nhms_2019.pdf

National Health and Morbidity Survey 2019 Technical Report − Volume I 254 Table 19.1: Prevalence of Suspected Epilepsy (Preliminary Results Based on Initial Screening) in Malaysia by Socio-Demographic Characteristics (n=16,681) Sociodemographic Characteristics Unweighted Count Estimated Population Prevalence (%) 95% CI Lower Upper MALAYSIA 245 522,221 1.7 1.35 2.02 Location Urban 143 375,650 1.6 1.24 2.04 Rural 102 146,571 1.8 1.34 2.53 Sex Male 133 298,422 1.9 1.43 2.50 Female 112 223,800 1.4 1.10 1.81 Age Group (Years) 0–9 55 90,689 1.8 1.27 2.56 10–19 55 150,497 2.9 1.90 4.43 20–29 33 90,532 1.5 0.88 2.45 30–39 30 79,851 1.5 0.87 2.67 40–49 23 42,593 1.2 0.67 2.08 50–59 20 31,503 1.0* 0.51 2.02 60–69 20 21,406 1.0* 0.54 1.98 70 & above 9 15,150 1.2* 0.44 3.34 Ethnicity Malaya 178 321,267 1.9 1.52 2.29 Chinese 22 321,267 1.1* 0.51 2.15 Indian 9 321,267 0.7* 0.32 1.54 Bumiputera Sabah 15 321,267 1.5* 0.78 3.00 Bumiputera Sarawak 6 321,267 1.0* 0.32 2.78 Others 15 321,267 2.7* 1.27 5.73 Marital status Single 150 363,934 2.3 1.81 2.99 Married 75 136,349 1.0 0.68 1.36 Widow(er) / Divorcee 20 21,939 1.2 0.69 2.21 Household Income Category Bottom 40% 180 394,441 1.8 1.46 2.32 Middle 40% 48 102,107 1.3 0.86 1.97 Top 20% 17 25,674 1.1* 0.59 2.16 *Prevalence with high RSE, interpret with caution a - Malay includes Orang Asli

Non-Communicable Diseases: Risk Factors and other Health Problems 255 Depression

National Health and Morbidity Survey 2019 Technical Report − Volume I 256 Depression Contributors to this section: Mohd Shaiful Azlan Kassim, Noor Ani Ahmad, Nurashikin Ibrahim, Sherina Mohd Sidik, Idayu Badilla Idris, Hjh Salina Abdul Aziz, Siti Hazrah Selamat Din, Abdul Aziz Harith, Zamtira Seman, Mohd Amierul Fikri Mahmud, Faizul Akmal Abd Rahims, Hazrin Hasim @ Hashim, Muhammad Faiz Mohd Hisham, Karen Sharmani a/p Sandanasamy. Introduction Depression is one of the most common mental health disorders in community settings and a major cause of disability. It is projected to be the leading cause of disease burden globally by 2030 [1]. Depression is a state of low mood and aversion to activity. It can affect a person’s thoughts, behaviour, motivation, feelings, and sense of well-being. It may feature sadness, difficulty in thinking and concentration and a significant increase or decrease in appetite and time spent sleeping. People experiencing depression may have feelings of dejection, hopelessness and, sometimes, suicidal thoughts [2]. According to the World Health Organization (WHO), more than 300 million people of all ages suffer from depression. Depression can lead to suicide. Close to 800,000 people die due to suicide every year. Suicide is the second leading cause of death in 15-29 years old [3]. The National Health Morbidity Survey (NHMS) found that mental health problems had increased from 10.7% in 1996 to 29.2% in 2015 [4][5]. In the NHMS 2011 report, the prevalence of lifetime depression was 2.4% and current depression was 1.8% [6]. Many scales have been developed to measure depressive symptoms [7]. Worldwide, the nine-item depression module from the Patient Health Questionnaire (PHQ-9) has been used extensively for assessing and detecting depression based on DSM-IV criteria for major depression. The PHQ-9 has been used in about 15 languages, and over 50 validity studies have been published. The Malay version of PHQ-9 reported sensitivity and specificity of 87% and 82% [8]. Objectives General objective To determine the prevalence of depression among Malaysian adults aged 18 years and above. Specific objectives

1. To determine the prevalence of depression among adults aged 18 years and above.
2. To determine the prevalence of depression by socio- demographic profiles. Methods The module on depression was targeted to household members aged 18 years and above from the randomly selected living quarters. Self-administered questionnaire, PHQ-9 was distributed to the respondents and were available in 2 choices of languages: Bahasa Malaysia and English. The Malay version of the PHQ-9 had been validated and was found to have good internal reliability with Cronbach’s alpha = 0.70 [8]. There were 9 statements related to depression with four responses for each statement, on a Likert scale scored from 0 (not at all) to 3 (nearly every day). The maximum total score was 27. In this study, score of ≥ 10 was defined as having depression [8].

Non-Communicable Diseases: Risk Factors and other Health Problems 257 Findings The prevalence of depression among adults aged 18 years and above in Malaysia was 2.3% (95% CI: 1.87, 2.78). By state, the prevalence was highest in WP Putrajaya [5.4% (95% CI: 3.29, 8.78)], and followed by Perlis [4.3% (95% CI: 2.50, 7.22)]. The prevalence of depression was significantly higher in rural areas at 3.6% (95% CI: 2.48, 5.24) compared to their counterparts from urban areas [(1.9% (95% CI: 1.50, 2.34)]. The prevalence of depression was higher among Bumiputera Sabah [5.2% (95% CI: 92.84, 9.22)]. The prevalence also significantly higher among single [3.2% (95% CI: 2.35, 4.46)] compared to married [1.8% (95% CI: 1.40, 2.31)]. Among occupation categories, not working subpopulation reported to has the highest prevalence of depression [4.5% (95% CI: 3.01, 6.65)]. By household income group, the higher prevalence was observed in income group below RM1,000 [4.9% (95% CI: 3.05, 7.74)] compared to others. Conclusion The prevalence of depression among adults aged 18 years and above in Malaysia was 2.3%. The current depression prevalence in other countries range from 2.2% to 10.4% [9]. Our national prevalence is comparable with the other national prevalence such as Japan and Thailand [9][10]. The findings emphasized on risk communication towards vulnerable subpopulation such as rural, single, Bumiputera Sabah, non- working, and very low household income group. Recommendations

1. Increase promotion and enhance awareness about the importance of mental health issues to the specific target groups for example Bumiputera Sabah, single and non- working subpopulation.
2. The publicity regarding mental health programs i.e. Minda Sihat Programme must be further expanded with a focus on reducing the stigma of mental illness among communities.
3. Multi-agency collaboration to provide intervention for the high-risk population i.e. social support system for single & widower/divorcee, empowerment of peer support and intervention to increase the employment rate. References

Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3: e442. 2. de Zwart, P.L.; et al. (2018). “Empirical evidence for definitions of episode, remission, recovery, relapse and recurrence in depression: a systematic review”. Epidemiology and Psychiatric Sciences: 1–19. doi:10.1017/S2045796018000227. PMID 29769159. 3. WHO 2019. Available from:https://www.who.int/news-room/fact-sheets/ detail/depression 4. Institute for Public Health (1996). National Health and Morbidity Survey 1996: Volume 6. Psycriatric Morbidity in Adults. Ministry of Health; 1996. 5. Institute for Public Health. (2015). National Health & Morbidity Survey 2015: Non-communicable diseases, risk factors & other health problems (volume II). 6. Institute for Public Health (2011). National Health and Morbidity Survey 2011. Vol. II. Non-communicable Diseases. Ministry of Health; 2011 7. Mitchell AKC, J.C. Screening for depression in clinical practice. An evidence-based guide. New York: Oxford University Press; 2010. 8. Sherina MS, Arroll B, Goodyear-Smith F. Criterion validity of the PHQ-9 (Malay version) in a primary care clinic in Malaysia. The Medical journal of Malaysia. 2012 Jun;67(3):309-15. 9. Kessler, R.C. and Bromet, E.J., 2013. The epidemiology of depression across cultures. Annual review of public health, 34, pp.119-138. 10. Kongsuk T. The prevalence of major depressive disorders in Thailand: results from the Epidemiology of Mental Disorders National Survey 2008. Available from: http://www.dmh.go.th/downloadportal/Morbidity/ Depress2551.pdf.

National Health and Morbidity Survey 2019 Technical Report − Volume I 258 Table 20.1: Prevalence of Depression Among Adults Aged 18 Years and Above in Malaysia by Socio-Demographic Characteristics (n=11,674) Sociodemographic Characteristics Count Estimated Population Prevalence (%) 95% CI Lower Upper MALAYSIA 261 472,420 2.3 1.87 2.78 State Johor 13 28,766 1.2* 0.58 2.26 Kedah 16 31,147 2.3* 1.06 5.00 Kelantan 6 11,937 1.2* 0.47 2.97 Melaka 17 18,551 3.8 2.17 6.46 Negeri Sembilan 19 50,965 5.0* 2.41 10.03 Pahang 24 32,582 3.6 2.50 5.24 Pulau Pinang 13 24,331 2.1* 0.95 4.39 Perak 11 24,207 1.6* 0.78 3.12 Perlis 23 6,686 4.3 2.50 7.22 Selangor 19 45,840 1.0 0.57 1.79 Terengganu 26 24,617 3.6* 1.76 7.07 Sabah 28 101,109 4.0 2.28 7.07 Sarawak 16 54,217 3.6 2.14 5.86 WP Kuala Lumpur 7 13,959 1.2* 0.45 3.04 WP Labuan 8 551 0.9* 0.38 2.20 WP Putrajaya 15 2,956 5.4 3.29 8.78 Location Urban 151 297,699 1.9 1.50 2.34 Rural 110 174,721 3.6 2.48 5.24 Sex Male 106 206,593 2.0 1.44 2.73 Female 155 265,827 2.6 2.02 3.30 Age Group (Years) 15-19 12 19,574 2.1* 1.00 4.37 20-24 35 89,345 3.1 1.94 4.84 25-29 37 118,087 3.9 2.47 6.19 30-34 26 47,340 1.8 1.06 2.99 35-39 25 42,592 1.8 1.12 2.98 40-44 12 17,450 1.0* 0.42 2.13 45-49 25 27,202 1.7 1.00 2.85 50-54 28 32,974 2.2 1.31 3.69 55-59 15 24,021 1.9* 0.89 3.83 60-64 14 31,523 3.1* 1.16 7.86 65-69 8 7,612 1.1* 0.44 2.63 70-74 7 3,410 0.7* 0.15 3.48 75 & above 17 11,292 2.4 1.36 4.35 Ethnicity Malaya 172 262,592 2.4 1.93 3.10 Chinese 19 42,203 0.9 0.54 1.67 Indian 30 34,192 2.7 1.55 4.72 Bumiputera Sabah 21 66,902 5.2* 2.84 9.22 Sociodemographic Characteristics Count Estimated Population Prevalence (%) 95% CI Lower Upper Bumiputera Sarawak 9 28,134 3.6* 1.57 7.92 Others 10 38,396 1.8* 0.74 4.10 Marital Status Single 79 198,486 3.2 2.35 4.46 Married 146 235,853 1.8 1.40 2.31 Widow(er)/Divorcee 34 29,315 2.0 1.23 3.23 Education Level No Formal Education 15 16,800 2.0* 0.80 4.93 Primary Education 53 74,453 2.0 1.34 3.09 Secondary Education 137 275,966 2.6 2.05 3.37 Tertiary Education 56 105,201 1.9 1.27 2.73 Occupation Government Employee 19 14,229 0.9* 0.46 1.85 Private Employee 69 142,474 1.8 1.26 2.54 Self Employed 48 78,335 2.2 1.47 3.17 Unpaid Worker/ Homemaker 49 98,686 2.7 1.88 3.88 Retiree 6 8,107 1.2* 0.23 5.70 Student 11 24,243 2.8* 1.29 6.16 Not Workingb 59 106,346 4.5 3.01 6.65 Household Income Group Less than RM 1,000 42 98,778 4.9 3.05 7.74 RM 1,000 - RM 1,999 60 93,050 2.2 1.52 3.24 RM 2,000 - RM 3,999 87 165,069 2.5 1.68 3.57 RM 4,000 - RM 5,999 30 48,413 1.5 0.89 2.44 RM 6,000 - RM 7,999 23 50,144 2.3 1.34 4.02 RM 8,000 - RM 9,999 10 12,083 1.3* 0.44 3.92 RM 10,000 and above 9 4,883 0.3* 0.14 0.82 Household Income Quintile Quintile 1 70 144,977 3.7 2.50 5.32 Quintile 2 61 99,437 2.4 1.67 3.44 Quintile 3 50 106,274 2.5 1.60 3.82 Quintile 4 42 64,375 1.5 0.97 2.36 Quintile 5 38 57,357 1.4 0.86 2.32 Household Income Category Bottom 40% 200 371,375 2.7 2.11 3.33 Middle 40% 46 80,951 1.6 1.08 2.47 Top 20% 15 20,094 1.1* 0.53 2.46 *Prevalence with high RSE, interpret with caution a - Malay includes Orang Asli b - Not working includes Unemployed, and Old Age