participants were divided into two groups: control and intervention, to assess the effectiveness of interventions provided by the pharmacist. Using the above algorithm developed by Sathian et al., (2010) [ 12 ], 50 participants were selected in each control and intervention group. Study instrument The study instrument was divided into three sections: Demographic and Clinical characteristics, Knowledge, Attitudes, and Perceptions (KAP) of MetS, and cardiovascular risk score. A definition of MetS[ 8 – 11 , 13 ]was provided at the beginning of the questionnaire. The research team developed the study instrument for assessing the KAP of MetS based on previously published investigations [ 13 – 18 ]. It was validated in both English and Malayalam by health researchers from the research institution, healthcare providers (HCPs) from the study hospital, the selected patients, and a Malayalam language teacher. The study instrument consisted of 35 questions for participants to answer. The first sections included questions about participants' demographics, medical history, and laboratory data. The second section was divided into three parts that analyze KAP on MetS. Part A consisted of ten multiple-choice questions to assess MetS knowledge. Every correct answer received one point, while an incorrect answer received zero points, resulting in a minimum score of 0 and a maximum score of 22, with 0 being the 'lowest possible' and 22 representing the 'highest possible' knowledge score. The knowledge scores were categorized into three levels: limited (scores 0–14), sufficient (scores 15–19), and excellent (scores 20–22) levels of knowledge [ 19 ]. Part B includes 10 questions on a 5-point Likert scale to examine participants' perceptions of MetS. Section C had six questions with a 5-point Likert scale to measure the participants' attitudes toward MetS. Based on participants' responses, strongly agree and agree responses were classified as Net Positive Responses (NPR), whereas strongly disagree, disagree, and neutral responses were categorized as Net Other Responses (NOR). Each positive response was worth one point. Scores for responses to negatively worded questions were reversed during statistical analysis. Participants' cardiovascular risk was assessed byusing the Framingham Global Risk Assessment criteria and the Framingham Risk Score (FRS) [ 8 , 11 , 20 ]. Cardiovascular risk was classified as low if the score was less than 10%, intermediate if it was between 10% and 20%, and high if it exceeded 20% [ 11 , 20 – 23 ]. Ethical considerations The study proposal was approved by the Lakshmi Hospital Ethics Committee, Palakkad (ECR/1231/Inst/KL/2019, dated 10/01/2023). All information gathered during the data collection process has been kept strictly confidential. No identifiable data was collected, and all information was securely handled and used exclusively for research purposes. Informed consent was obtained from all participants, which included the publication of data collated in anonymised form. The study complied with all ethical regulations outlined in the approval letter and the Helsinki declaration for human research. The current study did not interfere with the ongoing treatments of the participants, as the study instrument primarily evaluates their knowledge, attitude, and perception of MetS. Study procedures The data was collected by the researcher through direct interaction with eligible participants at the bedside or outpatient department while they were receiving treatment or purchasing medicine in the outpatient pharmacy. Additionally, eligible participants were contacted via phone call if they were not available at the study site during data collection. The recruited participants were randomly assigned to either the control or intervention group using an online sample randomizer software. All participants in both groups were asked to complete a questionnaire at the beginning of the study. The intervention group received an online educational program for 30 days, and data were collected again at the end of the 30 days using the same questionnaire. Participants in the intervention group were added to a WhatsApp group specifically created for the study. Educational materials covering all aspects of MetS, including definitions, risk factors, symptoms, complications, therapeutic goals, and self-care activities, were shared daily with the intervention group. The research team carefully selected and compiled health educational information from reputable sources like the Ministry of Health (MoH), India, Indian Diabetic Association, World Health Organization (WHO), American Heart Association (AHA), American Diabetes Association (ADA), American College of Cardiology (ACC), European Society of Cardiology (ESC), European Association for the Study of Diabetes (EASD), and other official bodies. Infographic images were created in both English and Malayalam languages to educate the intervention group participants, tailored to the study's objectives. Participants in the intervention group received daily reminders and free online educational materials on MetS via WhatsApp messages from the researcher. Daily reminders were sent to ensure participants took their medication as prescribed and were educated on the importance of compliance. Statistical analysis All data collected were tabulated and analyzed using the “Statistical Package for Social Sciences (SPSS) version 28.0”[ 24 ]. Descriptive statistics were used to describe demographic information, laboratory data, and responses to the KAP of MetS. The data were presented as frequencies, percentages, means, standard deviations (SD), median, and inter quartile range (IQR) where applicable. Prior to the inferential analysis of the relationship between the groups, the normality of the numerical data distribution was tested. A comparison was made in terms of the KAP of MetS, at baseline and after 30 days of the educational intervention for control and intervention groups. The Wilcoxon Signed-Rank test and the Mann-Whitney U test were used to analyze the effectiveness of the intervention provided to the patients. A p -value < 0.05 was considered statistically significant in this research. RESULTS A total of 150 patients with MetS were approached to participate in this survey, and only 107responded, resulting in a response rate of 71.3%. Seven participants were excluded due to incomplete data. Finally, 100 participants were included and were equally divided into control and intervention groups, with 50 participants in each group. Demographic characteristics of the study participants Overall, the majority of participants were between the ages of 61 and 70 years old (n = 37, 37%), with a mean age of54.63 ± 10.1 years. Females made up 55% of the participants, who were equally distributed between rural (50%) and urban (50%) areas. The majority were married(80%), had a secondary-level education (62%), were employed (61%), and almost half were obese (49%), with a mean abdominal circumference of 96.86 (SD = 9.52) cm, and a mean BMI of 30.46 (SD = 5.05). Around a quarter of the participants were found to be alcohol users (28%). The demographic characteristics of the participants are presented in Table 1 . Table 1 Demographic characteristics of the study participants (n = 100) Demographic variables Control group (n = 50) Intervention group (n = 50) Number (n) Percentage(%) Number (n) Percentage (%) Age (in years) 31–40 41–50 51–60 61–70 71–80 11 10 10 13 6 22.0 20.0 20.0 26.0 12.0 8 5 13 24 0 16.0 10.6 26.0 48.0 0 Gender Male Female 22 28 44.0 56.0 23 27 46.0 54.0 Location of residence Rural Urban 25 25 50.0 50.0 26 24 52.0 48.0 Marital status Single Married Separated Widow 3 39 1 7 6.0 78.0 2.0 14 1 41 3 5 2.0 82.0 6.0 10.6 Education level Never been to school Primary education Secondary education Higher education 0 7 32 11 0.0 14.0 64.0 22.0 0 10 30 10 0.0 20.0 60.0 20.0 Employment status Employed Unemployed Retired Other (own business) 32 7 10 1 64.0 14.0 20.0 2.0 29 11 8 2 58.0 22.0 16.0 4.0 Body mass index (kg/m 2 ) Normal weight (18.5–24.99) Overweight (≥ 25) Obese (≥ 30) 2 23 25 4.0 46.0 50.0 6 20 24 12.0 40.0 48.0 Abdominal circumference Female: Below 80cm ≥ 80 cm Male: Below 90cm ≥ 90 cm 2 26 2 20 4.0 52.0 4 40.0 0 27 4 19 0.0 54.0 8.0 38.0 Lifestyle Active Smoker Alcoholic User 7 14 14.0 28.0 5 14 10.0 28.0 Metabolic abnormalities among the study participants More than half of the participants (n = 59, 59.0%) in this current study had all four metabolic abnormalities (hypertension, diabetes mellitus, dyslipidemia, and abdominal obesity), while the rest (n = 41, 41.0%) had three metabolic abnormalities .Among all the participants, 86% (n = 43) in the intervention group and 92% (n = 46) in the control group reported a family history of MetS. All participants' parameters were collected within the last one-month period. At baseline, the control group had higher total cholesterol, triglycerides, LDL cholesterol, and lower HDL cholesterol levels compared to the intervention group. The baseline mean (± SD) fasting blood glucose and blood pressure values were similar in both groups. Details of the laboratory values at baseline and after 30 days are presented in Table 2 . Table 2 Laboratory parameters of the control and intervention group participants at pre- and post-intervention (n = 100) Laboratory parameters Control group (n = 50) Intervention group (n = 50) Pre-intervention Post-intervention Pre-intervention Post-intervention Mean ± SD Median (IQR) Mean ± SD Median (IQR) Mean ± SD Median (IQR) Mean ± SD Median (IQR) Total cholesterol (mmol/L) 5.39 ± 1.25 5.81(2.35) 5.63 ± 1.53 5.81(2.37) 5.61 ± 1.52 5.68(1.83) 5.25 ± 1.18 5.42(1.5) Triglyceride (mmol/L) 1.91 ± 0.66 1.92 (1.0) 1.95 ± 0.66 1.96 (0.7) 2.09 ± 0.91 1.95 (1.08) 2.11 ± 0.90 1.91 (1.05) HDL cholesterol (mmol/L) Female Male 1.23 ± 0.33 1.09 ± 0.24 1.30 (0.3) 1.04 (0.3) 1.22 ± 0.28 1.06 ± 0.19 1.21 (0.4) 1.11 (0.3) 1.17 ± 0.2 1.13 ± 0.32 1.23 (0.25) 1.12 (0.6) 1.2 ± 0.18 1.17 ± 0.19 1.23 (0.2) 1.32 (0.3) LDL-cholesterol (mmol/L) 2.82 ± 0.79 2.81 (1.3) 2.81 ± 0.73 2.88 (1.1) 3.29 ± 1.25 3.05 (1.55) 3.26 ± 1.22 2.81 (1.56) FBG (mmol/L) 9.15 ± 3.58 8.21 (5.2) 8.36 ± 2.91 7.84 (4.0) 10.63 ± 5.47 8.81 (4.55) 10.16 ± 3.88 8.82 (4.23) Blood pressure Systolic Diastolic 142.22 ± 8.47 81.98 ± 7.14 143.01 (6) 79.20 (10) 140.12 ± 7.15 82.41 ± 6.17 139.21 (8) 83.53 (8) 142.63 ± 16.1 81.51 ± 7.33 143.21 (16) 83.32 (11) 138.32 ± 10.6 79.55 ± 5.83 138.33 (12) 79.01 (9) FBG = Fasting blood glucose; HDL = High-density lipoprotein; IQR = Interquartile range; LDL = Low-density lipoprotein; SD = Standard deviation The assessment of 10-year cardiovascular risk using the Framingham Risk Score (FRS) showed that over half of the study participants in the control (n = 34; 68%) and intervention (n = 32; 64%) groups were at high risk (FRS > 20%). After 30 days of intervention, a statistically significant improvement (p < 0.01) was observed in the intervention group. Effectiveness of intervention on the participants’ knowledge of MetS Overall, at baseline, only 4 participants (4.1%) had an excellent level of knowledge of MetS, while12% (n = 12) had sufficient knowledge, and the majority of participants (n = 84, 84%) had limited knowledge. In the control group, 90% (n = 45), 8% (n = 4), and 2% (n = 1) of participants had limited, sufficient and excellent knowledge, respectively at baseline. Meanwhile, in the intervention group, 78% (n = 39), 16% (n = 8), and 6% (n = 3) of participants had limited, sufficient, and excellent knowledge, respectively at baseline. After 30 days of intervention, 16% (n = 8) of participants had excellent knowledge, and 36% (n = 18) had sufficient knowledge of MetS. Tables 3 and 4 show the individual scores and knowledge levels of MetS for the participants. Table 3 Knowledge score of the control and intervention group participants at pre- and post-intervention (n = 100) Knowledge level of MetS (Score) Total score Pre-intervention (n = 100) Post-intervention (n = 100) Control group (n = 50) Intervention group (n = 50) Total (n = 100) Control group (n = 50) Intervention group (n = 50) Total (n = 100) Limited Knowledge (0–14) 0 10 (20%) 2 (4%) 12 (12%) 9 (18%) 1 (1%) 10 (10%) 1 1 (2%) 0 (0%) 1 (1%) 0 (0%) 0 (0%) 0 (0%) 2 1 (2%) 2 (4%) 3 (3%) 1 (2%) 0 (0%) 1 (1%) 3 2 (4%) 3 (6%) 5 (5%) 2 (4%) 0 (0%) 2 (2%) 4 1 (2%) 3 (6%) 4 (4%) 2 (4%) 0 (0%) 2 (4%) 5 2 (4%) 2 (4%) 4 (4%) 1 (2%) 0 (0%) 1 (1%) 6 3 (6%) 2 (4%) 5 (5%) 3 (6%) 1 (2%) 4 (4%) 7 2 (4%) 1 (2%) 3 (3%) 1 (2%) 0 (0%) 1 (1%) 8 3 (6%) 3 (6%) 6 (6%) 2 (4%) 0 (0%) 2 (2%) 9 1 (2%) 2 (4%) 3 (3%) 2 (4%) 1 (2%) 3 (3%) 10 6 (12%) 2 (4%) 8 (8%) 7 (14%) 2 (4%) 9 (9%) 11 7 (14%) 3 (6%) 10 (10%) 7 (14%) 6 (12%) 13 (13%) 12 1 (2%) 3 (6%) 4 (4%) 6 (12%) 4 (8%) 10 (10%) 13 1 (2%) 5 (10%) 6 (6%) 1 (2%) 4 (8%) 5 (5%) 14 4 (8%) 6 (12%) 10 (10%) 2 (4%) 5 (10%) 7 (7%) Sufficient Knowledge (15–19) 15 1 (2%) 4 (8%) 5 (5%) 1 (2%) 2 (4%) 3 (3%) 16 0 (0%) 1 (2%) 1 (1%) 0 (0%) 5 (10%) 5 (5%) 17 2 (4%) 1 (2%) 3 (3%) 0 (0%) 3 (6%) 3 (3%) 18 1 (2%) 0 (0%) 1 (1%) 2 (4%) 7 (14%) 9 (9%) 19 0 (0%) 2 (4%) 2 (2%) 0 (0%) 1 (2%) 1 (1%) Excellent Knowledge (20–22) 20 0 (0%) 2 (4%) 2 (2%) 0 (0%) 4 (8%) 4 (4%) 21 0 (0%) 1 (2%) 1 (1%) 0 (0%) 2 (4%) 2 (2%) 22 1 (2%) 0 (0%) 1 (1%) 1 (2%) 2 (4%) 3 (3%) Table 4 Level of knowledge of metabolic syndrome among the participants (n = 100) Knowledge level of MetS (Score) Control group (n = 50) Intervention group (n = 50) Pre-intervention Post-intervention Pre-intervention Post-intervention Limited Knowledge (0–14) 45 (90%) 46 (92%) 39 (78%) 24 (48) Sufficient Knowledge (15–19) 4 (8%) 3 (6%) 8 (16%) 18 (36%) Excellent Knowledge (20–22) 1 (2%) 1 (2%) 3 (6%) 8 (16%) Inferential statistics were used to compare the effectiveness of the intervention and the differences between the groups pre- and post-intervention. Before running the inferential statistical analysis, the distribution of the numerical data was examined using the Kolmogorov-Smirnov test. It was found that all the numerical data were not normally distributed (p < 0.05). Therefore, the Wilcoxon signed-rank test was used to analyze the association between the pre- and post-knowledge of MetS in the intervention group (n = 47) (25). The results showed that the educational intervention provided to the patients had a statistically significant change in knowledge among the patients with MetS (Z=-6.5631, p < 0.001). The median (IQR) knowledge score was 13.0 (6.0) points and 17.0 (8.0) points, pre- and post-intervention, respectively. In contrast, in the control group, it was observed that due to the absence of an intervention, there were no statistically significant changes in terms of knowledge (Z=-0.462, p = 0.367) among the participants in the control group. The association of knowledge of MetS among the control and intervention groups at pre- and post-intervention, as analyzed using the Mann-Whitney U test, showed that there were significant differences in knowledge among these groups (p < 0.05).Tables 5 and 6 show the results of these analyses. Table 5 Comparison of pre-and post-intervention knowledge scores within groups Groups Wilcoxon Signed-Rank test Median (IQR) Z statistic P- value* Pre- intervention Post- intervention Intervention group 13.0(6.0) 17.0(8.0) -6.531 < 0.001 Control group 9.5(7.0) 10.0(8.0) -0.462 0.367 *Significant at the 0.01 level (2-tailed) Table 6 Comparison of pre-and post-intervention knowledge scores among groups Data collection time Mann-Whitney U test Median (IQR) Z statistic P- value* Control group Intervention group Pre-intervention 9.5(7.0) 13.0(6.0) -2.888 0.010 Post-intervention 10.0(8.0) 17.0(8.0) -5.603 < 0.001 *Significant at the 0.01 level (2-tailed) Effectiveness of intervention on the participants’ attitudes toward MetS A positive response rate (PRR) (26) was calculated for each questionnaire item by dividing the total number of NPR by the total number of responses and then multiplying by 100. An overall PRR greater than 50% indicated positive attitudes towards MetS among participants. At baseline, the mean PRR for all 10 items assessing attitude was 38.27%, reflecting overall negative attitudes towards MetS among study participants. In comparison, the intervention group had a baseline mean PRR of 54.8%, while the control group had a mean PRR of 33.2%. Following the educational intervention, the mean PRR in the intervention group increased to 58.53%. Inferential analysis the educational intervention over a month resulted in a statistically significant change in attitude (Z=-2.925, p < 0.001) in the intervention group. Additionally, a statistically significant change in attitude was also noted in the control group after a month (Z=-3.363, p < 0.001). Significant differences in attitudes towards MetS were observed between the control and intervention groups (p < 0.05) during pre- and post-intervention. The results of the inferential analysis are shown in Tables 7 and 8 . Table 7 Comparison of pre-and post-intervention attitudes scores within groups Groups Wilcoxon Signed-Rank test Median (IQR) Z statistic P- value* Pre- intervention Post- intervention Intervention group 29.0(10.0) 35.0(12.0) -2.925 < 0.001 Control group 20.5(9.0) 22.8(10.0) -3.363 < 0.001 *Significant at the 0.01 level (2-tailed) Table 8 Comparison of pre-and post-intervention attitudes scores among groups Data collection time Mann-Whitney U test Median (IQR) Z statistic P- value* Control group (n = 50) Intervention group (n = 47) Pre-intervention 20.5(9.0) 29.0(10.0) -4.314 < 0.001 Post-intervention 22.8(10.0) 35.0(12.0) -6.231 50% suggests positive perceptions of MetS among the participants. At baseline, the mean PRR for all 6 items on the perception assessment was 78.32%, showing an overall positive perception toward MetS among all the participants. Both the control group (mean PRR = 61.33%) and the intervention group (mean PRR = 89.52%) participants had positive perceptions at baseline or pre-intervention. The mean PRR increased to 96.98% in the intervention group after the educational intervention. According to the Wilcoxon signed-rank test, the intervention resulted in a statistically significant change in perception score (Z=-4.693, p < 0.001) among the patients with MetS. The median (IQR) perception score was 21.0 (5.0) points and 29.0 (6.0) points, pre- and post-intervention, respectively. Compared to the baseline, no statistically significant changes were noted in perceptions of MetS (Z=-1.862, p = 0.756) in the control group after a month. Significant differences in perception of MetS were observed between the participants in the control and intervention groups in pre- and post-intervention (p < 0.05). The results of inferential analysis are shown in Tables 9 and 10 . Table 9 Comparison of pre-and post-intervention perception scores within groups Groups Wilcoxon Signed-Rank test Median (IQR) Z statistic P- value* Pre- intervention Post- intervention Intervention group 21.0(5.0) 29.0(6.0) -4.693 < 0.001 Control group 21.0(5.0) 23.0(5.0) -1.862 0.756 *Significant at the 0.01 level (2-tailed) Table 10 Comparison of pre-and post-intervention perception scores among groups Data collection time Mann-Whitney U test Median (IQR) Z statistic P- value* Control group (n = 50) Intervention group (n = 47) Pre-intervention 21.0(5.0) 21.0(5.0) -5.397 < 0.001 Post-intervention 23.0(5.0) 29.0(6.0) -7.267 < 0.001 *Significant at the 0.01 level (2-tailed) DISCUSSION The findings of the current research indicated that MetS is more frequently observed in older women over the age of 50. Global research has consistently identified aging as a major risk factor for the onset of MetS [ 15 , 16 , 27 – 32 ]. A higher occurrence of MetS among women has also been documented in regions such as Iran [ 28 ], Africa [ 33 ], Indonesia [ 34 ], and China [ 35 ]. This trend may be linked to the processes of aging and menopause, which make females more susceptible to developing MetS, with postmenopausal women facing a greater risk[ 36 ]. Most of the participants in this study were employed adults, which might also explain work-related issues such as stress, sedentary lifestyles, and poor nutrition contributing to the development of MetS. The current findings indicated that most patients with MetS were likely to exhibit all conditions of the syndrome. Diabetes and obesity were prevalent among the participants, aligning with earlier studies that highlighted a significant association between these conditions and the diagnosis of MetS among university staff [ 15 , 35 , 37 ]. In contrast, diabetes was reported as the least common metabolic condition (11.7%) among MetS patients in Hong Kong [ 35 ]. In this study, a significant portion of the patients fell into the high-risk category for cardiovascular diseases (CVDs) based on the Framingham Risk Score (FRS), even while receiving treatment for existing comorbidities. About 95.6% and 74.3% of MetS patients exhibited a notably higher risk for CVDs, particularly within the low-risk group [ 38 , 39 ]. Conversely, research conducted in Pakistan indicated a 20.4% higher prevalence of high risk for CVD among newly diagnosed MetS patients who were not undergoing treatment than people on treatment [ 40 ]. The elevated percentage of patients classified as high-risk in this study could be attributed to sociodemographic factors, lifestyle choices, dietary habits, and existing comorbidities. It is crucial to recognize that the outcomes of this study highlight the necessity of conducting CVD risk assessments and providing timely management for individuals with MetS. Moreover, utilizing appropriate cardiovascular risk stratification tools tailored to specific populations may enhance the understanding of CVD risk in patients presenting with MetS[ 41 – 43 ]. The current research indicates that most patients with MetS possess limited knowledge of the condition. This observation aligns with findings from various other global studies [ 35 , 44 – 48 ]. One study documented a low level of MetS awareness (67.2%) among hospitalized patients with cardiometabolic risk factors (56%) [ 45 ]. A separate investigation in community settings found that knowledge of MetS was also lacking (61%), with 51.9% of participants diagnosed with MetS[ 35 ]. A study conducted in Spain revealed that awareness of cardiovascular disease (CVD) risk amongst MetS patients was insufficient (39.6%) [ 48 ]. A self-reported survey indicated lower knowledge levels across all aspects of cardiometabolic health [ 49 ]. In contrast to our findings, a different study reported that 66% of MetS patients possessed moderate knowledge regarding lifestyle and cardiovascular risk factors [ 50 ]. Despite a brief introduction to MetS provided in the questionnaire, a significant portion of participants in this research were unaware of the definition of MetS, mirroring results from earlier studies [ 44 , 45 ]. Individuals with MetS exhibited a lack of understanding of the recommended targets for cardiometabolic components related to the condition [ 35 , 45 ]. While participants in the current study recognized the necessity of regular clinic visits, they have not acquired sufficient understanding of MetS, including key elements related to managing its components. Most participants were uninformed about the significance of lifestyle modifications, stress management, healthy eating habits, and ongoing health monitoring; a finding consistent with prior research [ 50 ]. This lack of knowledge could stem from inadequate education about MetS within the current healthcare systems. In this study, patients displayed negative attitudes toward MetS, although the majority acknowledged the positive effects of regular physical activity on MetS management and the mitigation of complications, which aligns with previous research [ 50 ]. Many working adults with MetS cited their job nature as a factor contributing to their physical inactivity, reflecting conclusions from studies involving female market traders [ 46 ] and office workers [ 51 ], yet they held the belief that physical activity could enhance their cardiometabolic health [ 51 ]. Employers are urged to introduce policies aimed at promoting physical activity among their employees. This initiative could significantly enhance health, decrease absenteeism, and boost productivity. Additionally, the improvement of lipid levels in MetS patients should be prioritized through appropriate dietary choices and regular monitoring, alongside other cardiometabolic indicators, to lower the risk of CVD. The negative attitudes among the participants in this study can be linked to insufficient focus on the management of MetS. In this regard, primary care healthcare professionals who frequently encounter patients at the onset of MetS should tackle these negative attitudes. These providers should promote healthy lifestyle practices and direct patients to dietitians when necessary. Most participants in this study perceived the cardiovascular risks associated with MetS and various lifestyle factors related to it. They also expressed a positive perception of the effects of MetS on quality of life. Patients with MetS were more inclined to have positive views on the complications related to metabolic diseases and complications [ 46 , 49 , 51 ]. Understanding the condition is crucial for encouraging adherence to treatment plans and lifestyle modifications [ 52 – 54 ]. The present study indicated that MetS patients with positive attitudes towards MetS tend to view the condition more positively; however, the knowledge of MetS is not necessarily aligned with an individual's perceived risk and control over the condition. This study underscores that despite having favourable views and attitudes toward MetS, patients still lack fundamental knowledge regarding it, aligning with findings from other studies [ 49 , 55 ]. We believe these outcomes may stem from inadequate patient education on MetS, resulting in those affected failing to acquire knowledge about modifiable risk factors and healthy lifestyle choices that could mitigate the risk of metabolic complications. Following the intervention, the knowledge, attitudes, and perceptions regarding MetS among participants showed significant improvement relative to their initial levels. Therefore, the findings of this study demonstrate the effectiveness of pharmacist-led educational interventions in enhancing understanding and attitudes towards MetS. Similar results were documented where pharmacist-led educational efforts greatly enhanced medication adherence behaviors among patients with chronic diseases in the intervention group [ 56 , 57 ]. In light of the post-pandemic attrition rates of healthcare professionals in medical fields, this study advocates for the integration of telehealth education to achieve notably improved health outcomes for patients with MetS. The digital platform provides enhanced engagement in treatment and patient education in today's environment. There were several limitations present in this study. A convenience sampling technique was used to recruit the study participants, and the study was conducted only in the Palakkad region, so the outcome of the research may not be accurate and may not reflect the entire population of Kerala or India. As the study was conducted using a self-administered questionnaire, there could be a recall bias. CONCLUSION Knowledge, Attitudes, and Perceptions of MetS are crucial for preventing the development of metabolic complications such as CVDs, cerebrovascular attacks, and organ damage. Patients in this study exhibited limited knowledge and negative attitudes towards MetS. The educational intervention provided to these patients was effective in improving their KAP of MetS. HCPs should be encouraged to engage in patient education, particularly regarding chronic illnesses both the hospital and community levels. The effective use of online or digital-based health education in all healthcare settings is warranted to consistently educate patients with medical illnesses. Declarations Data availability All data generated or analyzed during this research are included in this submitted article. For any inquiries regarding data access or additional information, please contact the corresponding author at [email protected] . The data are available under Creative Commons Attribution 4.0 International License and can be freely used with proper attribution. Funding This work did not receive any funding. Clinical Trial Number Not applicable. Ethics declarations Ethics approval The ethical approval for this study was received from the Lakshmi Hospital Ethics Committee, Palakkad (Reference number ECR/1231/Inst/KL/2019). Competing interests The authors declare no competing interests. Author Contribution First Author wrote the manuscript Second author was the supervisor of this research workBoth authors reviewed the manuscript References Ren H, Wang J, Gao Y, Yang F, Huang W. Metabolic syndrome and liver-related events: a systematic review and meta-analysis. BMC EndocrDisord. 2019;19(1):40. 10.1186/s12902-019-0366-3 . Chin KY, Wong SK, Ekeuku SO, Pang KL. 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Abdominal obesity, high blood pressure, high fasting blood glucose, and dyslipidemia are considered the four key components of MetS. These metabolic risk factors can impact various health conditions such as cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), cerebrovascular complications, bone mineral disease (BMD), liver-related events (LRE), and gastrointestinal disorders [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Cardiovascular disease, characterized by heart and blood vessel problems, remains the leading cause of death globally [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In 2020, an estimated 244.1\u0026nbsp;million individuals worldwide were diagnosed with ischemic heart disease (IHD), with 19.1\u0026nbsp;million deaths attributed to CVDs [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite advancements in the management and treatment of non-communicable diseases (NCDs) like CVDs, T2DM, renal disease, and cerebrovascular diseases, the number of individuals with multiple NCDs continues to rise. Poor patient education plays a significant role in the rise of metabolic disorders. Many individuals lack proper knowledge about the importance of healthy lifestyle choices, such as diet and exercise, which are crucial for preventing or managing conditions like obesity, diabetes, and hypertension. Without adequate understanding, patients may not recognize the risks associated with poor eating habits, sedentary behavior, or non-compliance with prescribed treatments. Furthermore, inadequate education can lead to misunderstandings about the significance of regular monitoring, such as blood sugar or cholesterol levels, increasing the likelihood of complications. In many cases, patients may also struggle to navigate complex medical information and treatment options, leading to confusion and non-adherence to care plans. As a result, these gaps in knowledge contribute to the rising prevalence of metabolic disorders, highlighting the urgent need for healthcare systems to prioritize better patient education to prevent and manage these conditions effectively. Hence, a study was conducted to assess the Knowledge, Attitudes, and Perceptions (KAP) of MetS among patients with MetS, estimate cardiovascular risk scores, and provide educational interventions on MetS for these patients.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and population\u003c/h2\u003e\u003cp\u003eThis interventional study was carried out among MetS patients in a private hospital setting in Palakkad, Kerala, utilizing a validated, structured study tool. This study included patients over the age of 18, regardless of gender, who had been diagnosed with MetS. Patients diagnosed with at least three metabolic abnormalities, including hypertension, diabetes mellitus, abdominal obesity, and dyslipidemia (low HDL cholesterol or hyper triglyceridemia), were eligible to participate in this study.\u003c/p\u003e\u003cp\u003eThe JIS-proposed definition of MetS - \"Harmonised\" criterion [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] was used to identify study participants. The following clinical indicators were utilized as diagnostic criteria for MetS in this study.\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAbdominal obesity is defined as a waist circumference of more than 90 cm (35 inches) for men and 80 cm (32 inches) for women [(8].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eImpaired glycemic control is defined as fasting venous blood glucose levels greater than 125 mg/ dL or 7.0 m mol/L [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eParticipants with high blood pressure (\u0026ge;\u0026thinsp;130/85 mmHg) or who are taking hypertension medication [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eParticipants with high triglyceride levels (above 150 mg/dL or 1.7 mmol/L) or low fasting HDL cholesterol levels (below 40 mg/dL or 1 mmol/L for men and 50 mg/dL or 1.2 mmol/L for women) or those taking hyper triglyceridemia or low HDL cholesterol drugs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample size estimation\u003c/h3\u003e\n\u003cp\u003eThe sample size for the current interventional investigation was determined using the formula devised by Sathian et al., (2010)[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] for the Relevance of Sample Size Determination in Medical Research. The study used a research instrument with 35 questions, including 9 questions on demographic variables and 26 questions to assess MetS's KAP. The participants were divided into two groups: control and intervention, to assess the effectiveness of interventions provided by the pharmacist. Using the above algorithm developed by Sathian et al., (2010) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], 50 participants were selected in each control and intervention group.\u003c/p\u003e\n\u003ch3\u003eStudy instrument\u003c/h3\u003e\n\u003cp\u003eThe study instrument was divided into three sections: Demographic and Clinical characteristics, Knowledge, Attitudes, and Perceptions (KAP) of MetS, and cardiovascular risk score. A definition of MetS[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]was provided at the beginning of the questionnaire. The research team developed the study instrument for assessing the KAP of MetS based on previously published investigations [\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It was validated in both English and Malayalam by health researchers from the research institution, healthcare providers (HCPs) from the study hospital, the selected patients, and a Malayalam language teacher. The study instrument consisted of 35 questions for participants to answer. The first sections included questions about participants' demographics, medical history, and laboratory data.\u003c/p\u003e\u003cp\u003eThe second section was divided into three parts that analyze KAP on MetS. Part A consisted of ten multiple-choice questions to assess MetS knowledge. Every correct answer received one point, while an incorrect answer received zero points, resulting in a minimum score of 0 and a maximum score of 22, with 0 being the 'lowest possible' and 22 representing the 'highest possible' knowledge score. The knowledge scores were categorized into three levels: limited (scores 0\u0026ndash;14), sufficient (scores 15\u0026ndash;19), and excellent (scores 20\u0026ndash;22) levels of knowledge [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePart B includes 10 questions on a 5-point Likert scale to examine participants' perceptions of MetS. Section C had six questions with a 5-point Likert scale to measure the participants' attitudes toward MetS.\u003c/p\u003e\u003cp\u003eBased on participants' responses, strongly agree and agree responses were classified as Net Positive Responses (NPR), whereas strongly disagree, disagree, and neutral responses were categorized as Net Other Responses (NOR). Each positive response was worth one point. Scores for responses to negatively worded questions were reversed during statistical analysis.\u003c/p\u003e\u003cp\u003eParticipants' cardiovascular risk was assessed byusing the Framingham Global Risk Assessment criteria and the Framingham Risk Score (FRS) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Cardiovascular risk was classified as low if the score was less than 10%, intermediate if it was between 10% and 20%, and high if it exceeded 20% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eEthical considerations\u003c/h3\u003e\n\u003cp\u003eThe study proposal was approved by the Lakshmi Hospital Ethics Committee, Palakkad (ECR/1231/Inst/KL/2019, dated 10/01/2023). All information gathered during the data collection process has been kept strictly confidential. No identifiable data was collected, and all information was securely handled and used exclusively for research purposes. Informed consent was obtained from all participants, which included the publication of data collated in anonymised form. The study complied with all ethical regulations outlined in the approval letter and the Helsinki declaration for human research. The current study did not interfere with the ongoing treatments of the participants, as the study instrument primarily evaluates their knowledge, attitude, and perception of MetS.\u003c/p\u003e\n\u003ch3\u003eStudy procedures\u003c/h3\u003e\n\u003cp\u003eThe data was collected by the researcher through direct interaction with eligible participants at the bedside or outpatient department while they were receiving treatment or purchasing medicine in the outpatient pharmacy. Additionally, eligible participants were contacted via phone call if they were not available at the study site during data collection.\u003c/p\u003e\u003cp\u003eThe recruited participants were randomly assigned to either the control or intervention group using an online sample randomizer software. All participants in both groups were asked to complete a questionnaire at the beginning of the study. The intervention group received an online educational program for 30 days, and data were collected again at the end of the 30 days using the same questionnaire.\u003c/p\u003e\u003cp\u003eParticipants in the intervention group were added to a WhatsApp group specifically created for the study. Educational materials covering all aspects of MetS, including definitions, risk factors, symptoms, complications, therapeutic goals, and self-care activities, were shared daily with the intervention group. The research team carefully selected and compiled health educational information from reputable sources like the Ministry of Health (MoH), India, Indian Diabetic Association, World Health Organization (WHO), American Heart Association (AHA), American Diabetes Association (ADA), American College of Cardiology (ACC), European Society of Cardiology (ESC), European Association for the Study of Diabetes (EASD), and other official bodies. Infographic images were created in both English and Malayalam languages to educate the intervention group participants, tailored to the study's objectives.\u003c/p\u003e\u003cp\u003eParticipants in the intervention group received daily reminders and free online educational materials on MetS via WhatsApp messages from the researcher. Daily reminders were sent to ensure participants took their medication as prescribed and were educated on the importance of compliance.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAll data collected were tabulated and analyzed using the \u0026ldquo;Statistical Package for Social Sciences (SPSS) version 28.0\u0026rdquo;[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Descriptive statistics were used to describe demographic information, laboratory data, and responses to the KAP of MetS. The data were presented as frequencies, percentages, means, standard deviations (SD), median, and inter quartile range (IQR) where applicable. Prior to the inferential analysis of the relationship between the groups, the normality of the numerical data distribution was tested. A comparison was made in terms of the KAP of MetS, at baseline and after 30 days of the educational intervention for control and intervention groups. The Wilcoxon Signed-Rank test and the Mann-Whitney U test were used to analyze the effectiveness of the intervention provided to the patients. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant in this research.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 150 patients with MetS were approached to participate in this survey, and only 107responded, resulting in a response rate of 71.3%. Seven participants were excluded due to incomplete data. Finally, 100 participants were included and were equally divided into control and intervention groups, with 50 participants in each group.\u003c/p\u003e\n\u003ch3\u003eDemographic characteristics of the study participants\u003c/h3\u003e\n\u003cp\u003eOverall, the majority of participants were between the ages of 61 and 70 years old (n\u0026thinsp;=\u0026thinsp;37, 37%), with a mean age of54.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1 years. Females made up 55% of the participants, who were equally distributed between rural (50%) and urban (50%) areas. The majority were married(80%), had a secondary-level education (62%), were employed (61%), and almost half were obese (49%), with a mean abdominal circumference of 96.86 (SD\u0026thinsp;=\u0026thinsp;9.52) cm, and a mean BMI of 30.46 (SD\u0026thinsp;=\u0026thinsp;5.05). Around a quarter of the participants were found to be alcohol users (28%). The demographic characteristics of the participants are presented in 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\u003eDemographic characteristics of the study participants (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDemographic variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (in years)\u003c/p\u003e\u003cp\u003e31\u0026ndash;40\u003c/p\u003e\u003cp\u003e41\u0026ndash;50\u003c/p\u003e\u003cp\u003e51\u0026ndash;60\u003c/p\u003e\u003cp\u003e61\u0026ndash;70\u003c/p\u003e\u003cp\u003e71\u0026ndash;80\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003cp\u003e10\u003c/p\u003e\u003cp\u003e10\u003c/p\u003e\u003cp\u003e13\u003c/p\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.0\u003c/p\u003e\u003cp\u003e20.0\u003c/p\u003e\u003cp\u003e20.0\u003c/p\u003e\u003cp\u003e26.0\u003c/p\u003e\u003cp\u003e12.0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003cp\u003e5\u003c/p\u003e\u003cp\u003e13\u003c/p\u003e\u003cp\u003e24\u003c/p\u003e\u003cp\u003e0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.0\u003c/p\u003e\u003cp\u003e10.6\u003c/p\u003e\u003cp\u003e26.0\u003c/p\u003e\u003cp\u003e48.0\u003c/p\u003e\u003cp\u003e0\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMale\u003c/p\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.0\u003c/p\u003e\u003cp\u003e56.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46.0\u003c/p\u003e\u003cp\u003e54.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLocation of residence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRural\u003c/p\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.0\u003c/p\u003e\u003cp\u003e50.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52.0\u003c/p\u003e\u003cp\u003e48.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSingle\u003c/p\u003e\u003cp\u003eMarried\u003c/p\u003e\u003cp\u003eSeparated\u003c/p\u003e\u003cp\u003eWidow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003cp\u003e39\u003c/p\u003e\u003cp\u003e1\u003c/p\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0\u003c/p\u003e\u003cp\u003e78.0\u003c/p\u003e\u003cp\u003e2.0\u003c/p\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003cp\u003e41\u003c/p\u003e\u003cp\u003e3\u003c/p\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003cp\u003e82.0\u003c/p\u003e\u003cp\u003e6.0\u003c/p\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNever been to school\u003c/p\u003e\u003cp\u003ePrimary education\u003c/p\u003e\u003cp\u003eSecondary education\u003c/p\u003e\u003cp\u003eHigher education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e7\u003c/p\u003e\u003cp\u003e32\u003c/p\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003cp\u003e14.0\u003c/p\u003e\u003cp\u003e64.0\u003c/p\u003e\u003cp\u003e22.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e10\u003c/p\u003e\u003cp\u003e30\u003c/p\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003cp\u003e20.0\u003c/p\u003e\u003cp\u003e60.0\u003c/p\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003cp\u003eRetired\u003c/p\u003e\u003cp\u003eOther (own business)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003cp\u003e7\u003c/p\u003e\u003cp\u003e10\u003c/p\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.0\u003c/p\u003e\u003cp\u003e14.0\u003c/p\u003e\u003cp\u003e20.0\u003c/p\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29\u003c/p\u003e\u003cp\u003e11\u003c/p\u003e\u003cp\u003e8\u003c/p\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58.0\u003c/p\u003e\u003cp\u003e22.0\u003c/p\u003e\u003cp\u003e16.0\u003c/p\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBody mass index (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNormal weight (18.5\u0026ndash;24.99)\u003c/p\u003e\u003cp\u003eOverweight (\u0026ge;\u0026thinsp;25)\u003c/p\u003e\u003cp\u003eObese (\u0026ge;\u0026thinsp;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003cp\u003e23\u003c/p\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003cp\u003e46.0\u003c/p\u003e\u003cp\u003e50.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003cp\u003e20\u003c/p\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.0\u003c/p\u003e\u003cp\u003e40.0\u003c/p\u003e\u003cp\u003e48.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAbdominal circumference\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFemale:\u003c/p\u003e\u003cp\u003eBelow 80cm\u003c/p\u003e\u003cp\u003e\u0026ge;\u0026thinsp;80 cm\u003c/p\u003e\u003cp\u003eMale:\u003c/p\u003e\u003cp\u003eBelow 90cm\u003c/p\u003e\u003cp\u003e\u0026ge;\u0026thinsp;90 cm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003cp\u003e26\u003c/p\u003e\u003cp\u003e2\u003c/p\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003cp\u003e52.0\u003c/p\u003e\u003cp\u003e4\u003c/p\u003e\u003cp\u003e40.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e27\u003c/p\u003e\u003cp\u003e4\u003c/p\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003cp\u003e54.0\u003c/p\u003e\u003cp\u003e8.0\u003c/p\u003e\u003cp\u003e38.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle\u003c/b\u003e\u003c/p\u003e\u003cp\u003eActive Smoker\u003c/p\u003e\u003cp\u003eAlcoholic User\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.0\u003c/p\u003e\u003cp\u003e28.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.0\u003c/p\u003e\u003cp\u003e28.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMetabolic abnormalities among the study participants\u003c/h2\u003e\u003cp\u003eMore than half of the participants (n\u0026thinsp;=\u0026thinsp;59, 59.0%) in this current study had all four metabolic abnormalities (hypertension, diabetes mellitus, dyslipidemia, and abdominal obesity), while the rest (n\u0026thinsp;=\u0026thinsp;41, 41.0%) had three metabolic abnormalities .Among all the participants, 86% (n\u0026thinsp;=\u0026thinsp;43) in the intervention group and 92% (n\u0026thinsp;=\u0026thinsp;46) in the control group reported a family history of MetS.\u003c/p\u003e\u003cp\u003eAll participants' parameters were collected within the last one-month period. At baseline, the control group had higher total cholesterol, triglycerides, LDL cholesterol, and lower HDL cholesterol levels compared to the intervention group. The baseline mean (\u0026plusmn;\u0026thinsp;SD) fasting blood glucose and blood pressure values were similar in both groups. Details of the laboratory values at baseline and after 30 days are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLaboratory parameters of the control and intervention group participants at pre- and post-intervention (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" 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=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eLaboratory parameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal cholesterol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.81(2.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.81(2.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e5.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.68(1.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e\u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e5.42(1.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglyceride (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.92 (1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.96 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e2.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.95 (1.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e\u003cp\u003e2.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.91 (1.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL cholesterol (mmol/L)\u003c/p\u003e\u003cp\u003eFemale\u003c/p\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.30 (0.3)\u003c/p\u003e\u003cp\u003e1.04 (0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.21 (0.4)\u003c/p\u003e\u003cp\u003e1.11 (0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.23 (0.25)\u003c/p\u003e\u003cp\u003e1.12 (0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.23 (0.2)\u003c/p\u003e\u003cp\u003e1.32 (0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-cholesterol (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.81 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.88 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e3.05 (1.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e\u003cp\u003e3.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.81 (1.56)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFBG (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e9.15\u0026thinsp;\u0026plusmn;\u0026thinsp;3.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.21 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e8.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.84 (4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e\u003cp\u003e10.63\u0026thinsp;\u0026plusmn;\u0026thinsp;5.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e8.81 (4.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e\u003cp\u003e10.16\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e8.82 (4.23)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood pressure\u003c/p\u003e\u003cp\u003eSystolic\u003c/p\u003e\u003cp\u003eDiastolic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e142.22\u0026thinsp;\u0026plusmn;\u0026thinsp;8.47\u003c/p\u003e\u003cp\u003e81.98\u0026thinsp;\u0026plusmn;\u0026thinsp;7.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e143.01 (6)\u003c/p\u003e\u003cp\u003e79.20 (10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e140.12\u0026thinsp;\u0026plusmn;\u0026thinsp;7.15\u003c/p\u003e\u003cp\u003e82.41\u0026thinsp;\u0026plusmn;\u0026thinsp;6.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e139.21 (8)\u003c/p\u003e\u003cp\u003e83.53 (8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e142.63\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e\u003cp\u003e81.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e143.21 (16)\u003c/p\u003e\u003cp\u003e83.32 (11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e138.32\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u003c/p\u003e\u003cp\u003e79.55\u0026thinsp;\u0026plusmn;\u0026thinsp;5.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e138.33 (12)\u003c/p\u003e\u003cp\u003e79.01 (9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFBG\u0026thinsp;=\u0026thinsp;Fasting blood glucose; HDL\u0026thinsp;=\u0026thinsp;High-density lipoprotein; IQR\u0026thinsp;=\u0026thinsp;Interquartile range; LDL\u0026thinsp;=\u0026thinsp;Low-density lipoprotein; SD\u0026thinsp;=\u0026thinsp;Standard deviation\u003c/p\u003e\u003cp\u003eThe assessment of 10-year cardiovascular risk using the Framingham Risk Score (FRS) showed that over half of the study participants in the control (n\u0026thinsp;=\u0026thinsp;34; 68%) and intervention (n\u0026thinsp;=\u0026thinsp;32; 64%) groups were at high risk (FRS\u0026thinsp;\u0026gt;\u0026thinsp;20%). After 30 days of intervention, a statistically significant improvement (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was observed in the intervention group.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eEffectiveness of intervention on the participants\u0026rsquo; knowledge of MetS\u003c/h2\u003e\u003cp\u003eOverall, at baseline, only 4 participants (4.1%) had an excellent level of knowledge of MetS, while12% (n\u0026thinsp;=\u0026thinsp;12) had sufficient knowledge, and the majority of participants (n\u0026thinsp;=\u0026thinsp;84, 84%) had limited knowledge. In the control group, 90% (n\u0026thinsp;=\u0026thinsp;45), 8% (n\u0026thinsp;=\u0026thinsp;4), and 2% (n\u0026thinsp;=\u0026thinsp;1) of participants had limited, sufficient and excellent knowledge, respectively at baseline. Meanwhile, in the intervention group, 78% (n\u0026thinsp;=\u0026thinsp;39), 16% (n\u0026thinsp;=\u0026thinsp;8), and 6% (n\u0026thinsp;=\u0026thinsp;3) of participants had limited, sufficient, and excellent knowledge, respectively at baseline. After 30 days of intervention, 16% (n\u0026thinsp;=\u0026thinsp;8) of participants had excellent knowledge, and 36% (n\u0026thinsp;=\u0026thinsp;18) had sufficient knowledge of MetS. Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e show the individual scores and knowledge levels of MetS for the participants.\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\u003eKnowledge score of the control and intervention group participants at pre- and post-intervention (n\u0026thinsp;=\u0026thinsp;100)\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\u003eKnowledge level of MetS (Score)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTotal score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003ePre-intervention (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003ePost-intervention (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"14\" rowspan=\"15\"\u003e\u003cp\u003e\u003cb\u003eLimited Knowledge (0\u0026ndash;14)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 (12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 (18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e10 (10%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2 (2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4 (4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2 (2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9 (9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6 (12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e13 (13%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e10 (10%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5 (5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7 (7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eSufficient Knowledge\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(15\u0026ndash;19)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e16\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5 (5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e18\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7 (14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9 (9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eExcellent Knowledge (20\u0026ndash;22)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4 (4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e21\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2 (2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3 (3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\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\u003eLevel of knowledge of metabolic syndrome among the participants (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eKnowledge level of MetS (Score)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLimited Knowledge (0\u0026ndash;14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45 (90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (78%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24 (48)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSufficient Knowledge (15\u0026ndash;19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 (36%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcellent Knowledge (20\u0026ndash;22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (16%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eInferential statistics were used to compare the effectiveness of the intervention and the differences between the groups pre- and post-intervention. Before running the inferential statistical analysis, the distribution of the numerical data was examined using the Kolmogorov-Smirnov test. It was found that all the numerical data were not normally distributed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Therefore, the Wilcoxon signed-rank test was used to analyze the association between the pre- and post-knowledge of MetS in the intervention group (n\u0026thinsp;=\u0026thinsp;47) (25). The results showed that the educational intervention provided to the patients had a statistically significant change in knowledge among the patients with MetS (Z=-6.5631, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The median (IQR) knowledge score was 13.0 (6.0) points and 17.0 (8.0) points, pre- and post-intervention, respectively.\u003c/p\u003e\u003cp\u003eIn contrast, in the control group, it was observed that due to the absence of an intervention, there were no statistically significant changes in terms of knowledge (Z=-0.462, p\u0026thinsp;=\u0026thinsp;0.367) among the participants in the control group. The association of knowledge of MetS among the control and intervention groups at pre- and post-intervention, as analyzed using the Mann-Whitney U test, showed that there were significant differences in knowledge among these groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).Tables\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e show the results of these analyses.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of pre-and post-intervention knowledge scores within groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eWilcoxon Signed-Rank test\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZ statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre-\u003c/p\u003e\u003cp\u003eintervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePost-\u003c/p\u003e\u003cp\u003eintervention\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntervention group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13.0(6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.0(8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9.5(7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.0(8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.367\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant at the 0.01 level (2-tailed)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of pre-and post-intervention knowledge scores among groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eData collection time\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eMann-Whitney U test\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZ statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntervention group\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9.5(7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.0(6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.0(8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.0(8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.603\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant at the 0.01 level (2-tailed)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eEffectiveness of intervention on the participants\u0026rsquo; attitudes toward MetS\u003c/h2\u003e\u003cp\u003eA positive response rate (PRR) (26) was calculated for each questionnaire item by dividing the total number of NPR by the total number of responses and then multiplying by 100. An overall PRR greater than 50% indicated positive attitudes towards MetS among participants. At baseline, the mean PRR for all 10 items assessing attitude was 38.27%, reflecting overall negative attitudes towards MetS among study participants. In comparison, the intervention group had a baseline mean PRR of 54.8%, while the control group had a mean PRR of 33.2%. Following the educational intervention, the mean PRR in the intervention group increased to 58.53%.\u003c/p\u003e\u003cp\u003eInferential analysis the educational intervention over a month resulted in a statistically significant change in attitude (Z=-2.925, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in the intervention group. Additionally, a statistically significant change in attitude was also noted in the control group after a month (Z=-3.363, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Significant differences in attitudes towards MetS were observed between the control and intervention groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) during pre- and post-intervention. The results of the inferential analysis are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and \u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of pre-and post-intervention attitudes scores within groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eWilcoxon Signed-Rank test\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZ statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre-\u003c/p\u003e\u003cp\u003eintervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePost-\u003c/p\u003e\u003cp\u003eintervention\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntervention group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.0(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35.0(12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.925\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20.5(9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22.8(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant at the 0.01 level (2-tailed)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of pre-and post-intervention attitudes scores among groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eData collection time\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eMann-Whitney U test\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZ statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20.5(9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.0(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.8(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35.0(12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant at the 0.01 level (2-tailed)\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\u003eEffectiveness of intervention on the participants\u0026rsquo; perception of MetS\u003c/h2\u003e\u003cp\u003eThe PRR was calculated for each questionnaire item, and an overall PRR of \u0026gt;\u0026thinsp;50% suggests positive perceptions of MetS among the participants. At baseline, the mean PRR for all 6 items on the perception assessment was 78.32%, showing an overall positive perception toward MetS among all the participants. Both the control group (mean PRR\u0026thinsp;=\u0026thinsp;61.33%) and the intervention group (mean PRR\u0026thinsp;=\u0026thinsp;89.52%) participants had positive perceptions at baseline or pre-intervention. The mean PRR increased to 96.98% in the intervention group after the educational intervention.\u003c/p\u003e\u003cp\u003eAccording to the Wilcoxon signed-rank test, the intervention resulted in a statistically significant change in perception score (Z=-4.693, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) among the patients with MetS. The median (IQR) perception score was 21.0 (5.0) points and 29.0 (6.0) points, pre- and post-intervention, respectively. Compared to the baseline, no statistically significant changes were noted in perceptions of MetS (Z=-1.862, p\u0026thinsp;=\u0026thinsp;0.756) in the control group after a month. Significant differences in perception of MetS were observed between the participants in the control and intervention groups in pre- and post-intervention (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The results of inferential analysis are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of pre-and post-intervention perception scores within groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eWilcoxon Signed-Rank test\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZ statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre-\u003c/p\u003e\u003cp\u003eintervention\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePost-\u003c/p\u003e\u003cp\u003eintervention\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntervention group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.0(5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.0(6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.0(5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.0(5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.756\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant at the 0.01 level (2-tailed)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of pre-and post-intervention perception scores among groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eData collection time\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eMann-Whitney U test\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eZ statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIntervention group (n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.0(5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21.0(5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23.0(5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.0(6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-7.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant at the 0.01 level (2-tailed)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe findings of the current research indicated that MetS is more frequently observed in older women over the age of 50. Global research has consistently identified aging as a major risk factor for the onset of MetS [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29 CR30 CR31\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A higher occurrence of MetS among women has also been documented in regions such as Iran [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Africa [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], Indonesia [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and China [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This trend may be linked to the processes of aging and menopause, which make females more susceptible to developing MetS, with postmenopausal women facing a greater risk[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMost of the participants in this study were employed adults, which might also explain work-related issues such as stress, sedentary lifestyles, and poor nutrition contributing to the development of MetS. The current findings indicated that most patients with MetS were likely to exhibit all conditions of the syndrome. Diabetes and obesity were prevalent among the participants, aligning with earlier studies that highlighted a significant association between these conditions and the diagnosis of MetS among university staff [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In contrast, diabetes was reported as the least common metabolic condition (11.7%) among MetS patients in Hong Kong [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, a significant portion of the patients fell into the high-risk category for cardiovascular diseases (CVDs) based on the Framingham Risk Score (FRS), even while receiving treatment for existing comorbidities. About 95.6% and 74.3% of MetS patients exhibited a notably higher risk for CVDs, particularly within the low-risk group [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Conversely, research conducted in Pakistan indicated a 20.4% higher prevalence of high risk for CVD among newly diagnosed MetS patients who were not undergoing treatment than people on treatment [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The elevated percentage of patients classified as high-risk in this study could be attributed to sociodemographic factors, lifestyle choices, dietary habits, and existing comorbidities. It is crucial to recognize that the outcomes of this study highlight the necessity of conducting CVD risk assessments and providing timely management for individuals with MetS. Moreover, utilizing appropriate cardiovascular risk stratification tools tailored to specific populations may enhance the understanding of CVD risk in patients presenting with MetS[\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe current research indicates that most patients with MetS possess limited knowledge of the condition. This observation aligns with findings from various other global studies [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45 CR46 CR47\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. One study documented a low level of MetS awareness (67.2%) among hospitalized patients with cardiometabolic risk factors (56%) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. A separate investigation in community settings found that knowledge of MetS was also lacking (61%), with 51.9% of participants diagnosed with MetS[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A study conducted in Spain revealed that awareness of cardiovascular disease (CVD) risk amongst MetS patients was insufficient (39.6%) [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. A self-reported survey indicated lower knowledge levels across all aspects of cardiometabolic health [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn contrast to our findings, a different study reported that 66% of MetS patients possessed moderate knowledge regarding lifestyle and cardiovascular risk factors [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Despite a brief introduction to MetS provided in the questionnaire, a significant portion of participants in this research were unaware of the definition of MetS, mirroring results from earlier studies [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Individuals with MetS exhibited a lack of understanding of the recommended targets for cardiometabolic components related to the condition [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. While participants in the current study recognized the necessity of regular clinic visits, they have not acquired sufficient understanding of MetS, including key elements related to managing its components. Most participants were uninformed about the significance of lifestyle modifications, stress management, healthy eating habits, and ongoing health monitoring; a finding consistent with prior research [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This lack of knowledge could stem from inadequate education about MetS within the current healthcare systems.\u003c/p\u003e\u003cp\u003eIn this study, patients displayed negative attitudes toward MetS, although the majority acknowledged the positive effects of regular physical activity on MetS management and the mitigation of complications, which aligns with previous research [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Many working adults with MetS cited their job nature as a factor contributing to their physical inactivity, reflecting conclusions from studies involving female market traders [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and office workers [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], yet they held the belief that physical activity could enhance their cardiometabolic health [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Employers are urged to introduce policies aimed at promoting physical activity among their employees. This initiative could significantly enhance health, decrease absenteeism, and boost productivity. Additionally, the improvement of lipid levels in MetS patients should be prioritized through appropriate dietary choices and regular monitoring, alongside other cardiometabolic indicators, to lower the risk of CVD.\u003c/p\u003e\u003cp\u003eThe negative attitudes among the participants in this study can be linked to insufficient focus on the management of MetS. In this regard, primary care healthcare professionals who frequently encounter patients at the onset of MetS should tackle these negative attitudes. These providers should promote healthy lifestyle practices and direct patients to dietitians when necessary.\u003c/p\u003e\u003cp\u003eMost participants in this study perceived the cardiovascular risks associated with MetS and various lifestyle factors related to it. They also expressed a positive perception of the effects of MetS on quality of life. Patients with MetS were more inclined to have positive views on the complications related to metabolic diseases and complications [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Understanding the condition is crucial for encouraging adherence to treatment plans and lifestyle modifications [\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The present study indicated that MetS patients with positive attitudes towards MetS tend to view the condition more positively; however, the knowledge of MetS is not necessarily aligned with an individual's perceived risk and control over the condition. This study underscores that despite having favourable views and attitudes toward MetS, patients still lack fundamental knowledge regarding it, aligning with findings from other studies [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. We believe these outcomes may stem from inadequate patient education on MetS, resulting in those affected failing to acquire knowledge about modifiable risk factors and healthy lifestyle choices that could mitigate the risk of metabolic complications.\u003c/p\u003e\u003cp\u003eFollowing the intervention, the knowledge, attitudes, and perceptions regarding MetS among participants showed significant improvement relative to their initial levels. Therefore, the findings of this study demonstrate the effectiveness of pharmacist-led educational interventions in enhancing understanding and attitudes towards MetS. Similar results were documented where pharmacist-led educational efforts greatly enhanced medication adherence behaviors among patients with chronic diseases in the intervention group [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In light of the post-pandemic attrition rates of healthcare professionals in medical fields, this study advocates for the integration of telehealth education to achieve notably improved health outcomes for patients with MetS. The digital platform provides enhanced engagement in treatment and patient education in today's environment. There were several limitations present in this study. A convenience sampling technique was used to recruit the study participants, and the study was conducted only in the Palakkad region, so the outcome of the research may not be accurate and may not reflect the entire population of Kerala or India. As the study was conducted using a self-administered questionnaire, there could be a recall bias.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eKnowledge, Attitudes, and Perceptions of MetS are crucial for preventing the development of metabolic complications such as CVDs, cerebrovascular attacks, and organ damage. Patients in this study exhibited limited knowledge and negative attitudes towards MetS. The educational intervention provided to these patients was effective in improving their KAP of MetS. HCPs should be encouraged to engage in patient education, particularly regarding chronic illnesses both the hospital and community levels. The effective use of online or digital-based health education in all healthcare settings is warranted to consistently educate patients with medical illnesses.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this research are included in this submitted article. For any inquiries regarding data access or additional information, please contact the corresponding author at [email protected]. The data are available under Creative Commons Attribution 4.0 International License and can be freely used with proper attribution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work did not receive any funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical approval for this study was received from the Lakshmi Hospital Ethics Committee, Palakkad (Reference number ECR/1231/Inst/KL/2019).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFirst Author wrote the manuscript Second author was the supervisor of this research workBoth authors reviewed the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRen H, Wang J, Gao Y, Yang F, Huang W. 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Patient Prefer Adherence. 2023;17:119\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/PPA.S394201\u003c/span\u003e\u003cspan address=\"10.2147/PPA.S394201\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Metabolic Syndrome, Diabetes, Hypertension, Obesity, Educational Intervention","lastPublishedDoi":"10.21203/rs.3.rs-7923737/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7923737/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eMetabolic syndrome (MetS) is a group of metabolic abnormalities that significantly worsen several medical conditions, making it a major global health concern. Hence, a study was conducted to assess the knowledge, attitudes, and perceptions (KAP) of MetS, estimate cardiovascular risk scores, and provide educational interventions among patients with MetS.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e\u003cp\u003eAn interventional study was conducted among patients aged 18 years and above, diagnosed with MetS, and living in Palakkad, Kerala. A structured, validated questionnaire with 35 items was used to collect data. The intervention was provided face-to-face and online for one month, educating the patients on MetS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMajority of the patients were female (56%), with a mean age of 54.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1 years, and were obese (49%). At baseline, both the control (Median IQR\u0026thinsp;=\u0026thinsp;9.5, p\u0026thinsp;=\u0026thinsp;0.367) and intervention (Median IQR\u0026thinsp;=\u0026thinsp;13.0, p\u0026thinsp;=\u0026thinsp;0.001) group participants exhibited limited knowledge, attitudes, and perceptions toward MetS. Their 10-year cardiovascular risk assessed by Framingham Risk Score (FRS) showed that over half of the study participants in the control group (n\u0026thinsp;=\u0026thinsp;34; 68%) and intervention group (n\u0026thinsp;=\u0026thinsp;32; 64%) were at high risk (FRS\u0026thinsp;\u0026gt;\u0026thinsp;20%). The educational intervention provided to the patients led to a statistically significant change in knowledge (Z=-6.5631, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), attitudes (Z=-2.925, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and perceptions (Z=-4.693, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) among the patients with MetS.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003ePatients in this study exhibited limited knowledge and negative attitudes towards MetS. The educational intervention provided to these patients was effective in improving KAP; hence, patient education should be encouraged at both hospital and community levels.\u003c/p\u003e","manuscriptTitle":"Effectiveness of Educational Interventions in Improving the Knowledge, Attitudes, and Perceptions Among Patients With Metabolic Syndrome at a Tertiary Care Hospital Setting in Palakkad District, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-12 11:30:58","doi":"10.21203/rs.3.rs-7923737/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-21T16:49:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-17T08:17:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T06:36:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245748176214896584083468824930341073891","date":"2025-11-12T06:17:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26992647436179245235585718292092136935","date":"2025-11-10T04:55:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171309906831142324510396200382436565292","date":"2025-11-09T10:18:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-31T12:57:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-31T12:51:02+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-30T07:09:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-28T15:31:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2025-10-28T15:08:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"44a4447d-44d2-4ef1-9b30-631a82e7c35b","owner":[],"postedDate":"November 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:00:17+00:00","versionOfRecord":{"articleIdentity":"rs-7923737","link":"https://doi.org/10.1186/s12982-025-01260-8","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2025-12-18 15:57:23","publishedOnDateReadable":"December 18th, 2025"},"versionCreatedAt":"2025-11-12 11:30:58","video":"","vorDoi":"10.1186/s12982-025-01260-8","vorDoiUrl":"https://doi.org/10.1186/s12982-025-01260-8","workflowStages":[]},"version":"v1","identity":"rs-7923737","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7923737","identity":"rs-7923737","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}