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ISSN: Print -2349-0977, Online - 2349-4387


 
 Table of Contents  
ORIGINAL CONTRIBUTION: NON-COMMUNICABLE DISEASES
Year : 2014  |  Volume : 1  |  Issue : 3  |  Page : 178-185

Prevalence of modifiable and non-modifiable risk factors and lifestyle disorders among health care professionals


1 Department of Community Medicine, Maulana Azad Medical College, New Delhi, India
2 Deputy Medical Superintendent, Maharishi Valmiki Hospital, Pooth Khurd, Delhi, India

Date of Web Publication27-May-2015

Correspondence Address:
Shantanu Sharma
Department of Community Medicine, Maulana Azad Medical College, Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2349-0977.157757

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  Abstract 

Introduction: Health care workers are mentors to general populations for a healthy life. Life style disorders are not just limited to the general population but even the doctors and nurses who guide them on their prevention are also getting victimized. The current study was carried out to collect the data on the lifestyle-associated disorders among health professionals in India. Objectives: The aim was to assess the prevalence and associated risk factors (modifiable and non-modifiable) of lifestyle disorders among Health professionals. Materials and Methods: This was a hospital-based cross-sectional study carried out in a secondary level/block level hospital of north-west Delhi. A study tool based on the World Health Organization (WHO) STEPS questionnaire for assessing non-communicable diseases and their risk factors was used. Fasting venous blood sample was collected to assess the lipid profile and fasting blood sugar. Anthropometric measurements of the participants were also taken. Data were analyzed using SPSS version 17. Results: Of the total 100 participants who consented to participate, 60% were females and 40% were males. The prevalence of diabetes and hypertension among health professionals were 5% and 10%, respectively. There were 52 participants who had abnormal waist-hip ratio. According to the WHO classification for Asians, 42% were overweight, while 22% were found to be obese. Alcohol intake (P=0.005), gender (P=0.00), occupation (P=0.018), total cholesterol levels (P=0.038), and triglycerides levels (P=0.046) had a significant association with waist-hip ratio, whereas alcohol intake (P=0.01), hypertension (P=0.05), moderate intensity sports (P=0.025) were significantly associated with body mass index. Conclusions: The prevalence of risk factors for lifestyle diseases was high among the health professionals. Thus, there is a need to motivate them to practice healthy lifestyle for prevention against lifestyle diseases and that they can advocate their patients.

Keywords: Lifestyle diseases, WHO STEPS, health professionals, risk factors


How to cite this article:
Sharma S, Anand T, Kishore J, Dey BK, Ingle G K. Prevalence of modifiable and non-modifiable risk factors and lifestyle disorders among health care professionals. Astrocyte 2014;1:178-85

How to cite this URL:
Sharma S, Anand T, Kishore J, Dey BK, Ingle G K. Prevalence of modifiable and non-modifiable risk factors and lifestyle disorders among health care professionals. Astrocyte [serial online] 2014 [cited 2020 Sep 27];1:178-85. Available from: http://www.astrocyte.in/text.asp?2014/1/3/178/157757


  Introduction Top


Lifestyle diseases characterize those diseases whose occurrence is primarily based on the daily habits of people and are the result of an inappropriate relationship of people with their environment. Lifestyles are born of a multitude of causes, from childhood determinants to personality makeup to influences in the cultural, physical, economic, and political environments. [1] In recent times, these lifestyle patterns have modified significantly which has led to increasing both physical and mental diseases in the world population. [2]

Lifestyle diseases such as stroke, cancer, heart disease and diabetes are by far the leading causes of mortality in the world, representing 60% of all deaths. In 2005, non-communicable diseases (NCDs) caused an estimated 35 million deaths and contributed to 60% of deaths worldwide. About a quarter of these NCD deaths were in low and middle-income countries. The trend of NCD burden is projected to rise over the next decade, particularly in low- and middle-income countries. As developing countries experience rapid urbanization, citizens are failing to maintain healthy diets or adequate levels of physical activity. In India, 10% of adults suffer from hypertension while the country is home to 25-30 million diabetics. Three out of every 1000 people suffer a stroke. The number of deaths due to heart attack is projected to increase from 1.2 to 2 million in 2010. [3] Demographic transition due to improved living conditions is associated with three fold increase in the prevalence of diabetes in rural India. [4] The report, jointly prepared by the World Health Organization (WHO) and the World Economic Forum says India will incur an accumulated loss of $236.6 billion by 2015 on account of unhealthy lifestyles and faulty diet. The chronic diseases are mainly being caused by a small number of shared risk factors: improper diet, inadequate physical activity, tobacco use and excessive alcohol consumption. [5] Practicing health professionals constitute an important segment of public health care. They have good access to information on disease frequency and determinants. Therefore, knowledge and awareness regarding the health consequences of lifestyle changes are generally expected to be high among clinicians. This in turn could influence the prevalence of lifestyle diseases such as diabetes and hypertension among them. There is a paucity of data on the lifestyle-associated disorders among health professionals particularly in developing countries. Therefore, the present study was conducted to assess the prevalence and associated risk factors (modifiable and non-modifiable) of lifestyle disorders among health professionals.


  Material and Methods Top


Study setting

This was a hospital-based cross-sectional study carried out in a secondary level/block level hospital of north-west Delhi. Maharishi Valmiki hospital is a 150 bedded mutispeciality hospital situated at Pooth Khurd in the peripheral aspect of north-west Delhi. The hospital provides treatment to 8.5 lakhs of the rural area, including bordering of north-west district of Delhi. Of all the 150 working staff, including doctor and nurses in the hospital, 100 gave the consent for the study. Inclusion criteria: All the health professionals including all doctors and nurses in any ward of the hospital who were working in this hospital minimum of 6 months were eligible to participate in the study.

Exclusion criteria

Interns, nursing orderly and pharmacist were excluded.

Data were collected through WHO STEPS questionnaire. After the completion of the questionnaire, weight and height measurement was carried out of each participant. Weight was measured bare footed and light clothes using a digital weighing machine and to the nearest 0.05 kg. Height was measured to the nearest 0.5 cm by using portable height meter after removing shoes, and placing heels together. Outcome variable was obesity defined by using South Asian cut-off of body mass index (BMI >23) [6] and waist-hip ratio. Other dependent variables included in the questionnaire were lipid profile, waist circumference, hip circumference, fasting blood sugar, blood pressure (BP). BP was measured using digital B machine available in the hospital. An average of three readings was recorded finally. All the laboratory tests, including blood sugar, serum cholesterol, high-density lipoproteins (HDL), low-density lipoproteins (LDL), triglycerides (TG) were done in the hospital NAAC accredited lab oratory. The independent variables used in the study were age, monthly income, gender, tobacco use, alcohol use, smoking, drinking alcohol, eating green vegetables and fruits, physical exercise like jogging, lifting weights, walking, cycling, etc. The questionnaire included history of tobacco use like currently using tobacco products such as cigarettes, cigar or pipes; is he/she currently smoking, what is the frequency; does he/she use smokeless tobacco products; are they exposed to passive smoking at home or workplace. The questionnaire on use of alcohol asked if they had consumed it in past 30 days, what was the frequency, how many standard drinks on single occasion, was it taken with meals. They were also asked of their fruits and vegetables intake, number of days they eat fruits and vegetables and number of servings on each day. Questions included type of oil used most often for meal preparation and number of days they eat meals not prepared at home. The questionnaire included questions on physical activity involved in their work whether of vigorous or moderate intensity or if they involved in sports of vigorous or moderate intensity. The details of physical activity included number of days spent per week and number of hours on each day. Time spent sitting or reclining was also asked.

Standard definitions

Health professionals, current smoker, past smoker, current alcohol, past alcohol consumption, physical activity (needs to be defined), hypertension, diabetes.

Statistical analysis

Data were analyzed using software SPSS version 17. Mean and standard deviation was calculated for continuous variables, while proportions of categorical variables were reported. Chi-square was used to find an association between categorical independent variables and dependent variables (BMI and waist-hip ratio) and P ≥0.05 was considered as significant. All the variables with P <0.10 were then put into univariate regression analysis to determine the relationship of each independent variable with the outcomes variable. Multiple logistic regression analysis techniques were applied to select the group of variables independently associated with obesity. Odds ratio and 95% confidence intervals (CI) were reported to interpret the results.


  Ethical Aspects Top


The study subjects were explained the purpose of the study and assured confidentiality. Written informed consent was taken before taking detailed information. Ethical clearance was obtained from the Institutional Ethics Committee.


  Results Top


Demographic profile of participants

A total of 100 health professionals were included in the study. Out of 100 participants, 60% were females and 40% were males. Majority of the participants were nurses (58%), and were educated up to post high school (54%). The highest number of nurses belonged to the age group 31-40 years (47%). Ninety-eight percent of health workers had monthly family income more than 30,375 [Table 1].
Table 1: Socio-demographic Profile of the Study Participants (n=100)


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Drinking and smoking habits

Of all the Health professionals, 12.5% were currently using tobacco or one of its products. Only 5% of the health professionals smoke, all of whom were males and four out of five used to smoke daily (80%). Two of them started smoking before adulthood (<20 years) (40%) and rest three in their third decade of life (60%). Four out of five were using manufactured cigarettes (80%), and on an average smoking three cigarettes per day. All of these used to smoke daily in the past as well. One of them was also using smokeless tobacco and one had left after using in the past. A few (7%) workers reported to have been suffering from exposure of passive smoking at workplace and one of them at home also. About half of the male doctors were alcoholics. On an average they used to consume 4-5 pegs last year. In the past 30 days, 12% had consumed alcohol. The mean pegs consumed by the workers in the past 30 days were 2 (CI: 1-14).

Intake of fruits and vegetables

All of them consumed alcohol with food. Fruits were not a part of the diet in 9% of the workers. Only one-third of the workers (34%) were consuming fruits regularly. Among the rest, 44% consumed fruits 3-5 times a week and 9% consumed only once or twice in a week. Those who consumed fruits regularly used to consume at an average of 1-2 fruits daily. Almost 100% used to eat vegetables daily. The average number. of servings of vegetables per day was 2. Approximately, 87% of the workers regularly used to eat vegetables. One-third of the workers (34%) ate meals that were not prepared at home only occasionally or just once a month and 24% workers ate outside meals once in 2 weeks. Only 5% were eating meals outside every week. Vegetable oil was most often used for meal preparation in households of 76% of the workers. Some 7% of the workers also used butter as a major oil or fat for cooking meals often.

Habits of physical activity in life

One-fifth (24%) of the workers said that their work involved vigorous-intensity activities that causes large increase in breathing rate or heart rate for at least 10 min continuously (majorly of whom were nurses). Mean number of days their work involved vigorous-intensity activity was 3 days/week and the mean number of hours for which their work involved intensive activity on a typical day was 1.75 h. Approximately half of the workers (53%) replied that their work involved moderately intensity activity that caused small increase in heart rate for at least 10 min continuously and the mean number of days their work involved such moderate-intensity activity is 4 and means hours was 1.6. As filled in the proforma, about 63% walked or used a bicycle for at least 10 min continuously to get to and fro from places with a mean of 6 days in a week and 30 min on a typical day. Only 21% of the workers played vigorous-intensity sports for at least 10 min continuously with a mean of 3 days in a week and 30 min on a typical day. Less than one-fourth (23%) of the workers used to play moderate-intensity sports with a mean of 5 days in a week and 30 min on a typical day.

Prevalence of diabetics, hypertension and obesity

The prevalence of hypertension among health professionals was 10%. Out of 10 hypertensives, 7 were taking medicines and rest others taking either non-allopathic medicines or on controlled salt intake. Among the total, only five workers, despite being in the medical field, had never got their sugar levels measured; all of whom were over 30 years of age. The prevalence of diabetes among health professionals was 5%. Of the five, four were taking allopathic medicines and one on diet control. BP among 6 out of 10 hypertensives was high despite being on medications and 4 new cases with BP with more than 140 (systolic) or 90 mmHg (diastolic) were identified. According to the study done, 52% of the health professionals had abnormal waist-hip ratio. The cut-off being 0.85 for women and 0.95 for men in the study. [7] Mean BMI was 24.57± 4.3. The waist-hip ratio ranged from 0.66 to 2.53. A major chunk (52%) of the workers were overweight, some (12%) were obese according to WHO criteria for Asians [Table 2]. [8]
Table 2: Body Mass Index of the Study Group


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Lipid profile of participants

Only 7% of the health professionals had total cholesterol levels >200 mg/dl, while 12% workers had TG levels >150 mg/dl. HDL levels <40 mg/dl was found among 67.2% of the nurses and 47.6% of the doctors (P=0.03).

To prove the association between predictors of obesity among health professionals and indicators of obesity like waist--hip ratio and BMI, chi-square test was done. Among all the factors tested only the following predictors, alcohol intake (P=0.005), gender (P=0.00), occupation (P=0.018), total cholesterol levels (P=0.038) and TG levels (P=0.046) had a significant association with waist-hip ratio shown in [Table 3]. Similarly, alcohol intake (P=0.01), hypertension (P=0.05), moderate intensity sports (P=0.025) had a signification association with BMI as shown in [Table 4].
Table 3: Association Between Predictors of Obesity and Waist-hip Ratio


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Table 4: Association Between BMI and its Predictors


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  Discussion Top


Obesity is assuming epidemic proportions worldwide. It is also becoming a common health problem in Indian population. The current cross-sectional study re-affirmed this finding. A high percentage of health professionals were found to be overweight and obese. In spite of being the health guide to others, health professionals themselves are falling into unhealthy population group and hence getting predisposed to the development of chronic lifestyle diseases. Doctors are a respected source of health related information and are well positioned to provide preventive health counseling to patients. Thus, encouraging healthy-lifestyles among them would result in more likelihood of them providing preventive and health promotive counseling to their patients. [9] The present study assessed modifiable behavioral risk factors like tobacco use, alcohol intake, physical activity and dietary habits among healthcare workers. It showed that the occurrence of NCDs among healthcare workers is high. Prevalence of tobacco use was 12.5%. It was significantly associated with male gender and doctors as a profession. The findings are similar to another study by Sarna et al., [10] where the authors reported 12% prevalence of smoking among healthcare workers.

The prevalence of tobacco use was still low when compared with what was reported in some other countries like China, where a study by Smith et al. reported that 36.3% health workers used to smoke. [11]

This high prevalence of tobacco use among healthcare workers is a cause of concern because it has been shown that a significant barrier to anti-tobacco counseling by healthcare workers is self-use of tobacco. Thus it is important that healthcare workers must not engage in tobacco use practices. [12]

For alcohol use, it was found that more than half of the doctors reported positively about alcohol use. An interesting finding was that postgraduate professionals reported more of alcohol use than lower education classes. Alcohol use was significantly associated with male gender, doctors, and higher education status. The findings are higher when compared with a study carried out in South Africa by Okeke et al. where 22% workers reported alcohol use. [13] Another study conducted in Kenna and Lewis found that gender was significantly associated with alcohol use like in the present study.[14]

A significantly higher percentage of females had abdominal obesity as compared with males. This may be the reason that prevalence of abdominal obesity was significantly high among nurses than doctors. This is comparable to the findings reported in another study by Haddad et al. where higher percentage of female healthcare workers were obese when compared with males. [15]

Blood investigation for total cholesterol levels and TG levels were also done. The results for the above parameters are not statistically significant among education classes, gender, and profession class. Total cholesterol was more than 240 mg/dl in only 1.7% of subjects. High TGs were found in only 10% of males. Another study conducted in Taiwan by Lin and Li found 9% doctors and 5% of nurses having higher cholesterol levels. [16]

A total of 3.4% of nurses had lower HDL levels. These findings are lower than that was reported by another study carried out in Turkey by Oguz et al., who found that 31.3% of nurses had lower HDL levels. [17]

The present study emphasize on behavior change campaign among health professionals to motivate them to adopt healthy life style and prevention of NCDs.


  Limitations of the Study Top


One of the greatest limitations of the study was its study design. Results were based on the limited period, which may vary over different periods of time. However, the study highlights the emerging risk of chronic lifestyle diseases among healthcare professionals as majority of participants were found to be overweight and obese.

 
  References Top

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Priya HM, Bhat SS, Sundeep Hegde K. Prevalence, Knowledge and Attitude of Tobacco Use Among Health Professionals In Mangalore City, Karnataka. Oral Health Community Dent 2008;2:19-24.  Back to cited text no. 12
    
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Oðuz A, Saðun G, Uzunlulu M, Alpaslan B, Yorulmaz E, Tekiner E, et al. Frequency of abdominal obesity and metabolic syndrome in healthcare workers and their awareness levels about these entities. Türk Kardiyol Dern Arº 2008;36:302-9.  Back to cited text no. 17
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]


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