METHODS: A nested case-control study in nonsmoking postmenopausal women (334 cases, 417 controls) was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Unconditional logistic regression models were used to estimate ORs and 95% confidence intervals (CI) for the association between HbAA, HbGA, HbAA+HbGA, and HbGA/HbAA and EOC and invasive serous EOC risk.
RESULTS: No overall associations were observed between biomarkers of acrylamide exposure analyzed in quintiles and EOC risk; however, positive associations were observed between some middle quintiles of HbGA and HbAA+HbGA. Elevated but nonstatistically significant ORs for serous EOC were observed for HbGA and HbAA+HbGA (ORQ5vsQ1, 1.91; 95% CI, 0.96-3.81 and ORQ5vsQ1, 1.90; 95% CI, 0.94-3.83, respectively); however, no linear dose-response trends were observed.
CONCLUSION: This EPIC nested case-control study failed to observe a clear association between biomarkers of acrylamide exposure and the risk of EOC or invasive serous EOC.
IMPACT: It is unlikely that dietary acrylamide exposure increases ovarian cancer risk; however, additional studies with larger sample size should be performed to exclude any possible association with EOC 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.
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: A cross-sectional study was carried out in two general paediatric wards in a public hospital. SGNA and STAMP were performed on 82 children (52 boys and 30 girls) of age 1-7 years. The scores from both methods were compared against Academy of Nutrition and Dietetics/American Society of Parental and Enteral Nutrition Consensus Statement for identification of paediatric malnutrition. The objective measurements include anthropometry (weight, height and mid-arm circumference), dietary intake and biochemical markers (C-reactive protein, total lymphocytes and serum albumin). Kappa agreement between methods, sensitivity, specificity and cross-classification were computed.
Results: SGNA and STAMP identified 45% and 79% of the children to be at risk of malnutrition, respectively. Using a compendium of objective parameters, 46% of the children were confirmed to be malnourished. The agreement between SGNA and objective measurements (k = 0.337) was stronger than between STAMP and objective measurements (k = 0.052) in evaluating the nutritional status of hospitalized children. SGNA also has a 4-fold higher specificity (70.45%) than STAMP (18.18%) in detecting children who are malnourished.
Conclusion: SGNA is a valid nutrition assessment tool in diagnosing malnutrition status among hospitalized children in Malaysia. The discrepancy in specificity values between the two methods explains the distinguished roles between SGNA and STAMP. The use of STAMP will have to be followed up with a more valid tool such as SGNA to verify the actual nutrition status of the paediatric population.
METHODS: A cross-sectional study was conducted among 260 children admitted to general medical wards. SGNA and anthropometric measurements were used as references. Kappa agreement, diagnostic values, and area under the curve (AUC) were analyzed to evaluate the diagnostic ability of the AND/ASPEN malnutrition diagnosis tool. Logistic binary regression was performed to determine the predictive ability of each malnutrition diagnosis tool on the length of hospital stay.
RESULTS: The AND/ASPEN diagnosis tool detected the highest malnutrition rate (41%) among the hospitalized children in comparison with the reference methods. This tool demonstrated fair specificity of 74% and sensitivity of 70% compared with the SGNA. It obtained a weak agreement in determining the presence of malnutrition by kappa (0.06-0.42) and receiver operating characteristic curve analysis (AUC = 0.54-0.72). The use of the AND/ASPEN tool obtained an odds ratio of 0.84 (95% CI, 0.44-1.61; P = 0.59) in predicting the length of hospital stay.
CONCLUSIONS: The AND/ASPEN malnutrition tool is an acceptable nutrition assessment tool for hospitalized children in general medical wards.
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: An exhaustive literature search was performed, in order to identify the relevant studies describing the epidemiology, pathogenesis, nutritional intervention and outcome of PEW in ESRD on hemodialysis.
RESULTS AND CONCLUSION: The pathogenesis of PEW is multifactorial. Loss of appetite, reduced intake of nutrients and altered lean body mass anabolism/catabolism play a key role. Nutritional approach to PEW should be based on a careful and periodic assessment of nutritional status and on timely dietary counseling. When protein and energy intakes are reduced, nutritional supplementation by means of specific oral formulations administered during the hemodialysis session may be the first-step intervention, and represents a valid nutritional approach to PEW prevention and treatment since it is easy, effective and safe. Omega-3 fatty acids and fibers, now included in commercially available preparations for renal patients, could lend relevant added value to macronutrient supplementation. When oral supplementation fails, intradialytic parenteral nutrition can be implemented in selected patients.