METHODS: We searched Ovid MEDLINE, EMBASE, the Cochrane Library, Web of Science and PubMed databases through to December 2013 using the terms "percutaneous endoscopic gastrostomy", "gastrostomy", "PEG", "nasogastric", "nasogastric tube", "nasogastric feeding" and "intubation". We included randomized controlled trials (RCTs) and non-RCTs which compared PEG with NG feeding in individuals with non-stroke dysphagia.
RESULTS: 9 studies involving 847 participants were included in the final analysis, including two randomized trials. Pooled analysis indicated no significant difference in the risk of pneumonia [relative risk (RR) = 1.18, 95% confidence interval (CI) = 0.87-1.60] and overall complications [relative risk (RR) = 0.80, 95% confidence interval (CI) = 0.63-1.02] between PEG and NG feeding. A meta-analysis was not possible for mortality and nutritional outcomes, but three studies suggested improved mortality outcomes with PEG feeding while two out of three studies reported PEG feeding to be better from a nutritional perspective.
CONCLUSIONS: Firm conclusions could not be derived on whether PEG feeding is beneficial over NG feeding in older persons with non-stroke dysphagia, as previously published literature were unclear or had a high risk of bias. A well-designed and adequately powered RCT, which includes carer strain and quality of life as outcome measures is therefore urgently needed.
METHODS: Multivariable-adjusted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average of 13.9 years of follow-up, there were 7024 incident prostate cancers and 934 prostate cancer deaths.
RESULTS: Height was not associated with total prostate cancer risk. Subgroup analyses showed heterogeneity in the association with height by tumour grade (P heterogeneity = 0.002), with a positive association with risk for high-grade but not low-intermediate-grade disease (HR for high-grade disease tallest versus shortest fifth of height, 1.54; 95% CI, 1.18-2.03). Greater height was also associated with a higher risk for prostate cancer death (HR = 1.43, 1.14-1.80). Body mass index (BMI) was significantly inversely associated with total prostate cancer, but there was evidence of heterogeneity by tumour grade (P heterogeneity = 0.01; HR = 0.89, 0.79-0.99 for low-intermediate grade and HR = 1.32, 1.01-1.72 for high-grade prostate cancer) and stage (P heterogeneity = 0.01; HR = 0.86, 0.75-0.99 for localised stage and HR = 1.11, 0.92-1.33 for advanced stage). BMI was positively associated with prostate cancer death (HR = 1.35, 1.09-1.68). The results for waist circumference were generally similar to those for BMI, but the associations were slightly stronger for high-grade (HR = 1.43, 1.07-1.92) and fatal prostate cancer (HR = 1.55, 1.23-1.96).
CONCLUSIONS: The findings from this large prospective study show that men who are taller and who have greater adiposity have an elevated risk of high-grade prostate cancer and prostate cancer death.
Methods: Post-stroke patients who attended the outpatient clinics in three hospitals of Peninsular Malaysia were enrolled in the study. The risk of malnutrition was assessed using the Malnutrition Risk Screening Tool-Hospital. Data including demographic characteristics, clinical profiles, dietary nutrients intake, body mass index (BMI) and hand grip strength were collected during the survey. The crude odds ratio (OR) and adjusted odds ratio (AOR) were reported for univariate and multivariate logistic regression analyses, respectively.
Results: Among 398 patients included in the study, 40% were classified as high-risk for malnutrition. In the multivariable logistic regression, tube feeding (AOR: 13.16, 95% confidence interval [CI]: 3.22-53.77), loss of appetite (AOR: 8.15, 95% CI: 4.71-14.12), unemployment (AOR: 4.26, 95% CI: 1.64-11.12), wheelchair-bound (AOR: 2.23, 95% CI: 1.22-4.09) and BMI (AOR: 0.87, 95% CI: 0.82-0.93) were found to be significant predictors of malnutrition risk among stroke patients.
Conclusion: The risk of malnutrition is highly prevalent among post-stroke patients. Routine nutritional screening, identification of risk factors, and continuous monitoring of dietary intake and nutritional status are highly recommended even after the stroke patient is discharged.
Methods: This cross-sectional study was conducted with 202 independently mobile OP (males 32%) in seven LTC homes in the Klang Valley of Malaysia. Trained personnel measured their anthropometrics, body composition, gait speed, hand grip strength and timed up-and-go (TUG) duration. Criteria of the European Working Group on Sarcopenia in Older People (EWGSOP) and of the Asian Working Group for Sarcopenia were used to identify the presence of sarcopenia. The mini-nutritional assessment (MNA) was used to determine their nutritional status. Additionally, logistic regression analysis was performed to identify significant risk factors associated with pre-sarcopenia/sarcopenia.
Results: Pre-sarcopenia/sarcopenia was detected in 103 (51%) OP. The significant risk factors were body mass index (BMI, weight/height2; adjusted odds ratio [AOR] = 0.44, P < 0.001), percentage of body fat (PBF; AOR = 1.26, P < 0.001), age group (≥ 80 years; AOR = 3.63, P = 0.025) and 'at risk of malnutrition' status (AOR = 2.63, P = 0.049).
Conclusion: Sarcopenia is common among OP in LCT homes. The risk increases with decreasing BMI, increasing PBF, age ≥ 80 years and suboptimal nutrition status.
METHODS AND STUDY DESIGN: Collective food data from MyHeARTs 2012 database were used to construct the MyUM Adolescent FFQ. Seventy-eight participants between 13 and 15 years old in 2014 were selected through convenient sampling for test-retest study. They completed the MyUM Adolescent FFQ twice, with an interval period of one week. One hundred and fifty-six MyHeARTs study participants who were 15 years old in 2014 were randomly selected for this comparative valid-ity study. They completed a 7-day diet history (7DDH) and subsequently completed the self-administered MyUM Adolescent FFQ.
RESULTS: Pearson's correlations between the FFQ and 7DDH for all macronutrients were statistically significant. Energy-adjusted correlations for protein, carbohydrate, and fat were 0.54, 0.63 and 0.49 respectively. Most of the micronutrients and minerals, were statistically correlated ranging from 0.31 to 0.49 after energy adjustment. Cross-classification analyses revealed that more than 70 percent of adolescents were classified into either the same or adjacent quartile of nutrient intake when comparing data of 7DDH and FFQ. No serious systematic bias was evident in the Bland-Altman plots.
CONCLUSION: The 200-item FFQ developed for Malaysian adolescents has moderate to good comparative validity for assessment of macronutrient and micronutrient intake.
METHODS: This cross-sectional study recruited children below 18 years old admitting into general paediatric ward in a public hospital. The PNST and Subjective Global Nutritional Assessment (SGNA) were performed on 100 children (64 boys and 36 girls). The objective measurements include anthropometry (z-scores for weight, height and body mass index), dietary history and biochemical markers were measured. These were used to classify malnutrition as per Academy of Nutrition and Dietetics/American Society of Parental and Enteral Nutrition (AND/ASPEN) Consensus Statement for identification of paediatric malnutrition and WHO growth standards for children. Cohen's kappa was computed to report the level of agreement.
RESULTS: The PNST identified 57% of hospitalized children as being at risk of malnutrition. In this study, there was a stronger agreement between PNST with AND/ASPEN malnutrition classification (k = 0.602) as when PNST was compared with WHO (k = 0.225) and SGNA (k = 0.431). The PNST shows higher specificity (85.29%) and sensitivity (78.79%) when compared with AND/ASPEN than with WHO malnutrition criteria (55.81% specificity and 66.67% sensitivity).
CONCLUSION: This study showed the usefulness of routine use of PNST for screening the malnutrition risk of hospitalized children in Malaysian tertiary hospital settings.
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).
CONCLUSIONS: We observed a very good correlation between the markers over a period of 15 years. We confirm a role of LTL in BC carcinogenesis and suggest an effect of mtDNA copy number on BC risk.
METHODS: Using data from 272,098 women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we assessed dietary intake of 92 foods and nutrients estimated by dietary questionnaires. Cox regression was used to quantify the association between each food/nutrient and risk of breast cancer. A false discovery rate (FDR) of 0.05 was used to select the set of foods and nutrients to be replicated in the independent Netherlands Cohort Study (NLCS).
RESULTS: Six foods and nutrients were identified as associated with risk of breast cancer in the EPIC study (10,979 cases). Higher intake of alcohol overall was associated with a higher risk of breast cancer (hazard ratio (HR) for a 1 SD increment in intake = 1.05, 95% CI 1.03-1.07), as was beer/cider intake and wine intake (HRs per 1 SD increment = 1.05, 95% CI 1.03-1.06 and 1.04, 95% CI 1.02-1.06, respectively), whereas higher intakes of fibre, apple/pear, and carbohydrates were associated with a lower risk of breast cancer (HRs per 1 SD increment = 0.96, 95% CI 0.94-0.98; 0.96, 95% CI 0.94-0.99; and 0.96, 95% CI 0.95-0.98, respectively). When evaluated in the NLCS (2368 cases), estimates for each of these foods and nutrients were similar in magnitude and direction, with the exception of beer/cider intake, which was not associated with risk in the NLCS.
CONCLUSIONS: Our findings confirm a positive association of alcohol consumption and suggest an inverse association of dietary fibre and possibly fruit intake with breast cancer risk.
METHODS: Biomarkers of internal exposure were measured in red blood cells (collected at baseline) by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS) . In this cross-sectional analysis, four dependent variables were evaluated: HbAA, HbGA, sum of total adducts (HbAA + HbGA), and their ratio (HbGA/HbAA). Simple and multiple regression analyses were used to identify determinants of the four outcome variables. All dependent variables (except HbGA/HbAA) and all independent variables were log-transformed (log2) to improve normality. Median (25th-75th percentile) HbAA and HbGA adduct levels were 41.3 (32.8-53.1) pmol/g Hb and 34.2 (25.4-46.9) pmol/g Hb, respectively.
RESULTS: The main food group determinants of HbAA, HbGA, and HbAA + HbGA were biscuits, crackers, and dry cakes. Alcohol intake and body mass index were identified as the principal determinants of HbGA/HbAA. The total percent variation in HbAA, HbGA, HbAA + HbGA, and HbGA/HbAA explained in this study was 30, 26, 29, and 13 %, respectively.
CONCLUSIONS: Dietary and lifestyle factors explain a moderate proportion of acrylamide adduct variation in non-smoking postmenopausal women from the EPIC cohort.