This document presents the results of a study on the incidence of lifestyle diseases in the IT industry. The study found high rates of cardiometabolic risk factors like hypertension, obesity, high cholesterol, and diabetes among IT employees. The prevalence of multiple risk factors clustering together increased with higher BMI, weight, and age. It was also higher in employees with shorter heights. The study recommends implementing workplace health promotion programs to increase awareness and encourage lifestyle modifications to reduce disease risk.

1. Case study :
Incidence of Lifestyle Diseases in
IT Industry
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3. Investigator: Dr. Ravindra L Kulkarni
Consultant & Interventional
Cardiologist
MD, FSCAI specialize in clinical
Research and interventional
cardiology.
Practicing in Leading multi specialty
hospitals in Pune.
Involved in health talks, health
check ups and Corporate wellness.
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4. Background
 Increasing trend in NCDs worldwide
(WHO, 2008)
 Contribution of lifestyle factors
 IT industry workers are at risk
◦ Odd working hours
◦ Erratic eating habits
◦ Sedentary work style
◦ Constant stress levels
• Effect on work performance &
productivity
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5. Objectives
1. To establish
prevalence of cardio-metabolic risk factors
in employees of IT industry.
2. To observe clustering of cardio-metabolic
risk factors (CMRF) within
body mass index (BMI), height, weight
& age groups.
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6. Methods
 Observational study
 Data obtained from annual medical health records of
employees (from 2 leading BPO industries in Pune)
 CMRF clustering i.e. ≥ 2 risk factors (IDF 2005)
◦ TG ≥ 150 mg/dl
◦ HDL < 40 mg/dl in males OR <50 mg/dl in females
◦ BP systolic ≥ 130 OR diastolic ≥ 85mmHg
◦ FPG ≥ 100 mg/dl
 ADA 2011 criteria & JNC-7 guidelines used for T2DM,
HTN
 Analyzed across
◦ Height, Weight, BMI Categories
◦ Age Categories
◦ Gender www.justforhearts.org

7. Results
Observations Criteria Total (%) Males (%) Females (%)
(n = 1350) (n = 1063) (n = 287)
IFG FPG ≥ 100 mg/dl 10.0 10.2 9.2
Hypertension SBP ≥ 140 mmHg 19.3 20.1 16.7
DBP ≥ 90 mmHg
Obesity ≥ 30 kg/m2 9.4 8.8 11.5
≥ 27.5 kg/m2 22.5 21.6 25.6
High T. Chole T.Chole ≥200 19.2 20.3 14.9
mg/dl
High TG ≥ 150 mg/dl 23.8 26.6 13.1
Low HDL <40 mg/dl (M) 67.3 60.4 93.1
< 50 mg/dl (F)
High LDL ≥ 130 mg/dl 19.5 19.7 18.5
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8. Results
Overall Prevalence
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9. Prevalence of CMRF clustering
across age groups
Prevalence
< 30 Y < 40 Y <50 Y ≥ 50 Y
Age Groups
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10. Prevalence of CMRF clustering across
BMI groups
WHO Criteria
%
P=0.000
Public health
achievable
targets for Asians
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11. Prevalence of CMRF clustering
across Genders
Prevalence
Gender
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12. Determinants of CMRF
(Logistic Regression)
Independent Groups Sig Odd’s 95% CI
Variables Ratio
Lower Upper
AGE < 31 Y 1.00
≥ 31 < 33 Y 0.002 2.75 1.42 5.29
≥ 33 < 35 Y 0.003 2.71 1.4 5.25
≥ 35 Y 0.012 2.27 1.19 4.32
HEIGHT ≥ 174 cm 1.00
≥ 168 < 174 cm 0.662 1.10 0.71 1.7
≥ 162 < 168 cm 0.061 1.56 0.98 2.51
< 162 cm 0.030 1.90 1.06 3.39
WEIGHT < 63 Kg 1.00
≥ 63 < 71 Kg 0.062 1.58 0.97 2.57
≥ 71 < 79 Kg 0.008 1.98 1.19 3.30
≥ 79 Kg 0.000 3.55 2.09 6.01
GENDER Females 1.00
Males 0.317 0.79 0.5 1.24
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13. Conclusion
1. There is a high burden of cardio-metabolic risk factors in
young employees working in IT industry.
2. The prevalence of CMRF clustering increases with increasing
BMI, body weight & age.
3. The prevalence of CMRF clustering decreases with
increasing height. (i.e. short height = high risk)
4. Need to spread awareness among IT employees about far-
reaching effects
5. Need to initiate Workplace Health Promotion programs
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14. Limitations Future Plans
 Opportunistic analysis • To initiate diabetes
 No data on- prevention program in IT
◦ SES industry.
◦ Family history of DM/ • Impact of a lifestyle
HTN modification program on
◦ Abdominal obesity CMRFs.
(WC) • Use of email & SMS
◦ Tobacco & alcohol technologies
consumption
• Benefits both for the
◦ Duration of exposure to
work style employees and the
 No OGTT was performed employers
• Better industrial outputs
and growth
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