INTRODUCTION:

Cardiovascular diseases remain a leading cause of mortality worldwide, with occupational stress and lifestyle behaviors recognized as key modifiable risks.^1,2 Cardiovascular conditions remain the leading contributor to mortality worldwide, with stress, poor diet, inactivity, and substance use recognized as modifiable drivers of disease^4,6Within professional groups, employees in the information technology (IT) sector are particularly vulnerable due to extended work hours, high performance demands, and predominantly sedentary routines.^9,10

Persistent stress not only disrupts neuroendocrine function but can also foster unhealthy coping behaviors that elevate cardiovascular risk⁵.

India’s rapidly expanding IT workforce faces unique challenges in this regard. Long hours spent in front of digital screens, coupled with intense workload expectations, contribute to psychological strain and lifestyle imbalances. With the parallel rise of cardiovascular disease across the country, examining the interplay between work stress and health-related habits in this occupational group becomes especially important. Stress and psychological distress have been shown to adversely impact not only occupational groups but also family and community settings, underscoring the pervasive effects of unmanaged stress on well-being.¹⁹

This study was therefore conducted to assess levels of stress, lifestyle factors such as activity, sitting time, sleep quality, and diet, and their relationship among IT professionals in Chennai. By mapping these risk patterns and integrating the perspectives of workers themselves, the findings are intended to guide workplace health promotion programs and nurse-led preventive initiatives tailored to the IT setting.

OBJECTIVES:

1. To determine the level of occupational stress among IT professionals.

2. To assess the prevalence of physical inactivity among IT professionals.

3. To evaluate the quality of sleep among IT professionals.

4. To identify lifestyle behaviours (dietary practices, tobacco use, alcohol consumption, sitting time) contributing to heart risk among IT professionals

MATERIALS AND METHODS:

Study Design and Setting:

A descriptive cross-sectional design was adopted to study occupational stress and cardiovascular-related lifestyle behaviors among IT professionals in Chennai.

Participants and Sampling:

A total of 135 professionals working in the IT sector participated. Eligibility required at least one year of work experience in IT and voluntary consent to take part. Participants were recruited through purposive sampling.

Data Collection:

Information was obtained using a structured questionnaire distributed via Google Forms. The tool gathered demographic details and assessed:

· Stress: Measured using WRSI-8.

· Physical activity: Calculated as minutes of moderate activity plus twice the minutes of vigorous activity, expressed as MVPA.

· Sedentary behavior: Reported sitting time in hours per day.

· Sleep: Both duration and quality, rated on a 1–5 scale (1 = poor, 5 = very good).

· Dietary habits: Evaluated through a diet index with scores representing unhealthy, mixed, or healthy patterns.

· Tobacco and alcohol use: Recorded as yes/no responses.

· Awareness: Checked through questions on cardiovascular risk factors and warning signs.

Classification Frameworks:

· Stress levels: Low (0–8), Mild (9–16), Moderate (17–24), High (25–32).

· Physical activity (MVPA): Inactive (<150 minutes/week), Meets recommendation (150–299 minutes/week), Optimal (≥300 minutes/week).

· Sleep quality: Poor (1–2), Fair (3), Good (4–5).

DATA ANALYSIS:

The dataset was analyzed using descriptive statistics such as frequency and percentage. Associations were tested with chi-square analysis, while Pearson and Spearman correlations explored relationships between continuous variables. Regression models were applied to examine predictors of lifestyle risk. Subgroup analyses considered gender and work patterns. A significance threshold of p < 0.05 was used.

RESULTS:

Table 1: Frequency And Percentage Distribution Of The Demographic Variables N=135

Demographic variables

Frequency

Percentage %

Age in years

25-35

36-45

46-55

>55

60.0

22.2

13.3

4.5

Gender

Male

Female

65.2

34.8

Education level

Graduate

Post graduate

65.8

34.2

Years in IT / Experience

7-10

4-6

1-3

< 1

57.0

21.5

19.3

2.2

Work Pattern

Hybrid

On-site

Fully remote

45.2

39.3

15.6

Work Hours/Day

8–9

10-11

=12

54.1

27.4

11.9

6.7

Table 1 presents the demographic profile of the participants. The majority of respondents were between 25–35 years of age (60%), followed by those aged 36–45 years (22.2%), with smaller proportions in the 46–55 years (13.3%) and above 55 years (4.5%) categories. Most participants were male (65.2%), and 34.8% were female. In terms of education, a larger proportion were graduates (65.8%), while 34.2% were postgraduates.

Regarding work experience in the IT field, more than half had 7–10 years of experience (57%), while 21.5% reported 4–6 years, 19.3% had 1–3 years, and only 2.2% had less than 1 year of experience. With respect to work pattern, nearly half worked in a hybrid model (45.2%), while 39.3% worked on-site and 15.6% worked fully remote. Most participants reported working 8–9 hours per day (54.1%), followed by 10–11hours (27.4%), while 11.9% worked less than 8 hours and 6.7% reported ≥12 hours of work per day.

Table 2. Prevalence of Stress, Lifestyle Behaviors, and Risk Factors N=135

S. No.

Variables

Frequency

Percentage %

Level of stress

a. Moderate

b. Mild

c. High

47.41

34.07

17.9

MVPA Level

a. In active

b. Moderately active

c. Active

69.6

21.5

8.9

Sitting Category

a. >9 h- High

b. 6-8 hours- Moderate

121

89.6

10.4

Sleep Duration

a. Short (<7h)

b. Optimal (7-8h)

64.44

35.56

Quality of sleep

a. Good (4–5)

b. Fair (3)

c. Poor (1–2)

66.7

26.7

6.7

Diet index

a. Mixed (5–8)

b. Healthy (9–12)

c. Unhealthy (0–4)

114

84.4

10.4

5.2

BMI Category

a. Normal

b. Overweight

c. Underweight

d. Obese

28.89

20.0

15.56

35.55

Tobacco use

a. No

b. Yes

127

94.07

5.93

Alcohol use

a. No

b. Yes

108

80.0

20.0

10.

Comorbidity

a. Obesity

b. Diabetes

c. High cholesterol

d. Hypertension

e. Vascular conditions

35.55

20.74

17.04

15.56

10.37

Among the 135 IT professionals surveyed, the majority reported moderate stress levels, with 70% categorized as physically inactive based on MVPA minutes. Extended sitting was highly prevalent, with nearly 90% spending ≥9 hours per day in sedentary activities. Regarding sleep, one-third reported short sleep duration (<7 hours), while about 33% rated their sleep quality as poor or fair. Tobacco use was reported by 5.9% of participants, and 12% reported alcohol consumption. With respect to nutritional status, 35.5% of the sample were classified as obese, 20% as overweight, and 15.6% as underweight, while only 28.9% fell into the normal BMI range. Comorbidities were also common: obesity (25.9%), diabetes (20.7%), high cholesterol (17.0%), and hypertension (15.6%) were most frequently reported. Importantly, the majority of participants exhibited clustering of multiple risk factors, with more than half having at least two concurrent risks, highlighting the elevated cardiovascular health burden in this occupational group.

Figures 1 Distributions of MVPA

Figures 2 Distributions of sleep quality.

ANALYTICAL RESULTS:

Pearson correlation between stress score and MVPA was weak and nonsignificant (r=0.13, p=0.155). Spearman correlation yielded rho=0.00, p=0.993. Stress score showed no significant correlation with awareness (rho=-0.06, p=0.514). Chi-square tests revealed no significant associations: Stress × MVPA (χ², p=0.144), Stress × Sleep Quality (χ², p=0.092).

DISCUSSION:

The study assessed stress and lifestyle behaviors linked to cardiovascular risk among IT professionals. Findings show that moderate levels of stress were common, alongside a clustering of unfavorable lifestyle practices. Although statistical associations between stress and physical activity or sleep were not significant, the coexistence of multiple risk factors indicates a concerning overall burden.

Objective 1 – Stress levels. Nearly half of participants reported moderate stress, reflecting the occupational demands of IT work. Similar observations have been documented in prior studies among technology employees in India ^5,15. Although fewer participants fell into the high-stress category, the prevalence of moderate stress highlights a considerable need for intervention. Prolonged exposure to occupational stress has been linked with sympathetic activation and long-term cardiovascular consequences^4,17.

Objective 2 – Lifestyle patterns. The results demonstrated widespread inactivity and excessive sitting, with about 70% classified as physically inactive and nearly 90% sitting for nine or more hours daily. These findings align with earlier evidence showing that prolonged sedentary behavior independently contributes to CVD outcomes ³(Biswas et al., 2015). Sleep quality was suboptimal for a third of participants, and only a small fraction adhered to a healthy diet. Tobacco and alcohol use were less common, but still contribute to risk clustering. Together, these behaviors mirror earlier reports that identified poor diet, lack of exercise, and substance use as key contributors to cardiovascular disease ^7,8.

Objective 3 – Stress and lifestyle associations. Although stress scores did not significantly correlate with MVPA or sleep quality, the co-occurrence of stress with sedentary behavior is clinically meaningful. Prior evidence suggests that chronic stress diminishes motivation to exercise and encourages passive coping mechanisms⁴. The absence of statistical significance in this study may indicate that sedentary habits are already widespread in this occupational group, reducing variability for correlation tests. The coexistence of stress, obesity, and other comorbidities such as diabetes and hypertension observed in this study mirrors earlier findings that reported a strong association between occupational stress, obesity, and related health problems among professionals.¹⁸

Objective 4 – Subgroup patterns. Male employees and those in hybrid work arrangements reported higher stress and more sedentary time compared to their counterparts. This suggests gendered differences in coping and the impact of work arrangements that blur boundaries between professional and personal life. Previous occupational health research has highlighted similar variations in stress exposure and coping strategies.^{9,10,
11,12,13,14,16}

Qualitative insights. Participants recommended practical solutions such as incorporating daily walking or yoga, limiting fast food intake, taking brief breaks from prolonged sitting, practicing meditation, and ensuring adequate sleep. Many also emphasized the importance of preventive health check-ups and organizational wellness initiatives. These suggestions are consistent with global health guidelines and highlight the value of involving employees in workplace health planning.

Overall, while statistical associations between stress and lifestyle behaviors were weak, the combination of multiple risks presents a significant threat to cardiovascular health.¹⁷ The results emphasize the importance of workplace wellness strategies, including stress management, physical activity promotion, and healthier food environments, with a central role for nurses in leading and sustaining such programs. The findings reinforce that unmanaged stress, whether in professional or domestic contexts, contributes to psychological distress and poor health outcomes.¹⁹

NURSING IMPLICATIONS:

According to the study's findings, nurses play a vital role in promoting health and preventing illness among working professionals. Stress management, physical activity promotion, and sleep hygiene education are among the workplace wellness initiatives that occupational health nurses can create and carry out. Regular health screenings, cardiovascular risk factor monitoring, and lifestyle counseling on healthy eating, quitting smoking, and relaxation techniques are all things that nurses can do. By incorporating evidence-based practices such as yoga, mindfulness training, and ergonomic modifications, stress and sedentary risks can be reduced. Additionally, nurses advocate for workplace policy changes that establish flexible schedules and encourage healthy behaviors.

RECOMMENDATIONS:

Based on the findings, the following actions are suggested:

1. Workplace health programs should prioritize stress reduction strategies, promotion of exercise, and sleep hygiene education tailored to IT professionals.

2. Routine cardiovascular risk assessments should be conducted, with nurses actively involved in monitoring and counseling.

3. Ergonomic adjustments and short activity breaks should be encouraged to minimize prolonged sitting and its negative health effects.

4. Awareness campaigns focusing on modifiable cardiovascular risks should be regularly organized to improve knowledge and promote healthy self-care.

5. Future research should employ objective measures of stress and physical activity, include longitudinal follow-up, and examine the effectiveness of targeted workplace interventions.

CONCLUSION:

This study highlights that IT professionals face a substantial burden of cardiovascular risk due to the combined effects of occupational stress, extended sedentary time, insufficient physical activity, and inadequate sleep. Although stress did not show a strong statistical relationship with individual behaviors such as exercise or sleep quality, the clustering of multiple risks is concerning. The findings emphasize the need for comprehensive health promotion initiatives in IT workplaces. Nurses, with their expertise in prevention and health education, can play a central role in designing and implementing strategies focused on stress management, lifestyle modification, and cardiovascular risk screening. Future investigations should address current limitations by using longitudinal designs, objective measurement tools, and larger, more diverse samples to strengthen the evidence base for workplace interventions.

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Received on 16.09.2025 Revised on 08.12.2025

Accepted on 28.01.2026 Published on 30.04.2026

Available online from May 02, 2026

Asian J. Nursing Education and Research. 2026;16(2):97-101.

DOI: 10.52711/2349-2996.2026.00020

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