This document reports on a study that assessed the prevalence of established nutritional and behavioral risk factors for breast cancer among healthy women in Kandy and Jaffna, Sri Lanka. The study found several significant differences in risk factors between the two groups. Women in Kandy had higher consumption of processed meats, coconut oil, and eggs compared to Jaffna. Women in Jaffna breastfed for longer durations on average. Using a breast cancer risk assessment tool, a higher proportion of women in Jaffna were found to be at high lifetime risk of breast cancer compared to Kandy. The study concludes there are differences in dietary and reproductive risk factors for breast cancer between the two populations.

1. Prevalence of Established Nutritional
and Behavioral Risk Factors of Breast
Cancer among Apparently Healthy
Women
R.Shobana
Department of Applied Nutrition
Faculty of Livestock, Fisheries and Nutrition
Wayamba University of Sri Lanka

2. Background
25.4%
7.7%
5.8%
5.7%
4.4%
50.9%
Breast
Ovary
Lip,mouth
Colon, rectum
Uterus
Others
Figure 1: Leading Cancer sites among Sri Lankan women
(National Cancer Control Program – 2009)
 The most common gynecological cancer in the world
 The most common among Sri Lankan women
 Over 508,000 women died worldwide due to breast
cancer in 2011 – (WHO, 2013)

3. Identification of risk factors, their distribution among
population and risk assessment in healthy women 
promote screening
 Number of deaths due to breast cancer is increasing
 majority of cases are diagnosed at late stage
 Routine screening is important for early detection
 reduce the burden of breast cancer

4. Risk factors
of breast
cancer
Heredity
Reproduction
Behavior
Diet
Diet and behavior can be modified to reduce the risk of
breast cancer

5. Objectives
 To determine the prevalence of established risk factors
of breast cancer among apparently healthy women
 To identify the difference in the presence of risk factors
between two geographical locations
 To estimate the lifetime breast cancer risk of apparently
healthy women in two geographical locations

6. Methodology
Sample selection
Data collection
100 individuals
from Kandy
and 150 from
Jaffna
Interviewer
administered
general
questionnaire
Interviewer
administered
food frequency
questionnaire

7. Data analysis Physical Activity
Level (PAL) –
General Practice
Physical Activity
Questionnaire
Statistical analysis
 Descriptive statistics
 Chi-square tests and independent t-
tests – identify the difference in the
presence of risk factors in selected
two geographical locations
Breast cancer
risk assessment
– Gail breast
cancer risk
assessment tool

8. Results
Table 1: Reproductive and anthropometric
characteristics of individuals in Kandy and Jaffna
*significantly different at 95% confident
Reproductive characteristics Kandy Jaffna p value
Mean SD Mean SD
Age at menarche 12.7 ±1.2 13.8 ±1.6 0.030*
Parity 2.27 ±0.9 2.82 ±1.3 0.000*
Cumulative time duration of breast
feeding (months)
69.9 ±35.8 47.5 ±28.3 0.003*
Mean time duration of breast feeding
(months)
31.3 ±13.0 17.6 ±8.1 0.000*
BMI (kgm-2) 24.9 ±3.7 24.0 ±4.8 0.040*

9. Table 2: Dietary and behavioral factors affecting
breast cancer
*significantly different at 95% confident
Dietary risk factors Dietary protective factors Behavioral factors
Consumption of
 Processed meat
 Cheese
 Butter/margarine
 Coconut oil
 Carbonated beverage
High frequency
consumption of
 Egg
 Milk
Consumption of
 Sesame oil
High Frequency
consumption of
 Fish
 Soya meat
 Cruciferous vegetables
Night shift working
Passive smoking
Physical Activity Level

10. Difference in distribution of dietary risk factors
33.0
94.0
22.0
0.7
22.0
36.7
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Processed meat Coconut oil Carbonated
Beverage
Frequency(%)
Food items
Kandy
Jaffna
Figure 2: Consumption of food items that increase the risk of breast
cancer

11. Frequency consumption of egg and milk
Figure 3: Frequency consumption
of egg
22.0
74.0
4.0
28.7
52.0
19.3
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
< 4
times/week
≥ 4
times/week
Non
consumers
Frequency(%)
Frequency consumption of egg
Kandy
Jaffna
5.0
32.0
10.0
53.0
5.2
13.4
33.4
48.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
≤ 3
times/month
1-6
times/week
≥ once a day Non
consumers
Frequency(%)
Frequency consumption of milk
Kandy
Jaffna
Figure 4: Frequency consumption
of milk

12. Frequency consumption of protective dietary factors
29.0
39.0 40.0 41.0 41.0
58.0
18.0
56.0
60.7
26.0
50.0
40.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
≤ 4
times/week
> 4
times/week
< 4
times/week
≥ 4
times/week
≤ 4
times/week
4
times/week
Frequency(%)
Food consumption frequency
Kandy
Jaffna
>
Figure 5: Frequency consumption of food items that reduce the risk of breast
cancer
Fish Cruciferous vegetablesSoya meat

13. Life time risk of breast cancer in study sample
(determined by Gail risk assessment tool)
28.3%
71.7%
High risk
Low risk
0 20 40 60 80 100
Kandy
Jaffna 66.9%
79.1%
0 20 40
Kandy
Jaffna 33.1%
20.9%
Figure 7: Distribution of low risk group
Figure 6: Distribution of life time risk of breast cancer
Figure 8: Distribution of high risk group

14. Conclusion
Risk factors Kandy Jaffna
Dietary risk factors
High consumption of
 Processed meat
 Coconut oil
 Cheese
 Butter/margarine
 Egg
Low consumption of
 Cruciferous vegetables
 Soya meat
Reproductive risk
factors
Young age at menarche
Low parity
Higher BMI
Short duration of breast
feeding
 Majority of the study sample in both locations  under low risk
 Among the high risk group, high proportion represented by
subjects in Jaffna (Based on Gail risk assessment tool)
 Table 3: Dietary and reproductive risk factors common in Kandy
and Jaffna

15. Acknowledgement
I would like to extend my sincere gratitude to
 my principal supervisor and co-supervisor
 all study participants in Kandy and Jaffna
 all my colleagues

16. References
 National Cancer Control Program. (2009) Cancer Incidence Data: Sri Lanka year 2001-
2005. Cancer Registry, 7th publication. Colombo: National Cancer Control program.
 World Health Organization (2013) Breast cancer: prevention and control [online]
Available from: http://www.who.int/cancer/detection/breastcancer/en/index1.html
[accessed on 02/04/2016].
 Thiebaut, A. C. M., Kipnis, V., Chang, S.-C., Subar, A. F., Thompson, F. E., Rosenberg, P. S.,
… Schatzkin, A. (2007). Dietary fat and postmenopausal invasive breast cancer in the
National Institutes of Health-AARP Diet and Health Study cohort. Journal of the National
Cancer Institute, 99(6), 451–62. http://doi.org/10.1093/jnci/djk094 [accessed on
10/04/2016].
 Friedenreich, C. M., Courneya, K. S., & Bryant, H. E. (2001). Influence of physical activity
in different age and life periods on the risk of breast cancer. Epidemiology (Cambridge,
Mass.), 12(6), 604–12. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11679785
[accessed on 11/04/2016].

19. Characteristics
Kandy (%) Jaffna (%)
p value
Educational level
Primary 2.0 4.7
Secondary 8.0 22.7
G.C.E O/L 40.0 36.0 0.01*
G.C.E A/L 40.0 32.0
Higher 10.0 4.7
Employment status
Yes 33.0 22.0
No 67.0 78.0 0.050
Table 3: Distribution of selected demographic
characteristics in study sample
*significantly different at 95% confident interval

20. Characteristics Kandy (%) Jaffna (%) p value
Night shift working
Yes 6.0 0.7
No 94.0 99.3 0.012*
Night shift frequency
None 94.0 99.3
Once a week 3.0 0.7
2/more times per week 3.0 0.0 0.350
Passive smoking
Yes 21.0 10.0
No 79.0 90.0 0.009*
Duration of exposure to passive smoking per day
None 79.0 90.0
< 2 hours 16.0 7.3
≥ 2 hours 5.0 2.7 0.845
Physical Activity Level
Inactive 77.0 67.3
Moderately inactive 12.0 24.0
Moderately active 9.0 4.0 0.030*
Active 2.0 4.7
Table 4: Distribution of selected lifestyle characteristics
in study sample

21. Table 5: Distribution of selected reproductive
characteristics in study sample
Characteristics Kandy (%) Jaffna (%) p value
Overweight/obese at adolescent
Yes 33.0 29.3
No 67.0 70.7 0.534
Irregular periods
Amenorrhoea 6.0 5.3 0.822
Polymenorrhoea 6.0 4.7 0.642
Pregnant history
Ever become pregnant 90.0 89.3
Never become pregnant 10.0 10.7 0.866
Abortion history
Yes 14.0 14.7
No 86.0 85.3 0.883
Contraceptive usage
Yes 35.0 27.3
No 65.0 72.7 0.197

22. Table 6: Distribution of selected disease history in
study sample
Diseases Kandy (%) Jaffna (%) p value
Diabetes
Yes 13.0 16.7
No 87.0 83.3 0.429
Gestational diabetes
Yes 2.0 4.0
No 98.0 96.0 0.379
Hypertension
Yes 21.0 17.3
No 79.0 82.7 0.467
Gestational hypertension
Yes 8.0 4.7
No 92.0 95.3 0.277

23. Characteristics Kandy (%)Jaffna (%) p value
Cumulative time duration of breast cancer
(months)
0-12 months 12.0 16.0
13-24 months 8.0 12.0
25-36 months 5.0 13.3
37-48 months 14.0 22.7
≥ 49 months 61.0 36.0 0.003*
cumulative time duration of breast feeding
≥ 24 months
Yes 80.0 72.0
No 10.0 17.3 0.151
Mean time duration of breast feeding
< 24 months 33.0 78.0
≥ 24 months 67.0 22.0 0.000*
Table 7:Distribution of characteristic of breast
feeding time duration in study sample
*significantly different at 95% confident interval

24. Characteristics Kandy (%) Jaffna (%) p value
Pork 5.0 0.0 0.006*
Mutton 12.0 30.0 0.001*
Sausages
Consumers 33.0 0.7
Non consumers 67.0 99.3 0.000*
Meat balls
Consumers 9.0 0.0
Non consumers 91.0 100.0 0.000*
Meat an processed meat

25. 84.0
33.0
9.0
76.0
0.7 0.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
Meat Sausages Meat balls
Frequency(%)
Meat and processed meat
Kandy
Jaffna
84.0
3.0 5.0
12.0
76.0
2.0 0.0
30.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
Poultry Beef Pork Mutton
Frequency(%)
Types of meat
Kandy
Jaffna
Figure 1: Frequency distribution of meat
and processed meat among individuals in
Kandy and Jaffna
Figure 2: Frequency distribution of different
types of meat among individuals in Kandy
and Jaffna
Distribution of meat and processed meat among
individuals in Kandy and Jaffna

26. 47.0
84.0
77.0
68.0
30.0
52.0
32.0
76.0
70.0
5.3
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
Milk Yogurt Ice cream Curd Cheese
Frequency(%)
Milk and milk products
Kandy
Jaffna33.0
25.0
92.0
29.0
11.0
96.0
81.0
63.3
38.0
60.7
64.0
58.7
81.3
86.7
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Shark Salmon Dried fish Prawns Crabs Egg (Hen) Soya meat
Frequency(%)
Protein sources
Kandy
Jaffna
Distribution of protein sources among individuals in
Kandy and Jaffna
Figure 3: Protein source consumption frequency among individuals in
Kandy and Jaffna
Figure 4: Milk and milk products consumption frequency among
individuals in Kandy and Jaffna
Distribution of milk and milk products among
individuals in Kandy and Jaffna

27. 94.0
40.0
75.0
22.0
81.3
28.7
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Coconut oil Vegetable oil Butter/Margarine
Frequency(%)
Types of fat
Kandy
Jaffna
Figure 5 : Different types of fat consumption frequency among
individuals in Kandy and Jaffna
Distribution of different types of oil among individuals
in Kandy and Jaffna

28. Characteristics Kandy Jaffna p value
Mean SD Mean SD
Age at interview 48.7 ±10.7 53.2 ±10.5 0.960
Age at menarche 12.7 ±1.2 13.8 ±1.6 0.030*
Age at menopause 48.7 ±3.5 48.6 ±3.9 0.196
Age at first live birth 25.9 ±4.1 26.9 ±4.7 0.137
Age at last child birth 30.6 ±4.3 32.2 ±4.3 0.867
Parity 2.27 ±0.9 2.82 ±1.3 0.000*
Number of abortion 1.29 ±0.6 1.19 ±0.4 0.205
Cumulative time duration of breast
feeding (months) 69.9 ±35.8 47.5 ±28.3 0.003*
Mean time duration of breast
feeding (months) 31.3 ±13.0 17.6 ±8.1 0.000*
BMI (kgm-2) 24.9 ±3.7 24 ±4.8 0.040*
*significantly different at 95% confident interval
Table 1: Descriptive characteristics of apparently healthy
women participated in the study

29. Distribution of frequency consumption of significantly
different dietary risk factors
22.0
74.0
28.7
52.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
< 4 times/week≥ 4 times/week
Frequency(%)
Egg consumption frequency
Kandy
Jaffna
5.0
32.0
10.0
3.2
13.3
33.3
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
≤ 3
times/month
1-6 times/week ≥ Once a day
Frequency(%)
Milk consumption frequency
Kandy
Jaffna

30. Distribution of life time risk of breast cancer in study sample
54.1%
45.9% low risk
High risk
40 45 50 55 60
Kandy
Jaffna 57.8%
48.4%
0 10 20 30 40 50 60
Kandy
Jaffna 42.2%
51.6%
Figure 5: Distribution of risk category
Figure 6: Distribution of high risk
category
Figure 7: Distribution of low risk
category