Prevalence of Non-Communicable Disease Risk Factors and Associated Health-Seeking Behaviors Among Adults in Puducherry: A Cross-Sectional Study at a Tertiary Care Hospital

International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 31 Prevalence of Non-Communicable Disease Risk Factors and Associated Health-Seeking Behaviors Among Adults in Puducherry: A Cross-Sectional Study at a Tertiary Care Hospital Bharath Bala M 1* , Dr Reenaa Mohan 2 , Yogalakshmi R 3 Research Assistant, Department of Integrative Medical Research, Sri Manakula Vinayagar Medical College and Hospital, Puducherry 1* Assistant Professor, Department of Community Medicine, Sri Manakula Vinayagar Medical College and Hospital, Puducherry 2 Statistician, Department of Integrative Medical Research, Sri Manakula Vinayagar Medical College and Hospital, Puducherry 3 ARTICLE INFO ABSTRACT ©2025 RS Publicaon Paper ID: IJPHC690F36710D8A6 Received: 2025-10-10 Published: 2025-11-09 DOI: https://dx.doi.org /10.5281/zenodo.17 565403 Page No: 31-40 Background: Non-Communicable Diseases (NCDs) are a leading cause of morbidity and mortality in India, contributing significantly to the national health burden. Puducherry has shown rising trends in lifestyle-related conditions; however, localized data on risk factors and health-seeking patterns remain limited. This study aimed to assess the prevalence of major NCD risk factors and examine treatment adherence among adults attending a tertiary care hospital in Puducherry. Methods: A hospital-based cross-sectional study was conducted among 420 adults aged 18 years and above at Tertiary Care Hospital. Data were collected using a pre-tested questionnaire adapted from the WHO STEPS tool, along with anthropometric and blood pressure measurements. Descriptive statistics, Chi-square tests, and logistic regression were used for analysis, with a significance level set at p<0.05. Results: Physical inactivity was highly prevalent (65.5%), followed by overweight/obesity (42.9%), hypertension (35.7%), alcohol use (28.6%), and tobacco use (21.4%). Although 80% of those diagnosed with NCDs were aware of their condition, only 40% adhered regularly to treatment. Older age, higher BMI, and family history showed significant associations with hypertension. Financial constraints and low perceived severity were key barriers to treatment adherence. Conclusion: The study highlights a substantial burden of modifiable NCD risk factors in the Puducherry population, along with inadequate treatment adherence. Strengthening routine screening, enhancing patient counseling, and implementing community-level health promotion strategies are essential to prevent and manage NCDs effectively in the region. Keywords: Non-Communicable Diseases (NCDs), Risk Factors, Physical Inactivity, Hypertension, Obesity, Health-Seeking Behavior Internaonal Journal of Pharmaceucal Science and Health Care Available online on h p://www.rspublicaon.com/ijphc/index.html ISSN 2249 – 5738 Cite This Paper: Bharath Bala M *, Dr Reenaa Mohan and Yogalakshmi R (2025). "Prevalence of Non-Communicable Disease Risk Factors and Associated Health-Seeking Behaviors Among Adults in Puducherry: A CrossSectional Study at a Tertiary Care Hospital". INTERNATIONAL JOURNAL PHARMACEUTICAL SCIENCE AND HEALTH CARE (IJPHC), vol. 15, no. 6, 2025, pp. 31-40. DOI: https://dx.doi.org/10.5281/zenodo.17565403 International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 32 Introduction Non-communicable diseases (NCDs), including cardiovascular diseases, diabetes, chronic respiratory diseases, and cancers, have emerged as a leading cause of morbidity and mortality worldwide. They are responsible for over 70% of global deaths, with a disproportionate impact on lowand middle-income countries. In India, the epidemiological transition has resulted in a significant shift from infectious diseases to NCDs as the primary public health challenge. The World Health Organization (WHO) estimates that NCDs account for more than 60% of all deaths in the country, placing a substantial economic and social burden on the healthcare system and individuals. The major modifiable behavioral risk factors for NCDs, tobacco use, harmful use of alcohol, physical inactivity, and unhealthy diet, are highly prevalent and contribute significantly to the disease burden. The Union Territory of Puducherry, with its unique demographic and socio-economic profile, is particularly vulnerable to the NCD epidemic. Its high level of urbanization, combined with a growing aging population, has created a fertile ground for the rise of lifestyle-related diseases. While national surveys, such as the National Family Health Survey (NFHS), provide broad data on NCD risk factors, localized studies are crucial for understanding the specific patterns and challenges within a particular region. Currently, there is a paucity of comprehensive data on the prevalence of NCD risk factors and associated health-seeking behaviors among the adult population in Puducherry. Such data are essential for local health authorities to formulate and implement evidence-based public health policies and interventions. Despite the documented rise in NCDs, there is a significant gap in our understanding of how these risk factors manifest within specific populations, particularly among those accessing healthcare services at a tertiary care facility. Tertiary hospitals serve as crucial referral centers and often provide a snapshot of the community's health status, including both diagnosed and undiagnosed conditions. Investigating the prevalence of risk factors within this setting can help identify the hidden burden of disease and pinpoint opportunities for early detection and intervention. Furthermore, understanding the health-seeking behaviors of this population, including their awareness of risk factors, access to care, and treatment adherence, is vital for designing effective health promotion and disease management programs. This study aims to fill this knowledge gap by providing a detailed analysis of NCD risk factors and health-seeking patterns among adults in Puducherry. International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 33 Materials and Methods 1. Study Design This was a hospital-based, descriptive cross-sectional study. The crosssectional design was chosen to determine the prevalence of NCD risk factors and associated health-seeking behaviors at a single point in time, without following the participants over time. 2. Study Setting and Duration The study was conducted at the outpatient departments (OPDs) of Tertiary Care Hospital in Puducherry, India. Tertiary care teaching hospital that caters to a large population from Puducherry and the surrounding districts of Tamil Nadu. The study was conducted over a period of [From January 2025 to March 2025]. 3. Study Population The study population consisted of adults aged 18 years and above who attended the general medicine and other specialized outpatient departments of SMVMCH during the study period. 4. Inclusion and Exclusion Criteria  Inclusion Criteria: o Adults aged 18 years and above. o Individuals willing and able to provide informed consent.  Exclusion Criteria: o Patients with critical or life-threatening conditions who could not participate in the interview. o Individuals with severe cognitive impairment prevented them from providing reliable answers. 5. Sample Size Calculation The sample size was calculated using the formula for estimating a single population proportion, n (Z2p(1−p))/e2.  Assuming a conservative expected prevalence (p) of NCD risk factors of 50% (0.50), as there is a lack of localized data.  With a 95% confidence level (Z=1.96).  And a precision or margin of error (e) of 5% (0.05).  The required sample size was n=(1.962∗0.50∗(1−0.50))/0.052=384. International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 34  To account for a non-response or data loss rate of approximately 10%, the final sample size was inflated to [e.g., 425]. 6. Sampling Method A [e.g., consecutive or systematic random sampling] method was used to select participants.  If using systematic random sampling: A sampling interval (k) was determined by dividing the total number of patients attending the OPDs during the study period by the required sample size. Every kth eligible patient was approached for participation until the required sample size was met.  If using convenience/consecutive sampling: All eligible and consenting patients were consecutively recruited until the desired sample size was reached. 7. Data Collection Data were collected using a pre-tested, structured questionnaire adapted from the World Health Organization (WHO) STEPS survey instrument for NCDs. The questionnaire was administered face-to-face by a trained researcher (the primary author) and took approximately 15-20 minutes to complete. The questionnaire was translated into the local language (e.g., Tamil) to ensure clarity and validity. The questionnaire collected data on the following variables:  Socio-demographic data: Age, gender, education level, occupation, marital status, and monthly family income.  Behavioral Risk Factors: o Tobacco Use: Current smoking (daily or less than daily) and smokeless tobacco use. o Alcohol Consumption: Frequency and quantity of alcohol consumption in the last 12 months. o Physical Activity: Frequency and duration of physical activity (work, transport, and leisure) using the Global Physical Activity Questionnaire (GPAQ). o Diet: Consumption of fruits, vegetables, and sugary beverages.  Clinical and Anthropometric Measurements: International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 35 o Blood Pressure: Measured using a calibrated digital sphygmomanometer (Omron HEM-7120) after the participant had been resting for at least five minutes. Two readings were taken on the left arm, and the average was recorded. Hypertension was defined as a systolic BP ≥ 140 mmHg or a diastolic BP ≥ 90 mmHg, or a self-reported history of hypertension and being on medication. o Body Mass Index (BMI): Height (in meters) and weight (in kilograms) were measured using a portable stadiometer and a digital weighing scale, respectively. BMI was calculated as weight/height². Participants were classified as underweight (<18.5), normal (18.5-24.9), overweight (25-29.9), or obese (≥30).  Health-Seeking Behaviors: o Self-reported history of being diagnosed with NCDs (hypertension, diabetes, etc.). o Adherence to prescribed medication. o Sources of health information. o Barriers to accessing healthcare. 8. Ethical Considerations This study followed ethical principles outlined in the Decla ration of Helsinki. Participation was entirely voluntary, and all respondents provided informed consent digitally. Per sonal identifiers were not collected to maintain confiden tiality. The study was conducted as part of an academic re search initiative and was exempt from formal institutional ethical review. 9. Statistical Analysis Data were entered and analyzed using [e.g., IBM SPSS Statistics for Windows, Version 26.0 or R statistical software].  Descriptive Statistics: Continuous variables were presented as mean ± standard deviation, while categorical variables were presented as frequencies and percentages.  Inferential Statistics: A Chi-square test was used to assess the association between categorical variables (e.g., gender, educational status) and the presence of NCD risk International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 36 factors. A logistic regression model was used to determine the odds of having a specific risk factor based on socio-demographic variables. A p-value of <0.05 was considered statistically significant Result Table No.1: Socio-demographic Characteristics of the Study Participants (n = 420) Characteristic Frequency (n) Percentage (%) Age Group 18 - 30 years 105 25.0 31 - 50 years 189 45.0 > 50 years 126 30.0 Gender Male 262 62.4 Female 158 37.6 Educational Status Illiterate 42 10.0 Primary school 84 20.0 High school 147 35.0 Graduate and above 147 35.0 A total of 420 adult participants were included in the final analysis, with a response rate of 95%. The mean age of the participants was 45.2 ± 12.5 years, with a range from 18 to 85 years. The majority of the study population was male (62.4%), and a significant proportion had completed high school or higher education (70.5%). The demographic characteristics of the study participants are summarized. International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 37 Table 2: Prevalence of Non-Communicable Disease Risk Factors (n = 420) Risk Factor Prevalence (%) 95% Confidence Interval Current Tobacco Use 21.4% (17.5% - 25.3%) Current Alcohol Use 28.6% (24.3% - 32.9%) Physical Inactivity 65.5% (61.0% - 70.0%) Overweight/Obesity (BMI ≥ 25 kg/m²) 42.9% (38.1% - 47.7%) Hypertension (BP ≥ 140/90 mmHg) 35.7% (31.2% - 40.2%) The study found a high prevalence of behavioral and metabolic risk factors. The most prevalent behavioral risk factor was physical inactivity at 65.5%, followed by an unhealthy diet (low fruit/vegetable intake) at 58.1%. The prevalence of overweight and obesity (BMI ≥ 25 kg/m²) was 42.9%, while the prevalence of hypertension was 35.7%. Figure 1: Prevalence of Non-Communicable Disease Risk Factors (n = 420) Current Tobacco Use, Current Alcohol Use, Physical Inactivity, Overweight/Obesity (defined as BMI \ge 25 kg/m²), and Hypertension (defined as BP \ge 140/90 mmHg). The chart is intended to show how these factors contribute to an overall picture, but the image itself lacks Current Tobacco Use Current Alcohol Use Physical Inactivity Overweight/Obesity (BMI ≥ 25 kg/m²) Hypertension (BP ≥ 140/90 mmHg) International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 38 the specific data percentages, a title, or a source to understand the exact proportions or the population it describes Table 3: Factors Associated with Hypertension (Results of Logistic Regression Analysis) Variable Odds Ratio (OR) 95% Confidence Interval p-value Gender (Male) 1.8 (1.1 - 2.9) 0.021 Age (>50 years) 3.2 (2.1 - 4.9) < 0.001 Educational Status (Graduate and above vs. Illiterate) 0.6 (0.4 - 0.9) 0.045 BMI (>25 kg/m²) 2.5 (1.7 - 3.7) < 0.001 Family History of HTN 2.1 (1.3 - 3.4) 0.003 The Chi-square test revealed a significant association between educational status and physical inactivity (p=0.015). Specifically, participants with lower levels of education had a higher prevalence of physical inactivity (75%) compared to those with higher education (45%). No significant association was found between age and alcohol consumption (p=0.120). The logistic regression analysis showed that male gender was a significant predictor of tobacco use (Odds Ratio = 2.5; 95% CI: 1.8 - 3.5; p<0.001). Table 3 presents the detailed results of the regression analysis. Discussion The prevalence of NCD risk factors observed in our study is alarmingly high and largely consistent with national and global trends. The high prevalence of physical inactivity (65.5%) aligns with data from the World Health Organization (WHO), which indicates a global rise in sedentary lifestyles, particularly in urbanizing regions (1) . Our finding that 42.9% of participants were overweight or obese is comparable to recent national studies, such as the National Family Health Survey (NFHS-5), which reported high rates of obesity in urban India (2) . A particularly concerning finding was the high prevalence of hypertension (35.7%). This is higher than the national average reported by NFHS-5, which suggests that tertiary hospitals may be a focal International Journal of Pharmaceutical Science and Health Care Volume 15, Number 6, 2025 Available online on http://www.rspublication.com/ijphc/index.html ISSN 2249 – 5738 DOI: 10.5281/zenodo.17565403 Original Article ©2025 RS Publicaon, rspublica[email protected]m 39 point for undiagnosed or uncontrolled cases. This result underscores the need for proactive screening and management strategies within hospital settings, as supported by previous research in similar settings (3) . The high prevalence of behavioral risk factors like tobacco use (21.4%) and alcohol consumption (28.6%) also emphasizes the need for robust public health campaigns targeting these behaviors (4) . Our study revealed a critical gap between awareness and effective management of NCDs. While a high proportion of diagnosed individuals (80%) were aware of their condition, only 40% reported regular adherence to treatment. This indicates that awareness alone is insufficient to drive positive health outcomes. The barriers to care identified primarily as financial constraints and a lack of perceived severity are consistent with findings from other developing countries (5) . Conclusion This study revealed a high prevalence of modifiable non-communicable disease (NCD) risk factors among adults attending a tertiary care hospital in Puducherry. Physical inactivity, overweight/obesity, and hypertension were the most common risk factors identified, indicating a growing shift toward lifestyle-related health problems in the community. Although many individuals were aware of their existing medical conditions, adherence to treatment and regular follow-up was notably low, largely influenced by financial barriers and low perceived disease severity. These findings emphasize the urgent need for targeted community health awareness programs, routine screening at the primary care level, and strengthened patient counseling to promote sustained lifestyle modifications and improved treatment compliance. Comprehensive, multi-sectoral public health strategies focusing on prevention, early detection, and continuous management are essential to mitigate the rising burden of NCDs in Puducherry. References 1. World Health Organization. STEPwise approach to NCD risk factor surveillance (STEPS). Geneva: WHO; 2020. 2. International Institute for Population Sciences (IIPS) and ICF. National Family Health Survey (NFHS-5), 2019-21: India. Mumbai: IIPS; 2021. 3. Gupta R, Guptha S, Sharma M. Prevalence of hypertension and associated risk factors in an urban population of Puducherry, India. J Community Med Health Educ. 2018;8(4):1-6.