An Evaluation of the Risk Factors Associated with Hypertension in the Scheduled Caste Population of Mumbai, India: A Cross-Sectional Study

An Evaluation of the Risk Factors Associated with Hypertension in the Scheduled Caste Population of Mumbai, India: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An Evaluation of the Risk Factors Associated with Hypertension in the Scheduled Caste Population of Mumbai, India: A Cross-Sectional Study Saylee Deshmukh, Laxman Bhurke, Jayesh Adavade, Parul Gupta, Sunita Mata, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6102020/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Hypertension is a major health issue worldwide, with an increasing incidence in developing nations. This research examines the prevalence and contributing factors of hypertension in the Scheduled Caste community in Mumbai, India, considering the effects of urbanization and lifestyle modifications. Objective To determine the prevalence of hypertension and assess the association of various demographic, lifestyle, and dietary factors with hypertension in the Scheduled Caste community in Mumbai, India. Methods A cross-sectional study was carried out during the years 2021–2022 in five regions of Mumbai, with substantial Scheduled Caste population. A total of 4,806 participants above 18 years of age were selected through purposive sampling. Data collection involved interviews and measurements of blood pressure and anthropometric data. The study used chi-square tests and multivariate logistic regression analysis to identify significant predictors of hypertension. Results The study found that 39.5% of participants had hypertension. Significant risk factors for hypertension included age (≥ 35 years), male gender, higher BMI (≥ 25), addiction (smoking, alcohol, pan masala/gutka), and a sedentary lifestyle. Conversely, high consumption of leafy vegetables was associated with a lower prevalence of hypertension. No significant associations were found between hypertension and fruit consumption and diet type (vegetarian vs. non-vegetarian). Conclusions Hypertension is prevalent in the Scheduled Caste population in Mumbai, driven by modifiable risk factors such as BMI, addiction, and physical activity. The findings emphasize the need for targeted public health interventions to address these risk factors and reduce the burden of hypertension in this population. Future research is needed with larger and more diverse populations to further explore these associations. Hypertension Scheduled Caste Mumbai Non-communicable diseases Risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Non-communicable diseases (NCDs) are a major global health concern, affecting both developed and developing countries. Research has shown that NCDs and their associated risk factors are prevalent in many regions, including low- and middle-income countries, where they account for a significant proportion of mortality rates. This trend is expected to continue in the future. 1 Urban residents in India tend to exhibit a substantial number of NCD risk factors, including obesity and elevated blood sugar levels, whereas rural East India has experienced a significant increase in the prevalence of mental health issues among individuals with NCDs. 2 , 3 Urban areas in Sudan exhibit a significant prevalence of non-communicable diseases (NCDs), with hypertension being the most frequently observed condition. 4 Contradictions or intriguing facts arise when considering the socioeconomic dimensions of Non-Communicable Disease (NCD) prevalence. For instance, tobacco use is more prevalent among lower socioeconomic classes, whereas obesity is more common among higher socioeconomic classes in India. 5 Hypertension is a prevalent health issue in India, with differing rates across regions and populations, as indicated by various studies. According to the 2019–2021 National Family Health Survey (NFHS-5), the prevalence of hypertension was 24% among men and 21% among women, an increase from the previous round (2015–16), where it was 19% and 17%, respectively. The survey also found that among the tribal population, the prevalence was 34.0% among men and 28.3% among women, and this has been attributed to lifestyle changes and acculturation. 6 , 7 The occurrence of hypertension in Scheduled Caste communities varies based on regional and study-specific factors. A study conducted in selected villages in West Bengal, India, found that the prevalence of hypertension among the Scheduled Caste population was 17.93%. This study also revealed a noteworthy relationship between hypertension and factors, such as age, BMI, WHR, and salt intake. 8 Scheduled Castes make up a disadvantaged group in Indian society, which may result in a variety of health disparities, such as those related to high blood pressure. 9 The present study was conducted in the scheduled caste community of Mumbai, India under Scheduled Caste Subplan (an initiative of Government of India) to determine the prevalence and risk factors of hypertension, including age, body mass index (BMI), addiction, and unbalanced diet. Methods Study design and setting The present study was a cross-sectional survey in five regions of Mumbai with a significant Scheduled Caste population, including Ambedkar Nagar in Ghatkopar, Sahayadri Nagar & Ashok Nagar in Chembur, Sangharsh Nagar in Andheri, Kohinoor SRA in Kurla, and Kasarwadi in Dadar. The participants were individuals from the Scheduled Caste community residing in these areas and were selected through purposive sampling. The ethical committee of the RRAP Central Ayurveda Research Institute in Mumbai approved the study, and an informed consent was obtained from each participant included in the study. The initiation of the study was authorized following approval from the local authorities in each of the five regions. Sample size calculation A sample size of 4806 was calculated based on a confidence interval of 95%, absolute error (d) of 0.42, and standard deviation (SD) of as15 based on previous studies on hypertension. 10 Study population and inclusion criteria The research encompassed both male and female individuals from scheduled castes aged 18 and above and resided in five selected areas of Mumbai, as mentioned above purposive sampling. Data collection: During the time frame of July 2021 to March 2022, a structured interview schedule was conducted for the recruited individuals on a door-to-door basis. The interview schedule contained important information, such as age, lifestyle, socioeconomic status, occupation, education, diet, addiction, and physical activity. Blood pressure was measured with the participant's right arm in the sitting position using a mercury sphygmomanometer. To ensure accuracy, the instrument's intra- and inter-rater reliability were checked in 25 individuals before use. For the analysis, the average value of the two readings taken at a five-minute interval was used. The study measured the participants' anthropometric data, including weight and height. Criteria and definitions Hypertension, as defined by the JNC VII guidelines, categorizes individuals as hypertensive when their systolic blood pressure (SBP) is equal to or greater than 140 mmHg or their diastolic blood pressure (DBP) is equal to or greater than 90 mmHg. 11 High BMI : As per the WHO guidelines, overweight is defined by a BMI of 23–24.9 Kg/m 2 and obesity is defined as 25 Kg/m 2 and above. High BMI levels included overweight and obesity categories. 12 Addiction: Smoking, alcohol, tobacco, and pan masala/gutka addiction were defined as individuals currently exposed to one or more of these addictions, while non-addicted individuals included those who had never been exposed to any of these addictions. Physical activity: Participants who were primarily engaged in sedentary activities were classified as sedentary, while those who had at least 10 min of moderate to intense activities were considered active. Fruit consumption: Participants who consumed fruits at least three times per week were considered optimum. Consumption of leafy vegetables Participants who consumed leafy vegetables at least three times per week were considered optimum. Statistical analysis: Descriptive statistics were generated using cross-tabulations, and the chi-square test was used to investigate the relationship between categorical variables. Additionally, a multivariate logistic regression analysis was conducted to assess the combined influence of age, BMI, addictions (smoking, alcohol consumption, pan masala/gutka, tobacco), frequency of fruit intake, frequency of leafy vegetables intake and physical activity on hypertension simultaneously. A significance level of 5% was applied to all the statistical tests. The data analysis was performed using SPSS Version 29.0. Results This study involved 4,806 individuals, comprising 2,388 males and 2,418 females. The subjects' ages ranged from 18 to 92 years, with a mean age of 40.92 ± 14.34 years. Specifically, the mean age for males was 40.55 ± 14.45 years, and for females, it was 41.29 ± 14.21 years. A summary of the general characteristics of the study population is presented in Fig. 1 . In this study, 88.2% of the participants were found to be literate. Regarding dietary habits, 212 participants had a vegetarian diet, 117 had optimum fruit intake and 4152 participants had optimum green leafy vegetable consumption. A total of 208 participants engaged in moderate to intense physical activity. With respect to addiction, 1017 had addiction either of smoking, alcohol, pan masala/gutka, and tobacco. 1593 participants had a BMI more than or equal to 25. Figures 2 & 3 show prevalence of hypertension in males and females included in the study whereas Fig. 4 represents stages of Hypertension in the study population. Figure 5 represents observed and expected values for hypertension whereas Table 1 presents the association between hypertension and various factors, including age, addiction status, BMI, physical activity, gender, leafy vegetable consumption, diet type, and fruit consumption. The chi-square test was used to analyze the relationship between these factors and hypertension in the study population. These results offer insight into the significant contributors to hypertension in this population. A strong association (p < 0.05) was observed between hypertension and age, gender, BMI, physical activity, and addiction status. The condition was highly prevalent in individuals aged 35 years and above (χ² = 1408.38), males (χ² = 29.24), those with a BMI of 25 or higher (χ² = 76.43), individuals with a sedentary lifestyle (χ² = 78.96) and addiction (χ² = 380.14). The individuals who consumed sufficient amount of leafy vegetables had a lower incidence of hypertension. Additionally, the study demonstrated a non-significant relationship (p > 0.05) between fruit consumption (χ² = 0.0) and diet type (χ² = 0.0015), whether vegetarian or nonvegetarian. Table 1 Distribution of participants in different categories of risk factors SN Risk factors Chi- Square (χ²) p-value Degree of Freedom 1. Age * 1408.38 0.00 1 2. Addiction * 380.14 0.00 1 3. BMI* 76.43 0.00 1 4. Physical activity * 78.96 0.00 1 5. Gender* 29.24 0.00 1 6. Leafy Vegetable consumption * 15.61 0.00 1 7. Type of diet 0.00 0.97 1 8. Fruit consumption 0.00 1.0 1 Multivariate logistic regression analysis was conducted to examine the contribution of all of the above-mentioned risk factors to hypertension (Table 2 & Fig. 6 ). The coefficient for males was positive (0.46), and the odds ratio was 1.58 (95% CI: 1.37–1.82), indicating that males were approximately 58% more likely to have hypertension than females. The z-value of 6.36 and a significant p-value < 0.05, strongly suggest that gender is a significant predictor of hypertension. Age emerged as a significant predictor of hypertension, with individuals aged ≥ 35 years having a much higher likelihood of hypertension, with a coefficient of 2.58 and an odds ratio of 13.21 (95% CI: 11.03–15.81). This finding is supported by a very high z-value of 28.11 and a p-value of less than 0.0001. The coefficient for having a BMI ≥ 25 was 0.3586, with an odds ratio of 1.43 (95% CI: 1.24–1.65), indicating a 43% increase in the likelihood of hypertension for individuals in this BMI category. A z-value of 4.85 and a significant p-value of (< 0.05) suggest that BMI is also a meaningful predictor of hypertension. The study revealed a positive association between addiction status and hypertension, with coefficient 1.36, an odds ratio of 3.88 (95% CI: 3.75–4.02), with a significant p-value (< 0.05). Less consumption of leafy vegetable consumption and less physical activity were significantly associated with hypertension with the odds ratios of 1.39 and 1.88. Notably, fruit consumption and type of diet did not appear to be a substantial predictor of hypertension in this analysis, with a negative coefficient and non-significant p-value (> 0.05). Table 2 Multivariate Logistic Regression Analysis Risk factors Coefficient Standard Error z-value p-value Odds ratio (OR) 95% CI Lower 95% CI Upper Male * 0.46 0.07 6.36 0.00 1.58 1.37 1.82 Age ≥ 35 * 2.58 0.09 28.11 0.00 13.21 11.03 15.81 BMI ≥ 25 * 0.36 0.07 4.85 0.00 1.43 1.24 1.65 Addicted* 1.36 0.01 74.87 0.00 3.88 3.75 4.02 Optimum fruit intake -0.02 0.19 -0.09 0.93 0.98 0.67 1.44 Less leafy vegetable intake* 0.44 0.07 5.82 0.00 1.39 0.29 0.59 Sedentary* 0.64 0.01 37.96 0.00 1.89 1.83 1.95 Vegetarian -0.04 0.15 -0.28 0.78 0.96 0.72 1.28 Discussion Prevalence of Hypertension: This research demonstrated that a substantial portion of male and female participants, respectively, were impacted by hypertension, a key modifiable risk factor for cardiovascular diseases. Specifically, over 43% of men and 36% of women were affected. This percentage is notably higher than the National Family Health Survey (NFHS-5) conducted in 2019–2020, which reported 24% of men and 21% of women experiencing hypertension. This highlights the considerable significance of this health issue among the Scheduled Caste population in the selected area. Factors associated with Hypertension: This study aimed to investigate the relationship between hypertension and factors such as age, gender, addiction, Body Mass Index (BMI), physical activity, fruit consumption, leafy vegetable consumption, and diet type (vegetarian or non-vegetarian). Significant gender differences have been found to be closely associated with hypertension. This study aligns with prior research, as biological factors such as sex hormones, chromosomal variations, and other protective biological gender differences play a role in women's resistance to hypertension. Additionally, the results of the logistic regression demonstrate that the risk for hypertension was 50% greater in men. 13 , 14 , 15 The Chi-Square test revealed a significant correlation between age and hypertension status. Individuals aged 35 years demonstrated a greater prevalence of hypertension. This result aligns with the well-established concept that the risk of hypertension increases with age owing to factors such as arterial stiffness and the accumulation of risk factors over time. 16 Furthermore, logistic regression analysis demonstrated that the risk was 13 times higher in individuals aged > 35 years. Addiction was significantly associated with hypertension, as evidenced by the results of the chi-square test. This relationship can be attributed to the physiological and psychological consequences of addictive behaviors, such as smoking and substance use, which are known to elevate blood pressure. The development of hypertension due to smoking involves impaired endothelial function, arterial stiffness, inflammation, lipid modification, and alterations in antithrombotic and prothrombotic factors. 17 Smokeless tobacco, in particular, can lead to sodium retention and poor blood pressure control. 18 , 19 , 20 , 21 , 22 Alcohol consumption has also been shown to cause hypertension by stimulating the renin-angiotensin-aldosterone system, increasing cortisol levels, and increasing vascular reactivity owing to higher intracellular calcium levels. Additionally, alcohol consumption can stimulate the endothelium to release vasoconstrictors and cause a loss of relaxation owing to inflammation and oxidative injury of the endothelium. 23 Furthermore, logistic regression analysis indicated that the risk was 2.88 times higher in the addicted population. Implementation of de-addiction program may facilitate reducing hypertension prevalence in the selected area. A significant association was observed between BMI and hypertension. Individuals with a BMI of 25 or higher were more likely to have hypertension, as per the results of the chi-square test, supporting the role of high BMI as a major risk factor for cardiovascular conditions. Excess body weight increases the strain on the heart and blood vessels due to atherosclerosis, leading to elevated blood pressure. 24 The findings of the chi-square analysis demonstrated a substantial association between a sedentary lifestyle and hypertension. It is widely acknowledged that sedentary behavior is a significant risk factor for hypertension due to its association with metabolic syndrome. 25 , 26 , 27 Engaging in physical activity has been shown to lower blood pressure and improve cardiovascular health, making it a vital component of prevention and management strategies for hypertension. 28 Logistic regression suggests that individuals with a sedentary lifestyle have an 80% risk of developing hypertension. Less consumption of leafy vegetable was found as a significant risk factor for hypertension which is consistent with finding of previous studies. 29 Optimum intake of leafy vegetables reduce blood pressure due to high amount of fibers present. 30 Public health campaigns promoting the intake of leafy vegetables could be instrumental in preventing hypertension, particularly in populations at risk. In this study, it was discovered that the optimum consumption of fruits and a vegetarian diet had a negative impact on hypertension. This contradicts the findings of earlier research, 31 , 32 but additional investigation is necessary to determine if other dietary and lifestyle factors may be overshadowing the relationship. Key message: The present study attempted to provide a snapshot of the health status of the scheduled caste population considering their increasing interaction with modernization. Modernization has led to an increase in sedentary lifestyle, BMI among the population, which in turn has resulted in a higher prevalence of hypertension. The gender distribution in the study was well-balanced, which effectively eliminated the potential for selection bias. The comprehensive information gathered on alcohol, smoking, and physical activity provided valuable insights into the associated risks that were linked to the studied health outcomes. The current investigation represents the initial endeavor to assess the risk factors associated with hypertension within the scheduled caste population of Mumbai, India. Future research could expand upon this by conducting larger-scale studies that encompass multiple states within the country. Conclusion The research demonstrates a high prevalence of hypertension among the Scheduled Caste population in Mumbai, India emphasizing hypertension as a significant health concern in this community. Age, gender, BMI, addiction status, and physical activity were identified as key predictors of hypertension. Specifically, older age, male gender, higher BMI, and a sedentary lifestyle were strongly associated with an increased likelihood of hypertension. Moreover, individuals with addictions to substances like tobacco, alcohol, and pan masala/gutka showed a higher risk of developing hypertension. The study found that low consumption of leafy vegetables was a significant risk factor for hypertension, while fruit consumption and vegetarian diet type did not significantly impact hypertension prevalence. The findings suggest the need for targeted public health interventions that focus on modifiable risk factors like addiction cessation, promoting physical activity, and encouraging the consumption of leafy vegetables for reducing the burden of hypertension and improving cardiovascular health in the Scheduled Caste population. The research offers an initial evaluation of hypertension within this specific community and specific region which highlights the importance of conducting more extensive research across multiple states and regions to gain a deeper understanding and address the health disparities associated with hypertension more effectively. Declarations Conflicts of interest: There are no conflicts of interest. Acknowledgement : We are grateful to Director General, Central Council of Research in Ayurvedic Sciences (CCRAS), Ministry of AYUSH, Government of India for the support throughout the study. Ethics approval: The ethical approval has been sought from Institutional Ethics Committee (IEC), CCRAS-CARI, Mumbai. (F-6-94/IEC/Tech/Mumb/2021-22/01) Consent to participate: An informed consent was obtained from each participant included in the study. The initiation of the study was authorized following approval from the local authorities in each of the five regions. Consent for publication: The consent for publication has been sought from CCRAS headquarters, New Delhi, India Availability of data and materials: The data is available with CCRAS headquarters, New Delhi, India Competing interest: There is no competing interest Funding: The current study was sponsored by Central Council of Research in Ayurvedic Sciences (CCRAS), Ministry of AYUSH, Government of India. Author Contributions: SD, LB, DM, SM, GR, NS: wrote and reviewed main manuscript. JA, PG, AM: prepared figures. All authors reviewed the manuscript. References Aloudat, T., Boulle, P., Kravitz, A. S., & Van Tulleken, A. (2019). Chronic non-communicable diseases (pp. 841–864). oxford university. https://doi.org/10.1093/med/9780199565276.003.0046 . Anand, T., Anand, T., Kishore, J., Kishore, J., Garg, A., Garg, A., Ray, P. C., Sharma, U., Sharma, U., Chakraborty, M., Chakraborty, M., & Ingle, G. K. (2014). Prevalence of Risk Factors for Chronic Non-communicable Diseases Using WHO Steps Approach in an Adult Population in Delhi. Journal of Family Medicine and Primary Care , 3 (2), 112. https://doi.org/10.4103/2249-4863.137617 . Rajan, V., Singh, A. K., Patra, S., Patro, B. K., & Behera, P. (2024). Prevalence of common mental disorders and treatment gap among patients with non-communicable diseases in the rural areas of East India. Social Psychiatry and Psychiatric Epidemiology . https://doi.org/10.1007/s00127-024-02618-0 . Omer, S., Elmubarak, M., Mustafaalhamed, M., Elmubarak, M., Adam, A., Younis, A., Mukhtar, Rihab. I., A.Elmubarak, M., T.M.Abdoun, G., & Elsanousi, S. (2023). Prevalence of non-communicable Diseases (NCDs) in an urban area in Sudan and the role of medical students in health promotion of patients with NCDs. International Journal of Scholarly Research in Medicine and Dentistry , 2 (1), 001–007. https://doi.org/10.56781/ijsrmd.2023.2.1.0028 . Anand, T., Anand, T., Kishore, J., Kishore, J., Garg, A., Garg, A., Ray, P. C., Sharma, U., Sharma, U., Chakraborty, M., Chakraborty, M., & Ingle, G. K. (2014). Prevalence of Risk Factors for Chronic Non-communicable Diseases Using WHO Steps Approach in an Adult Population in Delhi. Journal of Family Medicine and Primary Care , 3 (2), 112. https://doi.org/10.4103/2249-4863.137617 . International Institute for Population Sciences, & ORC Macro. MEASURE/DHS+ (Programme). (2000). National family health survey (NFHS-2), India, 1998-99 (Vol. 1). International Institute for Population Sciences, Mumbai, India. Babu, B. V., Raina, S. K., Thomas, N., Masoodi, S. R., Hazarika, C. R., Jebasingh, F. K., Kerketta, A. S., & Basappa, Y. C. (2023). Hypertension Prevalence, Awareness, Treatment, Control and Risk Factors in Tribal Population of India: a Multi-Centric Cross-Sectional Study. Journal of Racial and Ethnic Health Disparities . https://doi.org/10.1007/s40615-023-01817-w Biswas, M., & Manna, C. K. (2011). Prevalence of Hypertension and Sociodemographic Factors within the Scheduled Caste Community of the District Nadia, West Bengal, India. High Blood Pressure & Cardiovascular Prevention , 18 (4), 179–185. https://doi.org/10.2165/11593600-000000000-00000 . Gosal, R. P. S. (1987). Distribution of scheduled caste population in India. Social Science Information , 26 (3), 493–511. https://doi.org/10.1177/053901887026003002 . Kaur P, Sakthivel M, Venkatasamy V, Jogewar P, Gill SS, Kunwar A, Sharma M, Pathni AK, Durgad K, Sahoo SK, Wankhede A, Kumar N, Bharadwaj V, Das B, Chavan T, Khedkar S, Sarode L, Bangar SD, Krishna A, Shivashankar R, Ganeshkumar P, Pragya P, Bhargava B. India Hypertension Control Initiative: Blood Pressure Control Using Drug and DoseSpecific Standard Treatment Protocol at Scale in Punjab and Maharashtra, India, 2022. Global Heart. 2024; 19(1): 30. DOI: https://doi.org/10.5334/gh.1305 . Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo Jr JL, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289(19): 2560–72. WHO/IASO/IOTF. The Asia –Pacific perspective: redefining obesity and its treatment. Melbourne: Health Communication Austrailia; 2000. Cutler JA, Sorlie PD, Wolz M, Thom T, Fields LE, Roccella EJ. Trends in hypertension prevalence, awareness, treatment, and control rates in United States adults between 1988–1994 and 1999–2004. Hypertension. 2008;52(5):818–827 Sandberg K, Ji H. Sex differences in primary hypertension. Biol Sex Differ. 2012;3(1):7. Vitale C, Fini M, Speziale G, Chierchia S. Gender differences in the cardiovascular effects of sex hormones. Fundam Clin Pharmacol. 2010;24(6):675–685. Kim HL. Arterial stiffness and hypertension. Clin Hypertens. 2023 Dec 1;29(1):31. doi: 10.1186/s40885-023-00258-1 . PMID: 38037153; PMCID: PMC10691097. Virdis A, Giannarelli C, Neves MF, Taddei S, Ghiadoni L. Cigarette smoking and hypertension. Curr Pharm Des. 2010;16(23):2518-25. doi: 10.2174/138161210792062920 . PMID: 20550499. Westman EC. Does smokeless tobacco cause hypertension? Southern Medical Journal. 1995 Jul;88(7):716–720. DOI: 10.1097/00007611-199507000-00004 . PMID: 7597474. Singh, P.K.; Dubey, R.; Singh, L.; Singh, N.; Kumar, C.; Kashyap, S.; Subramanian, S.V.; Singh, S. Mixed Effect of Alcohol, Smoking, and Smokeless Tobacco Use on Hypertension among Adult Population in India: A Nationally Representative Cross-Sectional Study. Int. J. Environ. Res. Public Health 2022 , 19 , 3239. https://doi.org/10.3390/ijerph19063239 . Ghosh S, Kumar M. Prevalence and associated risk factors of hypertension among persons aged 15–49 in India: a cross-sectional study. BMJ Open 2019; 9 :e029714. doi: 10.1136/bmjopen-2019-029714 . Lal D, Virk AK, Bhardwaj A, Lal KK, Bora J, Nadda A, et al. (2024) Pestilent relationship between smoking and hypertension or pulse pressure among males over 15 years in India: NFHS-5 Survey. PLoS ONE 19(5): e0294898. https://doi.org/10.1371/journal.pone.0294898 S. Khanal, S.A. Khan, D. Baral, S. Shrestha, N. Baral, M. Lamsal. Oxidant-antioxidant status and assessment of cardiovascular morbidity in Pan Masala containing Tobacco users: a cross-sectional study. BMC Res. Notes.2018(11):727. Husain K, Ansari RA, Ferder L. Alcohol-induced hypertension: Mechanism and prevention. World J Cardiol. 2014 May 26;6(5):245 − 52. doi: 10.4330/wjc.v6.i5.245 . PMID: 24891935; PMCID: PMC4038773. Ledwozyw A, Michalak J, Stepień A, Kadziołka A. The relationship between plasma triglycerides, cholesterol, total lipids and lipid peroxidation products during human atherosclerosis. Clin Chim Acta. 1986;155:275–283. doi: 10.1016/0009-8981(86)90247-0 . Joardar AI, Khaled MFI, Mahabub SME, Singha CK, Atiqul-Haque M. Factors Associated with Hypertension among Urban Dwellers with Sedentary Lifestyle: A Cross-Sectional Study. J Natl Inst Neurosci Bangladesh, 2020;6(2): 129–134. Singh, R. B., Fedacko, J., Pella, D., Macejova, Z., Ghosh, S., De, A. K., … Gupta, A. K. (2011). Prevalence and risk factors for prehypertension and hypertension in five Indian cities. Acta Cardiologica , 66 (1), 29–37. https://doi.org/10.1080/AC.66.1.2064964 Juan José Beunza, Miguel Ángel Martínez-González, Shah Ebrahim, Maira Bes-Rastrollo, Jorge Núñez, José Alfredo Martínez, Álvaro Alonso, Sedentary Behaviors and the Risk of Incident Hypertension: The SUN Cohort, American Journal of Hypertension. 2007;20(11):11561162. Hegde SM, Solomon SD. Influence of Physical Activity on Hypertension and Cardiac Structure and Function. Curr Hypertens Rep. 2015 Oct;17(10):77. doi: 10.1007/s11906-015-0588-3 . PMID: 26277725; PMCID: PMC4624627. O M Akpa, A P Okekunle, et al. Frequent vegetable consumption is inversely associated with hypertension among indigenous Africans, European Journal of Preventive Cardiology . 2022;29(18):2359–2371. Adebawo, O., Salau, B., Ezima, E. et al. Fruits and vegetables moderate lipid cardiovascular risk factor in hypertensive patients. Lipids in Health and Disease .2006;5:14. Madsen, H., Sen, A. & Aune, D. Fruit and vegetable consumption and the risk of hypertension: a systematic review and meta-analysis of prospective studies. Eur J Nutr 62, 1941–1955 (2023). https://doi.org/10.1007/s00394-023-03145-5 . Chuang, Shao-Yuan; Chiu, Tina H.T.; Lee, Chun-Yi; Liu, Ting-Ting; Tsao, Chwen Keng; Hsiung, Chao A.; Chiu, Yen-Feng. Vegetarian diet reduces the risk of hypertension independent of abdominal obesity and inflammation: a prospective study. Journal of Hypertension 34(11):p 2164–2171, November 2016. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6102020","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":423853005,"identity":"9fdc0ece-df94-4029-810f-338fa6857168","order_by":0,"name":"Saylee Deshmukh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDCCA0D8gIFBDsx+QLSWBAYGYzA7gRQtiQ0MEAZhwHf+8DOJhAqb9A3XDj8E2mInp9tAQIvkjTQziYQzabkbbqcZALUkG5sdIKDF4AaDmURi22GglgSQlgOJ2whqOX/8m0Tiv//pBrfTPxCp5UAO0JaGAwkGt3OItEXyRk6xRcKxZMOZt3MKgBqJ8Avf+eMbb3yosZPnu52++cOHCjs5glqAgEUCRCqAVRoQVg4CzB9ApHwDcapHwSgYBaNgBAIAhE9OWVWo7NMAAAAASUVORK5CYII=","orcid":"","institution":"CCRAS-Central Ayurveda Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Saylee","middleName":"","lastName":"Deshmukh","suffix":""},{"id":423853006,"identity":"0e51d80f-956d-4b22-8823-485844f5a1ae","order_by":1,"name":"Laxman Bhurke","email":"","orcid":"","institution":"CCRAS-Central Ayurveda Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Laxman","middleName":"","lastName":"Bhurke","suffix":""},{"id":423853007,"identity":"a0c28464-bf6c-49ac-afe4-a29855cb319b","order_by":2,"name":"Jayesh Adavade","email":"","orcid":"","institution":"CCRAS-Central Ayurveda Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Jayesh","middleName":"","lastName":"Adavade","suffix":""},{"id":423853008,"identity":"64966653-e259-4abf-bb44-cd75df84f2ab","order_by":3,"name":"Parul Gupta","email":"","orcid":"","institution":"CCRAS-Central Ayurveda Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Parul","middleName":"","lastName":"Gupta","suffix":""},{"id":423853009,"identity":"2c6cc563-aae3-41aa-8eb9-b84884a54616","order_by":4,"name":"Sunita Mata","email":"","orcid":"","institution":"Central Council for Research in Ayurvedic Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sunita","middleName":"","lastName":"Mata","suffix":""},{"id":423853010,"identity":"65350275-6b17-4f56-9399-20334d1ace59","order_by":5,"name":"Deepa Makhija","email":"","orcid":"","institution":"Central Council for Research in Ayurvedic Sciences","correspondingAuthor":false,"prefix":"","firstName":"Deepa","middleName":"","lastName":"Makhija","suffix":""},{"id":423853011,"identity":"5dd5a126-4d40-45cf-8af1-00a3e164bbe2","order_by":6,"name":"Aparna Manathottathil","email":"","orcid":"","institution":"Central Council for Research in Ayurvedic Sciences","correspondingAuthor":false,"prefix":"","firstName":"Aparna","middleName":"","lastName":"Manathottathil","suffix":""},{"id":423853012,"identity":"09dcac94-d138-46fe-91fd-30837ac955da","order_by":7,"name":"Govind Reddy","email":"","orcid":"","institution":"CCRAS-Central Ayurveda Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Govind","middleName":"","lastName":"Reddy","suffix":""},{"id":423853013,"identity":"1c6801ef-1aae-4348-afd3-ca16cdf964aa","order_by":8,"name":"Narayanam Shrikant","email":"","orcid":"","institution":"Central Council for Research in Ayurvedic Sciences","correspondingAuthor":false,"prefix":"","firstName":"Narayanam","middleName":"","lastName":"Shrikant","suffix":""}],"badges":[],"createdAt":"2025-02-25 06:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6102020/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6102020/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77909924,"identity":"6d4320ab-745b-4a2f-85a5-54a986d581b1","added_by":"auto","created_at":"2025-03-06 17:38:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7209,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeneral characteristics of the population\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Onlinedrawingimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/88683b17b6fa13bff983ab75.png"},{"id":77909475,"identity":"2429f25f-d209-46da-abbc-1d9bf8e9ce8e","added_by":"auto","created_at":"2025-03-06 17:30:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34922,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Hypertension in males\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/966576cb235c5e658a4a7560.png"},{"id":77909923,"identity":"6b37715c-3b77-430b-958d-b4a604bdd7c3","added_by":"auto","created_at":"2025-03-06 17:38:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35821,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Hypertension in females\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/c286c8847018987ad31aa798.png"},{"id":77909487,"identity":"ad4bb181-3c54-4e63-b5cd-583862430c50","added_by":"auto","created_at":"2025-03-06 17:30:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48521,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStages of Hypertension\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/1e9be84aebf29e89a190ed6e.png"},{"id":77909488,"identity":"db30dfb3-15e9-4449-bd2c-806e67aca3e4","added_by":"auto","created_at":"2025-03-06 17:30:14","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":88812,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eObserved and expected values for HTN\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/352b962c4c0386dd0732b2cb.jpeg"},{"id":77909493,"identity":"8d9e7d7a-a15d-497b-b28d-f13f273d4bf4","added_by":"auto","created_at":"2025-03-06 17:30:14","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":99738,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot of multivariate logistic regression analysis\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/166aefe939db27b1a0e7c56d.jpeg"},{"id":77911129,"identity":"56777ca7-3fa2-4f6a-88f5-047486befa53","added_by":"auto","created_at":"2025-03-06 17:54:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1279234,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6102020/v1/fc58a93b-f98b-4f9c-9e31-fd7774c6caca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Evaluation of the Risk Factors Associated with Hypertension in the Scheduled Caste Population of Mumbai, India: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNon-communicable diseases (NCDs) are a major global health concern, affecting both developed and developing countries. Research has shown that NCDs and their associated risk factors are prevalent in many regions, including low- and middle-income countries, where they account for a significant proportion of mortality rates. This trend is expected to continue in the future.\u003csup\u003e1\u003c/sup\u003e Urban residents in India tend to exhibit a substantial number of NCD risk factors, including obesity and elevated blood sugar levels, whereas rural East India has experienced a significant increase in the prevalence of mental health issues among individuals with NCDs.\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e3\u003c/sup\u003e Urban areas in Sudan exhibit a significant prevalence of non-communicable diseases (NCDs), with hypertension being the most frequently observed condition.\u003csup\u003e4\u003c/sup\u003e Contradictions or intriguing facts arise when considering the socioeconomic dimensions of Non-Communicable Disease (NCD) prevalence. For instance, tobacco use is more prevalent among lower socioeconomic classes, whereas obesity is more common among higher socioeconomic classes in India.\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHypertension is a prevalent health issue in India, with differing rates across regions and populations, as indicated by various studies. According to the 2019\u0026ndash;2021 National Family Health Survey (NFHS-5), the prevalence of hypertension was 24% among men and 21% among women, an increase from the previous round (2015\u0026ndash;16), where it was 19% and 17%, respectively. The survey also found that among the tribal population, the prevalence was 34.0% among men and 28.3% among women, and this has been attributed to lifestyle changes and acculturation.\u003csup\u003e6\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe occurrence of hypertension in Scheduled Caste communities varies based on regional and study-specific factors. A study conducted in selected villages in West Bengal, India, found that the prevalence of hypertension among the Scheduled Caste population was 17.93%. This study also revealed a noteworthy relationship between hypertension and factors, such as age, BMI, WHR, and salt intake.\u003csup\u003e8\u003c/sup\u003e Scheduled Castes make up a disadvantaged group in Indian society, which may result in a variety of health disparities, such as those related to high blood pressure.\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe present study was conducted in the scheduled caste community of Mumbai, India under Scheduled Caste Subplan (an initiative of Government of India) to determine the prevalence and risk factors of hypertension, including age, body mass index (BMI), addiction, and unbalanced diet.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThe present study was a cross-sectional survey in five regions of Mumbai with a significant Scheduled Caste population, including Ambedkar Nagar in Ghatkopar, Sahayadri Nagar \u0026amp; Ashok Nagar in Chembur, Sangharsh Nagar in Andheri, Kohinoor SRA in Kurla, and Kasarwadi in Dadar. The participants were individuals from the Scheduled Caste community residing in these areas and were selected through purposive sampling. The ethical committee of the RRAP Central Ayurveda Research Institute in Mumbai approved the study, and an informed consent was obtained from each participant included in the study. The initiation of the study was authorized following approval from the local authorities in each of the five regions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eA sample size of 4806 was calculated based on a confidence interval of 95%, absolute error (d) of 0.42, and standard deviation (SD) of as15 based on previous studies on hypertension.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eStudy population and inclusion criteria\u003c/h3\u003e\n\u003cp\u003eThe research encompassed both male and female individuals from scheduled castes aged 18 and above and resided in five selected areas of Mumbai, as mentioned above purposive sampling.\u003c/p\u003e\n\u003ch3\u003eData collection:\u003c/h3\u003e\n\u003cp\u003eDuring the time frame of July 2021 to March 2022, a structured interview schedule was conducted for the recruited individuals on a door-to-door basis. The interview schedule contained important information, such as age, lifestyle, socioeconomic status, occupation, education, diet, addiction, and physical activity. Blood pressure was measured with the participant's right arm in the sitting position using a mercury sphygmomanometer. To ensure accuracy, the instrument's intra- and inter-rater reliability were checked in 25 individuals before use. For the analysis, the average value of the two readings taken at a five-minute interval was used. The study measured the participants' anthropometric data, including weight and height.\u003c/p\u003e\n\u003ch3\u003eCriteria and definitions\u003c/h3\u003e\n\u003cp\u003e Hypertension, as defined by the JNC VII guidelines, categorizes individuals as hypertensive when their systolic blood pressure (SBP) is equal to or greater than 140 mmHg or their diastolic blood pressure (DBP) is equal to or greater than 90 mmHg.\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHigh BMI\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eAs per the WHO guidelines, overweight is defined by a BMI of 23\u0026ndash;24.9 Kg/m\u003csup\u003e2\u003c/sup\u003e and obesity is defined as 25 Kg/m\u003csup\u003e2\u003c/sup\u003e and above. High BMI levels included overweight and obesity categories.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAddiction:\u003c/h3\u003e\n\u003cp\u003eSmoking, alcohol, tobacco, and pan masala/gutka addiction were defined as individuals currently exposed to one or more of these addictions, while non-addicted individuals included those who had never been exposed to any of these addictions.\u003c/p\u003e\n\u003ch3\u003ePhysical activity:\u003c/h3\u003e\n\u003cp\u003eParticipants who were primarily engaged in sedentary activities were classified as sedentary, while those who had at least 10 min of moderate to intense activities were considered active.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFruit consumption:\u003c/h2\u003e \u003cp\u003eParticipants who consumed fruits at least three times per week were considered optimum.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eConsumption of leafy vegetables\u003c/h2\u003e \u003cp\u003eParticipants who consumed leafy vegetables at least three times per week were considered optimum.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eDescriptive statistics were generated using cross-tabulations, and the chi-square test was used to investigate the relationship between categorical variables. Additionally, a multivariate logistic regression analysis was conducted to assess the combined influence of age, BMI, addictions (smoking, alcohol consumption, pan masala/gutka, tobacco), frequency of fruit intake, frequency of leafy vegetables intake and physical activity on hypertension simultaneously. A significance level of 5% was applied to all the statistical tests. The data analysis was performed using SPSS Version 29.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":" \u003cp\u003eThis study involved 4,806 individuals, comprising 2,388 males and 2,418 females. The subjects' ages ranged from 18 to 92 years, with a mean age of 40.92\u0026thinsp;\u0026plusmn;\u0026thinsp;14.34 years. Specifically, the mean age for males was 40.55\u0026thinsp;\u0026plusmn;\u0026thinsp;14.45 years, and for females, it was 41.29\u0026thinsp;\u0026plusmn;\u0026thinsp;14.21 years. A summary of the general characteristics of the study population is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In this study, 88.2% of the participants were found to be literate. Regarding dietary habits, 212 participants had a vegetarian diet, 117 had optimum fruit intake and 4152 participants had optimum green leafy vegetable consumption. A total of 208 participants engaged in moderate to intense physical activity. With respect to addiction, 1017 had addiction either of smoking, alcohol, pan masala/gutka, and tobacco. 1593 participants had a BMI more than or equal to 25.\u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026amp; 3 show prevalence of hypertension in males and females included in the study whereas Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e represents stages of Hypertension in the study population.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e represents observed and expected values for hypertension whereas Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the association between hypertension and various factors, including age, addiction status, BMI, physical activity, gender, leafy vegetable consumption, diet type, and fruit consumption. The chi-square test was used to analyze the relationship between these factors and hypertension in the study population. These results offer insight into the significant contributors to hypertension in this population. A strong association (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was observed between hypertension and age, gender, BMI, physical activity, and addiction status. The condition was highly prevalent in individuals aged 35 years and above (χ\u0026sup2; = 1408.38), males (χ\u0026sup2; = 29.24), those with a BMI of 25 or higher (χ\u0026sup2; = 76.43), individuals with a sedentary lifestyle (χ\u0026sup2; = 78.96) and addiction (χ\u0026sup2; = 380.14). The individuals who consumed sufficient amount of leafy vegetables had a lower incidence of hypertension. Additionally, the study demonstrated a non-significant relationship (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) between fruit consumption (χ\u0026sup2; = 0.0) and diet type (χ\u0026sup2; = 0.0015), whether vegetarian or nonvegetarian.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of participants in different categories of risk factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi- Square (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDegree of Freedom\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1408.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAddiction\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e380.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBMI*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGender*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLeafy Vegetable consumption\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eType of diet\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFruit consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis was conducted to examine the contribution of all of the above-mentioned risk factors to hypertension (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026amp; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The coefficient for males was positive (0.46), and the odds ratio was 1.58 (95% CI: 1.37\u0026ndash;1.82), indicating that males were approximately 58% more likely to have hypertension than females. The z-value of 6.36 and a significant p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, strongly suggest that gender is a significant predictor of hypertension. Age emerged as a significant predictor of hypertension, with individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;35 years having a much higher likelihood of hypertension, with a coefficient of 2.58 and an odds ratio of 13.21 (95% CI: 11.03\u0026ndash;15.81). This finding is supported by a very high z-value of 28.11 and a p-value of less than 0.0001. The coefficient for having a BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 was 0.3586, with an odds ratio of 1.43 (95% CI: 1.24\u0026ndash;1.65), indicating a 43% increase in the likelihood of hypertension for individuals in this BMI category. A z-value of 4.85 and a significant p-value of (\u0026lt;\u0026thinsp;0.05) suggest that BMI is also a meaningful predictor of hypertension. The study revealed a positive association between addiction status and hypertension, with coefficient 1.36, an odds ratio of 3.88 (95% CI: 3.75\u0026ndash;4.02), with a significant p-value (\u0026lt;\u0026thinsp;0.05). Less consumption of leafy vegetable consumption and less physical activity were significantly associated with hypertension with the odds ratios of 1.39 and 1.88.\u003c/p\u003e \u003cp\u003eNotably, fruit consumption and type of diet did not appear to be a substantial predictor of hypertension in this analysis, with a negative coefficient and non-significant p-value (\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate Logistic Regression Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOdds ratio (OR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI Lower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI Upper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;35\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;25\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAddicted*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOptimum fruit intake\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLess leafy vegetable intake*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSedentary*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVegetarian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Hypertension:\u003c/h2\u003e \u003cp\u003eThis research demonstrated that a substantial portion of male and female participants, respectively, were impacted by hypertension, a key modifiable risk factor for cardiovascular diseases. Specifically, over 43% of men and 36% of women were affected. This percentage is notably higher than the National Family Health Survey (NFHS-5) conducted in 2019\u0026ndash;2020, which reported 24% of men and 21% of women experiencing hypertension. This highlights the considerable significance of this health issue among the Scheduled Caste population in the selected area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with Hypertension:\u003c/h2\u003e \u003cp\u003eThis study aimed to investigate the relationship between hypertension and factors such as age, gender, addiction, Body Mass Index (BMI), physical activity, fruit consumption, leafy vegetable consumption, and diet type (vegetarian or non-vegetarian). Significant gender differences have been found to be closely associated with hypertension. This study aligns with prior research, as biological factors such as sex hormones, chromosomal variations, and other protective biological gender differences play a role in women's resistance to hypertension. Additionally, the results of the logistic regression demonstrate that the risk for hypertension was 50% greater in men.\u003csup\u003e13\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e14\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e15\u003c/sup\u003e The Chi-Square test revealed a significant correlation between age and hypertension status. Individuals aged 35 years demonstrated a greater prevalence of hypertension. This result aligns with the well-established concept that the risk of hypertension increases with age owing to factors such as arterial stiffness and the accumulation of risk factors over time. \u003csup\u003e16\u003c/sup\u003e Furthermore, logistic regression analysis demonstrated that the risk was 13 times higher in individuals aged\u0026thinsp;\u0026gt;\u0026thinsp;35 years.\u003c/p\u003e \u003cp\u003eAddiction was significantly associated with hypertension, as evidenced by the results of the chi-square test. This relationship can be attributed to the physiological and psychological consequences of addictive behaviors, such as smoking and substance use, which are known to elevate blood pressure. The development of hypertension due to smoking involves impaired endothelial function, arterial stiffness, inflammation, lipid modification, and alterations in antithrombotic and prothrombotic factors. \u003csup\u003e17\u003c/sup\u003e Smokeless tobacco, in particular, can lead to sodium retention and poor blood pressure control.\u003csup\u003e18\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e19\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e20\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e21\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e22\u003c/sup\u003e Alcohol consumption has also been shown to cause hypertension by stimulating the renin-angiotensin-aldosterone system, increasing cortisol levels, and increasing vascular reactivity owing to higher intracellular calcium levels. Additionally, alcohol consumption can stimulate the endothelium to release vasoconstrictors and cause a loss of relaxation owing to inflammation and oxidative injury of the endothelium. \u003csup\u003e23\u003c/sup\u003e Furthermore, logistic regression analysis indicated that the risk was 2.88 times higher in the addicted population. Implementation of de-addiction program may facilitate reducing hypertension prevalence in the selected area.\u003c/p\u003e \u003cp\u003eA significant association was observed between BMI and hypertension. Individuals with a BMI of 25 or higher were more likely to have hypertension, as per the results of the chi-square test, supporting the role of high BMI as a major risk factor for cardiovascular conditions. Excess body weight increases the strain on the heart and blood vessels due to atherosclerosis, leading to elevated blood pressure.\u003csup\u003e24\u003c/sup\u003e The findings of the chi-square analysis demonstrated a substantial association between a sedentary lifestyle and hypertension. It is widely acknowledged that sedentary behavior is a significant risk factor for hypertension due to its association with metabolic syndrome.\u003csup\u003e25\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e26\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e27\u003c/sup\u003e Engaging in physical activity has been shown to lower blood pressure and improve cardiovascular health, making it a vital component of prevention and management strategies for hypertension. \u003csup\u003e28\u003c/sup\u003e Logistic regression suggests that individuals with a sedentary lifestyle have an 80% risk of developing hypertension. Less consumption of leafy vegetable was found as a significant risk factor for hypertension which is consistent with finding of previous studies.\u003csup\u003e29\u003c/sup\u003e Optimum intake of leafy vegetables reduce blood pressure due to high amount of fibers present.\u003csup\u003e30\u003c/sup\u003e Public health campaigns promoting the intake of leafy vegetables could be instrumental in preventing hypertension, particularly in populations at risk.\u003c/p\u003e \u003cp\u003eIn this study, it was discovered that the optimum consumption of fruits and a vegetarian diet had a negative impact on hypertension. This contradicts the findings of earlier research,\u003csup\u003e31\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e32\u003c/sup\u003e but additional investigation is necessary to determine if other dietary and lifestyle factors may be overshadowing the relationship.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eKey message:\u003c/h2\u003e \u003cp\u003eThe present study attempted to provide a snapshot of the health status of the scheduled caste population considering their increasing interaction with modernization. Modernization has led to an increase in sedentary lifestyle, BMI among the population, which in turn has resulted in a higher prevalence of hypertension. The gender distribution in the study was well-balanced, which effectively eliminated the potential for selection bias. The comprehensive information gathered on alcohol, smoking, and physical activity provided valuable insights into the associated risks that were linked to the studied health outcomes. The current investigation represents the initial endeavor to assess the risk factors associated with hypertension within the scheduled caste population of Mumbai, India. Future research could expand upon this by conducting larger-scale studies that encompass multiple states within the country.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe research demonstrates a high prevalence of hypertension among the Scheduled Caste population in Mumbai, India emphasizing hypertension as a significant health concern in this community. Age, gender, BMI, addiction status, and physical activity were identified as key predictors of hypertension. Specifically, older age, male gender, higher BMI, and a sedentary lifestyle were strongly associated with an increased likelihood of hypertension. Moreover, individuals with addictions to substances like tobacco, alcohol, and pan masala/gutka showed a higher risk of developing hypertension. The study found that low consumption of leafy vegetables was a significant risk factor for hypertension, while fruit consumption and vegetarian diet type did not significantly impact hypertension prevalence. The findings suggest the need for targeted public health interventions that focus on modifiable risk factors like addiction cessation, promoting physical activity, and encouraging the consumption of leafy vegetables for reducing the burden of hypertension and improving cardiovascular health in the Scheduled Caste population. The research offers an initial evaluation of hypertension within this specific community and specific region which highlights the importance of conducting more extensive research across multiple states and regions to gain a deeper understanding and address the health disparities associated with hypertension more effectively.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eWe are grateful to Director General, Central Council of Research in Ayurvedic Sciences (CCRAS), Ministry of AYUSH, Government of India for the support throughout the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eThe ethical approval has been sought from Institutional Ethics Committee (IEC), CCRAS-CARI, Mumbai. (F-6-94/IEC/Tech/Mumb/2021-22/01)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eAn informed consent was obtained from each participant included in the study. The initiation of the study was authorized following approval from the local authorities in each of the five regions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eThe consent for publication has been sought from CCRAS headquarters, New Delhi, India\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data is available with CCRAS headquarters, New Delhi, India\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u003c/strong\u003e There is no competing interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe current study was sponsored by Central Council of Research in Ayurvedic Sciences (CCRAS), Ministry of AYUSH, Government of India.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD, LB, DM, SM, GR, NS: wrote and reviewed main manuscript.\u003c/p\u003e\n\u003cp\u003eJA, PG, AM: prepared figures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Aloudat, T., Boulle, P., Kravitz, A. S., \u0026amp; Van Tulleken, A. (2019).\u0026nbsp;\u003cem\u003eChronic non-communicable diseases\u003c/em\u003e\u0026nbsp;(pp. 841\u0026ndash;864). oxford university. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/med/9780199565276.003.0046\u003c/span\u003e\u003cspan address=\"10.1093/med/9780199565276.003.0046\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Anand, T., Anand, T., Kishore, J., Kishore, J., Garg, A., Garg, A., Ray, P. C., Sharma, U., Sharma, U., Chakraborty, M., Chakraborty, M., \u0026amp; Ingle, G. K. (2014). Prevalence of Risk Factors for Chronic Non-communicable Diseases Using WHO Steps Approach in an Adult Population in Delhi.\u0026nbsp;\u003cem\u003eJournal of Family Medicine and Primary Care\u003c/em\u003e,\u0026nbsp;\u003cem\u003e3\u003c/em\u003e(2), 112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/2249-4863.137617\u003c/span\u003e\u003cspan address=\"10.4103/2249-4863.137617\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Rajan, V., Singh, A. K., Patra, S., Patro, B. K., \u0026amp; Behera, P. (2024). Prevalence of common mental disorders and treatment gap among patients with non-communicable diseases in the rural areas of East India.\u0026nbsp;\u003cem\u003eSocial Psychiatry and Psychiatric Epidemiology\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00127-024-02618-0\u003c/span\u003e\u003cspan address=\"10.1007/s00127-024-02618-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Omer, S., Elmubarak, M., Mustafaalhamed, M., Elmubarak, M., Adam, A., Younis, A., Mukhtar, Rihab. I., A.Elmubarak, M., T.M.Abdoun, G., \u0026amp; Elsanousi, S. (2023). Prevalence of non-communicable Diseases (NCDs) in an urban area in Sudan and the role of medical students in health promotion of patients with NCDs.\u0026nbsp;\u003cem\u003eInternational Journal of Scholarly Research in Medicine and Dentistry\u003c/em\u003e,\u0026nbsp;\u003cem\u003e2\u003c/em\u003e(1), 001\u0026ndash;007. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.56781/ijsrmd.2023.2.1.0028\u003c/span\u003e\u003cspan address=\"10.56781/ijsrmd.2023.2.1.0028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Anand, T., Anand, T., Kishore, J., Kishore, J., Garg, A., Garg, A., Ray, P. C., Sharma, U., Sharma, U., Chakraborty, M., Chakraborty, M., \u0026amp; Ingle, G. K. (2014). Prevalence of Risk Factors for Chronic Non-communicable Diseases Using WHO Steps Approach in an Adult Population in Delhi.\u0026nbsp;\u003cem\u003eJournal of Family Medicine and Primary Care\u003c/em\u003e,\u0026nbsp;\u003cem\u003e3\u003c/em\u003e(2), 112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/2249-4863.137617\u003c/span\u003e\u003cspan address=\"10.4103/2249-4863.137617\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e International Institute for Population Sciences, \u0026amp; ORC Macro. MEASURE/DHS+ (Programme). (2000).\u0026nbsp;\u003cem\u003eNational family health survey (NFHS-2), India, 1998-99\u003c/em\u003e\u0026nbsp;(Vol. 1). International Institute for Population Sciences, Mumbai, India.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Babu, B. V., Raina, S. K., Thomas, N., Masoodi, S. R., Hazarika, C. R., Jebasingh, F. K., Kerketta, A. S., \u0026amp; Basappa, Y. C. (2023). Hypertension Prevalence, Awareness, Treatment, Control and Risk Factors in Tribal Population of India: a Multi-Centric Cross-Sectional Study.\u0026nbsp;\u003cem\u003eJournal of Racial and Ethnic Health Disparities\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40615-023-01817-w\u003c/span\u003e\u003cspan address=\"10.1007/s40615-023-01817-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Biswas, M., \u0026amp; Manna, C. K. (2011). Prevalence of Hypertension and Sociodemographic Factors within the Scheduled Caste Community of the District Nadia, West Bengal, India.\u0026nbsp;\u003cem\u003eHigh Blood Pressure \u0026amp; Cardiovascular Prevention\u003c/em\u003e,\u0026nbsp;\u003cem\u003e18\u003c/em\u003e(4), 179\u0026ndash;185. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2165/11593600-000000000-00000\u003c/span\u003e\u003cspan address=\"10.2165/11593600-000000000-00000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Gosal, R. P. S. (1987). Distribution of scheduled caste population in India.\u0026nbsp;\u003cem\u003eSocial Science Information\u003c/em\u003e,\u0026nbsp;\u003cem\u003e26\u003c/em\u003e(3), 493\u0026ndash;511. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/053901887026003002\u003c/span\u003e\u003cspan address=\"10.1177/053901887026003002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Kaur P, Sakthivel M, Venkatasamy V, Jogewar P, Gill SS, Kunwar A, Sharma M, Pathni AK, Durgad K, Sahoo SK, Wankhede A, Kumar N, Bharadwaj V, Das B, Chavan T, Khedkar S, Sarode L, Bangar SD, Krishna A, Shivashankar R, Ganeshkumar P, Pragya P, Bhargava B. India Hypertension Control Initiative: Blood Pressure Control Using Drug and DoseSpecific Standard Treatment Protocol at Scale in Punjab and Maharashtra, India, 2022. Global Heart. 2024; 19(1): 30. DOI: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5334/gh.1305\u003c/span\u003e\u003cspan address=\"10.5334/gh.1305\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo Jr JL, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289(19): 2560\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e WHO/IASO/IOTF. The Asia \u0026ndash;Pacific perspective: redefining obesity and its treatment. Melbourne: Health Communication Austrailia; 2000.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Cutler JA, Sorlie PD, Wolz M, Thom T, Fields LE, Roccella EJ. Trends in hypertension prevalence, awareness, treatment, and control rates in United States adults between 1988\u0026ndash;1994 and 1999\u0026ndash;2004.\u0026nbsp;\u003cem\u003eHypertension.\u003c/em\u003e\u0026nbsp;2008;52(5):818\u0026ndash;827\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Sandberg K, Ji H. Sex differences in primary hypertension.\u0026nbsp;\u003cem\u003eBiol Sex Differ.\u003c/em\u003e\u0026nbsp;2012;3(1):7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Vitale C, Fini M, Speziale G, Chierchia S. Gender differences in the cardiovascular effects of sex hormones.\u0026nbsp;\u003cem\u003eFundam Clin Pharmacol.\u003c/em\u003e\u0026nbsp;2010;24(6):675\u0026ndash;685.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Kim HL. Arterial stiffness and hypertension. Clin Hypertens. 2023 Dec 1;29(1):31. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40885-023-00258-1\u003c/span\u003e\u003cspan address=\"10.1186/s40885-023-00258-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 38037153; PMCID: PMC10691097.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Virdis A, Giannarelli C, Neves MF, Taddei S, Ghiadoni L. Cigarette smoking and hypertension. Curr Pharm Des. 2010;16(23):2518-25. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2174/138161210792062920\u003c/span\u003e\u003cspan address=\"10.2174/138161210792062920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 20550499.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Westman EC. Does smokeless tobacco cause hypertension? Southern Medical Journal. 1995 Jul;88(7):716\u0026ndash;720. DOI: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00007611-199507000-00004\u003c/span\u003e\u003cspan address=\"10.1097/00007611-199507000-00004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 7597474.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Singh, P.K.; Dubey, R.; Singh, L.; Singh, N.; Kumar, C.; Kashyap, S.; Subramanian, S.V.; Singh, S. Mixed Effect of Alcohol, Smoking, and Smokeless Tobacco Use on Hypertension among Adult Population in India: A Nationally Representative Cross-Sectional Study.\u0026nbsp;\u003cem\u003eInt. J. Environ. Res. Public Health\u003c/em\u003e\u0026nbsp;\u003cb\u003e2022\u003c/b\u003e,\u0026nbsp;\u003cem\u003e19\u003c/em\u003e, 3239. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph19063239\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19063239\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Ghosh\u0026nbsp;S,\u0026nbsp;Kumar\u0026nbsp;M. Prevalence and associated risk factors of hypertension among persons aged 15\u0026ndash;49 in India: a cross-sectional study. \u003cem\u003eBMJ Open\u003c/em\u003e\u0026nbsp;2019;\u003cb\u003e9\u003c/b\u003e:e029714.\u0026nbsp;doi:\u0026nbsp;\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2019-029714\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2019-029714\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Lal D, Virk AK, Bhardwaj A, Lal KK, Bora J, Nadda A, et al. (2024) Pestilent relationship between smoking and hypertension or pulse pressure among males over 15 years in India: NFHS-5 Survey. PLoS ONE 19(5): e0294898. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0294898\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0294898\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e S.\u0026nbsp;Khanal,\u0026nbsp;S.A.\u0026nbsp;Khan,\u0026nbsp;D.\u0026nbsp;Baral,\u0026nbsp;S.\u0026nbsp;Shrestha,\u0026nbsp;N.\u0026nbsp;Baral,\u0026nbsp;M.\u0026nbsp;Lamsal. Oxidant-antioxidant status and assessment of cardiovascular morbidity in Pan Masala containing Tobacco users: a cross-sectional study. BMC Res. Notes.2018(11):727.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Husain K, Ansari RA, Ferder L. Alcohol-induced hypertension: Mechanism and prevention. World J Cardiol. 2014 May 26;6(5):245\u0026thinsp;\u0026minus;\u0026thinsp;52. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4330/wjc.v6.i5.245\u003c/span\u003e\u003cspan address=\"10.4330/wjc.v6.i5.245\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 24891935; PMCID: PMC4038773.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Ledwozyw A, Michalak J, Stepień A, Kadziołka A. The relationship between plasma triglycerides, cholesterol, total lipids and lipid peroxidation products during human atherosclerosis.\u0026nbsp;\u003cem\u003eClin Chim Acta.\u003c/em\u003e\u0026nbsp;1986;155:275\u0026ndash;283. doi:\u0026nbsp;\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0009-8981(86)90247-0\u003c/span\u003e\u003cspan address=\"10.1016/0009-8981(86)90247-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Joardar AI, Khaled MFI, Mahabub SME, Singha CK, Atiqul-Haque M. Factors Associated with Hypertension among Urban Dwellers with Sedentary Lifestyle: A Cross-Sectional Study. J Natl Inst Neurosci Bangladesh, 2020;6(2): 129\u0026ndash;134.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Singh, R. B., Fedacko, J., Pella, D., Macejova, Z., Ghosh, S., De, A. K., \u0026hellip; Gupta, A. K. (2011). Prevalence and risk factors for prehypertension and hypertension in five Indian cities.\u0026nbsp;\u003cem\u003eActa Cardiologica\u003c/em\u003e,\u0026nbsp;\u003cem\u003e66\u003c/em\u003e(1), 29\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/AC.66.1.2064964\u003c/span\u003e\u003cspan address=\"10.1080/AC.66.1.2064964\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Juan Jos\u0026eacute; Beunza, Miguel \u0026Aacute;ngel Mart\u0026iacute;nez-Gonz\u0026aacute;lez, Shah Ebrahim, Maira Bes-Rastrollo, Jorge N\u0026uacute;\u0026ntilde;ez, Jos\u0026eacute; Alfredo Mart\u0026iacute;nez, \u0026Aacute;lvaro Alonso, Sedentary Behaviors and the Risk of Incident Hypertension: The SUN Cohort,\u0026nbsp;\u003cem\u003eAmerican Journal of Hypertension.\u003c/em\u003e 2007;20(11):11561162.\u003c/span\u003e \u003c/li\u003e\u003cli\u003e\u003cspan\u003e Hegde SM, Solomon SD. Influence of Physical Activity on Hypertension and Cardiac Structure and Function. Curr Hypertens Rep. 2015 Oct;17(10):77. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11906-015-0588-3\u003c/span\u003e\u003cspan address=\"10.1007/s11906-015-0588-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 26277725; PMCID: PMC4624627.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e O M Akpa, A P Okekunle, et al. Frequent vegetable consumption is inversely associated with hypertension among indigenous Africans,\u0026nbsp;\u003cem\u003eEuropean Journal of Preventive Cardiology\u003c/em\u003e. 2022;29(18):2359\u0026ndash;2371.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Adebawo, O., Salau, B., Ezima, E.\u0026nbsp;\u003cem\u003eet al.\u003c/em\u003e\u0026nbsp;Fruits and vegetables moderate lipid cardiovascular risk factor in hypertensive patients.\u0026nbsp;\u003cem\u003eLipids in Health and Disease\u003c/em\u003e.2006;5:14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Madsen, H., Sen, A. \u0026amp; Aune, D. Fruit and vegetable consumption and the risk of hypertension: a systematic review and meta-analysis of prospective studies.\u0026nbsp;\u003cem\u003eEur J Nutr\u003c/em\u003e\u0026nbsp;62, 1941\u0026ndash;1955 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00394-023-03145-5\u003c/span\u003e\u003cspan address=\"10.1007/s00394-023-03145-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Chuang, Shao-Yuan; Chiu, Tina H.T.; Lee, Chun-Yi; Liu, Ting-Ting; Tsao, Chwen Keng; Hsiung, Chao A.; Chiu, Yen-Feng. Vegetarian diet reduces the risk of hypertension independent of abdominal obesity and inflammation: a prospective study. Journal of Hypertension 34(11):p 2164\u0026ndash;2171, November 2016.\u003c/span\u003e \u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hypertension, Scheduled Caste, Mumbai, Non-communicable diseases, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-6102020/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6102020/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHypertension is a major health issue worldwide, with an increasing incidence in developing nations. This research examines the prevalence and contributing factors of hypertension in the Scheduled Caste community in Mumbai, India, considering the effects of urbanization and lifestyle modifications.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo determine the prevalence of hypertension and assess the association of various demographic, lifestyle, and dietary factors with hypertension in the Scheduled Caste community in Mumbai, India.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study was carried out during the years 2021\u0026ndash;2022 in five regions of Mumbai, with substantial Scheduled Caste population. A total of 4,806 participants above 18 years of age were selected through purposive sampling. Data collection involved interviews and measurements of blood pressure and anthropometric data. The study used chi-square tests and multivariate logistic regression analysis to identify significant predictors of hypertension.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study found that 39.5% of participants had hypertension. Significant risk factors for hypertension included age (\u0026ge;\u0026thinsp;35 years), male gender, higher BMI (\u0026ge;\u0026thinsp;25), addiction (smoking, alcohol, pan masala/gutka), and a sedentary lifestyle. Conversely, high consumption of leafy vegetables was associated with a lower prevalence of hypertension. No significant associations were found between hypertension and fruit consumption and diet type (vegetarian vs. non-vegetarian).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHypertension is prevalent in the Scheduled Caste population in Mumbai, driven by modifiable risk factors such as BMI, addiction, and physical activity. The findings emphasize the need for targeted public health interventions to address these risk factors and reduce the burden of hypertension in this population. Future research is needed with larger and more diverse populations to further explore these associations.\u003c/p\u003e","manuscriptTitle":"An Evaluation of the Risk Factors Associated with Hypertension in the Scheduled Caste Population of Mumbai, India: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-06 17:30:08","doi":"10.21203/rs.3.rs-6102020/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":"90ddd985-bac8-43f9-b23f-e42f04c2568e","owner":[],"postedDate":"March 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-06T17:30:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-06 17:30:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6102020","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6102020","identity":"rs-6102020","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}