1. ASSOCIATED FACTORS FOR TUBERCULOSIS CASES IN PASIR PUTEH, KELANTAN 2012-2015
Hafizuddin A1, Zawiyah D1, Sharina D2
1Pasir Puteh District Health Office
2Kelantan State Health Department

2. INTRODUCTION

3. Tuberculosis (TB) is one of the main public health issues in many countries including Malaysia, and remains a major source of morbidity and mortality worldwide.7 Malaysia spent $15 million for TB control programmes in
As for 2014, the incidence and prevalence rates for TB in Malaysia are 99 per 100,000 and 131 per 100,000 population respectively. Malaysia’s TB mortality rate is 5.8 per 100,000 population (excluding TB/HIV infection).11,12

4. TABLE 1 : TB CASE NOTIFICATIONS FOR 2014 & 2015
TOTAL TB CASE NOTIFICATIONS
2014
2015
MALAYSIA
24711
24220
KELANTAN
1366
1233
(TB/Leprosy Unit, Kelantan State Health Department,2016)

5. Risk factors for prevalence of TB have been reported to include: 3,7,8
socio-economic factors (age, sex, employment and education)
patient factors (diabetes status, smoking, HIV status)
disease factors (history of multiple disease treatment)

6. (TB/Leprosy Unit, Kelantan State Health Department,2016)

7. GRAPH 2 : KELANTAN TB CASES FOR 2014 & 2015
(TB/Leprosy Unit, Kelantan State Health Department,2016)

8. Studying the associated factors for the prevalence of TB is a convenient way to evaluate the effectiveness of TB control programmes and may help us to identify patients with the highest vulnerability.7,10
This study certainly provided a façade of the current situation impacted by this old nemesis of ours, and could be useful for us to establish preventive measures to curb the future incidence of TB among our population.

9. OBJECTIVES

10. To determine the socio-demography, risk factors and categories in TB cases for Pasir Puteh district from
To determine the factors associated with TB cases in Pasir Puteh district from

11. METHODOLOGY

12. Study design:
Objective 1 (Phase 1) : Cross sectional study
Objective 2 (Phase 2) : Case-control study
Study location:
Pasir Puteh District Health Office
Reference population:
Tuberculosis cases in Pasir Puteh district
Source population:
Tuberculosis case patients notified to PKD Pasir Puteh
Sampling frame:
Tuberculosis cases notified to PKD Pasir Puteh between 1st of January 2012 to 31st of December 2015

13. Study sample:
Tuberculosis cases notified to PKD Pasir Puteh between 1st of January 2012 to 31st December 2015 who fulfilled the inclusion and no exclusion criteria
Inclusion criteria:
Confirmed cases of tuberculosis that is notified to PKD Pasir Puteh
Exclusion criteria:
Incomplete record of 30% of variables.

14. Sampling method:
Phase 1 : Universal sampling
Phase 2 : Simple random sampling for control group with ratio of 1:1 and all TB cases are selected for case group.
Mode of data collection:
This study involve secondary data collection from MyTB (TBIS) Registry; TB Cases Registry for case group, and TB Contacts Registry for control group.
All data information will be collected using checklist performa and data collection form designed by researcher consisting of socio-demography, risk factors and outcome of cases.

15. STUDY VARIABLES INDEPENDENT VARIABLES Socio-demographic factors
Risk factors
OUTCOMES
TB (Case) : Confirmed and registered cases of TB
Non-TB (Control): Registered TB contacts who have no symptoms, negative Mantoux and no CXR abnormality.

16. FIGURE 1 : FLOW CHART OF THE STUDY

17. SAMPLE SIZE CALCULATION
P0 : Proportion of Diabetes among Malaysian population (NHMS, 2015)
P1 : Proportion of diabetes among TB patients in Kelantan (Expert opinion)
Sample size needed for power of 80% and alpha 0.05 : 406 x 2 = (10% non response group) = = 893 samples (794 samples were used for this research)

18. STATISTICAL ANALYSIS

19. (Using IBM SPSS statistics version 18)
1) Data entry, exploration and cleaning
Data checking for any missing value
2) Descriptive statistics
Categorical data: n (%)
Numerical data: mean (sd) or median (IQR)
3) Simple logistic regression
All the variables will be tested whether there is an association with tuberculosis cases.
Only variables with p-value < 0.25 or clinically important is selected for variable selection.

20. 4) Multiple logistic regression
3 rules in selecting model: statistical significant, parsimony, biological plausible.
Checking interaction: two-way interaction will be checked in the model.
Checking overall fitness of the model: using Hosmer-Lemeshow test, classification table and area under ROC curve

21. 5) Data presentation, interpretation and conclusion
Crude OR, adjusted OR, 95% CI, Wald statistic and p-value will be reported.
p-value < 0.05 will be considered significant.

22. RESULTS

23. TABLE 2 : SOCIO-DEMOGRAPHY OF TUBERCULOSIS PATIENTS
IN PASIR PUTEH (n=397)
Factors
Frequency (%)
Ethnicity
Malay
Others
378 (95.2)
19 (4.8)
Gender
Male
Female
248 (62.5)
149 (37.5)
Occupation
Student
Govt/Private Sector
Self-employed
Unemployed
15 (3.8)
78 (19.6)
109 (27.5)
195 (49.1)

24. TABLE 3 : SOCIO-DEMOGRAPHY OF TUBERCULOSIS PATIENTS
IN PASIR PUTEH (n=397)
Factors
Frequency (%)
Age
*47 (18)
Age Group
Children (5-12)
Teenagers (13-18)
Adults (19-60)
Elderly (>60)
2 (0.5)
17 (4.3)
264 (66.5)
114 (28.7)
Education Level
None
Primary
Secondary
Tertiary
71 (17.9)
90 (22.7)
228 (57.4)
8 (2.0)
*Mean (SD)

25. TABLE 4 : RISK FACTORS AMONG TUBERCULOSIS PATIENTS
IN PASIR PUTEH (n=397)
Factors
Frequency (%)
Diabetes No
Yes
282 (71.0)
115 (29.0)
Smoking
226 (56.9)
171 (43.1)
HIV Status
Negative
Positive
354 (89.2)
43 (10.8)
BCG Scar
Absent
Present
98 (24.7)
299 (75.3)

27. BY SIMPLE LOGISTIC REGRESSION (n=794)
TABLE 5 : FACTORS ASSOCIATED WITH TUBERCULOSIS CASES IN PASIR PUTEH
BY SIMPLE LOGISTIC REGRESSION (n=794)
Factors
TB Case frequency (%)
Crude OR
(95% CI)
Wald statistics
(df)
p value
Non-TB
n=397 TB
Gender
Female
Male
213 (53.7)
184 (46.3)
149 (37.5)
248 (62.5)
1.00
1.97 (1.45,2.55)
20.60 (1)
<0.01
Ethnicity
Malay
Others
387 (97.5)
10 (2.5)
378 (95.2)
19 (4.8)
1.94 (0.89,4.23)
2.80 (1)
0.094
Occupation
Student
Govt/Private
Self-employed
Unemployed
176 (44.3)
67 (16.9)
57 (14.4)
97 (24.4)
15 (3.8)
78 (19.6)
109 (27.5)
195 (49.1)
13.66 (7.34,25.39)
22.43 (12.10,41.58)
23.58 (13.19,42.15)
68.28 (1)
97.67 (1)
(1)

28. BY SIMPLE LOGISTIC REGRESSION (n=794)
TABLE 6 : FACTORS ASSOCIATED WITH TUBERCULOSIS CASES IN PASIR PUTEH
BY SIMPLE LOGISTIC REGRESSION (n=794)
Factors
TB Case frequency (%)
Crude OR
(95% CI)
Wald statistics
(df)
p value
Non-TB
n=397 TB
Age Group
Teenagers (13-18)
Infants/Toddlers (<5)
Children (5-12)
Adults (19-60)
Elderly (>60)
99 (24.9)
12 (3.0)
64 (16.1)
183 (46.1)
39 (9.8)
17 (4.3)
0 (0.0)
2 (0.5)
264 (66.5)
114 (28.7)
1.00
0.00 (0.00,0.00)
0.182 (0.04,0.81)
8.40 (4.85,14.53)
17.02 (9.06,31.96)
0.00 (1)
4.96 (1)
57.94 (1)
77.75 (1)
0.999
0.026
<0.01
Diabetes No
Yes
396 (99.7)
1 (0.3)
282 (71.0)
115 (29.0)
(22.42, )
25.47 (1)
Smoking
325 (81.9)
72 (121.5)
226 (56.9)
171 (43.1)
3.41 (2.47,4.72)
55.38 (1)
HIV Status
Negative
Positive
395 (99.5)
354 (89.2)
43 (10.8)
23.99 (5.77,99.74)
19.10 (1)

29. BY MULTIPLE LOGISTIC REGRESSION (n=794)
TABLE 7 : FACTORS ASSOCIATED WITH TUBERCULOSIS CASES IN PASIR PUTEH
BY MULTIPLE LOGISTIC REGRESSION (n=794)
Factors
Crude ORa
(95% CI)
Adjusted ORb
Wald statisticsb
(df)
p valueb
Gender
Female
Male
1.00
1.97 (1.45,2.55)
2.28 (1.61,3.23)
21.90 (1)
<0.01
Age Group
Teenagers (13-18)
Adults (19-60)
Elderly (>60)
8.40 (4.85,14.53)
17.02 (9.06,31.96)
6.01 (3.43,10.52)
10.16 (5.28,19.55)
39.45 (1)
48.22 (1)
Diabetes No
Yes
(22.42, )
(14.52,763.54)
21.23 (1)
Smoking
3.41 (2.47,4.72)
1.49 (1.00,2.22)
3.94 (1)
0.047
HIV Status
Negative
Positive
23.99 (5.77,99.74)
25.78 (5.04,131.73)
15.24 (1)
aSimple logistic regression
bMultiple logistic regression
Classification table : 78.3%
Area under ROC curve : 0.85
No interaction. The model reasonably fits well.

30. DISCUSSION

31. Ethnicity has no significant association as this study is carried out in a Malay majority area.
A striking feature of TB, which is apparent in prevalence surveys from most part of the world, is that TB is more a disease of men than of women as reported by Borgdorff et al.5 There is significant association between male gender and TB prevalence as reported by this study and could be explained by the higher mobility of the male group due to work requirement.
McKenna et al reported that farm [AOR 3.7(95%CI 3.4,4.1)], industrial and healthcare workers [AOR 1.0 (95%CI 0.9,1.1)] have higher risk of getting TB but in this study, all occupational groups have higher odds of getting TB with significant association.9

32. From our study, the TB infection was comparatively higher in adult and elderly groups. Elderly (>60 year old) has 10-fold higher risk of getting TB with significant p-value, and such finding is apparent in developed countries as well (Canada, Australia, Scandinavian) as reported by Raviglione et al and Nissapatorn et al.3
The association between smoking and TB has rarely been highlighted. However, Slama et al reported that currents smokers were found to be 2.6 (95%CI 1.6,4.3) times more likely to develop TB. As for our study, smoking is a significant associated factor as well with AOR 1.49 (95%CI 1.0,2.2).6

33. Giri et al in their study found out that 17% of their HIV patients have TB co-infection (χ2=27.8, p<0.0001) indicating that severely depressed immunity makes them susceptible to TB infection. In our study, HIV positive patients have 25 times higher odd of getting TB infection with significant p-value as well.4
Similar to previous study (Nissapatorn et al), we found that host comorbidity (diabetes mellitus) was significantly associated with TB infection. Patients with diabetes were 100 times more likely to develop TB than those without diabetes with significant p-value (<0.01).1

34. CONCLUSION & RECOMMENDATIONS

35. In conclusion, male, elderly, diabetic, smoking and HIV positive status are the significant associated factors for getting infected with tuberculosis in Pasir Puteh district.
Population groups with the above risk factors must be identified and screened for TB meticulously. Elderly people are considered as high risk group for TB, hence chest x-ray and TB screening is mandatory.

36. Quit Smoking Clinics must be empowered to curb smoking and later mitigating the risk of getting TB. Patients who attend Quit Smoking Clinic must be educated regarding TB disease and others adverse effects of smoking, and recommended for TB screening as well.
All newly-diagnosed HIV patients are compulsory to do TB screening (inclusive of chest x-ray).

37. Considering the increasing burden of DM, particularly in areas with highly prevalent TB, TB control programs will need to expand efforts to focus on treatment and monitoring of patients with DM and TB disease.
Annual CXR screening for all diabetic patients must be done proactively so that TB cases among diabetic patients will not be overlooked.
As Kelantan has high prevalence of diabetes among population, TB health education and screening programs must be done regularly in the community to ensure that larger proportion of diabetic patients are grabbed and screened for TB.

38. ACKNOWLEDGEMENT

39. Health Inspectors, TB Unit, Pasir Puteh District Health Office
Assistant Medical Officers, Pasir Puteh District Health Office
Staff nurses, Chest Clinic, HRPZ II
Staff nurses, Chest Clinic, HTA

40. REFERENCES

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Nissapatorn, V., et al. "Tuberculosis in HIV/AIDS patients: a Malaysian experience." Southeast Asian journal of tropical medicine and public health 36.4 (2005): 946.
Nissapatorn, V., et al. "Tuberculosis in Malaysia: a continuing surge." Southeast Asian Journal of Tropical Medicine and Public Health 38.1 (2007): 231.
Giri, Purushottam A., Jayant D. Deshpande, and Deepak B. Phalke. "Prevalence of pulmonary tuberculosis among HIV positive patients attending antiretroviral therapy clinic." North American journal of medical sciences 5.6 (2013): 367.
Borgdorff, M. W., et al. "Gender and tuberculosis: a comparison of prevalence surveys with notification data to explore sex differences in case detection." The International Journal of Tuberculosis and Lung Disease 4.2 (2000):
Slama, Karen, et al. "Tobacco and tuberculosis: a qualitative systematic review and meta-analysis [Review Article]." The International Journal of Tuberculosis and Lung Disease (2007):
Liew, S. M., et al. "Tuberculosis in Malaysia: predictors of treatment outcomes in a national registry." The International Journal of Tuberculosis and Lung Disease 19.7 (2015):
Ibrahim, Jamaiah. "Tuberculosis: an eight year ( ) retrospective study at the University of Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia." Southeast Asian Journal of Tropical Medicine and Public Healt 41.2 (2010):
McKenna, M. T., Hutton, M., Cauthen, G., & Onorato, I. M. (1996). The association between occupation and tuberculosis. A population-based survey. American journal of respiratory and critical care medicine, 154(3),
Aziah, A. M. "Tuberculosis in Malaysia: combating the old nemesis." Med J Malaysia 59.1 (2004): 1-4.
TB/Leprosy Unit, Kelantan State Health Department,2016
National Health and Morbidity Survery 2015, Malaysia Public Health institute
World Health Organization, Malaysia 2014 Tuberculosis Country Profiles.

42. © 2016 PASIR PUTEH DISTRICT HEALTH OFFICE. ALL RIGHTS RESERVED.
DR HAFIZUDDIN
© 2016 PASIR PUTEH DISTRICT HEALTH OFFICE. ALL RIGHTS RESERVED.