METHODS: Therefore, using linear programming, this study is aimed to develop a healthy and balanced menu with minimal cost in accordance to individual needs that could in return help to prevent cancer. A cross sectional study involving 100 adults from a local university in Kuala Lumpur was conducted in 3 phases. The first phase is the data collection for the subjects, which includes their socio demographic, anthropometry and diet recall. The second phase was the creation of a balanced diet model at a minimum cost. The third and final phase was the finalization of the cancer prevention menu. Optimal and balanced menus were produced based on respective guidelines of WCRF/AICR (World Cancer Research Fund/ American Institute for Cancer Research) 2007, MDG (Malaysian Dietary Guidelines) 2010 and RNI (Recommended Nutrient Intake) 2017, with minimum cost.
RESULTS: Based on the diet recall, most of subjects did not achieve the recommended micronutrient intake for fiber, calcium, potassium, iron, B12, folate, vitamin A, vitamin E, vitamin K, and beta-carotene. While, the intake of sugar (51 ± 19.8 g), (13% ± 2%) and sodium (2585 ± 544 g) was more than recommended. From the optimization model, three menus, which met the dietary guidelines for cancer prevention by WCRF/AICR 2007, MDG 2010 and RNI 2017, with minimum cost of RM7.8, RM9.2 and RM9.7 per day were created.
CONCLUSION: Linear programming can be used to translate nutritional requirements based on selected Dietary Guidelines to achieve a healthy, well-balanced menu for cancer prevention at minimal cost. Furthermore, the models could help to shape consumer food choice decision to prevent cancer especially for those in low income group where high cost for health food has been the main deterrent for healthy eating.
MATERIALS AND METHODS: This is a cross-sectional study involving 382 older people living in the community in Malaysia. Data was collected using convenience sampling through an online questionnaire that consisted of three parts: sociodemographic details, knowledge, and attitude related to COVID-19.
RESULTS: The overall correct rate of knowledge was 77.3%, indicating that participants had slightly good knowledge related to COVID-19. The participants showed a positive attitude with a mean score of 26.0 (SD = 5.0). There were significant associations between knowledge and education level (P = 0.00) and marital status (P = 0.02). Marital status was significantly associated with attitude towards COVID-19 (P = 0.03). A weak positive correlation was found between knowledge and attitude (r = 0.17, P = 0.00) suggesting that an increase in knowledge will increase the positive attitude among older people.
CONCLUSION: Older people reported good knowledge and positive attitudes towards COVID-19. The Malaysian government should provide relevant health education for those with lower education levels and divorced or widowed to improve knowledge and attitudes towards COVID-19.
METHODS: Unstructured observations and a focus-group discussion were carried out with 18 participants involved in a six-week SRT program in a residential care facility in Kuala Lumpur.
RESULTS: Analysis revealed four themes: (i) Enthusiastic participation; (ii) Connections across boundaries; (iii) Expressing and reflecting; and (iv) Successful use of triggers.
CONCLUSIONS: The findings suggest that the process of reminiscence, on which the program was based, was enjoyable for the participants and created opportunities to form connections with other members of the group. The use of relevant triggers in the SRT program that related to Malaysian cultures, ethnicities and religions was helpful to engage the participants and was acceptable across the different religions and ethnicities.
CONTENT: Databases search of Scopus, ScienceDirect, PubMed, Directory of Open Access Journals (DOAJ), Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus, MyJournal, Biblioteca Regional de Medicina (BIREME), BioMed Central (BMC) Public Health, Medline, Commonwealth Agricultural Bureaux (CAB), EMBASE (Excerpta Medica dataBASE) OVID, and Web of Science (WoS) was performed, which include the article from 1st January 2008 until 31st August 2018 using medical subject heading (MeSH). Articles initially identified were screened for relevance.
SUMMARY: Out of 744 papers screened, nine eligible studies did meet our inclusion criteria. Prison and housing environments were evaluated for TB transmission in living environment, while the other factor was urbanization. However, not all association for these factors were statistically significant, thus assumed to be conflicting or weak to end up with a strong conclusion.
OUTLOOK: Unsustainable indoor environment in high congregate setting and overcrowding remained as a challenge for TB infection in Malaysia. Risk factors for transmission of TB, specifically in high risk areas, should focus on the implementation of specialized program. Further research on health care environment, weather variability, and air pollution are urgently needed to improve the management of TB transmission.
Methods: The sociodemographic data of 3325 TB cases from January 2013 to December 2017 in Gombak district were collected from the MyTB web and TB Information System database. Environmental data were obtained from the Department of Environment, Malaysia; Department of Irrigation and Drainage, Malaysia; and Malaysian Metrological Department from July 2012 to December 2017. Multiple linear regression (MLR) and artificial neural network (ANN) were used to develop the prediction model of TB cases. The models that used sociodemographic variables as the input datasets were referred as MLR1 and ANN1, whereas environmental variables were represented as MLR2 and ANN2 and both sociodemographic and environmental variables together were indicated as MLR3 and ANN3.
Results: The ANN was found to be superior to MLR with higher adjusted coefficient of determination (R2) values in predicting TB cases; the ranges were from 0.35 to 0.47 compared to 0.07 to 0.14, respectively. The best TB prediction model, that is, ANN3 was derived from nationality, residency, income status, CO, NO2, SO2, PM10, rainfall, temperature, and atmospheric pressure, with the highest adjusted R2 value of 0.47, errors below 6, and accuracies above 96%.
Conclusions: It is envisaged that the application of the ANN algorithm based on both sociodemographic and environmental factors may enable a more accurate modeling for predicting TB cases.
OBJECTIVE: This study aimed to evaluate the social support associated with the family caregivers of older people.
METHODS: A cross-sectional study was conducted among 231 family caregivers of older people conveniently selected from two districts in Kelantan, a state in the North-East Region of Peninsular Malaysia. Data were gathered between June to December 2021 using a Multidimensional Scale of Perceived Social Support (MSPSS) questionnaire. Descriptive statistics were used to summarize the data in frequencies and percentages. Independent t-test and one-way analysis of variance were used to examine correlations among variables.
RESULTS: The mean scores of social support for family caregivers were significantly higher among their family (Mean ± SD; 5.44 ± 0.969) and other important people (5.25 ± 1.123) compared to their friends (4.84 ± 1.094). Caregivers' gender and duration of caregiving were significant factors associated with social support (p <0.05).
CONCLUSIONS: The family caregivers received maximum support from their family and other important people, but they were less supported by their friends. This study also observed that the perceived social support of the caregivers of older people was affected by several factors, such as gender and duration of caregiving. This finding gives nurses and other healthcare workers the basic information they need to enhance nursing interventions and promote social support among those who care for older people, which can positively impact caregiving.
METHODS: This was a pure experimental research on Wistar rats with a post-test control group design. Five experimental groups (X1, X2, X3, X4, X5) were given 0.0375 mg, 0.075 mg, 0.15 mg, 0.3 mg, and 0.6 mg of low-density polyethylene microplastics mixed in 2cc distilled water, respectively. Furthermore, except for control (C), the groups received microplastics an oral probe for 90 days.
RESULTS: The molecular response of hippocampal neurons of Wistar rats to microplastics in the blood significantly decreased SOD enzyme expression, while CAT enzyme was unaffected. It considerably increased neuronal membrane damage (expression of MDA), increased considerably neuronal deoxyribonucleic acid damage (expression of 8-OHdG), and decreased blood serum Aβ42 levels (pathway analysis, all t-value >1.96).
CONCLUSION: The pathway analysis showed that hippocampal neurons were significantly affected by microplastic particles in the blood.