Nutrient Profiling Model Towards Recommendation of A Healthy Diet: A Scoping Review

The objective of this study is to identify the availability of Nutrient Profiling (NP) models worldwide and discuss their application. This scoping review is based on the Preferred Reporting Items for Systematic Review and Meta-Analyses Extension for the Scoping Review (PRISMA-ScR) and the Arksey and O’Malley framework. Articles related to NP among adults published from 2012 to 2022, written in English, were retrieved from the Web of Science, Science Direct, Scopus, and Pubmed databases. Mendeley software was used for database acquisition and MS Excel for the syntesis process. Only 17 articles out of 2,019 article titles identified met the inclusion criteria for the review. This review discovers that the applications of NP in nutrition policies include food labelling, Front-Of-Pack (FOP), and regulations on food marketing, health, and nutrition. Fibre is the nutrient that needs to be included in the NP application compared to saturated fats, fatty acids, sodium, and total sugar. This scoping review demonstrates the scientific basis of the NP model’s development in public health policy, leading to advocacy and the recommendation of healthy diets

Prediction of body fat loss in relation to change in nutrient intake among housewives participating in the MyBFF@ home study

Background: Diet compositions are likely to be one of the influential factors for body fat deposition. The aim of this paper was to determine the nutrient changes and its association to body fat loss among the overweight and obese housewives in the MyBFF@home study. Methods: Data of participants in the MyBFF@home study (intervention and control groups) were analysed. Participants in the intervention group received personalised dietary counselling consisted of reduced calorie diet 1200–1500 kcal/day, while the control group was assigned to receive women’s health seminars. The dietary assessment was done during the intervention phase at baseline, 1 month (m), 2 m, 3 m and 6 m using a 3-day food diary. Body fat was measured using a bioelectrical impedance analyser (In-body 720) at baseline and at the end of the intervention phase. The mean differences of nutrient intake and body compositions during the intervention phase were measured with paired t-test. The changes in body fat and nutrients intake were calculated by subtracting baseline measurements from those taken at 6 months. Multiple linear regression analysis was conducted to determine the extent to which the changes in each gram of nutrients per 1000 kcal were predictive of changes in body fat mass. Results: There were significant reductions in energy, all macronutrients, dietary fibre, calcium and iron intake in both study groups after the intervention phase (p <  0.05). In the intervention group, body fat loss increased with the reduction of each gram of carbohydrate, protein and fat per 1000 kcal, (p <  0.05), and decreased with the reduction of each gram of calcium and fibre intake per 1000 kcal (p <  0.05). In the control group, body fat loss increased with the reduction of each gram fat per 1000 kcal (p <  0.05) and decreased with the reduction of each gram iron per 1000 kcal. Conclusion: Changes in the intake of various nutrients have different effects on body fat loss between the intervention and control group

Risk Factors Associated with Underweight Children Under the Age of Five in Putrajaya, Malaysia: A Case-Control Study

The study aimed to determine the associated factors for underweight among children under five years old in Putrajaya, Malaysia. This was a case-control study with a one-to-one ratio matched by sex as well as by three age categories (6‒11 months, 12‒35 months, dan 36‒59 months) between underweight and normal-weight children. There were 364 underweight children and 364 children with normal weight recruited from four government clinics and 118 preschools in Putrajaya. Both groups were assessed via face-to-face interviews; anthropometric measurements; haemoglobin level through finger prick blood sample; and a self-administered 3-day food diary. Underweight is defined as a weight-for-age z score less than -2SD based on World Health Organization (WHO) 2006 Growth Chart. The logistic regression’s final model revealed that various factors were significantly associated with underweight among children under five in Putrajaya. These factors included father being employed as a non-government servant [aOR:1.45 (95% CI:1.04‒2.02) compared to government servant], children from B40 group with a monthly household income less than <RM 7,380 (USD 1727.33) [aOR:2.17 (95% CI:1.01‒4.66) compared to T20], monthly expenditure for childcare less than RM 1,000 (USD 234.06), [aOR:1.77 (95% CI:1.01‒3.10) compared to ≥RM 2,000], underweight mother during prepregnancy [aOR:1.89 (95% CI:1.10‒3.26)] compared to normal weight, anemic children [aOR:1.57 (95% CI:1.15‒2.16)] compared to normal children, children using pacifiers [aOR:1.75 (95% CI:1.21‒2.73)] compared to not using pacifiers and children staying with unregistered babysitters [aOR:2.33 (85% CI:1.52‒3.59)] compared to those attending kindergarten. The above findings suggest several factors are significantly associated with underweight among children under five years old. Therefore, it highlights on the importance of improving household socioeconomic status, maternal nutritional status, and infant and young child feeding practices to prevent underweight issues in this population

Food insecurity situation in Malaysia: findings from Malaysian Adult Nutrition Survey (MANS) 2014

Food insecurity affects food intake, and it could prevent an individual from consuming enough nutritious food to support and maintain health. The aim of this paper is to determine the prevalence and factors influencing food insecurity among Malaysian households. In 2014, the Malaysian Adult Nutrition Survey (MANS) was carried out, and one of the components measured was food insecurity. Six out of sixteen questions from the food security core-module questionnaire were adopted and answered by 2962 adults. The results showed that about 25.0% adult experienced food quantity insufficiency, 25.5% had food variety insufficiency, 21.9% practised reduced size of the meal, and 15.2% skipped main meal due to lack of money to spend on. For the parents, 23.7% only rely on cheap food to feed children, and 20.8% could not afford to purchase various foods to feed their children. Location, strata, race, level of education, working status and household income shows significant difference while none of the nutritional status components found to be difference in all six parameters of food insecurity measured. Logistic regression with adjusted odds ratios discovered race, education level and household income were related to risk to all six parameters of food insecurity. In conclusion, food insecurity can be a serious problem in Malaysia. An effective and comprehensive effort by the government in terms of policy solution is required to increase education level and ensure an adequate income for every household. Therefore, future research should focus on some of those promising policy solutions and at the same time, study the other possible underlying factors that may lead to food insecurity

Factors Associated with High Sodium Intake Assessed from 24-hour Urinary Excretion and the Potential Effect of Energy Intake

Dietary consumption and other environmental factors are known factors associated with sodium intake. However, little is known about the influence of energy intake on this relationship. The aim of this study was to determine the risk factors associated with high sodium intake assessed from urine sodium excretion and the influence of energy intake. A nationwide, cross-sectional study was conducted from 2015 to 2016 among Malaysian health staff (MySalt 2015). A total of 1027 participants from 1568 targeted participants aged 18 years and older that were randomly selected were included in this study. Sodium intake was determined by measuring sodium excretion in the 24 hr urine test. Dietary, sociodemography, and anthropometry variables as associated risk factors were assessed. Multiple logistic regression models were used to determine the association between high sodium intake (≥2000 mg/day urinary sodium) and potential risk factors. The prevalence of high sodium intake in this study was 70.1% (n=733). High sodium intake was associated with male (OR 1.93, 95% confidence interval (CI) 1.41, 2.64), Bumiputera Sarawak ethnicity (OR 0.24, 95% CI 0.09, 0.62), and energy-adjusted sodium intake (mg/d) (OR 1.19, 95% CI 1.03–1.39). Our results suggested that sex, ethnicity, and energy-adjusted sodium consumption were strong risk factors associated with high sodium intake independent from energy and other potential confounding factors

Malnutrition among the Elderly in Malaysia and Its Associated Factors: Findings from the National Health and Morbidity Survey 2018

Background. Malaysia is predicted to become an ageing population by 2035. Malnutrition among the elderly is one of growing concern. This study aims to identify the prevalence of malnutrition and its associated factors among the elderly in Malaysia. Methods. Data from the National Health and Morbidity Survey (NHMS) 2018 was analysed. This survey applied a multistage stratified cluster sampling design to ensure national representativeness. Malnutrition was identified using a validated Mini Nutrition Assessment-Short Form (MNA-SF). Variables on sociodemographic, health status, and dietary practices were also obtained. The complex sampling analysis was used to determine the prevalence and associated factors of at-risk or malnutrition among the elderly. Result. A total of 3,977 elderly completed the MNA-SF. The prevalence of malnutrition and at-risk of malnutrition was 7.3% and 23.5%, respectively. Complex sample multiple logistic regression found that the elderly who lived in a rural area, with no formal or primary level of education, had depression, Instrumental Activity of Daily Living (IADL) dependency, and low quality of life (QoL), were underweight, and had food insecurity and inadequate plain water intake were at a significant risk of malnutrition (malnutrition and at-risk), while Chinese, Bumiputra Sarawak, and BMI more than 25 kgm−2 were found to be protective. Conclusions. Currently, three out of ten elderly in Malaysia were at-risk or malnutrition. The elderly in a rural area, low education level, depression, IADL dependency, low QoL, underweight, food insecurity, and inadequate plain water intake were at risk of malnutrition in Malaysia. The multiagency approach is needed to tackle the issue of malnutrition among the elderly by considering all predictors identified from this study

Comparison between self-reported physical activity (IPAQ-SF) and pedometer among overweight and obese women in the MyBFF@home study

Abstract Background Several methods have been developed to determine a person’s physical activity level. However, there is limited evidence in determining whether someone is physically active or not. This study aims to determine the level of physical activity and to compare the usage of short version International Physical Activity Questionnaire (IPAQ-SF) and pedometer among overweight and obese women who were involved in the My Body is Fit and Fabulous at home (MyBFF@home) study. Methods Baseline and sixth month data from the MyBFF@home study were used for this purpose. A total of 169 of overweight and obese respondents answered the IPAQ-SF and were asked to use a pedometer for 7 days. Data from IPAQ-SF were categorised as inactive and active while data from pedometer were categorised as insufficiently active and sufficiently active by standard classification. Data on sociodemographic and anthropometry were also obtained. Cohen’s kappa was applied to measure the agreement of IPAQ-SF and pedometer in determining the physical activity level. Pre-post cross tabulation table was created to evaluate the changes in physical activity over 6 months. Results From 169 available respondents, 167 (98.8%) completed the IPAQ-SF and 107 (63.3%) utilised the pedometer. A total of 102 (61.1%) respondents were categorised as active from the IPAQ-SF. Meanwhile, only 9 (8.4%) respondents were categorised as sufficiently active via pedometer. Cohen’s κ found there was a poor agreement between the two methods, κ = 0.055, p > 0.05. After sixth months, there was + 9.4% increment in respondents who were active when assessed by IPAQ-SF but − 1.3% reductions for respondents being sufficiently active when assessed by pedometer. McNemar’s test determined that there was no significant difference in the proportion of inactive and active respondents by IPAQ-SF or sufficiently active and insufficiently active by pedometer from the baseline and sixth month of intervention. Conclusion The IPAQ-SF and pedometer were both able to measure physical activity. However, poor agreement between these two methods were observed among overweight and obese women