Stroke is a major global public health challenge and one of the leading causes of morbidity, mortality, and long-term disability worldwide. According to the World Health Organization (WHO), stroke ranks as the second most common cause of death and the third leading cause of disability-adjusted life years (DALYs) lost globally. Approximately 15 million people suffer a stroke annually, of whom nearly 5 million die and another 5 million are left permanently disabled, placing a substantial burden on healthcare systems, families, and communities [1-4].

In India, the burden of stroke has increased significantly over the last two decades due to rapid epidemiological transition, rising prevalence of lifestyle-related risk factors, and an aging population. The estimated prevalence of stroke in India is 84–262 per 100,000 population, with incidence rates ranging from 105–152 per 100,000 annually. Alarmingly, nearly one-fifth of all strokes in India occur in individuals below the age of 40 years, reflecting an early onset compared to developed nations. Stroke has emerged as one of the top five leading causes of death in both urban and rural India [5-7].

Punjab, like many North Indian states, is facing a growing challenge of non-communicable diseases (NCDs), including cardiovascular diseases, diabetes, and hypertension. High prevalence of tobacco use, alcohol consumption, sedentary lifestyles, obesity, and poor dietary habits have contributed to an increased risk of stroke in the region. Moreover, gaps in public knowledge, cultural misconceptions, reliance on home remedies, and delayed health-seeking behaviors often result in missed opportunities for early recognition and timely intervention. Limited awareness of modifiable risk factors such as hypertension, diabetes, smoking, and dyslipidemia, as well as poor recognition of warning signs like sudden weakness, slurred speech, and loss of vision, further exacerbates the problem [8-11]

Timely recognition and urgent medical intervention are critical in reducing stroke-related disability and mortality. The concept of the “Golden Hour”—where thrombolytic therapy can restore cerebral blood flow if administered within 4.5 hours of symptom onset—is well-established. However, studies from India indicate that a large proportion of stroke patients fail to reach hospitals within this window, primarily due to a lack of awareness about stroke symptoms and the urgency of immediate medical care. Public knowledge about the FAST (Face drooping, Arm weakness, Speech difficulty, Time to act) approach remains inadequate in most communities [12-15].

Several studies conducted across different regions of India have consistently demonstrated low levels of stroke awareness among the general public.^14-16 While some urban populations show moderate knowledge about risk factors such as hypertension and diabetes, awareness of symptoms and emergency response remains poor, especially in rural areas. Data specific to Punjab remain limited, despite the high burden of NCDs and stroke risk factors prevalent in the state. Understanding public awareness and knowledge gaps in this context is crucial for planning community-based health education interventions, training health workers, and formulating effective policies to improve stroke prevention and management.

The present study was therefore undertaken to assess the level of awareness regarding stroke risk factors, warning signs, and immediate management among the general public of Punjab. By analyzing socio-demographic determinants such as age, gender, residence, education, and occupation, this study aims to identify vulnerable groups with poor awareness and provide evidence to guide targeted health promotion strategies. Ultimately, strengthening public knowledge of stroke can play a pivotal role in reducing the burden of disability and premature mortality associated with this preventable and treatable condition.

Study Design and Setting

A descriptive, cross-sectional study was conducted to assess the level of awareness regarding stroke risk factors, warning signs, and immediate management practices among the general public of Punjab. Data collection was carried out using a structured, self-administered questionnaire designed on Google Forms. This digital format allowed efficient distribution, ensured uniformity in responses, and enabled participation from both urban and rural populations across different districts of Punjab.

Study Population and Eligibility Criteria

The study included adults aged 18 years and above, residing in either urban or rural areas of Punjab. Both male and female participants from diverse educational and occupational backgrounds were included, provided they gave voluntary informed consent. To minimize bias, the following groups were excluded: healthcare professionals, medical students, and paramedical staff (due to their advanced medical knowledge), individuals with severe cognitive or communication difficulties, and incomplete or duplicate submissions. [16]

Sample Size Determination

The sample size was calculated using the single population proportion formula, assuming a 50% prevalence of adequate stroke awareness (since no prior state-specific data were available), with a 95% confidence interval and 5% margin of error. The minimum required sample size was 384, which was rounded up to 400 participants to account for non-responses and exclusions.

Sampling Technique

A purposive-cum-snowball sampling method was adopted. The survey link was disseminated through WhatsApp groups, email, and social media platforms. Community volunteers and village health workers assisted in sharing the survey among local residents, ensuring participation from both rural and urban populations. Respondents were also encouraged to forward the link within their networks to increase representation.

Study Tool (Questionnaire Design)

The questionnaire was developed after reviewing relevant literature, WHO guidelines, and validated tools from previous stroke awareness studies. It was divided into four sections:

• Socio-demographic profile – including age, gender, residence (urban/rural), education, occupation, and household income.

• Awareness of stroke risk factors – assessing knowledge of common risk factors such as hypertension, diabetes, smoking, alcohol use, obesity, and family history.

• Awareness of stroke warning signs/symptoms – evaluating recognition of sudden weakness, speech difficulty, visual impairment, severe headache, imbalance, and knowledge of the FAST test.

• Knowledge score categorization – each correct response was awarded 1 point and incorrect or “don’t know” responses were scored 0. The total score (0–20) was classified into four categories: excellent (16–20), good (12–15), fair (8–11), and poor (0–7).

Validation and Pilot Testing

The draft questionnaire was reviewed by experts in neurology, community medicine, and public health to establish face and content validity. A pilot test was conducted on 30 respondents from both rural and urban settings to assess clarity, cultural appropriateness, and comprehensibility. Based on feedback, minor modifications in wording were made. Internal consistency of the tool was confirmed with a Cronbach’s alpha of 0.81, indicating good reliability.

Data Collection Procedure

Participation was voluntary. The Google Form began with an informed consent statement, and only those who consented could proceed. All questions were mandatory, minimizing missing responses. The average completion time was 10–12 minutes. Data were automatically recorded into a password-protected Google Sheet accessible only to the research team.

Data Analysis

Data were exported into IBM SPSS Statistics version 25 for analysis. Descriptive statistics (frequencies and percentages) were used to summarize socio-demographic characteristics, awareness of risk factors, and recognition of warning signs. The Chi-square test (χ²) was applied to examine associations between knowledge level categories (excellent, good, fair, poor) and socio-demographic variables such as age, gender, education, occupation, and residence. A p-value less than 0.05 was considered statistically significant.

Ethical Considerations

The study adhered to the principles of the Declaration of Helsinki (2013 revision). Confidentiality of participants was strictly maintained, and no personally identifiable information was collected.

The study included 400 respondents, with the largest age group being 30–44 years (34.0%), followed by 45–59 years (25.5%) and 18–29 years (24.5%), while 16.0% were aged 60 years or above. Gender distribution was nearly balanced, with a slightly higher proportion of males (52.5%) compared to females (47.5%). More than half of the participants were urban residents (56.0%), while 44.0% were from rural areas, ensuring adequate representation of both groups. Educational status showed diversity: 10.5% had no formal schooling, 37.0% had completed secondary education, 35.0% were graduates, and 17.5% held postgraduate qualifications. Occupationally, the largest group comprised skilled or unskilled workers (29.0%), followed by homemakers (25.5%), service/professionals (22.0%), students (15.5%), and retired individuals (8.0%). In terms of economic background, 35.5% of households reported a monthly income between ₹10,001–25,000, 27.0% earned less than ₹10,000, 23.5% were in the ₹25,001–50,000 range, and 14.0% earned above ₹50,000. This distribution reflects a socio-demographically diverse and representative sample of Punjab’s population. (Table 1)

The assessment of stroke risk factors revealed a mixed level of awareness among the general public. Hypertension (69.0%) and diabetes (62.0%) were the most widely recognized contributors, reflecting relatively good awareness of traditional medical risks. More than half of the respondents correctly identified smoking or tobacco use (55.5%) and high cholesterol/obesity (54.5%) as   risk   factors,   while    awareness   of   alcohol consumption as a contributor was slightly lower at 51.0%. Knowledge about lifestyle and less obvious factors was comparatively limited—only 41.0% recognized physical inactivity, 46.5% linked uncontrolled stress, and 43.5% associated excess salt intake with increased stroke risk. Importantly, awareness regarding hereditary influences (32.0%) and advancing age (34.5%) was particularly poor. These findings highlight that while participants are moderately informed about common medical risks, there remain significant gaps in understanding the role of lifestyle, genetic, and age-related factors in stroke development. 

Table 1: Socio-Demographic Characteristics of Participants (n = 400)

Awareness of stroke warning signs showed considerable variability, with some symptoms being well recognized while others were poorly understood. The majority of participants correctly identified sudden difficulty in speaking or slurred speech (73.0%) and sudden weakness or numbness on one side of the body (69.0%) as key warning signs. However, awareness of sudden vision loss (51.0%), dizziness or balance problems (47.0%), and sudden confusion or difficulty understanding speech (49.0%) was moderate. Recognition of severe unexplained headache (44.5%) and difficulty walking or coordination issues (46.0%) was even lower, suggesting underappreciation of these important clinical features. A substantial proportion (64.5%) correctly rejected chest pain as a stroke symptom, reflecting partial clarity in distinguishing stroke from cardiac events. Notably, only 41.0% were familiar with the FAST test, a widely promoted tool for early detection, though encouragingly, 75.5% correctly emphasized the need for immediate hospital or emergency referral. These findings underscore the urgent need to strengthen community education on the full spectrum of stroke warning signs and the importance of timely response. (Table 2)

Table 2: Awareness of Stroke Risk Factors Among Participants (n = 400)

Based on cumulative scoring, only 17.0% of participants demonstrated excellent knowledge regarding stroke awareness, while 30.5% achieved a good score. A significant proportion of respondents fell into the fair (34.5%) and poor (18.0%) knowledge categories. This distribution suggests that while one-third of the population has reasonable awareness, more than half have only fair or poor knowledge levels, placing them at risk of delayed recognition and inappropriate response in stroke situations. These results underscore the need for targeted awareness campaigns to bridge these knowledge gaps. (Table 3)

Table 3: Awareness of Stroke Warning Signs/Symptoms Among Participants (n = 400)

Analysis of socio-demographic determinants revealed significant associations between knowledge levels and factors such as residence, education, and occupation, while age and gender showed no significant impact. Urban participants demonstrated higher proportions of excellent and good knowledge (22.1% and 33.5%) compared to rural respondents, where fair (39.4%) and poor (21.1%) categories predominated (p=0.002). Education was the strongest predictor of knowledge (p<0.001), with only 6.1% of those without formal schooling achieving excellent scores, compared to 30.2% among postgraduates. Similarly, occupational status influenced awareness (p=0.010): service/professionals had the highest excellent knowledge levels (26.7%), whereas homemakers (12.3%) and   skilled/unskilled   workers  (14.8%)  lagged behind. (Table 4).

These findings suggest that structural factors, particularly education, occupation, and place of residence, play a critical role in shaping stroke awareness in Punjab.

Table 4: Overall Knowledge Score Distribution on Stroke Awareness (n = 400)

This study provides valuable insights into the level of awareness regarding stroke risk factors, warning signs, and immediate management among the general public of Punjab. The findings highlight both encouraging aspects and critical gaps that could significantly influence timely recognition, prevention, and management of stroke in this population.

The results indicate that while a majority of participants were able to recognize traditional medical risk factors such as hypertension (69.0%) and diabetes (62.0%), awareness of lifestyle-related and less obvious contributors was considerably lower. For example, just over half correctly identified smoking (55.5%), obesity or high cholesterol (54.5%), and alcohol consumption (51.0%) as risk factors, whereas fewer than half recognized the role of physical inactivity (41.0%), stress (46.5%), or excess salt intake (43.5%). Even more concerning was the very limited recognition of non-modifiable risk factors such as family history (32.0%) and increasing age (34.5%). These findings are consistent with earlier Indian and international studies, which have repeatedly shown that while hypertension and diabetes are widely acknowledged, public knowledge about lifestyle and hereditary risks remains poor. This lack of awareness is particularly significant in Punjab, where tobacco and alcohol use, sedentary lifestyles, and dietary excesses are highly prevalent. (Table 5)

Table 5: Association Between Knowledge Level and Socio-Demographic Variables on Stroke Awareness (n = 400)

In terms of stroke warning signs, classical symptoms such as sudden speech difficulty (73.0%) and weakness or numbness on one side of the body (69.0%) were relatively well recognized. However, awareness of other important symptoms was much lower—vision loss (51.0%), severe headache (44.5%), dizziness or balance problems (47.0%), confusion (49.0%), and difficulty in walking (46.0%). Such gaps could contribute to delays in seeking urgent medical care, particularly in cases where non-classical symptoms predominate. Although a majority of respondents correctly rejected chest pain as a stroke symptom (64.5%), nearly one-third still misattributed it, reflecting persisting misconceptions. A particularly striking finding was that only 41.0% of participants were familiar with the FAST test, despite it being one of the most effective community tools for early stroke recognition. On a positive note, 75.5% of respondents correctly emphasized the need for immediate hospital or emergency referral when stroke was suspected, underscoring some degree of understanding about the urgency of medical intervention.

The overall knowledge score distribution revealed that only 17.0% of participants demonstrated excellent knowledge, while 30.5% had good knowledge. In contrast, more than half fell into the fair (34.5%) and poor (18.0%) categories, indicating widespread gaps in stroke literacy. These results align with findings from other studies in South Asia, which consistently report low levels of awareness compared to Western countries where structured awareness campaigns and public health policies have been more widely implemented. The knowledge deficits observed in this study are particularly concerning in Punjab, given the high burden of non-communicable diseases and the increasing incidence of stroke at younger ages.

The analysis of socio-demographic determinants further highlighted structural inequalities in awareness. Education was the strongest predictor of knowledge, with postgraduates showing markedly higher levels of awareness compared to those with no formal schooling. Occupational status also played a role, with service and professional groups demonstrating significantly higher knowledge than homemakers and unskilled workers. Similarly, urban participants were more knowledgeable than their rural counterparts, likely reflecting better access to healthcare facilities, information, and awareness campaigns. Interestingly, no significant associations were found with age or gender, suggesting that knowledge gaps are widely distributed across demographic groups and not confined to specific age bands or sexes.

Overall, the findings suggest that although there is a basic level of awareness regarding stroke risk factors and warning signs, critical gaps persist, particularly concerning lifestyle-related risks, non-classical symptoms, and knowledge of emergency response strategies. These gaps can directly contribute to delays in hospital arrival and missed opportunities for timely intervention, thereby worsening outcomes. The study therefore underscores the urgent need for comprehensive, community-based health education initiatives tailored to the population of Punjab, with a particular focus on vulnerable groups such as rural residents, those with lower education levels, and non-professional workers [11,13,15].

Strengths and Limitations

A major strength of this study is its inclusion of a socio-demographically diverse population from both urban and rural areas of Punjab, enabling meaningful comparisons across groups. The use of a validated questionnaire with good internal consistency (Cronbach’s alpha 0.81) adds to the reliability of the findings. Furthermore, the online Google Form format ensured wide outreach, cost-effectiveness, and minimized missing responses. However, the study also has certain limitations. Being an online, self-reported survey, it may have excluded digitally disadvantaged populations, particularly among the elderly and lower-income groups. The reliance on self-reported knowledge is subject to recall and social desirability bias. In addition, the cross-sectional design limits causal inference, and the use of a purposive-cum-snowball sampling technique may affect generalizability to the entire population of Punjab.

This study highlights that while awareness of stroke risk factors and warning signs among the general public of Punjab is moderate, critical gaps persist, particularly in recognizing lifestyle-related risks, hereditary factors, and non-classical symptoms. Although many participants were able to identify hypertension, diabetes, and sudden weakness or speech difficulty, knowledge of the FAST test and urgency of emergency management was inadequate in a large proportion. Socio-demographic determinants such as education, occupation, and place of residence were significant predictors of awareness, underscoring the need for targeted, community-oriented educational interventions. Strengthening public health campaigns, integrating stroke literacy into existing NCD programs, and empowering primary healthcare workers and pharmacists to spread awareness can play a pivotal role in reducing delays in stroke recognition and treatment. By bridging these knowledge gaps, Punjab can move closer to reducing the burden of stroke-related morbidity, disability, and premature mortality.

1. Lawrence, R.M., and R. Wilson. “Awareness of Stroke Warning Signs, Risk Factors and Response to Stroke: A Hospital Based Survey.” International Journal of Research in Medical Sciences, vol. 11, 2023, pp. 2550–2553.

2. Pandian, J.D., et al. “Public Awareness of Warning Symptoms, Risk Factors, and Treatment of Stroke in Northwest India.” Stroke, vol. 36, no. 3, March 2005, pp. 644–648.

3. Das, K., et al. “Awareness of Warning Symptoms and Risk Factors of Stroke in the General Population.” Journal of Clinical Neuroscience, vol. 14, no. 1, February 2007, pp. 12–16.

4. Workina, A., et al. “Knowledge of Risk Factors and Warning Signs of Stroke Among Patients with Heart Disease at Tikur Anbessa Specialized Hospital.” Open Access Emergency Medicine, vol. 13, February 2021, pp. 57–66.

5. Mehta, S., et al. “Assessing Public Awareness of Stroke: Knowledge of Warning Signs, Risk Factors, and Treatment Responses.” European Journal of Cardiovascular Medicine, vol. 14, no. 6, November–December 2024, pp. 7–12.

6. Joshi, H.P., et al. “Awareness of Risk Factors and Early Signs of Stroke in High Risk Population of Pune Region.” International Journal of Community Medicine and Public Health, vol. 9, no. 3, 2022, pp. 1332–1337.

7. Chhabra, M., et al. “Assessment of Knowledge on Risk Factors, Warning Signs, and Early Treatment Approaches of Stroke Among Community Adults in North India: A Telephone Interview Survey.” Journal of Neurosciences in Rural Practice, vol. 10, no. 3, 2019, pp. 417–422.

8. Arvind, B.A., et al. “Knowledge and Attitude About Risk Factors and Warning Signs of Stroke Among General Population in Chintamani Taluk, Karnataka.” RGUHS National Journal of Public Health, vol. 2, no. 3, 2017, pp. 27–35.

9. Sirisha, S., et al. “Awareness, Recognition, and Response to Stroke Among the General Public—An Observational Study.” Journal of Neurosciences in Rural Practice, vol. 12, no. 4, 2021, pp. 704–710.

10. Elshebiny, A., et al. “Awareness of Stroke Risk Factors, Warning Signs, and Preventive Behaviour Among Diabetic Patients in Al-Ahsa, Saudi Arabia.” Cureus, vol. 15, no. 2, February 2023, article e35337.

11. Mutairi, B.A., and F.A. Hamaid. “Public Awareness of Stroke Risk Factors, Warning Symptoms, and Significance of Acute Management and Prevention in Jeddah, Saudi Arabia.” International Journal of Medical and Dental Case Reports, vol. 5, no. 10, 2021, pp. 1791–1799.

12. Das, B.K., et al. “Awareness of Stroke Among Elderly Public in Eastern India.” Neurology Asia, vol. 16, no. 2, 2011, pp. 119–126.

13. Patnaik, L., et al. “Awareness of the Warning Symptoms and Risk Factors of Stroke Among Adults Seeking Health Care from a Rural Hospital of India.” Annals of Indian Academy of Neurology, vol. 18, no. 4, October–December 2015, pp. 487–488.

14. Balasundaram, P., et al. “Study on the Public Awareness of Stroke Risk Factors, Symptoms, Treatment and Rehabilitation: A Community Based Cross Sectional Survey from a Tertiary Referral Centre in South India.” National Board Examination Journal of Medical Sciences, vol. 2, no. 9, 2024, pp. 878–887.

15. Vati, J., and P. Sandha. “Knowledge Regarding Risk Factors, Warning Signs, and Immediate Response to Stroke Among Patients Attending General Outpatient Department in a Selected Multispeciality Hospital.” International Journal of Nursing Education and Research, vol. 10, no. 4, 2022, pp. 385–391.

16. Deepthi, S., et al. “Public Awareness of Stroke Recognition, Risk Factors and Access to Appropriate Treatment: A Hospital-Based Cross-Sectional Survey from a Tertiary Referral Centre in Southern India.” Journal of Clinical and Diagnostic Research, vol. 16, no. 7, 2022, pp. OC09–OC13.