Prevalence of Hypertension and its Associated Factors among Public Vehicle Drivers in Western Nepal: A Population-based Study

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Occupational risk factors interlinked to hypertension are poorly researched in Nepal. The study aimed to measure the prevalence of hypertension and its associated factors among public vehicle drivers. Methods : In this cross-sectional study, we enrolled 358 public vehicle drivers from Pokhara Metropolitan City by visiting randomly selected parking stations and approaching divers during their rest time. Trained examiners measured blood pressure for three times and completed a questionnaire to assess demographic, lifestyle and occupational factors. Blood pressure of 140/90 or more was diagnosed as hypertension. The chi-square test and binary logistic regression were used to identify the risk factors of hypertension. Results : The mean age of respondents was 37.3 ± 8.5 years, and all of them were male. The prevalence of hypertension was 41.9%. Age [adjusted odds ratio (aOR)=1.84], BMI (aOR=0.46), alcohol (aOR 0.44), and medication (aOR=0.05) were found to be significantly associated with hypertension. Conclusion : Nearly half of drivers had hypertension, which was associated with age, being overweight, alcohol and substance use and family history of hypertension. Drivers with these particular risk factors should be targeted for screening and management of hypertension. Drivers High Blood Pressure Hypertension Prevalence Nepal Background Hypertension effects 1.28 billion people globally. 1 Modified risk factors such as poor dietary habits (excessive sodium intake, a diet rich in saturated and trans fats, and insufficient consumption of fruits and vegetables), sedentary lifestyle, tobacco and alcohol use, and overweight or obesity play a role in increasing the risk of hypertension. 2 Despite the significant prevalence of hypertension, knowledge, treatment, and management remain inadequate, especially in low- and middle-income countries (LMICs). 3,4 Studies indicate that a significant number of patients with hypertension are misdiagnosed, and among those who are diagnosed, medication adherence is frequently inadequate. 5 Limited access to healthcare facilities, financial limitations, insufficient awareness of the long-term consequences of unmanaged hypertension, and cultural attitudes inhibit effective hypertension management in these contexts. 6 Moreover, healthcare systems in LMICs face difficulties in executing efficient screening, early detection, and follow-up methods, thereby increasing the illness burden. 7 Strengthening public health initiatives, increasing access to affordable drugs, and encouraging lifestyle changes are critical for addressing these problems and improving hypertension control in limited-resource countries. 8 Among various occupational groups, both short and long (bus) drivers represent a substantial workforce exposed to prolonged sitting, irregular work hours high levels of stress, and environmental factors such as air pollution and traffic-related stressors. 9 The prevalence of hypertension has been observed to vary among different occupational categories; some studies have revealed a frequency of 26%, 21.3%, or 14.8% among hospital staff 10 , while others reported a prevalence of 34.4% and 22.2% among bankers and traffic wardens, respectively. 11 Nepal, following the WHO Global Action Plan, has adopted the goal of achieving a 25% relative decrease in the prevalence of elevated blood pressure by 2025 compared to the levels recorded in 2010, aligning with the global targets for non-communicable diseases (NCDS) control. 12 The etiology of hypertension is influenced by several risk variables, including age, location, genetics, socioeconomic status, ethnicity, diet, and nutrition. Among the important risk factors for hypertension are factors related to our line of work. 13 Similarly, Nepal has made significant steps in the management of chronic diseases with the introduction of WHO-PEN, which is also recognized as an effective intervention program for NCDs 14 that can reduce NCDs-related premature death by 25%. The Multi-Sectoral Action Plan for the Prevention and Control of Non-Communicable Diseases (2014-2020) provided the foundation for the formulation of the PEN Implementation Plan (2016-2020) in Nepal. The integration of NCDS services into Nepal's primary health care (PHC) system was aided by the development of healthcare professionals' capacity in the management of NCDs 15 . Currently, the prevalence of hypertension in Nepal is 24.5%. 16 Gaps in hypertension management and regulation may arise from various factors, including health system-related barriers such as limited access, poor service delivery, and unaffordability. 17 This is the first attempt to concurrently investigate the relationship between lifestyle, anthropometric, and sociodemographic variables and hypertension among public transportation drivers. Early identification of those who are at risk will facilitate prompt intervention and support efforts to avoid cardiovascular disease. This study aimed to ascertain the prevalence of hypertension and its associated factors among drivers of public transportation in Pokhara, Nepal. Methods Study Design, Setting, and Study Population A cross-sectional study was conducted from April to December 2023 in Pokhara Metropolitan of Kaski, situated in central Nepal and serves as the capital of Gandaki Province. It is the second most populous city in Nepal, following Kathmandu, with a population of 599,504 residing in 120,594 houses as of 2021. 18 The study population was drivers aged above 18 years with a government-registered license. A public vehicle driver is primarily responsible for transporting individuals and goods from one location to another using designated vehicles for public transportation, such as buses, taxis, and micro-buses. Sampling Procedures The sampling procedures for our research involved three key steps. First, we identified the total number of registered drivers using data from local public transportation authorities. Second, we employed a lottery method to randomly select parking stations, where drivers were available, to ensure an unbiased selection process. Finally, we used convenience sampling at these selected stations, where data was obtained from drivers who were readily available and willing to participate, gathering anthropometric and demographic data from them. Data Collection Procedures Face-to-face interviews were used to collect data from drivers for sociodemographic, behavioural, and work-related characteristics, and physical measurements. The study tool was adapted from the World Health Organization’s validated STEPS tools version 3.1 19 , which have been validated in Nepali by the Nepal Health Research Council (NHRC). 16 For income, we used the basic level as defined by the Ministry of Labor, The Government of Nepal's Ministry of Employment and Social Security has published a notification through the Nepal Gazette. 20 Anthropometric measurements were carried out using established techniques and calibrated instruments. Blood Pressure Measurement Participants were asked to sit after resting for at least fifteen minutes, and blood pressure was recorded using a digital measuring instrument (Omron-WHO recommended). Five minutes apart, three blood pressure readings were obtained. The study considered the mean of the previous two readings. A systolic blood pressure measurement of no less than 140 mm Hg and a diastolic blood pressure measurement of no less than 90 mm Hg, or antihypertensive medication was considered hypertension. Anthropometric Measurements Weight was measured using a digital scale, and height was measured using a Height Measuring Stadiometer. Waist and hip circumferences were measured using Seca 201 Measuring tape. Body mass index (BMI) is computed by dividing weight in kilograms by height in meters squared. BMI was classified as normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), or obese (≥ 30 kg/m2). 21 Waist circumference (WC) that is specific to males can be defined as normal (<94 cm), overweight (94-101.9 cm), and being obese (≥102 cm), whereas male waist-to-hip ratio (WHR) is classified as normal (<0.90), overweight (0.90-0.99), and obese (≥1.0). 22 Waist and hip circumferences have been measured with Seca 201 Measuring Tape. As all participants were male, participants with waist circumference ≥ 90 centimeters were regarded as having central obesity. 23 Awareness Treatment and Control of HTN Participants who indicated that a physician never informed them of their hypertension were considered conscious of their hypertensive status. Participants who received any form of antihypertensive medication within the prior two weeks were marked as undergoing treatment. 24 Hypertensive participants with an average systolic BP < 140 mm Hg and an average diastolic BP < 90 mm Hg were considered to be under control. 25 Data Collection and Measurements The data collection tool was developed after an extensive review of related literature and prepared under continuous and close guidance and supervision of the academic supervisor. Reliability was ensured after the pretesting of the tools in a homogenous area. Tools were prepared in both English and Nepali language. A validated and WHO-recommended standard tool was used to assess the prevalence of hypertension and associated factors. The data entry format was prepared by REDCap software for entering the collected data in a precise manner. A pre-test was conducted among 20 drivers at the Dhulegauda parking station to check the quality of the tool and little modification was done. Moreover, software handling and errors were checked before the data collection, and the questionnaire was checked before deploying the form on REDCap. The dependent variable for this study, hypertension had a yes/no dichotomy. If a participant had at least one of the following characteristics or was receiving antihypertensive medication, they were deemed to have hypertension: (SBP ≥ 140 and DBP ≥ 90 mmHg) 26 . The independent variables for this study were age, ethnicity, marital status, degree of education, monthly income, body mass index, waist circumference, waist-height ratio, cigarette smoking, alcohol consumption, physical activity, diet, diabetes status, and family history of HTN, working experience, work hour per day (WHPD), workhour per weak (WHPW), rest break between driving, driving vehicle, Weekly average driving (WAD) and types of road. 27–29 Considering prior academic and professional experiences, WHPD, WAD, and WHPW were assessed by classifying participants into <13 and ≥13 years of experience, 800 km, and ≤48 and >48 hours per week respectively. 27 Analysis The gathered data were checked for consistency and completeness before being entered into REDCap Software. (v5.27.2) and analyzed using IBM SPSS Statistics for Windows, version 20.0 (Armonk, NY: IBM Corp). Descriptive statistics was shown as frequency, and percentage for categorical variables and mean, SD for continuous variables. Then, the chi-square test was applied to test the association between the independent and dependent variables. Finally, binary logistic regression was used to find factors associated with hypertension among drivers. In which variables having a p-value less than 0.25 were moved into multivariable binary logistic regression. Before moving in binary logistic regression, multicollinearity was checked, through variance inflation factor (VIF). 30 A P-value less than 0.05 was considered statistically significant in binary logistic regression. Frequency distributions, means and percentages were calculated as descriptive analysis. A multiple logistic regression analysis was performed with hypertension as the dependent variable and age, sex, ethnicity, smoking, alcohol consumption, physical activity, BMI, central obesity, and positive family history as the independent variables. Those variables with a p-value ≤ 0.05 were considered statistically significant associations. Ethical Approval and Consent of Participants This study received ethical approval from Pokhara University's Institutional Review Committee (020-080/81, 15-09-2023). Similarly, written permission was taken from the health division of Pokhara Metropolitan City. The aim, importance, and methodology of the research were also explained to every participant. Furthermore, they were told that they have the right to withdraw from the activity at any moment and that their identity will remain anonymous while information is captured. The data-gathering procedure then started after written informed consent was received. First-time hypertensive patients were encouraged to consult a doctor during the data collection period. Results Socio-demographic Characteristics A total of 358 were involved in the study ( Table 1 ). The mean age of the participants was 37 years. About two-fifths (39.7%) of the participants were of the age group 36-45 years. More than two-fifths (42.5%) of participants were Janajati. Almost all (92.7%) participants were married. Then, half of the participants had completed a secondary level of education. Almost all (96.6%) of the participants had monthly income as per Nepal Rastra Bank. Furthermore, a family history of hypertension was present in three-fifths (61.7%) of the patients. Nearly one-fifth of the participants (17.0%) were obese. Similarly, more than one in tenth (12.0%) participants had waist circumference categorized as Obese (≥ 102 cm). Also, more than two-fifths (27.7%) of the participants had a waist-to-hip ratio as obese (≥ 1.0). Lifestyle Characteristics More than three-quarters (79.3%) of participants had low (<3000 MET) physical activity. Likewise, nearly two-thirds (65.1%) of the participants did smoking. Among the participants who do smoke, about half (48.5%) of the participants did smoke for longer than seventeen years. Furthermore, more than three-fifths (63.1%) of the participants had alcohol intake. Almost all (98.3%) participants were non-vegetarian. Also, more than three-fifths (63.4%) of the participants had low fruit and vegetable intake (<5 servings). About three-fifths (58.9%) of the participants drive public buses whereas more than half of the participants (55%) had duration of driving for more than thirteen years. Likewise, about three-fifths (57.3%) of the participants had working hours as drivers for more than eight hours. Over a fifth (86.9%) of the participants did rest in between driving. Also, (54.2%) of the participants worked more than forty-eight hours per week and about half of the participants had a weekly average driving of less than 800 km. Prevalence of Hypertension This study found that the prevalence of hypertension among public vehicle drivers was 41.9%, with 64 (18%) being newly diagnosed and 86 (24%) having been previously diagnosed. Additionally, 25 drivers (7%) had never had their blood pressure checked, and half of this group had been identified with hypertension. Furthermore, only 28 drivers (8.7%) were taking the antihypertensive medicine as prescribed, although 37 drivers (11.1%) had prescriptions for it from their doctors. Factors associated with Hypertension Table 2 shows the crude and adjusted odds ratios for factors associated with hypertension. After adjustment, age [adjusted odds ratio (aOR)=1.84, 95%CI 1.13,3.00], BMI (aOR=0.46, 95%CI 0.27,0.76), alcohol (aOR 0.44, 95%CI 0.26, 0.73), and Medication (aOR=0.05, 95%CI 0.01-0.48|aOR 0.05, 95% CI 0.01-0.22). According to this study, people 35 years of age or older had 1.84 times the odds of having hypertension compared to people under that age (aOR: 1.84, 95% CI: 1.13–3.00, p = 0.013). However, among those with more education (≥10 years), the odds decreased to 0.49, suggesting a significant preventative effect (aOR: 0.49, 95% CI: 0.25–0.98, p = 0.044). A BMI of 25 or higher was associated with a lower chance of developing hypertension (aOR: 0.46, 95% CI: 0.27–0.76, p = 0.003), and alcohol consumption was also found to be protective against hypertension, with users showing lower risks (aOR: 0.44, 95% CI: 0.26–0.73, p = 0.002). Medication status, however, indicated a significant association with the illness, although limited physical activity (p = 0.441) and a family history of hypertension (p = 0.168) did not. Discussion We found less than half of drivers had hypertension, which was associated with age, substance use, and positive family history. The prevalence of hypertension was similar to at least one other study in the region, conducted in India (41.3%) 31 . However, this prevalence is above levels typically reported for other professionals in this occupation. Examples include long-distance truck drivers in south-west Nigeria (39.7%), 28 among bus drivers in Ghana (38.7%) 32 , bus drivers in Colombo Sri Lanka(36.7%) 33 , professional drivers in Spain(34.7%) 34 , and bus drivers in India (23.8-34.8%) 27,35 . We found only two studies with a higher prevalence of hypertension, namely, public transport drivers in India (49.9%) 36 and professional drivers in Iran (54.2%) 37 . The observed variances may be attributed to differences in operational definitions, sample sizes, and measurement instruments. The possible explanation for the variation in the prevalence of hypertension may be due to obesity and low physical activity, which could contribute to the increasing prevalence of hypertension. Our data also revealed age as a determinant of hypertension. A similar study conducted in Ethiopia 38 , Nagpur India 27 , Cameroon 39 , and Ghana 32 coincides with the findings of this study age of the driver was a higher risk of hypertension. The risk of cardiovascular diseases, particularly hypertension, increases with age. As people age, their body systems change, including the cardiovascular system, leading to cell degeneration that increases the risk of cardiovascular conditions such as hypertension. 40 These results imply that while addressing the risks of hypertension in occupational groups such as drivers, age is an essential demographic component to observe. Moreover, our study found a significant association between alcohol use and hypertension. While alcohol intake is generally considered a risk factor for hypertension, our findings suggest a protective association(aOR: 0.44,95% CI:0.26,0.73, p=0.002) that is different from those studies conducted in Ethiopia 38 south-west Nigeria 28 and various occupational groups in Nepal 24 . However, our findings suggest a protective association (aOR: 0.44, 95% CI: 0.26–0.73, p = 0.002) that is different from those reported in studies conducted in Ethiopia³⁷, southwestern Nigeria²⁷, and Nepal²³ in other occupational groups. This contrasting result could come from drivers' apprehension to reveal their alcohol consumption to researchers. Additionally, our findings revealed a significant association between hypertension and Body Mass Index (BMI). This aligns with research conducted in India Nagpur 27 in Nigeria 28 in South Africa 41 and truck drivers in Ethiopia 42 . Drivers with a BMI of ≥25 exhibited a higher prevalence of hypertension, highlighting the necessity for workplace interventions aimed at weight management. Encouraging physical activity and healthy food practices may reduce this risk among public vehicle drivers. Alarmingly, our study showed that 71.9% of participants reported low physical activity levels. Previous studies indicate that Ethiopian drivers who engage in regular exercise are less prone to developing hypertension. 38 , reinforcing the need for lifestyle modifications. Furthermore, Higher education (≥10 years) showed a protective impact against hypertension (aOR: 0.49, 95% CI: 0.25–0.98, p = 0.044), indicating that persons with higher educational levels might have enhanced health awareness and access to preventive resources. Medication status was strongly associated with hypertension, with diagnosed but untreated patients having considerably decreased chances (aOR: 0.02, 95% confidence interval: 0.01-0.22, p = 0.001). This may be due to differences in drivers' self-reported hypertension awareness and medication adherence. We recognize two major limitations of our study. First, the study employed convenience sampling, potentially constraining the generalizability of the results to the entire population of public vehicle drivers in Pokhara. This approach may create selection bias, since drivers who were readily accessible and eager to participate may not accurately represent the larger community of drivers. Second, since the research was conducted using a cross-sectional design, we were unable to establish the direction of causality. Nonetheless, it is unlikely that men with hypertension and risk factors for hypertension tend to become drivers. Conclusions Study found less than half of drivers had hypertension, which was associated with age, alcohol and substance use, and family history of hypertension. Drivers with these particular risk factors should be targeted for screening and management of hypertension. The research emphasizes the need to focus on modifiable risk factors smoking, alcohol and substance consumption, obese and duration of working hours per day/week, and duration of service. Abbreviations BP Blood Pressure CVD Cardiovascular Disease DBP Diastolic Blood Pressure ERB Ethical Review Board HTN Hypertension NCDs Non- communicable Diseases OR Odds Ratio PE Physical Exercise PEN Package of Essential Non-communicable Diseases SBP Systolic Blood Pressure SEAR South East Asia Region SPSS Statistical Package for the Social Sciences STEPS STEP wise Surveillance WHO World Health Organization Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Committee of Pokhara University and with authorized by the Health Division of Pokhara Metropolitan City. All study participants were informed of the study's purpose, their right to refuse or withdraw from participation at any time,and the assurance of anonymity and confidentiality of their information. Informed consent in writing was obtained from the study participants. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Consent for publication Not applicable Availability of Data and Materials All necessary data supporting the findings of this study are available from the corresponding author upon reasonable request. Competing of Interests The authors declare that they have no competing interests. Funding We wish to acknowledge the support we received for writing this paper from the University of California, San Francisco’s International Traineeships in AIDS Prevention Studies (ITAPS), U.S. NIMH, R25MH123256. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Authors Contribution NRC contributed to the study design, data collection, data analysis, and drafting of the paper. SRM, TRB, BKS, NRG, and BA each co-author made significant revisions to the manuscript and gave their approval to the finished version. Acknowledgments The authors would like to thank each one of the study participants from the bottom of their hearts. We would especially like to thank Mrs. Manisha and Mrs. Savyata Neupane for their assistance with the data collection. Authors' information (optional) 1 Nutrition Research Project of Kansai Medical University Japan in Annapurna Rural Municipality, Kaski, Nepal 2 Westmead Applied Research Centre, The University of Sydney, Sydney, Australia 3 Nepal One Health Institute, Kathmandu, Nepal 1,4,6 School of Health and Allied Sciences, Faculty of Health Sciences, Pokhara University, Pokhara, Nepal 5 Faculty of Health, Deakin University, Melbourne, Australia References Hypertension [Internet]. [cited 2025 Jan 19]. Available from: https://www.who.int/news-room/fact-sheets/detail/hypertension Al-Jawaldeh A, Abbass MMS. Unhealthy Dietary Habits and Obesity: The Major Risk Factors Beyond Non-Communicable Diseases in the Eastern Mediterranean Region. Front Nutr. 2022;9:817808. Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16:223–37. Schutte AE, Venkateshmurthy NS, Mohan S, Prabhakaran D. Hypertension in Low- and Middle-Income Countries. Circ Res. 2021;128:808–26. 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Tables Table 1 Demographic and Lifestyle-related Characteristics of Public Vehicle Drivers in Pokhara, Nepal Variables No. (%) Age Early adulthood (<35) 147 (41.1) Middle adulthood (≥35) 211 (58.9) Ethnicity Relatively advantage 96 (26.8) Relatively disadvantage 262 (73.2) Years of schooling 17300 346 (96.6) Family history of HTN Yes 137 (38.3) No 221 (61.7) Waist Normal (<94 cm) 237 (66.2) Obese (≥ 94 cm) 121 (33.6) Waist-hip ratio Normal (<0.9) 311 (86.9) Obese (≥ 0.9) 47 (13.1) Body mass index < 25 132 (36.9) ≥ 25 226 (63.1) Physical activity Low (<3000 MET) 284 (79.3) Adequate (≥ 3000 MET) 74 (20.7) Smoking Yes 224 (62.6) No 134 (37.4) Alcohol Yes 226 (63.1) No 132 (36.9) Diet Vegetarian 6 (1.7) Non-vegetarian 352 (98.3) Fruits and vegetable < 5 serving 228 (63.7) ≥ 5 serving 130 (36.3) Type of vehicle Public Bus 211 (58.9) Others 147 (41.1) Duration of driving 8 hours 205 (57.3) Work hours per week < 48 hours 164 (45.8) ≥ 48 hours 194 (54.3) Weekly average driving <800 km 185 (51.7) ≥ 800km 173 (48.5) NRS: Nepalese Rupee. Table 2 The prevalence of Hypertension in subgroups and which Factors were Associated with Hypertension of Public Vehicle Drivers in Pokhara, Nepal Variables Hypertension (%) cOR (95%CI) p-value aOR (95 %CI) p-value Background characteristics Age <35 year 28.6 1 1 ≥35 year 51.2 2.62 (1.67-4.10) <0.001 1.84(1.13-3.00) 0.013 Educational Status <10 years 49.3 1 1 ≥ 10 years 31.5 0.53(0.29-0.98) 0.043 0.49(0.25-0.98) 0.044 Alcohol consumption Yes 46.2 0.43(0.27-0.68) <0.001 0.44(0.26-0.73) 0.002 No 25 1 1 Family history of HTN Yes 51.1 0.54(0.35-0.83) 0.006 0.70(0.43-1.15) 0.168 No 36.2 1 1 Body mass index < 25 29.5 1 1 ≥ 25 49.1 0.43(0.27-0.68) <0.001 0.46(0.27-0.76) 0.003 Physical activity Adequate (≥ 3000 MET) 29.7 1 1 Low (<3000 MET) 45.1 0.54(0.10-2.86) 0.477 0.42(0.04-3.76) 0.441 Medication No Diagnosis 44 0.28(0.03-0.24) <0.001 0.05(0.01-0.48) 0.009 Diagnosis but not Treatment 36.5 0.21(0.03-0.15) <0.001 0.02(0.01-0.22) 0.001 On Treatment 96.5 1 1 Additional Declarations No competing interests reported. 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Sydney","correspondingAuthor":false,"prefix":"","firstName":"Shivaraj","middleName":"","lastName":"Mishra","suffix":""},{"id":465147295,"identity":"bee2e741-df27-45e5-b384-bf402af80bda","order_by":2,"name":"Barun Kumar Singh","email":"","orcid":"","institution":"Nepal One Health Institute","correspondingAuthor":false,"prefix":"","firstName":"Barun","middleName":"Kumar","lastName":"Singh","suffix":""},{"id":465147296,"identity":"9745250d-1a57-4be0-a6bb-0549dc4f09a4","order_by":3,"name":"Tulsiram Bhandari","email":"","orcid":"","institution":"Pokhara University","correspondingAuthor":false,"prefix":"","firstName":"Tulsiram","middleName":"","lastName":"Bhandari","suffix":""},{"id":465147297,"identity":"3732ca8f-88e8-4d2f-bf96-5ec1c13d7093","order_by":4,"name":"Baburam Acharya","email":"","orcid":"","institution":"Deakin University","correspondingAuthor":false,"prefix":"","firstName":"Baburam","middleName":"","lastName":"Acharya","suffix":""},{"id":465147298,"identity":"6ec8f1a6-6edd-4fd0-935e-3122ccafdf11","order_by":5,"name":"Nand Ram Gahatraj","email":"","orcid":"","institution":"Pokhara University","correspondingAuthor":false,"prefix":"","firstName":"Nand","middleName":"Ram","lastName":"Gahatraj","suffix":""}],"badges":[],"createdAt":"2025-03-26 09:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6310909/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6310909/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97707905,"identity":"6133f049-599e-4884-8478-a6c08e96a150","added_by":"auto","created_at":"2025-12-08 13:09:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1048456,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6310909/v1/d697c497-8af1-4878-9fe3-f229bb807551.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence of Hypertension and its Associated Factors among Public Vehicle Drivers in Western Nepal: A Population-based Study","fulltext":[{"header":"Background","content":"\u003cp\u003eHypertension effects 1.28 billion people globally.\u003csup\u003e1\u003c/sup\u003e Modified risk factors such as poor dietary habits (excessive sodium intake, a diet rich in saturated and trans fats, and insufficient consumption of fruits and vegetables), sedentary lifestyle, tobacco and alcohol use, and overweight or obesity play a role in increasing the risk of hypertension.\u003csup\u003e2\u003c/sup\u003e Despite the significant prevalence of hypertension, knowledge, treatment, and management remain inadequate, especially in low- and middle-income countries (LMICs).\u003csup\u003e3,4\u003c/sup\u003e Studies indicate that a significant number of patients with hypertension are misdiagnosed, and among those who are diagnosed, medication adherence is frequently inadequate.\u003csup\u003e5\u003c/sup\u003e Limited access to healthcare facilities, financial limitations, insufficient awareness of the long-term consequences of unmanaged hypertension, and cultural attitudes inhibit effective hypertension management in these contexts.\u003csup\u003e6\u003c/sup\u003e Moreover, healthcare systems in LMICs face difficulties in executing efficient screening, early detection, and follow-up methods, thereby increasing the illness burden.\u003csup\u003e7\u003c/sup\u003e Strengthening public health initiatives, increasing access to affordable drugs, and encouraging lifestyle changes are critical for addressing these problems and improving hypertension control in limited-resource countries.\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Among various occupational groups, both short and long (bus) drivers represent a substantial workforce exposed to prolonged sitting, irregular work hours high levels of stress, and environmental factors such as air pollution and traffic-related stressors.\u003csup\u003e9\u003c/sup\u003e The prevalence of hypertension has been observed to vary among different occupational categories; some studies have revealed a frequency of 26%, 21.3%, or 14.8% among hospital staff\u003csup\u003e10\u003c/sup\u003e, while others reported a prevalence of 34.4% and 22.2% among bankers and traffic wardens, respectively.\u003csup\u003e11\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNepal, following the WHO Global Action Plan, has adopted the goal of achieving a 25% relative decrease in the prevalence of elevated blood pressure by 2025 compared to the levels recorded in 2010, aligning with the global targets for non-communicable diseases (NCDS) control.\u003csup\u003e12\u003c/sup\u003e The etiology of hypertension is influenced by several risk variables, including age, location, genetics, socioeconomic status, ethnicity, diet, and nutrition. Among the important risk factors for hypertension are factors related to our line of work.\u003csup\u003e13\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, Nepal has made significant steps in the management of chronic diseases with the introduction of WHO-PEN, which is also recognized as an effective intervention program for NCDs\u003csup\u003e14\u003c/sup\u003e that can reduce NCDs-related premature death by 25%. The Multi-Sectoral Action Plan for the Prevention and Control of Non-Communicable Diseases (2014-2020) provided the foundation for the formulation of the PEN Implementation Plan (2016-2020) in Nepal. The integration of NCDS services into Nepal\u0026apos;s primary health care (PHC) system was aided by the development of healthcare professionals\u0026apos; capacity in the management of NCDs\u003csup\u003e15\u003c/sup\u003e. Currently, the prevalence of hypertension in Nepal is 24.5%.\u003csup\u003e16\u003c/sup\u003e Gaps in hypertension management and regulation \u0026nbsp;may arise from various factors, including health system-related barriers such as limited access, poor service delivery, and unaffordability.\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThis is the first attempt to concurrently investigate the relationship between lifestyle, anthropometric, and sociodemographic variables and hypertension among public transportation drivers. Early identification of those who are at risk will facilitate prompt intervention and support efforts to avoid cardiovascular disease. This study aimed to ascertain the prevalence of hypertension and its associated factors among drivers of public transportation in Pokhara, Nepal.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design, Setting, and Study Population \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted from April to December 2023 in Pokhara Metropolitan of Kaski, situated in central Nepal and serves as the capital of Gandaki Province. It is the second most populous city in Nepal, following Kathmandu, with a population of 599,504 residing in 120,594 houses as of 2021.\u003csup\u003e18\u003c/sup\u003e The study population was drivers aged above 18 years with a government-registered license. A public vehicle driver is primarily responsible for transporting individuals and goods from one location to another using designated vehicles for public transportation, such as buses, taxis, and micro-buses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling Procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sampling procedures for our research involved three key steps. First, we identified the total number of registered drivers using data from local public transportation authorities. Second, we employed a lottery method to randomly select parking stations, where drivers were available, to ensure an unbiased selection process. Finally, we used convenience sampling at these selected stations, where data was obtained from drivers who were readily available and willing to participate, gathering anthropometric and demographic data from them.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection Procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFace-to-face interviews were used to collect data from drivers for sociodemographic, behavioural, and work-related characteristics, and physical measurements. The study tool was adapted from the World Health Organization\u0026rsquo;s validated STEPS tools version 3.1\u003csup\u003e19\u003c/sup\u003e, which have been validated in Nepali by the Nepal Health Research Council (NHRC).\u003csup\u003e16\u003c/sup\u003e For income, we used the basic level as defined by the Ministry of Labor, The Government of Nepal\u0026apos;s Ministry of Employment and Social Security has published a notification through the Nepal Gazette.\u003csup\u003e20\u003c/sup\u003e Anthropometric measurements were carried out using established techniques and calibrated instruments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood Pressure Measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were asked to sit after resting for at least fifteen minutes, and blood pressure was recorded using a digital measuring instrument (Omron-WHO recommended). Five minutes apart, three blood pressure readings were obtained. The study considered the mean of the previous two readings. A systolic blood pressure measurement of no less than 140 mm Hg and a diastolic blood pressure measurement of no less than 90 mm Hg, or\u0026nbsp;antihypertensive medication was considered hypertension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnthropometric Measurements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWeight was measured using a digital scale, and height was measured using a Height Measuring Stadiometer. Waist and hip circumferences were measured using Seca 201 Measuring tape. Body mass index (BMI) is computed by dividing weight in kilograms by height in meters squared. BMI was classified as normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), or obese (\u0026ge; 30 kg/m2).\u003csup\u003e21\u003c/sup\u003e Waist circumference (WC) that is specific to males\u0026nbsp;can be defined as normal (\u0026lt;94 cm), overweight (94-101.9 cm), and being obese (\u0026ge;102 cm), whereas male waist-to-hip ratio (WHR) is classified as normal (\u0026lt;0.90), overweight (0.90-0.99), and obese (\u0026ge;1.0).\u0026nbsp;\u003csup\u003e22\u003c/sup\u003e Waist and hip circumferences have been measured with Seca 201 Measuring Tape. As all\u0026nbsp;participants were male, participants with waist circumference \u0026ge; 90 centimeters were regarded as having central obesity.\u003csup\u003e23\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAwareness Treatment and Control of HTN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants who indicated that a physician never informed them of their hypertension were considered conscious of their hypertensive status. Participants who received any form of antihypertensive medication within the prior two weeks were marked as undergoing treatment.\u003csup\u003e24\u003c/sup\u003e Hypertensive participants with an average systolic BP \u0026lt; 140 mm Hg and an average diastolic BP \u0026lt; 90 mm Hg were considered to be under control.\u003csup\u003e25\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection and Measurements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collection tool was developed after an extensive review of related literature and prepared under continuous and close guidance and supervision of the academic supervisor. Reliability was ensured after the pretesting of the tools in a homogenous area. Tools were prepared in both English and Nepali language. A validated and WHO-recommended standard tool was used to assess the prevalence of hypertension and associated factors. The data entry format was prepared by REDCap software for entering the collected data in a precise manner. A pre-test was conducted among 20 drivers at the Dhulegauda parking station to check the quality of the tool and little modification was done. Moreover, software handling and errors were checked before the data collection, and the questionnaire was checked before deploying the form on REDCap.\u003c/p\u003e\n\u003cp\u003eThe dependent variable for this study, hypertension had a yes/no dichotomy. If a participant had at least one of the following characteristics or was receiving antihypertensive medication, they were deemed to have hypertension: (SBP \u0026ge; 140 and DBP \u0026ge; 90 mmHg)\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe independent variables for this study were age, ethnicity, marital status, degree of education, monthly income, body mass index, waist circumference, waist-height ratio, cigarette smoking, alcohol consumption, physical activity, diet, diabetes status, and family history of HTN, working experience, work hour per day (WHPD), workhour per weak (WHPW), rest break between driving, driving vehicle, Weekly average driving (WAD) and types of road.\u003csup\u003e27\u0026ndash;29\u003c/sup\u003e Considering prior academic and professional experiences, WHPD, WAD, and WHPW were assessed by classifying participants into \u0026lt;13 and \u0026ge;13 \u0026nbsp;years of experience, \u0026lt;8 and \u0026nbsp;\u0026ge;8 hours per day, \u0026nbsp;\u0026le;800 km and \u0026gt;800 km, and \u0026le;48 and \u0026gt;48 hours per week respectively.\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gathered data were\u0026nbsp;checked for consistency and completeness before being entered into REDCap Software. (v5.27.2) and analyzed using IBM SPSS Statistics for Windows, version 20.0 (Armonk, NY: IBM Corp). Descriptive statistics was shown as frequency, and percentage for categorical variables and mean, SD for continuous variables. Then, the chi-square test was applied to test the association between the independent and dependent variables. Finally, binary logistic regression was used to find factors associated with hypertension among drivers. In which variables having a p-value less than 0.25 were moved into multivariable binary logistic regression. Before moving in binary logistic regression, multicollinearity was checked, through variance inflation factor (VIF).\u003csup\u003e30\u003c/sup\u003e A P-value less than 0.05 was considered statistically significant in binary logistic regression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrequency distributions, means and percentages were calculated as descriptive analysis. A multiple logistic regression analysis was performed with hypertension as the dependent variable and age, sex, ethnicity, smoking, alcohol consumption, physical activity, BMI, central obesity, and positive family history as the independent variables. Those variables with a p-value \u0026le; 0.05 were considered statistically significant associations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent of Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received ethical approval from Pokhara University\u0026apos;s Institutional Review Committee (020-080/81, 15-09-2023). Similarly, written permission was taken from the health division of Pokhara Metropolitan City. The aim, importance, and methodology of the research were also explained to every participant. Furthermore, they were told that they have the right to withdraw from the activity at any moment and that their identity will remain anonymous while information is captured. The data-gathering procedure then started after written informed consent was received. First-time hypertensive patients were encouraged to consult a doctor during the data collection period.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSocio-demographic Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 358 were involved in the study (\u003cstrong\u003eTable 1\u003c/strong\u003e). The mean age of the participants was 37 years. About two-fifths (39.7%) of the participants were of the age group 36-45 years. More than two-fifths (42.5%) of participants were Janajati. Almost all (92.7%) participants were married. Then, half of the participants had completed a secondary level of education. Almost all (96.6%) of the participants had monthly income as per Nepal Rastra Bank. Furthermore, a family history of hypertension was present in three-fifths (61.7%) of the patients. Nearly one-fifth of the participants (17.0%) were obese. Similarly, more than one in tenth (12.0%) participants had waist circumference categorized as Obese (\u0026ge; 102 cm). Also, more than two-fifths (27.7%) of the participants had a waist-to-hip ratio as obese (\u0026ge; 1.0).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLifestyle Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMore than three-quarters (79.3%) of participants had low (\u0026lt;3000 MET) physical activity. Likewise, nearly two-thirds (65.1%) of the participants did smoking. Among the participants who do smoke, about half (48.5%) of the participants did smoke for longer than seventeen years. Furthermore, more than three-fifths (63.1%) of the participants had alcohol intake. Almost all (98.3%) participants were non-vegetarian. Also, more than three-fifths (63.4%) of the participants had low fruit and vegetable intake (\u0026lt;5 servings). About three-fifths (58.9%) of the participants drive public buses whereas more than half of the participants (55%) had duration of driving for more than thirteen years. Likewise, about three-fifths (57.3%) of the participants had working hours as drivers for more than eight hours. Over a fifth (86.9%) of the participants did rest in between driving. Also, (54.2%) of the participants worked more than forty-eight hours per week and about half of the participants had a weekly average driving of less than 800 km.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of Hypertension\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study found that the prevalence of hypertension among public vehicle drivers was 41.9%, with 64 (18%) being newly diagnosed and 86 (24%) having been previously diagnosed. Additionally, 25 drivers (7%) had never had their blood pressure checked, and half of this group had been identified with hypertension. Furthermore, only 28 drivers\u0026nbsp;(8.7%) were taking the antihypertensive medicine as prescribed, although 37 drivers\u0026nbsp;(11.1%) had prescriptions for it from their doctors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with Hypertension\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e shows the crude and adjusted odds ratios for factors associated with hypertension. After adjustment, age [adjusted odds ratio (aOR)=1.84, 95%CI 1.13,3.00], BMI (aOR=0.46, 95%CI 0.27,0.76), alcohol (aOR 0.44, 95%CI 0.26, 0.73), and Medication (aOR=0.05, 95%CI 0.01-0.48|aOR 0.05, 95% CI 0.01-0.22).\u003c/p\u003e\n\u003cp\u003eAccording to this study, people 35 years of age or older had 1.84 times the odds of having hypertension compared to people under that age (aOR: 1.84, 95% CI: 1.13\u0026ndash;3.00, p = 0.013). However, among those with more education (\u0026ge;10 years), the odds decreased to 0.49, suggesting a significant preventative effect (aOR: 0.49, 95% CI: 0.25\u0026ndash;0.98, p = 0.044). A BMI of 25 or higher was associated with a lower chance of developing hypertension (aOR: 0.46, 95% CI: 0.27\u0026ndash;0.76, p = 0.003), and alcohol consumption was also found to be protective against hypertension, with users showing lower risks (aOR: 0.44, 95% CI: 0.26\u0026ndash;0.73, p = 0.002). Medication status, however, indicated a significant association with the illness, although limited physical activity (p = 0.441) and a family history of hypertension (p = 0.168) did not.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe found less than half of drivers had hypertension, which was associated with age, substance use, and positive family history. The prevalence of hypertension was similar to at least one other study in the region, conducted in India (41.3%)\u003csup\u003e31\u003c/sup\u003e.\u0026nbsp;However, this prevalence is above levels typically reported for other\u0026nbsp;professionals in this occupation. Examples include long-distance truck drivers in south-west Nigeria (39.7%),\u003csup\u003e28\u003c/sup\u003e among bus drivers in Ghana (38.7%)\u003csup\u003e32\u003c/sup\u003e, bus drivers in Colombo Sri Lanka(36.7%)\u003csup\u003e33\u003c/sup\u003e, professional drivers in Spain(34.7%)\u003csup\u003e34\u003c/sup\u003e, and bus drivers in India (23.8-34.8%)\u003csup\u003e27,35\u003c/sup\u003e.\u0026nbsp;We found only two studies with a higher prevalence of hypertension, namely, public transport drivers in India\u0026nbsp;(49.9%)\u003csup\u003e36\u003c/sup\u003e and professional drivers in Iran (54.2%)\u003csup\u003e37\u003c/sup\u003e.\u0026nbsp;The observed variances may be attributed to differences in operational definitions, sample sizes, and measurement instruments.\u0026nbsp;The possible explanation for the variation in the prevalence of hypertension may be due to obesity and low physical activity, which could contribute to the increasing prevalence of hypertension.\u003c/p\u003e\n\u003cp\u003eOur data also revealed age as a determinant of hypertension. A similar study conducted in Ethiopia\u003csup\u003e38\u003c/sup\u003e, Nagpur India\u003csup\u003e27\u003c/sup\u003e, Cameroon\u003csup\u003e39\u003c/sup\u003e, and Ghana\u003csup\u003e32\u003c/sup\u003e coincides with the findings of this study age of the driver was a higher risk of hypertension. The risk of cardiovascular diseases, particularly hypertension, increases with age. As people age, their body systems change, including the cardiovascular system, leading to cell degeneration that increases the risk of cardiovascular conditions such as hypertension.\u003csup\u003e40\u003c/sup\u003e These results imply that while addressing the risks of hypertension in occupational groups such as drivers, age is an essential demographic component to observe.\u003c/p\u003e\n\u003cp\u003eMoreover, our study found a significant association between alcohol use and hypertension. While alcohol intake is generally considered a risk factor for hypertension, our findings suggest a protective association(aOR: 0.44,95% CI:0.26,0.73, p=0.002) that is different from those studies conducted in Ethiopia\u003csup\u003e38\u003c/sup\u003e south-west Nigeria\u0026nbsp;\u003csup\u003e28\u003c/sup\u003e and various occupational groups in Nepal\u003csup\u003e24\u003c/sup\u003e.\u0026nbsp;However, our findings suggest a protective association (aOR: 0.44, 95% CI: 0.26\u0026ndash;0.73, p = 0.002) that is different from those reported in studies conducted in Ethiopia\u0026sup3;⁷, southwestern Nigeria\u0026sup2;⁷, and Nepal\u0026sup2;\u0026sup3; in other occupational groups.\u0026nbsp;This contrasting\u0026nbsp;result could come from drivers\u0026apos; apprehension to reveal their alcohol consumption to researchers.\u003c/p\u003e\n\u003cp\u003eAdditionally, our findings revealed a significant association between hypertension and Body Mass Index (BMI). This aligns with research conducted in India Nagpur\u003csup\u003e27\u003c/sup\u003e in Nigeria\u003csup\u003e28\u003c/sup\u003e in South Africa\u003csup\u003e41\u003c/sup\u003e and truck drivers in Ethiopia\u003csup\u003e42\u003c/sup\u003e.\u0026nbsp;Drivers with a BMI of \u0026ge;25 exhibited a higher prevalence of hypertension, highlighting the necessity for workplace interventions aimed at weight management.\u0026nbsp;Encouraging physical activity and healthy food practices may reduce this risk among public vehicle drivers.\u0026nbsp;Alarmingly, our study showed that 71.9% of participants reported low physical activity levels. Previous studies indicate that Ethiopian drivers who engage in regular exercise are\u0026nbsp;less prone to developing hypertension.\u003csup\u003e38\u003c/sup\u003e, reinforcing the need for lifestyle modifications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, Higher education (\u0026ge;10 years) showed a protective impact against hypertension (aOR: 0.49, 95% CI: 0.25\u0026ndash;0.98, p = 0.044), indicating that persons with higher educational levels might have enhanced health awareness and access to preventive resources. Medication status was strongly associated with hypertension, with diagnosed but untreated patients having considerably decreased chances (aOR: 0.02, 95% confidence interval: 0.01-0.22, p = 0.001). This may be due to differences in drivers\u0026apos; self-reported hypertension awareness and medication adherence.\u003c/p\u003e\n\u003cp\u003eWe recognize two major limitations of our study. First, the study employed convenience sampling, potentially constraining the generalizability of the results to the entire population of public vehicle drivers in Pokhara. This approach may create selection bias, since drivers who were readily accessible and eager to participate may not accurately represent the larger community of drivers. Second, since the research was conducted using a cross-sectional design, we were unable to establish the direction of causality. Nonetheless, it is unlikely that men with hypertension and risk factors for hypertension tend to become drivers.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eStudy found less than half of drivers had hypertension, which was associated with age, alcohol and substance use, and family history of hypertension. Drivers with these particular risk factors should be targeted for screening and management of hypertension. The research emphasizes the need to focus on modifiable risk factors smoking, alcohol and substance consumption, obese and duration of working hours per day/week, and duration of service.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\" style=\"margin-right: calc(26%); width: 74%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; BP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Blood\u0026nbsp;Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; CVD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Cardiovascular\u0026nbsp;Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; DBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Diastolic\u0026nbsp;Blood\u0026nbsp;Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; ERB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Ethical Review Board\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; HTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; NCDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Non-\u0026nbsp;communicable\u0026nbsp;Diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Odds\u0026nbsp;Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Physical\u0026nbsp;Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; PEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Package of Essential Non-communicable Diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; SBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Systolic\u0026nbsp;Blood\u0026nbsp;Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; SEAR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; South\u0026nbsp;East\u0026nbsp;Asia\u0026nbsp;Region\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; SPSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; Statistical\u0026nbsp;Package\u0026nbsp;for\u0026nbsp;the\u0026nbsp;Social\u0026nbsp;Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; STEPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; STEP\u0026nbsp;wise\u0026nbsp;Surveillance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.1818%;\"\u003e\n \u003cp\u003e\u0026nbsp; WHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.8182%;\"\u003e\n \u003cp\u003e\u0026nbsp; World Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Committee of Pokhara University and with authorized by the Health Division of Pokhara Metropolitan City. All study participants were informed of the study\u0026apos;s purpose, their right to refuse or withdraw from participation at any time,and the assurance of \u0026nbsp;anonymity and confidentiality of their information. Informed consent in writing was obtained from the study participants. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll necessary data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting of Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe wish to acknowledge the support we received for writing this paper from the University of California, San Francisco\u0026rsquo;s International Traineeships in AIDS Prevention Studies (ITAPS), U.S. NIMH, R25MH123256. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes\u0026nbsp;of\u0026nbsp;Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNRC contributed to the study design, data collection, data analysis, and drafting of the paper. SRM, TRB, BKS, NRG, and BA each co-author made significant revisions to the manuscript and gave their approval to the finished version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank each one of the study participants from the bottom of their hearts. We would especially like to thank Mrs. Manisha and Mrs. Savyata Neupane for their assistance with the data collection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information (optional)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eNutrition Research Project of Kansai Medical University Japan in Annapurna Rural Municipality, Kaski, Nepal\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eWestmead Applied Research Centre, The University of Sydney, Sydney, Australia\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eNepal One Health Institute, Kathmandu, Nepal\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1,4,6\u0026nbsp;\u003c/sup\u003eSchool of Health and Allied Sciences, Faculty of Health Sciences, Pokhara University, Pokhara, Nepal\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003eFaculty of Health, Deakin University, Melbourne, Australia\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHypertension [Internet]. 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BMC Health Serv Res. 2021;21:899. \u003c/li\u003e\n\u003cli\u003eChowdhury EK, Nelson MR, Ernst ME, Margolis KL, Beilin LJ, Johnston CI, et al. Factors Associated With Treatment and Control of Hypertension in a Healthy Elderly Population Free of Cardiovascular Disease: A Cross-sectional Study. Am J Hypertens. 2020;33:350\u0026ndash;61. \u003c/li\u003e\n\u003cli\u003eKanegae H, Oikawa T, Okawara Y, Hoshide S, Kario K. Which blood pressure measurement, systolic or diastolic, better predicts future hypertension in normotensive young adults? J Clin Hypertens. 2017;19:603\u0026ndash;10. \u003c/li\u003e\n\u003cli\u003eBorle AL, Jadhao A. Prevalence And Associated Factors of Hypertension Among Occupational Bus Drivers in Nagpur City, Central India- A Cross Sectional Study. Natl J Community Med. 2015;6:423\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eAmadi CE, Grove TP, Mbakwem AC, Ozoh OB, Kushimo OA, Wood DA, et al. Prevalence of cardiometabolic risk factors among professional male long-distance bus drivers in Lagos, south-west Nigeria: a cross-sectional study. Cardiovasc J Afr. 2018;29:106\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eAdal AB, Kassa RN, Habte MH, Jebesa MG, Ademe S, Tiruneh CT, et al. Undiagnosed hypertension and associated factors among long-distance bus drivers in Addis Ababa terminals, Ethiopia, 2022: A cross-sectional study. PLOS ONE [Internet]. 2024 [cited 2024 Jul 3];19. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10868739/\u003c/li\u003e\n\u003cli\u003eBursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008;3:17. \u003c/li\u003e\n\u003cli\u003eLakshman A, Manikath N, Rahim A, Anilakumari VP. Prevalence and Risk Factors of Hypertension among Male Occupational Bus Drivers in North Kerala, South India: A Cross-Sectional Study. Int Sch Res Not. 2014;2014:318532. \u003c/li\u003e\n\u003cli\u003eAnto EO, Owiredu WKBA, Adua E, Obirikorang C, Fondjo LA, Annani-Akollor ME, et al. Prevalence and lifestyle-related risk factors of obesity and unrecognized hypertension among bus drivers in Ghana. Heliyon. 2020;6:e03147. \u003c/li\u003e\n\u003cli\u003eJayarajah U, Jayakody AJ, Jayaneth JM, Wijeratne S. Prevalence of Hypertension and Its Associated Factors among a Group of Bus Drivers in Colombo, Sri Lanka. Int J Occup Environ Med. 2017;8:58\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eL\u0026oacute;pez-Gonz\u0026aacute;lez \u0026Aacute;A, Albaladejo-Blanco M, Arroyo-Bote S, Ram\u0026iacute;rez-Manent JI, L\u0026oacute;pez-Safont N, Garc\u0026iacute;a-Ruiz E, et al. Cardiovascular risk and associated risk factors in Spanish professional drivers. J Transp Health. 2021;23:101266. \u003c/li\u003e\n\u003cli\u003eJoshi AV, Hungund BR, Katti S, Viveki R. Prevalence of hypertension and its socio demographic and occupational determinants among bus drivers in North Karnataka \u0026ndash; A Cross sectional study. 2013;2. \u003c/li\u003e\n\u003cli\u003eDevarasu U, Jayaraj NP, Sugunadevi G, Kokila K. Hypertension and Lifestyle Determinants in Public Transport Drivers: A Sector-specific Study in Coimbatore, Tamil Nadu. Acta Medica Int. 2024;11:20. \u003c/li\u003e\n\u003cli\u003eEbrahimi H, Shayestefar M, Talebi SS, Christie J, Ebrahimi MH. Prevalence of hypertension and its associated factors among professional drivers: a population-based study. Acta Cardiol. 2023;78:543\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eRike ME, Diress M, Dagnew B, Getnet M, Hasano Kebalo A, Sinamaw D, et al. Hypertension and Its Associated Factors Among Long-Distance Truck Drivers in Ethiopia. Integr Blood Press Control. 2022;67\u0026ndash;79. \u003c/li\u003e\n\u003cli\u003eFokam DK, Bita AIG, Dakenyo NRD, Agbornkwai NA, Negueu AB. Obesity and High Blood Pressure among Professional Long-Distance Drivers in Yaound\u0026eacute;, Cameroon: Cross-Sectional Study. Occup Dis Environ Med. 2022;10:232\u0026ndash;54. \u003c/li\u003e\n\u003cli\u003eDriving to Better Health: Screening for Hypertension and Associated Factors Among Commercial Taxi Drivers in Buffalo City Metropolitan Municipality, South Africa. Open Public Health J. 2017;10:303\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003eAdedokun AO, Ter Goon D, Owolabi EO, Adeniyi OV, Ajayi AI. Driving to better health: screening for hypertension and associated factors among commercial TAXI drivers in buffalo City metropolitan Municipality, South Africa. Open Public Health J. 2017;10. \u003c/li\u003e\n\u003cli\u003eRike ME, Diress M, Dagnew B, Getnet M, Hasano Kebalo A, Sinamaw D, et al. Hypertension and Its Associated Factors Among Long-Distance Truck Drivers in Ethiopia. Integr Blood Press Control. 2022;15:67\u0026ndash;79. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Demographic and Lifestyle-related Characteristics of Public Vehicle Drivers in Pokhara, Nepal\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eEarly adulthood (\u0026lt;35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e147 (41.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eMiddle adulthood (\u0026ge;35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e211 (58.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eRelatively advantage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e96 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eRelatively disadvantage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e262 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears of schooling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026lt;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e209 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026ge; 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e149 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eMarried\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e332 (92.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e26 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome (NRs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026le; 17300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e12 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026gt; 17300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e346 (96.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily history of HTN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e137 (38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e221 (61.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWaist\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eNormal (\u0026lt;94 cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e237 (66.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eObese (\u0026ge; 94 cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e121 (33.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWaist-hip ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eNormal (\u0026lt;0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e311 (86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eObese (\u0026ge; 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e47 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026lt; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e132 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026ge; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e226 (63.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eLow (\u0026lt;3000 MET)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e284 (79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eAdequate (\u0026ge; 3000 MET)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e74 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e224 (62.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e134 (37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e226 (63.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e132 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eVegetarian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e6 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eNon-vegetarian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e352 (98.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFruits and vegetable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026lt; 5 serving\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e228 (63.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026ge; 5 serving\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e130 (36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of vehicle\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003ePublic Bus\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e211 (58.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003eOthers\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e147 (41.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of driving\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026lt; 14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e172 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026ge; 14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e186 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking hours per day\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026le; 8 hours\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e153 (42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026gt; 8 hours\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e205 (57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWork hours per week\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026lt; 48 hours\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e164 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026ge; 48 hours\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e194 (54.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeekly average driving\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026lt;800 km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e185 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5859%;\"\u003e\n \u003cp\u003e\u0026ge; 800km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4141%;\"\u003e\n \u003cp\u003e173 (48.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNRS: Nepalese Rupee.\u003c/p\u003e\n\u003cp\u003eTable 2 The prevalence of Hypertension in subgroups and which Factors were Associated with Hypertension of Public Vehicle Drivers in Pokhara, Nepal\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"109%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecOR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR (95 %CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eBackground characteristics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026lt;35 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026ge;35 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e51.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e2.62 (1.67-4.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.84(1.13-3.00)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026lt;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e49.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026ge; 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e31.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.53(0.29-0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.49(0.25-0.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e46.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.43(0.27-0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.44(0.26-0.73)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily history of HTN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e51.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.54(0.35-0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.70(0.43-1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026lt; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e29.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026ge; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.43(0.27-0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.46(0.27-0.76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eAdequate (\u0026ge; 3000 MET)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eLow (\u0026lt;3000 MET)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e45.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.54(0.10-2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.42(0.04-3.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eNo Diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.28(0.03-0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.05(0.01-0.48)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eDiagnosis but not Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e36.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.21(0.03-0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02(0.01-0.22)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eOn Treatment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e96.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Drivers, High Blood Pressure, Hypertension, Prevalence, Nepal","lastPublishedDoi":"10.21203/rs.3.rs-6310909/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6310909/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: Hypertension presents a major global health problem, impacting persons across all ages, backgrounds, and lifestyles. Occupational risk factors interlinked to hypertension are poorly researched in Nepal. The study aimed to measure the prevalence of hypertension and its associated factors among public vehicle drivers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In this cross-sectional study, we enrolled 358 public vehicle drivers from Pokhara Metropolitan City by visiting randomly selected parking stations and approaching divers during their rest time. Trained examiners measured blood pressure for three times and completed a questionnaire to assess demographic, lifestyle and occupational factors. Blood pressure of 140/90 or more was diagnosed as hypertension. The chi-square test and binary logistic regression were used to identify the risk factors of hypertension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The mean age of respondents was 37.3 ± 8.5 years, and all of them were male. The prevalence of hypertension was 41.9%. Age [adjusted odds ratio (aOR)=1.84], BMI (aOR=0.46), alcohol (aOR 0.44), and medication (aOR=0.05) were found to be significantly associated with hypertension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: \u0026nbsp;Nearly half of drivers had hypertension, which was associated with age, being overweight, alcohol and substance use and family history of hypertension. Drivers with these particular risk factors should be targeted for screening and management of hypertension.\u003c/p\u003e","manuscriptTitle":"Prevalence of Hypertension and its Associated Factors among Public Vehicle Drivers in Western Nepal: A Population-based Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 03:21:25","doi":"10.21203/rs.3.rs-6310909/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f35d95ee-6e07-4bd2-b9f3-19573dd5522a","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T13:09:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-09 03:21:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6310909","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6310909","identity":"rs-6310909","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}