Comparison of multiple and novel measures of dietary glycemic carbohydrate with insulin resistant status in older women

Background: Previous epidemiological investigations of associations between dietary glycemic intake and insulin resistance have used average daily measures of glycemic index (GI) and glycemic load (GL). We explored multiple and novel measures of dietary glycemic intake to determine which was most predictive of an association with insulin resistance. Methods: Usual dietary intakes were assessed by diet history interview in women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Daily measures of dietary glycemic intake (n = 329) were carbohydrate, GI, GL, and GL per megacalorie (GL/Mcal), while meal based measures (n = 200) were breakfast, lunch and dinner GL; and a new measure, GL peak score, to represent meal peaks. Insulin resistant status was defined as a homeostasis model assessment (HOMA) value of \u3e3.99; HOMA as a continuous variable was also investigated. Results: GL, GL/Mcal, carbohydrate (all P \u3c 0.01), GL peak score (P = 0.04) and lunch GL (P = 0.04) were positively and independently associated with insulin resistant status. Daily measures were more predictive than meal-based measures, with minimal difference between GL/Mcal, GL and carbohydrate. No significant associations were observed with HOMA as a continuous variable. Conclusion: A dietary pattern with high peaks of GL above the individual’s average intake was a significant independent predictor of insulin resistance in this population, however the contribution was less than daily GL and carbohydrate variables. Accounting for energy intake slightly increased the predictive ability of GL, which is potentially important when examining disease risk in more diverse populations with wider variations in energy requirements

Lean body mass associated with upper body strength in healthy older adults while higher body fat limits lower extremity performance and endurance

Impaired strength adversely influences an older person\u27s ability to perform activities of daily living. A cross-sectional study of 117 independently living men and women (age = 73.4 9.4 year; body mass index (BMI) = 27.6 4.8 kg/m2) aimed to assess the association between body composition and: (1) upper body strength (handgrip strength, HGS); (2) lower extremity performance (timed up and go (TUG) and sit to stand test (STS)); and (3) endurance (6-minute walk (SMWT). Body composition (% fat; lean body mass (LBM)) was assessed using bioelectrical impedance. Habitual physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire (MLTPA) and dietary macronutrient intake, assessed using 24 h recalls and 3-day food records. Regression analyses included the covariates, protein intake (g/kg), MLTPA, age and sex. For natural logarithm (Ln) of right HGS, LBM (p \u3c 0.001) and % body fat (p \u3c 0.005) were significant (r2 = 46.5%; p \u3c 0.000). For left LnHGS, LBM (p \u3c 0.000), age (p = 0.036), protein intake (p = 0.015) and LnMLTPA (p = 0.015) were significant (r2 = 0.535; p \u3c 0.000). For SMW, % body fat, age and LnMLTPA were significant (r2 = 0.346; p \u3c 0.000). For STS, % body fat and age were significant (r2 = 0.251; p \u3c 0.000). LBM is a strong predictor of upper body strength while higher % body fat and lower physical activity are associated with poorer outcomes on tests of lower extremity performance

Abnormal behavior detection using a multi-modal stochastic learning approach

This paper presents a new approach to trajectory-based abnormal behavior detection (ABD). While existing techniques include position in the feature vector, we propose to estimate the probability distribution locally at each position, hence reducing the dimensionality of the feature vector. Local information derived from accumulated knowledge for a particular position is integrated in the distribution enabling context-based decision for ABD. A stochastic competitive learning algorithm is employed to estimate the local distributions of the feature vector and the location of the distribution modes. The proposed algorithm is tested on the detection of driving under the influence of alcohol. The performance of the new algorithm is evaluated on synthetic data. First the local stochastic learning algorithm is compared to its global variant. Then it is compared to the Kohonen self organizing feature maps. In both cases, the proposed algorithm achieves higher detection rates (at the same false alarm rate) with fewer clusters

Development and validation of a short questionnaire for estimating the intake of zinc

Published online 04 August 2009. Zinc is an essential nutrient required for numerous metabolic functions. The aim of the present study was to develop a zinc-specific food frequency questionnaire (FFQ) and to determine its relative validity. A 74-item FFQ was designed for the measurement of zinc intake. Food items were included in the FFQ if their zinc content was >0.5 mg/100 g, and the food item contributed >5% of the recommended dietary intake. Female subjects (n = 22) were recruited to complete the questionnaire in addition to maintaining a weighed food record for 7 days. Mean intake of zinc obtained from the weighed records (8.8 ± 2.3 mg/day; mean ± SD) was significantly lower than that obtained from the FFQ (10.5 ± 3.1 mg/day; P < 0.01). Ranked zinc intakes obtained from the two instruments were significantly correlated (r s = 0.81, P < 0.001). Evaluation of progressively shortened versions of the FFQ, containing 23–61 food items and representing 60–90% of the contribution to total zinc intake, yielded correspondingly decreasing magnitudes of zinc intake, but the rank correlation with the weighed records was significant (P < 0.01). Rank correlations and analysis of plots from Bland–Altman analyses suggest that a shortened 37-item FFQ has comparable validity to the full FFQ. A shortened FFQ is likely to produce lower demands on the interviewer and/or respondent when assessing zinc intake.9 page(s

Development and validation of a food frequency questionnaire to assess omega-3 long chain polyunsaturated fatty acid intake in Australian children aged 9-13 years

Background: The present study aimed to develop a food frequency questionnaire (FFQ) assessing dietary omega-3 long chain polyunsaturated fatty acid (n-3 LCPUFA) intake in Australian children and to validate the FFQ against a 7-day food diary. Methods: The investigation comprised a cross-sectional and validation study. The study setting was two private primary schools in the in the Illawarra region of New South Wales. Twenty-two Australian children, aged 9-13 years, who were not on a special diet or receiving medical care that limited their food choice in the 3 months prior to recruitment, were recruited into the study. Results: A total of 131 items, classified according to seven food group categories, was included in the n-3 LCPUFA FFQ, as identified from published dietary surveys and a supermarket survey. Good correlations between the FFQ and the 7-day food diary were observed for eicosapentaenoic acid (EPA) [r = 0.691, 95% confidence interval (CI) = 0.51-0.83, P \u3c 0.001], docosahexaenoic acid (DHA) (r = 0.684, 95% CI = 0.45-0.84, P \u3c 0.001) and total n-3 LCPUFA (r = 0.687, 95% CI = 0.48-0.85, P \u3c 0.001). Bland-Altman plots showed an acceptable limit of agreement between the FFQ and the average 7-day food diary. However, the mean EPA, DHA and total n-3 LCPUFA intakes estimated from the FFQ were significantly higher than those from the average 7-day food diary estimates (P \u3c 0.001). Conclusions: A novel n-3 LCPUFA FFQ that has been developed to estimate dietary n-3 LCPUFA intakes in Australian children has been shown to have relative validity. The FFQ provides a useful contribution to dietary assessment methodology in this age group; however, reproducibility remains to be demonstrated

Glycemic index and glycemic load intake patterns in older Australian women

Aims: Dietary glycaemic index and glycaemic load have been associated with risk of chronic diseases, yet limited research exists on patterns of consumption in Australia. Our aims were to investigate glycaemic carbohydrate in a population of older women, identify major contributing food sources and determine low, moderate and high ranges.Methods: Subjects were 459 Brisbane women aged 42ÿ81 years participating in the Longitudinal Assessment of Ageing in Women. Diet history interviews were used to assess usual diet and results were analysed into energy and macronutrients using the FoodWorks dietary analysis program combined with a customised glycaemic index database.Results: Mean SD dietary glycaemic index was 55.6 4.4% and mean dietary glycaemic load was 115 25. A low glycaemic index in this population was 52.0, corresponding to the lowest quintile of dietary glycaemic index, and a low glycaemic load was 95. Glycaemic index showed a quadratic relationship with age (P = 0.01), with a slight decrease observed in women aged in their 60s relative to younger or older women. Glycaemic load decreased linearly with age (P \u3c 0.001). Bread was the main contributor to carbohydrate and dietary glycaemic load (17.1% and 20.8%, respectively), followed by fruit (15.5% and 14.2%), and dairy for carbohydrate (9.0%), or breakfast cereals for glycaemic load (8.9%).Conclusions: In this population, dietary glycaemic load decreased with increasing age; however, this was likely to be a result of higher energy intakes in younger women. Focus on careful selection of lower-glycaemic-index items within bread and breakfast cereal food groups would be an effective strategy for decreasing dietary glycaemic load in this population of older women

Effects of Supplementation with Purified Red Clover (Trifolium Pratense) Isoflavones on Plasma Lipids and Insulin Resistance in Healthy Prememopausal Women

Consumption of isoflavone-rich soyabean protein is reported to reduce total and LDL-cholesterol, but the specific components responsible are undetermined. In a previous crossover trial we showed that purified isoflavones, derived from red clover (Trifolium pratense), raised HDL3-cholesterol in premenopausal women; however, these findings were inconclusive due to period and carryover effects. In an attempt to overcome this problem, we utilised a parallel study designed to re-examine the effects of purified isoflavones on plasma lipoproteins and markers of insulin resistance in premenopausal women. Twenty-five healthy premenopausal women participated in a double-blind, randomised, parallel study. The treatment group (n 12) consumed a placebo for the first menstrual cycle and an isoflavone supplement (86 mg/d, derived from red clover) for three cycles, while the placebo group (n 13) consumed a placebo supplement for four menstrual cycles. Blood samples were collected weekly during cycles 1, 3 and 4. Supplementation with isoflavones resulted in a 15-fold increase in urinary isoflavone excretion (P<0.0001). There were no significant effects on total cholesterol, LDL- and HDL-cholesterol, HDL subfractions, triacylglycerol, lipoprotein(a), glucose or insulin concentrations. Our present results indicate that purified isoflavones derived from red clover have no effect on cholesterol homeostasis or insulin resistance in premenopausal women, a group which is at low risk of CHD