Socio-demographic factors and healthy lifestyle behaviours among Malaysian adults: National Health and Morbidity Survey 2019 | Scientific Reports –

Data and participants

This study utilized secondary data from NHMS 2019. The NHMS is a national survey coordinated by the Institute of Public Health, Ministry of Health Malaysia, and has been conducted annually since 2011. This study is a cross-sectional survey with the aims of determining Malaysians’ health status, monitoring disease trends, and assessing healthcare utilization in Malaysia. The NHMS 2019 employs a nationally representative sample of the non-institutionalised general population of Malaysians of all ages in Malaysia. This study employs two-stage stratified random sampling to ensure the resulting sample was representative of the country. The country’s population is stratified by urban and rural regions in each of the 16 states or federal territories, hence a total of 29 strata. The first stage involves systematic random sampling of Enumeration Blocks (EB) within each stratum. The second stage involves random sampling of twelve living quarters (LQ) within each selected EB. For the entire country of Malaysia, a total of 475 Enumeration Blocks (EB) were selected proportionate to the population size of each stratum. A total of 5676 LQs were selected from the selected EBs. Further details of the NHMS 2019 study have been described in the NHMS 2019 technical report14. Between July and October 2019, 14,965 participants were recruited (response rate of 87.2%). All participants signed an informed consent form.

For the present study, participants under the age of 18 years were excluded (n = 4493), as the study’s focus was on the adult population. Respondents with missing socio-demographic data and healthy lifestyle data were excluded (n = 3084). After these exclusions, 7388 respondents were included in the present analyses.

Assessment of lifestyle factors and socio-demographic variables

Body weight, height and body mass index (BMI) were determined. Body weight was measured in kilograms using a digital weighing machine (TANITA HD-319) and the height in centimetres was measured using SECA Stadiometer 213. The BMI was computed by dividing weight in kilograms by the squared height in metres. BMI was then classified according to the WHO BMI guidelines: (< 25 kg/m2 as underweight to normal weight, ≥ 25 kg/m2 as overweight or obese)15.

Four questions were used to assess fruit and vegetable consumption: (1) “In a typical week, how many days did you consume fruits?” (2) “Usually on the day you eat fruits, how many servings of fruits did you eat in a day?” (3) “In a typical week, how many days did you eat vegetables?” (4) “Usually on the day you eat vegetable, how many servings of vegetables did you eat in a day?” Food photographs were used to assist respondents in recalling the serving size of fruits and vegetables consumed. The photographs depicted a single serving of commonly consumed fruits and vegetables, including one slice of watermelon, one medium-sized orange, one cup of chopped raw leafy green vegetables and a half cup of other vegetables, cooked or chopped raw such as carrot. The total number of servings of fruits and vegetables consumed per day was calculated using responses to these four questions. Data from the first two questions were used to estimate respondents’ fruits intake. Another two questions were used to estimate respondents’ vegetable intake. The number of days in a week was multiplied by number of servings to estimate the number of servings per week that respondents consumed. Responses for the past 7-day questions were then divided by 7 to determine daily intake. The number of servings/day for fruits and vegetable intake were summed to estimate the servings of fruits and vegetables intake. The range of score was 0 to 12 servings/day. Based on the Malaysian Dietary Guidelines, consumption of ≥ 5 servings of fruits and vegetables per day was defined as adequate while consumption of < 5 servings of fruits and vegetables per day was defined as inadequate16.

The validated short version of the International Physical Activity Questionnaire (IPAQ) was used to assess levels of physical activity17. The IPAQ short form was developed to estimate overall physical activity levels through the assessment of three specific types of physical activity (low, moderate and vigorous-intensity activities) across a broad range of domains (home, at work, sitting, moderate leisure, vigorous leisure, transportation and other activities). Physical activity was quantified in terms of metabolic equivalents (MET minutes, or METs)18. The minutes and days of a week spent on low, moderate, and vigorous intensity activities were multiplied by 3.3, 4.0 and 8.0 respectively, to compute MET scores for each activity. The total physical activity score was calculated as the sum of all MET scores from three sub-components. MET score ranges from 0 to 25,704. Participants in this survey were classified as “active” if they had a total physical activity score of at least 600 METs per week according to the WHO’s recommendation19. Those who did not meet the weekly requirement of 600 METs were classified as “inactive”.

The Malay version of the Alcohol Use Disorder Identification Test (AUDIT-M) questionnaire was used to assess alcohol consumption20. The AUDIT is a validated 10-item questionnaire that includes alcohol consumption, drinking behaviours, and alcohol-related problems. Scores were classified as low risk (score ranging from 1 to 7) or risky (score ranging from 8 to 40). Non-drinker was defined as having had no alcohol consumption for the past 12 months, which includes never drinkers.

The smoking status was divided into two categories: smoker (those who smoked tobacco products on a daily or occasional basis at the time of the survey) and non-smoker (those are not currently smoked any tobacco products).

Construction of a healthy lifestyle score

BMI, diet, physical activity, cigarette smoking, and alcohol consumption were all used to calculate a healthy lifestyle score12. The composite score’s five modifiable lifestyle factors were chosen based on national recommendations for non-communicable disease risk factors21 and epidemiological evidence in Asians22,23. For each of these components, a binary variable was created with one point assigned (0 otherwise) if the participant meets each criteria as follows: a BMI of < 25 kg/m2, performs regular physical activity, has moderate (or less) alcohol consumption, consumes at least 5 servings of fruits and vegetables, and does not smoke12. The healthy lifestyle score was calculated as the sum of the binary point system, ranging from 0 to 5 points. Participants were classified into three groups: unhealthy, moderately healthy and healthy. Individuals with healthy lifestyle scores of 0–2 were classified as ‘unhealthy’, those with a healthy lifestyle score of 3 were classified as ‘moderately healthy’, and those with healthy lifestyle scores of 4–5 were classified as the ‘healthy’ group.

Socio-demographic variables

The independent variables, which were socio-demographic variables, were used as categorical variables in the analyses. Age was captured in the data as a continuous variable and recoded into three categories (18–30 years, 31–60 years, and 60 years and above). Highest educational levels were combined into three categories; primary, secondary and tertiary. ethnicity (Malay, Chinese, Indian and others), educational level (no formal education/ primary, secondary and tertiary), residential area (urban and rural) and marital status (single, married and divorced/widowed). Income information defined as monthly household income, was collected. The income categories were divided into three categories; bottom 40% (B40), middle 40% (M40), and top 20% (T20) of household income.

Statistical analyses

Data were analysed using IBM SPSS version 22; p-values of < 0.05 were considered statistically significant. Weighting was applied to take into account the complex study design.

A weighting factor was applied to each respondent to adjust for non-response and for the varying probabilities of selection. The weight used for estimation was given by:

$$ {\text{W }} = {\text{ W1 }} \times {\text{ W2 }} \times {\text{ F }} \times {\text{ PS}} $$

W1 = the inverse of probability of selecting the EBs, W2 = the inverse of probability of selecting the LQs within the EBs, F = the inverse of an EBs, LQs and individual level non-response adjustment factor, PS = a post stratification adjustment factor calculated by strata and gender.

Survey-weighted descriptive statistics were computed to provide nationally representative estimates. Survey-weighted descriptive analyses of socio-demographic factors related with healthy lifestyle behaviours (unhealthy, moderate healthy and healthy) were done. For categorical variables, frequency and weighted percentage were displayed. Rao-Scott Chi-square test was conducted to identify bivariate associations between socio-demographic factors and healthy lifestyle groups. Multinomial logistic regression adjusted for sampling design was used to determine the association of socio-demographic factors with the moderately healthy and healthy lifestyle behaviours, using the unhealthy lifestyle group as the reference group. All predictors were included in the baseline-category logic model to estimate the adjusted odd ratio (aOR) and 95% confidence interval (CI).

Ethics approval and consent to participate

All participants signed an informed consent form. The NHMS 2019 was approved by the Medical Research and Ethics Committee of Ministry of Health Malaysia (NMRR-18-3085-44207). When conducted the analysis for this study in 2022, informed consent of the study participants was not required because the database used in this study consists of de-identified secondary data released for research purposes. This study was carried out in accordance with the ethical standards of the Declaration of Helsinki and Ministry of Health Malaysia guidelines and regulations.