Case Study: Incidence of Lifestyle Diseases In IT Industry

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There has been an increasing trend in non-communicable diseases worldwide. Lifestyle
factors contribute to this rising prevalence. IT industry workers face many health challenges
due to shift duties, odd working hours, erratic eating habits, sedentary lifestyle (desk job)
& constant stress levels; which can hamper their performance. This study throws light on
current health scenario of IT industry employees.

Aim was to establish prevalence of cardio-metabolic risk factors in employees of IT
industry.& to observe clustering of cardio-metabolic risk factors within body mass index
(BMI) & age groups.

Healthcare Expert team who conducted this study : Dr R. L. Kulkarni, Dr C.S. Yajnik , Ms
Tejas . Y. Limaye, Dr Manisha R .Deokar & Dr Rasika M.Phutane

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Case Study: Incidence of Lifestyle Diseases In IT Industry

  1. 1. Case study :Incidence of Lifestyle Diseases in IT Industry www.justforhearts.org
  2. 2. Just For Hearts Rich Experience of Preventive health and Wellness. Serve an individual health requirements, Family health care, corporate wellness with Cardio Wellness room. 24*7 assistance available. Specialized doctors and healthcare professionals registered to cater your needs. Onsite activities such as health talks, health screenings, health check up, community events etc. 100% return policy incase of unsatisfactory services www.justforhearts.org
  3. 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. www.justforhearts.org
  4. 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 www.justforhearts.org
  5. 5. Objectives1. 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. www.justforhearts.org
  6. 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. 7. ResultsObservations Criteria Total (%) Males (%) Females (%) (n = 1350) (n = 1063) (n = 287) IFG FPG ≥ 100 mg/dl 10.0 10.2 9.2Hypertension 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 25.6High 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 www.justforhearts.org
  8. 8. ResultsOverall Prevalencewww.justforhearts.org
  9. 9. Prevalence of CMRF clustering across age groupsPrevalence < 30 Y < 40 Y <50 Y ≥ 50 Y Age Groups www.justforhearts.org
  10. 10. Prevalence of CMRF clustering across BMI groups WHO Criteria% P=0.000 Public health achievable targets for Asians www.justforhearts.org
  11. 11. Prevalence of CMRF clustering across GendersPrevalence Gender www.justforhearts.org
  12. 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 www.justforhearts.org
  13. 13. Conclusion1. 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 effects5. Need to initiate Workplace Health Promotion programs www.justforhearts.org
  14. 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 www.justforhearts.org
  15. 15. Free To Discuss in Public ForumJustfor Hearts Public forum is a plat form to discuss your health related questions.You can register and enter our Public Forum.Click here to Discuss more. Free Public Forum www.justforhearts.org
  16. 16. Follow Us OnTwitter : JustforHearts www.justforhearts.org

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