METHODS: A cross-sectional study was conducted among 134 geriatric patients with a mean age of 68.9 ± 8.4 who stayed at acute care wards in Hospital Tuanku Ampuan Rahimah, Klang from July 2017 to August 2017. The SGA, MNA, and GNRI were administered through face-to-face interviews with all the participants who gave their consent. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the GNRI and MNA were analyzed against the SGA. Receiver-operating characteristic (ROC) curve analysis was used to obtain the area under the curve (AUC) and suitable optimal cutoff values for both the GNRI and MNA.

RESULTS: According to the SGA, MNA, and GNRI, 26.9%, 42.5%, and 44.0% of the participants were malnourished, respectively. The sensitivity, specificity, PPV, and NPV for the GNRI were 0.622, 0.977, 0.982, and 0.558, respectively, while those for the MNA were 0.611, 0.909, 0.932, and 0.533, respectively. The AUC of the GNRI was comparable to that of the MNA (0.831 and 0.898, respectively). Moreover, the optimal malnutrition cutoff value for the GNRI was 94.95.

METHODS: A literature search was performed on six databases using the terms "malnutrition", "hospitalised elderly", "nutritional assessment", "Mini Nutritional Assessment (MNA)", "Geriatric Nutrition Risk Index (GNRI)", and "Subjective Global Assessment (SGA)".

RESULTS: According to the previous studies, the prevalence of malnutrition among hospitalized elderly shows an increasing trend not only locally but also across the world. Under-recognition of malnutrition causes the number of malnourished hospitalized elderly to remain high throughout the years. Thus, the development of nutritional screening and assessment tools has been widely studied, and these tools are readily available nowadays. SGA, MNA, and GNRI are the nutritional assessment tools developed specifically for the elderly and are well validated in most countries. However, to date, there is no single tool that can be considered as the universal gold standard for the diagnosis of nutritional status in hospitalized patients.

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.

METHODOLOGY: A total of 396 students from the Management and Science University (MSU) participated during the semester of March 2010. Stratified random sampling was used and consent was obtained before the questionnaire was distributed. ANOVA and the t-test were used for the univariate analysis and multiple linear regression was used for the multivariate analysis.

RESULTS: The participants ages ranged from 18 to 27 years (Mean ± SD = 23.3 ± 1.57), more than half being female (62.4%). The majority were 23 years old or younger, single, Malay and from non-Medical and Health Science faculties and with a family monthly income of less than 10,000 Ringgits Malaysia(79.5%; 99%, 65.9, 52.5%, 63.9%; respectively). Only 18.4% of participants reported a family history of cancer. About 32.1% had a medical check-up in the previous 12 months and 17.4% were smokers. Multivariate analysis showed the faculty type to be significantly associated with knowledge of cancer prevention (p = 0.04). Regular medical check-ups were associated with attitudes and practices of cancer prevention (p = 0.04, p=0.003 respectively), the latter being significantly influenced by sex, family history of cancer and smoking (p = 0.034, p=0.013, p=0.002; respectively).

METHODS AND STUDY DESIGN: A total of 116 items associated with sociodemographic characteristics (7 items), professional development (3 items), organisational culture's support for the NCP (2 items), knowledge (27 items), attitudes (39 items), practices (20 items), and perceived barriers to implementing the NCP (14 items) were generated for potential inclusion in the KAPB-NCP questionnaire. The questionnaire was reviewed online by an expert panel for its content validity. An in-depth review was conducted by the research team for evaluating the overall comprehensiveness of the questionnaire.

RESULTS: In total, 87 of 100 items of the KAPB sections showed an excellent content validity index (CVI; k* >0.74), whereas 10 showed a satisfactory CVI (k*=0.60-0.74). Only 3 items had a low CVI (k* <0.40). According to the expert panel revisions and the in-depth review, 72 items were incorporated into the questionnaire.

BACKGROUND: Continuous effort has been made to identify patients at high risk of malnutrition, but monitoring and documentation of nutritional intake are relative less emphasized upon.

METHODS: A needs assessment through a cross-sectional study design was carried out at six hospitals in Yogyakarta, Indonesia. A self-administered semi-structured questionnaire was filled out by 111 respondents recruited from three different professions (nurses, dietitians and serving assistants) in the wards.

RESULTS: Seventy per cent of the respondents perceived that the current dietary assessment tool used to record patients' food intake was simple; however, the disadvantage of this tool was its tedious process of computing nutritional values of food consumed. Furthermore, more than half respondents encountered problems in conducting food intake record of patients, primarily due to limited number of human resources, followed by time constraints and perception that such dietary assessment as not part of their job scope.

DISCUSSION: This study has revealed important information in developing a simple, valid and reliable dietary assessment tool for monitoring food intake of hospitalized patients to be applied by interdisciplinary hospital professionals.

CONCLUSIONS: Awareness of the important on monitoring nutrient intake of patients should be emphasized among healthcare professionals. The current dietary assessment tool requires modification due to lengthy time taken to complete the task and poor accuracy in intake estimation.

METHODS: To gain a more comprehensive picture on how these markers can modulate BC risk, alone or in conjunction, we performed simultaneous measurements of LTL and mtDNA copy number in up to 570 BC cases and 538 controls from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. As a first step, we measured LTL and mtDNA copy number in 96 individuals for which a blood sample had been collected twice with an interval of 15 years.

RESULTS: According to the intraclass correlation (ICC), we found very good stability over the time period for both measurements, with ICCs of 0.63 for LTL and 0.60 for mtDNA copy number. In the analysis of the entire study sample, we observed that longer LTL was strongly associated with increased risk of BC (OR 2.71, 95% CI 1.58-4.65, p = 3.07 × 10- 4 for highest vs. lowest quartile; OR 3.20, 95% CI 1.57-6.55, p = 1.41 × 10- 3 as a continuous variable). We did not find any association between mtDNA copy number and BC risk; however, when considering only the functional copies, we observed an increased risk of developing estrogen receptor-positive BC (OR 2.47, 95% CI 1.05-5.80, p = 0.04 for highest vs. lowest quartile).

METHODS: Data on highest education attained were gathered for 459,170 participants (70% women) from 10 European countries. A relative index of inequality (RII) based on adult education was calculated for comparability across countries and generations. Cox regression models were applied to estimate relative inequality in pancreatic cancer risk, stratifying by age, gender, and center, and adjusting for known pancreatic cancer risk factors.

RESULTS: A total of 1,223 incident pancreatic cancer cases were included after a mean follow-up of 13.9 (±4.0) years. An inverse social trend was found in models adjusted for age, sex, and center for both sexes [HR of RII, 1.27; 95% confidence interval (CI), 1.02-1.59], which was also significant among women (HR, 1.42; 95% CI, 1.05-1.92). Further adjusting by smoking intensity, alcohol consumption, body mass index, prevalent diabetes, and physical activity led to an attenuation of the RII risk and loss of statistical significance.

CONCLUSIONS: The present reanalysis does not sustain the existence of an independent social inequality influence on pancreatic cancer risk in Western European women and men, using an index based on adult education, the most relevant social indicator linked to individual lifestyles, in a context of very low pancreatic cancer survival from (quasi) universal public health systems.

METHODS: A cross-sectional study was conducted in the Kandy district, Sri Lanka. The nutritional status of older persons was assessed using the Mini Nutritional Assessment -Short Form (MNA-SF). A standardised questionnaire was used to record factors associated with malnutrition: demographic characteristics, financial characteristics, food and appetite, lifestyle, psychological characteristics, physical characteristics, disease and care, oral health, and social factors. Complex sample multinomial logistic regression analysis was performed.

RESULTS: Among the 999 participants included in the study, 748 (69.3%) were females and 251 (25.1%) were males. The mean age was 70.80 years (95% CI: 70.13, 71.47). The prevalence of malnutrition, risk of malnutrition and well-nutrition was 12.5%, 52.4% and 35.1% respectively. In the multivariate model, hypertension (adjusted OR = 1.71; 95% CI: 1.02, 2.89), alcohol consumption (aOR = 4.06; 95% CI: 1.17, 14.07), and increased age (aOR = 1.06; 95% CI: 1.01, 1.11) were positively associated with malnutrition. An increased number of people living with the older person (aOR: 0.91; 95% CI: 0.85, 0.97) was a protective factor among those at risk for malnutrition.

OBJECTIVE: The study aimed to derive dietary patterns empirically and to examine the consistency and generalizability of patterns across sex, ethnicity, and urban status in a working population.

DESIGN: This was a cross-sectional study using data from the Clustering of Lifestyle Risk Factors and Understanding its Association with Stress on Health and Well-Being among School Teachers in Malaysia study collected between August 2014 and November 2015. Dietary intake was assessed using a food frequency questionnaire, and dietary patterns were derived using factor analysis.

PARTICIPANTS/SETTING: Participants were teachers from selected public schools from three states in Peninsular Malaysia (n=4,618).

MAIN OUTCOME MEASURES: Dietary patterns derived using factor analysis.

STATISTICAL ANALYSES PERFORMED: Separate factor analysis was conducted by sex, ethnicity, and urban status to identify dietary patterns. Eigenvalue >2, scree plot, Velicer's minimum average partial analysis, and Horn's parallel analysis were used to determine the number of factors to retain. The interpretability of each dietary pattern was evaluated. The consistency and generalizability of dietary patterns across subgroups were assessed using the Tucker congruence coefficient.

RESULTS: There was no subgroup-specific dietary pattern found. Thus, dietary patterns were derived using the pooled sample in the final model. Two dietary patterns (Western and Prudent) were derived. The Western dietary pattern explained 15.4% of total variance, characterized by high intakes of refined grains, animal-based foods, added fat, and sugar-sweetened beverages as well as fast food. The Prudent dietary pattern explained 11.1% of total variance and was loaded with pulses, legumes, vegetables, and fruits.