association between obesity and eating pattern slides
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ASSOCIATION BETWEEN OBESITY AND EATING PATTERN IN OFFICE WORKER & NON-OFFICE WORKER AT MANAGENT & SCIENCE UNIVERSITY (MSU) SHAH ALAM
RESEARCH PROJECT PRESENTATION
Bachelor in Nutrition (Hons)Department of Health Professionals & Food Service
Faculty Of Health & Life SciencesManagement And Science University
2013
Prepared By: Izzat Eskandar Dzulqarnain Bin Mohd Sharial
012010050343
SupervisorMr.Rajasegar Anamalley
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INTRODUCTION
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- ± 60% of Malaysian adults were pre-obese and obese.
- Unhealthy diet -> chronic Non-Communicable Diseases (NCD) e.g. Obesity (Malaysia).
Health problem that are associated with eating habits are not new in Malaysia, and there are several contributing factors related to eating habits which includes gender, socio-economic status, ethnicity and culture
(Wan Manan et al; 2012)
- Prevalence of overweight and obesity (29.4% and 15.1%) comparable with NHMS III 2006 report (28.6% and 14.0%)
NHMS IV (National Health and Morbidity Survey )
2011, Vol. 2
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OBJECTIVESGeneral Objective:• To determine the association between obesity and eating
pattern in both office workers and non-office workers at Management & Science University (MSU) Shah Alam.
Specific Objectives: • To assess the Body Mass Index (BMI) and eating pattern of
both office worker and non-office worker.• To determine the association between body weight status and
eating pattern in both office worker and non-office worker regarding their socioeconomic status.
• To differentiate the association of body weight status and eating pattern in both office worker and non-office worker with their gender.
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HYPOTHESES
Null Hypothesis (H0) =There is no association between obesity and eating pattern in both office worker and non-office worker at Management & Science University (MSU) Shah Alam
Alternative Hypothesis (HA) = There is an association between obesity and eating pattern in both office worker and non-office worker at Management & Science University (MSU) Shah Alam
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RESEARCH PROBLEM
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LITERATURE REVIEW
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OBESITY
SEDENTARY JOB
(Jungwee Park, 2009)
DISCOURAGES PHYSICAL ACTIVITY
(Raine & Kim D, 2004)
ENCOURAGES EXCESSIVE
EATING(Raine & Kim
D, 2004)
POOR EATING HABITS
(Jungwee Park, 2009)
OBESITY RELATED TO EATING PATTERN
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Prevalence in Obesity- In Malaysia it is higher
in women 29.6% compared to men 25.0%
(NHMS 2011)
Gender, Eating Pattern & Obesity
- Less personal income in men were less likely to be obese rather than women
(Jungwee Park 2009)
Socioeconomic FactorLower socioeconomic status associated with larger body size, for women in medium-
and low-development countries (Lindsay M 2007)
Educational Level Factor- In England, adults with no
qualifications have the highest rates of obesity
(National Obesity Observatory 2012)
- Professional occupations have lower obesity
prevalence than any other group
(National Obesity Observatory 2012)
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METHODOLOGY
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Sampling Area • Management and Science University Shah Alam
Malaysia
Sampling Technique• Simple Random Sampling• n=200
Study Design• Cross Sectional Study
Study Variable • Independent variable
• Participant gender, educational and socioeconomic status
• Dependent variable • Eating pattern & Body Mass Index (BMI)
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Sampling Criteria • Inclusion Criterion
• Office or non-office worker• Exclusion Criterion
• A body builder or a pregnant women which currently not taking any pills or medication on losing weight or having a chronic disease
Instruments• Eating Behavior Pattern Questionnaire (EBPQ) (adapted
from Schulundt DG, PhD. Vanderbilt University School of Medicine SODA )
• Using Body Mass Index(BMI)• Weight & Height = SECA 703
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Data Collection• Data collected from questionnaire consisting of• Part A : Demographic Information• Part B : Socioeconomic Status• Part C : EBPQ
• Data collected over a period of 3 months
Data Analysis• Statistical Product and Services Solution (IBM SPSS
Statistics) 21.0• Analyzed using Chi Squared Test (x2) test
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RESULTS & DISCUSSION
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Low Fat Eating Snacking & Convenience Emotional Eating Planning Ahead Meal Skipping Cultural/Lifestyle Behaviour0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
Office Worker Body Mass Index (BMI) Status and Eating Pattern
Low Fat Eating Snacking & Convenience Emotional Eating Planning Ahead Meal Skipping Cultural/Lifestyle Behaviour0%
2%
4%
6%
8%
10%
12%
14%
Non-Office Worker Body Mass Index (BMI) Status and Eating Pattern
It is NOT significant between BMI status and eating pattern in both office & non-office worker , p>0.05Comparative with study in Meru,
Klang, Malaysia where a few of the eating pattern from the Eating
Behavior Pattern Questionnaire (EBPQ) = associated with BMI status (N.S Zofiran et al., 2011)
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RM600-RM699 RM1000-RM1999 RM2000-RM2999 RM3000-RM3999 RM4000-RM4999 RM5000 or more0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
Office Worker Body Mass Index (BMI) Status and Socioeconomic status
RM600-RM699 RM1000-RM1999 RM2000-RM2999 RM3000-RM3999 RM4000-RM4999 RM5000 or more0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
Non-Office Worker Body Mass Index (BMI) Status and Socioeconomic status
It is significant between BMI and socioeconomic status of office worker , p<0.05
It is NOT significant between BMI and socioeconomic status of non-office worker , p>0.05
A proportional study “Association of Socioeconomic Status with Obesity”
concludes that higher educational achievement and higher
socioeconomic status were associated with a lower risk of obesity in both men and women (Jane Wardle et al,.
2002)
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RM600-RM699 RM1000-RM1999 RM2000-RM2999 RM3000-RM3999 RM4000-RM4999 RM5000 or more0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
Office Worker Eating Pattern and Socioeconomic status
RM600-RM699 RM1000-RM1999 RM2000-RM2999 RM3000-RM3999 RM4000-RM4999 RM5000 or more0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
Non-Office Worker Eating Pattern and Socioeconomic status
It is significant between Eating Pattern and socioeconomic status of office worker , p<0.05
It is NOT significant between Eating Pattern and socioeconomic status of non-office worker , p>0.05
In a similar study found that a greater frequency of dining out are
found, among higher-income groups which might also related
with the inverse association between income and being
overweight among men. (Kuhle and Veugelers, 2008)
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Underweight Normal Weight Overweight Obese0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
Office Worker Body Mass Index (BMI) and Gender
Underweight Normal Weight Overweight Obese0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
Non-Office Worker Body Mass Index (BMI) and Gender
It is significant between BMI status and gender of office worker , p<0.05
It is NOT significant between BMI status and gender of non-office worker , p>0.05
Similar study in Selangor, Malaysia that determine the prevalence of obesity among adult women (20-59 years old) are high (S. M. Sidik and L. Rampal, 2009)
A conclusion by a study which also use the same Eating Pattern Behaviour Questionnaire (EBPQ) that gender did not have any effect
on BMI status. (N.S Zofiran et al., 2011)
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Low Fat Eating Snacking & Convenience Emotional Eating Planning Ahead Meal Skipping Cultural/Lifestyle Behaviour0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
18.00%
Office Worker Eating Pattern and Gender
Low Fat Eating Snacking & Convenience Emotional Eating Planning Ahead Meal Skipping Cultural/Lifestyle Behaviour0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
18.00%
Non-Office Worker Eating Pattern and GenderIt is significant between Eating Pattern and gender of both office worker and non-office worker , p<0.05
A similar studies using Dutch Eating Behaviour Questionnaire (DEBQ) reported that shift duties were positively associated with abnormal eating behavior among female nurses working in hospitals (H.Wong et al., 2010)
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CONCLUSION
From the result obtain from this study, it shows that majority of the findings which is the association between BMI status and
related factors that may lead to obesity are more prone to office worker. Thus conclude that obesity might be more related
on the eating pattern and socioeconomic status of the office worker conversely with non-office worker.
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LIMITATION
The data were obtained from cross-sectional study and as the number of subjects and the time was limited
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FUTURE STUDY
Further studies in a larger population, wider scope, longer time duration and with more specific categories and test should be done in the future
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GANTT CHART
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Task
Duration Nov 2012
Dec 2012
Jan 2013
Feb 2012
Mar 2013
Apr 2013
May 2013
Jun 2013
July 2013
August 2013
Sept 2013
Journal reading Literature ReviewPreparation of proposalDevelop questionnaireSlide presentation
Proposal submission
Sample collection
Data collection
Data analysis
Thesis writing
Thesis submission
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REFERENCES1. Hidy Wong, Martin C.S. Wong, Samuel Y.S. Wong, Albert Lee, School of Public Health and Primary Care, Faculty of Medicine,
Chinese University of Hong Kong, Hong Kong “The association between shift duty and abnormal eating behavior among nurses working in a major hospital: A cross-sectional study” International Journal of Nursing Studies 47 (2010) 1021–1027
2. Institute for Public Health (IPH) 2011. National Health and Morbidity Survey 2011 (NHMS 2011). Vol. II: Non-Communicable Diseases; 2011: 188 pages
3. Jane Wardle, Jo Waller, and Martin J. Jarvis. Sex Differences in the Association of Socioeconomic Status With Obesity. American Journal of Public Health: August 2002, Vol. 92, No. 8, pp. 1299-1304.doi: 10.2105/AJPH.92.8.1299
4. Kuhle, Stefan and Paul J. Veugelers. 2008. “Why does the social gradient in health not apply to overweight?” Health Reports.Vol. 19, no. 4.December.Statistics Canada Catalogue no. 82-003-XIE. p. 7-15. http://www.statcan.gc.ca/pub/82-003-x/2008004/ article/10746- eng.pdf (accessed February 5, 2009).
5. Lindsay McLaren Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada. Accepted for publication February 20, 2007. Vol. 29, 2007 “Socioeconomic Status and Obesity” DOI: 10.1093/epirev/mxm001 Advance Access publication May 2, 2007
6. National Obesity Observatory (NOO) (2012) Adult Obesity and Socioeconomic Status(Updated on September 2012) Retrieved from http://www.noo.org.uk/gsf.php5?f=7539&fv=16966
7. Nur Syuhada Zofiran, M. J., Kartini, I., Siti Sabariah, B., and Ajau, D. (2011) The relationship between eating behaviours, body image and BMI status among adolescence age 13 to 17 years in Meru, Klang, Malaysia Department of Nutrition & Dietetics, Faculty of Health Sciences, Universiti Teknologi American Journal Of Food And Nutrition Print: ISSN 2157-0167, Online: ISSN 2157-1317, doi:10.5251/ajfn.2011.1.4.185.192 © 2011, ScienceHuβ, http://www.scihub.org/AJFN
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8. Park, Jungwee. 2007. “Work stress and job performance.” Perspectives on Labour and Income.Vol. 8, no. 12.December.Statistics Canada Catalogue no. 75-001-XIE. p. 5-17. http://www.statcan.gc.ca/pub/75-001-x/2007112/ article/1046-eng.pdf (accessed February 5, 2009).
9. Raine, Kim D. 2004. Overweight and Obesity in Canada: A Population Health Perspective. Canadian Population Health Initiative. Canadian Institute for Health Information. Ottawa. 81 p. h t t p : / / s e c u r e .c i h i . c a / c i h i w e b / p r o d u c t s /CPHIOverweightandObesityAugust2004_e.pdf (accessed February 10, 2009).
10. S. M. Sidik and L. Rampal, “The prevalence and factors associated with obesity among adult women in Selangor, Malaysia,” Asia Pacific Family Medicine, vol. 8, no. 1, pp. 1–6, 2009.
11. Schlundt, D.G., M.K. Hargreaves and M.S. Buchowski, 2003. The eating behavior patterns questionnaire predicts dietary fat intake in African American women. J. Am. Dietetic Assoc., 103: 338-345.
12. Wan Abdul Manan WM, Nur Firdaus I, Safiah MY, Siti Haslinda MD, Poh BK, Norimah AK, Azmi MY, Tahir A, Mirnalini K, Zalilah MS, Fatimah S, Siti Norazlin MN &Fasiah W Mal J Nutr_18(2):221 – 230, 2012 Meal Patterns of Malaysian Adults: Findings from the Malaysian Adults Nutrition Survey (MANS)
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APPENDIX
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THANK YOU