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Non-Communicable Diseases: Risk Factors and other Health Problems 021 General Findings

National Health and Morbidity Survey 2019 Technical Report − Volume I 022 General Findings 3.1 Sample Coverage From the 5,147 eligible LQs, a total of 4,703 LQs were successfully interviewed, giving a LQ response rate of 91.4%. From these LQs, a total of 15,683 participants were eligible for interview. A total of 14,965 respondents were successfully interviewed, giving an individual response rate of 95.4%. The overall response rate for this community-based survey is therefore 87.2%. The response rate by state is presented in Table 3.1. Table 3.1: Response Rate by Living Quarters and Individual by State, NHMS 2019 State Living Quarters Individual Total
Response Rate (%)Eligible Interviewed Response Rate (%) Eligible Interviewed Response Rate (%) Johor 428 404 94.4 1,244 1,212 97.4 91.96 Kedah 255 241 94.5 788 760 96.4 91.15 Kelantan 261 250 95.8 801 791 98.8 94.59 Melaka 278 270 97.1 881 859 97.5 94.70 Negeri Sembilan 255 246 96.5 771 730 94.7 91.34 Pahang 272 265 97.4 908 894 98.5 95.92 Pulau Pinang 290 265 91.4 896 829 92.5 84.55 Perak 291 276 94.8 883 801 90.7 86.04 Perlis 260 253 97.3 730 722 98.9 96.24 Selangor 689 573 83.2 1,732 1,626 93.9 78.07 Terengganu 261 255 97.7 1,009 972 96.3 94.12 Sabah 415 374 90.1 1,417 1,344 94.8 85.48 Sarawak 329 296 90.0 1,160 1,067 92.0 82.76 WP Kuala Lumpur 281 238 84.7 688 664 96.5 81.74 WP Labuan 258 250 96.9 792 772 97.5 94.45 WP Putrajaya 324 247 76.2 983 922 93.8 71.50 MALAYSIA 5,147 4,703 91.4 15,683 14,965 95.4 8 7.1 9 3.2 Socio-Demographic Characteristics A total of 10.9% of the respondents of NHMS 2019 are from the state of Selangor. A total of 61.4% of the respondents are from urban localities and females made up 52.8% of the total respondents. Those of Malay ethnicity were 66.5% of the respondents, with Indian ethnicity, Bumiputera Sabah, Bumiputera Sarawak and others making up between 4% to 7% each. A total of 36.5% of the respondents reported their highest educational level to be up to secondary education, with those of no formal education and tertiary education at 16.2% each. Private employees made up 20.2% of the respondents, meanwhile government employees made up 7.0%, with a further 3.4% of retirees in the sample.
Non-Communicable Diseases: Risk Factors and other Health Problems 023 Based on the self-reported income of each individual, the household income was calculated and categorized based on state-specific cut-off for B40, M40 and T20 category. The cut- off values for each state were obtained from the Departments of Statistics Malaysia. A total of 68.1% of the respondents fell in the B40 category, with only 8% in the T20 category. This, as in most self-reported studies, shows a certain degree of under-reporting present in the income levels. The sociodemographic characteristics of all respondents in NHMS 2019 are presented in Table 3.2. Table 3.2: Sociodemographic Characteristics of Sample, NHMS 2019 Sociodemographic characteristics Count Percentage (%) MALAYSIA 14,965 100.0 State   Johor 1,212 8.1 Kedah 760 5.1 Kelantan 791 5.3 Melaka 859 5.7 Negeri Sembilan 730 4.9 Pahang 894 6.0 Pulau Pinang 829 5.5 Perak 801 5.4 Perlis 722 4.8 Selangor 1,626 10.9 Terengganu 972 6.5 Sabah 1,344 9.0 Sarawak 1,067 7.1 WP Kuala Lumpur 664 4.4 WP Labuan 772 5.2 WP Putrajaya 922 6.2 Location   Urban 9,183 61.4 Rural 5,782 38.6 Sex   Male 7,064 47.2 Female 7,901 52.8 Age Group (Years)   0 – 4 1,249 8.3 5 – 9 1,391 9.3 10 – 14 1,214 8.1 15 – 19 977 6.5 20 – 24 938 6.3 25 – 29 973 6.5 30 – 34 1,008 6.7 35 – 39 1,065 7.1 40 – 44 891 6.0 45 – 49 908 6.1 Sociodemographic characteristics Count Percentage (%) 50 – 54 957 6.4 55 – 59 941 6.3 60 – 64 838 5.6 65 – 69 645 4.3 70 – 74 455 3.0 75 and above 515 3.4 Citizenship Malaysian 14,064 94.0 Permanent Resident 134 0.9 Non-Malaysian 766 5.1 Ethnicity   Malaya 9,955 66.5 Chinese 1,669 11.2 Indian 875 5.8 Bumiputera Sabah 1,039 6.9 Bumiputera Sarawak 608 4.1 Others 819 5.5 Marital Status   Single 6,667 44.6 Married 7,165 47.9 Widow(er)/Divorcee 1,132 7.6 Education Level   No Formal Education 2,423 16.2 Primary Education 4,597 30.7 Secondary Education 5,462 36.5 Tertiary Education 2,426 16.2 Occupation   Government Employee 1,050 7.0 Private Employee 3,027 20.2 Self-Employed 1,900 12.7 Unpaid Worker/Homemaker 2,068 13.8 Retiree 511 3.4 Student 2,878 19.2 Not Workingb 3,523 23.6 Household Income Quintile   Quintile 1 2,754 19.6 Quintile 2 2,848 20.3 Quintile 3 2,805 20.0 Quintile 4 2,638 18.8 Quintile 5 2,973 21.2 Household Income Category   Bottom 40% (B40) 9,551 68.1 Middle 40% (M40) 3,347 23.9 Top 20% (T20) 1,120 8.0 a - Malay includes Orang Asli b - Not working includes unemployed, and old age

National Health and Morbidity Survey 2019 Technical Report − Volume I 024 3.3 Sample Representativeness The estimated population obtained in the NHMS 2019 closely resembles the actual population structure of Malaysia for 2019, as projected by the Department of Statistics Malaysia. The comparison is shown in Figure 3.1. Figure 3.1: Population Pyramid Comparing Estimated Population of NHMS 2019 and Projected Population of Malaysia for 2019 by Age and Sex [1] Reference: 1. Department of Statistics Malaysia (2016). Population Projection (Revised), Malaysia, 2010-2040

Non-Communicable Diseases: Risk Factors and other Health Problems 025 Non-Communi­ cable Diseases: Diabetes, Hypertension and Hypercho­ lesterolaemia

National Health and Morbidity Survey 2019 Technical Report − Volume I 026 Non-Communicable Diseases: Diabetes, Hypertension And Hypercholesterolaemia Introduction Non-Communicable Diseases (NCDs) are the leading cause of death worldwide. In 2016, NCDs were responsible for 71% of the 57 million deaths globally. An estimated 78% of all NCD deaths and 85% of premature adult NCD deaths occurred in low- and middle-income countries [1]. In Malaysia, NCDs contribute to 71% of premature deaths. According to Malaysian Burden of Disease and Injury Study (2009-2014), cardiovascular and circulatory diseases contributed to 34.8% of deaths [2]. Data from the previous National Health and Morbidity Survey (NHMS) in the year 2011 and 2015 showed an increasing trend for diabetes and hypercholesterolaemia and plateaued trend for hypertension. The prevalence of diabetes was from 11.2% (2011) to 13.4% (2015), hypertension from 32.7% (2011) to 30.3% (2015), and hypercholesterolaemia from 35.1% (2011) to 47.7% (2015) [3] [4]. Malaysia has made enormous gains in the development and delivery of the healthcare system over the past five decades. However, the proportion of Malaysians with risk factors is still high, hence resulting in a substantial economic burden to our country. This report provides a platform for the Ministry of Health to continuously monitor and assess the trends of population health, to strengthen our healthcare system and improve the overall well-being of our population. 4.1 Diabetes Contributors to this section: Hasimah Ismail, Nabilah Hanis Zainuddin, Nur Liana Ab Majid, Halizah Mat Rifin, Muhammad Fadhli Mohd Yusoff, Feisul Idzwan Mustapha, Arunah Chandran, Masni Mohamad, Fatanah Ismail, Wan Shakira Rodzlan Hasani, Jane Ling Miaw Yn, Tania Gayle Robert Lourdes, Thamil Arasu Saminathan, Ahzairin Ahmad Objectives General Objective To determine the prevalence of diabetes in Malaysia. Specific Objectives

  1. To determine the prevalence of overall raised blood glucose by socio-demographic sub-groups

  2. To determine the prevalence of known diabetes by socio- demographic sub-groups

  3. To determine the prevalence of raised blood glucose amongst those not known to have diabetes by socio- demographic sub-groups Methods The diabetes module was carried out on all respondents aged 18 years old and above. Data was collected through questionnaires and measurement of finger-prick for fasting blood glucose using the CardioChek® portable blood test system. Variable Definition

  4. Overall raised blood glucose was defined as known diabetes and raised blood glucose amongst those not known to have diabetes.

  5. Known diabetes was defined as self-reported or being told to have diabetes by a doctor or assistant medical officer.

  6. Raised blood glucose amongst those not known to have diabetes was defined as the respondent who was not known to have diabetes and had a fasting capillary blood glucose (FBG) of 7.0 mmol/L or more (or non-fasting blood glucose of more than 11.1 mmol/L) [5].

Non-Communicable Diseases: Risk Factors and other Health Problems 027 Findings A total of 10,464 respondents responded to the diabetes module. Overall Raised Blood Glucose The overall prevalence of raised blood glucose among adults aged 18 years and above in this survey was 18.3% (95% CI: 17.08, 19.58). The prevalence of overall raised blood glucose increased with age, from 5.4% (95% CI: 3.66, 7.91) in the 20-24 years age group, reaching a peak of 43.4% (95% CI: 37.37, 49.65) among the 65-69 years old. The prevalence was reported to be 5.4% (95% CI: 3.66, 7.91) among those aged 20-24 years old and peaked at 65-69 years old [43.4% (95% CI: 37.37, 49.65)]. The prevalence was similar in both urban and rural areas. There was a large variation between the states, with the highest prevalence of 33.2% (95% CI: 25.06, 42.54) in Negeri Sembilan, followed by Perlis [32.6% (95% CI: 25.97, 40.09)] and Pahang [25.7% (95% CI: 21.11, 30.99)], while the lowest prevalence was reported in Sabah [9.8% (95% CI: 7.40, 12.91)], WP Labuan [12.6% (95% CI: 8.57, 18.19)] and Sarawak [13.1% (95% CI: 10.58, 16.13)]. The prevalence among males and females were 18.2% (95% CI: 16.63, 19.90) and 18.4% (95% CI: 16.99, 19.89) respectively. Indians had the highest prevalence [31.4% (95% CI: 25.85, 37.53)], followed by Malays [21.6% (95% CI: 20.02, 23.17)], Chinese [15.1% (95% CI: 12.52, 18.08)], and Bumiputera Sarawak [12.3% (95% CI: 8.88, 16.68)]. Overall raised blood glucose was more common among widow(er) / divorcee [33.2% (95% CI: 29.27, 37.30)], those with no formal education [28.7% (95% CI: 23.10, 34.94)], retirees [45.8% (95% CI: 40.26, 51.37)] and those from the B40 group [18.5% (95% CI: 17.02, 20.10)]. Known Diabetes The prevalence of known diabetes was 9.4% (95% CI: 8.66, 10.20). The prevalence of known diabetes increased with age. The prevalence was reported to be 4.5% (95% CI: 3.04, 6.71) among those aged 35-39 years and peaked at 65-69 years of age 34.3% (95% CI: 28.59, 40.50). The prevalence in the urban areas was 9.7% (95% CI: 8.83, 10.74) compared to rural [8.2% (95% CI: 7.27, 9.19)]. There was a large variation between states; the highest prevalence of 15.2% (95% CI: 12.12, 19.00) in Perak, followed by Melaka [13.7% (95% CI: 10.10, 18.38)] and Perlis [13.5% (95% CI: 10.80, 16.64)]; while the lowest being Sabah [4.1% (95% CI: 2.51, 6.60)] and Sarawak [7.7% (95% CI: 6.15, 9.55)]. The prevalence of known diabetes in males and females were 9.0% (95% CI: 8.01, 10.15) and 9.8% (95% CI: 8.85, 10.84) respectively. In terms of ethnic groups, Indians had the highest prevalence [18.5% (95% CI: 15.12, 22.34)], followed by Malays [11.0% (95% CI: 10.10, 11.95)], Chinese [8.5% (95% CI: 6.69, 10.69)] and Bumiputera Sarawak [7.9% (95% CI: 5.24, 11.89)]. Known diabetes was more common among widow(er) / divorcee [20.9% (95% CI: 17.99, 24.05)], those with no formal education [18.0% (95% CI: 13.84, 23.12)], retiree [32.9% (95% CI: 27.32, 38.98)] and those from the B40 group [9.2% ( 95% CI: 8.33,10.17)]. Among those with known diabetes, 25.7% claimed that they were on insulin therapy, 85.6% claimed to be on oral anti- diabetic drugs within the past 2 weeks, 88.0% had received specific diabetes diet advice from healthcare personnel and 75.4% claimed to have been advised by healthcare personnel to lose weight. 23.0% opted for traditional and complementary medication. Majority of those with known diabetes sought treatment at MOH health clinics 68.2%, followed by MOH hospitals 15.0%, private clinics 12.1% and private hospitals 2.8%. About 0.4% self-medicated by purchasing medications directly from pharmacies and 0.2% sought traditional and complementary medicine practitioners. However, about 2.1% of respondents did not seek any treatment for diabetes. Among known diabetes, 55.5%, 36.4% and 8.1% reported having had an eye examination within 1 year, 1 to 3 years and more than 3 years ago respectively. Among those who received eye treatment in the last five years, 7.0% received laser treatment, 3.0% received eye injection and other treatments (eye/vitreous surgery) 4.0%. Raised Blood Glucose Amongst Those Not Known to have Diabetes The prevalence of raised blood glucose amongst those not known to have diabetes was 8.9% (95% CI: 7.96, 9.93). The prevalence of raised blood glucose amongst those not known to have diabetes increased with age. The prevalence was reported to be 4.8% (95% CI: 3.15, 7.33) among those aged 20-24 years old and peaked at 45-49 years old [14.2% (95% CI: 11.17, 17.85)]. The prevalence was higher in the rural, 10.2% (95% CI: 8.66, 11.87), compared to the urban areas, 8.5% (95% CI: 7.44, 9.79). There was a large variation between states; the highest prevalence of 20.5% (95% CI: 14.63, 28.05) in Negeri Sembilan, followed by Perlis [19.2% (95% CI: 12.79, 27.78)] and Pahang [16.2% (95% CI: 12.32, 21.06)].

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