Page 125 - Malaysian Journal of Health Promotion, Vol 4 (Supplementary 1) 2022
P. 125

Malaysian Journal of Health Promotion, Vol 4 (Supplementary 1) 2022
                                                                    rd
                      14  MOH-AMM Scientific Meeting 2022 in conjunction with 23  NIH Scientific Conference Abstract Book
                        th
               Institute for Public Health, National Institutes of Health (NIH), Ministry of Health Malaysia

               INTRODUCTION: This study aims to explore the association between dietary pattern and body
               mass index (BMI) in Malaysian adults.
               METHODS: Secondary data analyses were conducted on adults (n = 1,080) aged 18 to 59 years
               old who participated in the Malaysian Adults Nutrition Survey in 2014. Dietary information
               was  obtained  using  24-hour  dietary  recalls  conducted  by  qualified  nutritionists.  BMI  was
               calculated by dividing weight in kilograms by height in meters squared. Pearson product-
               moment correlation coefficient was computed to evaluate the relationship between total
               energy intake and BMI.
               RESULTS: Pearson (r = 0.298, n = 1,080, p < 0.01) showed a moderate positive correlation
                                                                                       2
               between total energy intake and BMI. The coefficient of determination r , in this study was
               0.089, meaning that 8.9% of variability in BMI can be explained by reporting of total energy
               intake of the 1,080 respondents. The remaining 91.1% of the variability in BMI was explained
               by  other  factors  in this study. There  was  a  significant,  positive  correlation between total
               carbohydrate (r = .234), protein (r = .147), total fat (r = .155), total sugar intake (r = .107), total
               dietary fibre (r = .147), total sodium (r = .124), and BMI at p < .05 (2-tailed) in which r- value
               referred to the strength of association between the nutrients and BMI.
               DISCUSSION/CONCLUSION: This study found that increase in total energy intake is correlated
               with an increase in BMI, suggesting that the amount of energy consumed by respondents may
               determine  their  BMI.  There  was  a  significant,  weak  positive  correlation  between  total
               carbohydrate, total  fat, total  sodium,  total dietary  fibre,  total  sugar  intake  and  BMI.  The
               association between carbohydrate and BMI had the highest r- value as compared to other
               nutrients. This result may be explained by the fact that carbohydrate is the major source of
               energy which contributes around 53% of total energy intake in diet among adults.

               ID 151 THE RELATIONSHIP BETWEEN RESILIENCE WITH DEPRESSION AMONG STUDENTS OF
               SEKOLAH TUNAS BAKTI

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                                   1
               Normawati Binti Ahmad , Normawati Binti Yusoff
               1 Institute for Health Behavioural Research, National Institutes of Health (NIH), Ministry of Health Malaysia
               2 Raja Perempuan Zainab II Hospital, Kota Bahru, Kelantan. Ministry of Health Malaysia

               INTRODUCTION: Depression was a mental health problem most frequently experienced by
               adolescents compared to other mental health problems. Adolescents especially those of low
               social  class  backgrounds  who  did  not  succeed  academically  and  are  detached  in  moral
               rehabilitation centers had actually at risk of depression. Resilience was seen as an element
               that  could  prevent  depression.  This  study  aimed  to  examine  the  relationship  between
               resilience with depression among moral rehabilitation center students’ of Sekolah Tunas Bakti
               (STB).
               METHODS: A cross-sectional study using a self-administered questionnaire. This study used
               Beck Depression Inventory-II (BDI II) and Ego Resilience Scale (ER89) instruments. Data were
               analyzed using descriptive, correlation, and regression.
               RESULTS:  The  result  showed  that  there  was  a  negative  significant  correlation  between
               resilience and depression. It means that high resilience could reduce depression.
               DISCUSSION/CONCLUSION: These findings could be used as a guideline for STB regarding the
               risk of depression among students and when developing intervention programs to improve
               resilience and reduce the level of depression.



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