The Association between Chronic Diseases and Work Productivity among Public Health Staff in Kota 

Bharu District

Nurul Ain Mohd Emeran1, Rohaida Ismail2,, Wan Norlida Ibrahim1

1

1 Department of Community Medicine, School of Medical Science, Universiti Sains Malaysia (HealthCampus).

2 Public Health Division, Kelantan State Health Department, Ministry of Health Malaysia

• Introduction• Objectives• Methodology• Results• Discussions• Conclusions• Recommendations• References• Acknowledgment

2

Outline

INTRODUCTION

3

Studies have been done to show the effect ofchronic diseases on the quality of life & workproductivity.

• Socioeconomic background• Health status• Workplace environment• Relationship with the employer or co‐workers• Salary satisfaction

4

The association

(Serxner et al., 2001; Solem et al., 2013; Steiner et al., 2004; Williams et al., 2009) 

Workers with chronic diseases have been shown tohave negative impact on productivity level

1. Suffered more work‐loss days per year.2. Reported more absenteeism.3. Having higher rate of presenteeism (working

while sick).4. High sickness absence.

5

Negative Impact

(Boles et al., 2004; Janssens et al., 2012; Tunceli et al., 2005)

• A ratio of a volume measure or dimension of outputto a volume measure or dimension of input use.

• A measure of the efficiency with which anorganization use the resources or inputs to producevaluable outputs such as products or services.

(OECD, 2001)

6

Productivity

7

Health & Work Productivity

Good health condition

High work productivity

High performing organization

Good governmental 

outcome

(Boles et al., 2004)

Working Together for Health(WHO, 2006)

• To protect & improve thehealth of their communities.

• Each member contributesdifferent skills & performsdifferent functions.

• Empower people abouthealth issues, enforce laws &regulations and ensureoccupational & environmentalsafety in the community.

8

Health Workers

• Healthy workforce :Lower health care expenditures to bespent by the employer or government.

Improves organizations’ productivity.

9

Healthy worker

(Serxner et al., 2001)

10

Public Health Workers

As crucial as other production labor 

force.

Important promoters & role models for maintaining a healthy 

lifestyle for the general population.

Function in evaluate effectiveness, accessibility & 

quality of the health services.

Involved in promotion of health & prevention of 

• Communicable diseases• Non‐communicable diseases • Environmental health.

Not just individuals but are integral 

parts of functioning health teams.

11

Our Prevalence

Prevalence (%)

Malaysia Kelantan Government employee

1. Overweight 29.4 31.5 34.22. Obesity 15.1 16.2 20.13. Diabetes mellitus 7.2 8.0 6.04. Hypertension 12.8 11.1 11.05. Hypercholesterolemia 8.4 3.6 11.96. Current smoker 19.3 18.7 25.5

(National Health and Morbidity Survey, 2011)

Prevalence of Nutritional Status, Self Reported Cardiovascular Diseases & Smoking Status among Malaysian

1. To describe the proportion of chronicdisease & distribution of work productivityamong public health staff in Kota BharuDistrict.

2. To determine the association betweenchronic diseases and work productivityamong public health staff in Kota BharuDistrict.

12

OBJECTIVES

• A cross‐sectional study

• 2 months duration : 1st February 2015 to 31stMarch 2015

• 363 workers from Public Health Division ofKelantan State Health Department in KotaBharu.

• Sampling method : Simple random sampling

13

METHODOLOGY

Inclusion criteria

• Duration of service at least 1year in Kelantan State HealthDepartment

Exclusion criteria

• Pregnant

STUDY CRITERIA

14

Questionnaire• Sociodemographic data

• Health status

• BMI

• Underlying chronic diseases

• Work productivity

• Stanford Presenteeism Scale questionnaire

• Reported days of emergency leaves

• Reported days of sick leaves

15

TOOLS 

• Presenteeism• Number of days with unproductive time while at workbecause of health problems.

• The presenteeism was measured using self‐administeredStanford Presenteeism Scale (SPS‐6) questionnairedeveloped by Koopman et al., (2002).

• Absenteeism• Number of days absent from work because of illness ordisease related to health (on leave).

16

OPERATIONAL DEFINITION

• Sickness absence• A person who was absent from work with certified sickleave/MC in 2014.

• Low work productivity described as having one or morecharacteristics :‐1. Absenteeism (missed ≥ 1 day of work) OR2. High presenteeism (high presenteeism score from

Stanford Presenteeism Scale) OR3. High sickness absence (missed ≥ 10 days of work)

• Analysis : Simple & multiple logistic regression analysis

17

OPERATIONAL DEFINITION

RESULTS

18

19

RESULTS

Table 1: Sociodemographic characteristic of public health staff in Kota Bharu (n=363).

Variables n (%)   

Age (mean±sd) 37.5±8.5

Duration of service (mean±sd) 11.0±10.0

GenderMaleFemale

115 (31.7)248 (68.3)

Educational levelPrimary/SecondaryTertiary

119 (32.8)244 (67.2)

OccupationDoctors/ProfessionalClerk/Support staffParamedics

35 (9.6)57 (15.7)

271 (74.7)

WorkplaceState Health DepartmentDistrict health officeHealth clinic

15 (4.1)56 (15.4)

292 (80.4)

20

RESULTS

21

RESULTS

Low work productivity = +absenteeism OR +high presenteeism OR +high sickness absence

Table 2 : Multiple logistic regression analysis of factors associated with low work productivityamong public health staff in Kota Bharu (n=363).

VariablesUnivariate analysis Multivariate analysis

Crude OR 95% CI Adjusted OR 95% CI p value

Female 0.62 0.38 ‐ 1.03 0.57 0.32 ‐ 0.99 0.049

Clerk/Support staff* 0.45 1.22 ‐ 7.20 3.08 1.17 ‐ 8.11 0.023

Paramedics* 0.36 1.33 ‐ 5.55 2.30 1.08 ‐ 4.94 0.032

Overweight/Obese 0.89 0.57 ‐ 1.40 ‐ ‐ ‐

Diabetes mellitus 6.41 1.94 ‐ 21.22 5.40 1.54 ‐ 18.99 0.009

Hypertension 7.09 2.50 ‐ 20.11 3.43 1.13 ‐ 10.35 0.029

Dyslipidemia 19.56 4.70 ‐ 81.41 11.87 2.79 ‐ 50.50 0.001

Arthritis 2.22 0.63 ‐ 7.82 ‐ ‐ ‐

Asthma/COAD 1.42 0.69 ‐ 2.92 ‐ ‐ ‐

*As compared to doctors & professionals 22

RESULTS

DISCUSSIONS

23

24

Prevalence of NCD

Malaysia Kelantan Government employee

Study sample

1. Overweight 29.4 31.5 34.2 40.8

2. Obesity 15.1 16.2 20.1 14.0

3. Diabetes mellitus 7.2 8.0 6.0 11.6

4. Hypertension 12.8 11.1 11.0 16.0

5. Hypercholesterolemia 8.4 3.6 11.9 19.3

6. Current smoker 19.3 18.7 25.5 9.1

Prevalence of Nutritional Status, Self Reported Cardiovascular Diseases & Smoking Status among Malaysian (NHMS III) versus Public Health Workers in Kota 

Bharu

• Male workers have higher odds of low workproductivity when compared to female.

• Long spell of sickness absence among male clerical andsupport staff thus impaired their productivity.

• No relation between work demand and sicknessabsence among female workers.

25

Gender & work productivity

(North et al., 1996)

• Lower grade staff reported to have 2 to 3 times higher oddson having lower work productivity.

• Lower rate of sickness absence in portraying workproductivity among higher officer as it strongly associatedwith high levels of control among them.

• Lower status occupations tend to be characterized by lowcontrol & have fewer ways of coping with high work demands

• They are more likely to be associated with high rates ofsickness absence.

26

Job rank & work productivity

(Bustillos et al. , 2014 )

(North et al., 1996)

Being a worker with certain chronic diseases (e.g DM, hypertension,dyslipidemia) shown to have higher odds of low work productivity.

Workers with DM reported more work‐loss day, increased worklimitation, reported more absenteeism & furthermore failed tomeet the productivity standard.

Hypertensive workers had almost 30% higher risk to experienceabsenteeism.

Employee who self‐identified themselves as havingdyslipidemia showed significant amount lost in work time tosickness absence.

27

Chronic diseases & work productivity

(Buton et al., 1999; Horward and porter, 2014; Tunceli et al., 2005; Williams et al., 2009)

• Chronis diseases leads to poor health andexhaustion among workers.

• These consequently lead to presenteeism.

• Sickness presenteeism is a risk factor for futuresickness absence and furthermore loss inproductivity level.

(Bergstrom et al., 2009)

28

The Consequences

• Public health workers in Kota Bharu have higherprevalence of overweight, diabetes melitus,hypertension and dyslipidemia.

• Male, low rank position workers & workers withcertain chronic diseases are at higher risk oflow work productivity.

29

CONCLUSIONS

• Awareness & wellness program in promotinghealthy lifestyle among healthcare personnelspecifically male & low rank workers.

• Primary prevention, early detection, propertreatment & prevent complications.

• Ensuring optimum clinical management forworkers with chronic disease(s).

• Further disease specific study to explore thepathways on how these specific diseases leadsto low work productivity.

30

RECOMMENDATIONS

• Bergström, G., Bodin, L., Hagberg, J., Aronnson, G., & Josephson, M. (2009). Sickness presenteeism today, sickness absenteeism tomorrow? Aprospective study on sickness presenteeism and future sickness absenteeism. Journal of Occupational and Environmental Medicine, 51, 629‐638.doi:10.1097/JOM.0b013e3181a8281b

• Boles, M., Pelletier, B. & Lynch, W. (2004). The relationship between health risks and work productivity. Journal of Occupational and EnvironmentalMedicine, 46(7), 737‐745.

• Burton, W. N., Conti, D. J., Chen, C.‐Y., Schultz, A. B. & Edington, D. W. (1999). The role of health risk factors and disease on worker productivity.Journal of Occupational and Environmental Medicine, 41(10), 863‐877.

• Bustillos, A. S., Vargas, K. G. & Gomero‐Cuadra, R. (2015). Work productivity among adults with varied Body Mass Index: Results from a Canadianpopulationbased survey. Journal of Epidemiology and Global Health, 5(2), 191‐199.

• Howard, J. T. & Potter, L. B. (2014). An assessment of the relationships between overweight, obesity, related chronic health conditions and workerabsenteeism. Obesity Research & Clinical Practice, 8(1), e1‐e15.

• Janssens, H., Clays, E., Kittel, F., De Bacquer, D., Casini, A. & Braeckman, L. (2012). The association between body mass index class, sicknessabsence, and presenteeism. Journal of Occupational and Environmental Medicine, 54(5), 604‐609.

• Koopman, C., Pelletier, K. R., Murray, J. F., Sharda, C. E., Berger, M. L., Turpin, R. S., Hackleman, P., Gibson, P., Holmes, D. M. & Bendel, T. (2002).Stanford presenteeism scale: health status and employee productivity. Journal of Occupational and Environmental Medicine, 44(1), 14‐20.

• Ministry of Health (2011). National Health and Morbidity Survey 2011 : Non Communicable Disease. Volume II.• North, F. M., Syme, S. L., Feeney, A., Shipley, M. & Marmot, M. (1996). Psychosocial work environment and sickness absence among British civil

servants: the Whitehall II study. American Journal of Public Health, 86(3), 332‐340.• Organisation for Economic Co‐Operation And Development (OECD). (2001). OECD Manual : Measurement of Aggregate and Industry‐Level

Productivity Growth. Retrieved from http://www.oecd.org/std/productivity‐stats/2352458.pdf• Serxner, S. A., Gold, D. B. & Bultman, K. K. (2001). The impact of behavioral health risks on worker absenteeism. Journal of Occupational and

Environmental Medicine, 43(4), 347‐354.• Solem, C. T., Sun, S. X., Sudharshan, L., Macahilig, C., Katyal, M. & Gao, X. (2013). Exacerbation‐related impairment of quality of life and work

productivity in severe and very severe chronic obstructive pulmonary disease. International Journal of Chronic Obstructive Pulmonary Disease, 8,641.

• Steiner, J. F., Cavender, T. A., Main, D. S. & Bradley, C. J. (2004). Assessing the impact of cancer on work outcomes. Cancer, 101(8), 1703‐1711.• Tunceli, K., Bradley, C. J., Nerenz, D., Williams, L. K., Pladevall, M. & Elston Lafata, J. (2005). The impact of diabetes on employment and work

productivity. Diabetes Care, 28(11), 2662‐2667.• Williams, S. A., Wagner, S., Kannan, H. & Bolge, S. C. (2009). The association between asthma control and health care utilization, work productivity

loss and health‐related quality of life. Journal of Occupational and Environmental Medicine, 51(7), 780‐785.• World Health Organization. (2006). Working Together for Health : The World Health Report. Retrieved from http://www.who.int/whr/2006/en/

31

REFERENCES

• Director General of Health, Ministry of Health,Malaysia.

• Kota Bharu District Health Office and Public HealthDivision of Kelantan State Health Department, Ministryof Health Malaysia.

• Department of Community Medicine, School of MedicalScience, Universiti Sains Malaysia (Health Campus).

32

ACKNOWLEDGEMENTS

Thank you

33