Search

Several animal and human studies have shown that zinc is associated with cellular damage and cardiac dysfunction. This study aims to investigate dietary zinc and the zinc-iron ratio, as predictors of incident cardiovascular disease (CVD) in a large longitudinal study of mid-age Australian women (aged 50-61 years). Data was self-reported and validated food frequency questionnaires were used to assess dietary intake. Energy-adjusted zinc was ranked using quintiles and predictors of incident CVD were examined using stepwise logistic regression. After six years of follow-up, 320 incident CVD cases were established. A positive association between dietary zinc intake, zinc-iron ratio and risk of CVD was observed even after adjusting for potential dietary and non-dietary confounders. Compared to those with the lowest quintile of zinc, those in the highest quintile (Odds Ratio (OR) = 1.67, 95% Confidence Interval (CI) = 1.08-2.62) and zinc-iron ratio (OR = 1.72, 95% CI = 1.05-2.81) had almost twice the odds of developing CVD ( p trend = 0.007). This study shows that high dietary zinc intake and zinc-iron ratio is associated with a greater incidence of CVD in women. Further studies are required detailing the source of zinc and iron in diet and their precise roles when compared to other essential nutrients., Competing Interests: The authors declare no conflict of interest. The founding sponsor had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Background: Few studies explored the effects of nutritional changes on body mass index (BMI), weight (Wt), waist circumference (WC) and hypertension, especially for the older Chinese population., Methods: By using China Health and Nutrition Survey 2004-2011 waves, a total of 6348 observations aged ≥ 60 were involved in the study. The number of participants dropped from 2197 in 2004, to 1763 in 2006, 1303 in 2009, and 1085 in 2011. Dietary information was obtained from participants using 24 hour-recall over three consecutive days. Height, Wt, WC, systolic and diastolic blood pressure were also measured in each survey year. The dietary pattern was derived by exploratory factor analysis using principal component analysis methods. Linear Mixed Models were used to investigate associations of dietary patterns with BMI, Wt and WC. Generalized Estimating Equation models were used to assess the associations between dietary patterns and hypertension., Results: Over time, older people's diets were shifting towards a modern dietary pattern (high intake of dairy, fruit, cakes and fast food). Traditional and modern dietary patterns had distinct associations with BMI, Wt and WC. Participants with a diet in the highest quartile for traditional composition had a β (difference in mean) of -0.23 (95 % CI: -0.44; -0.02) for BMI decrease, β of -0.90 (95 % CI: -1.42; -0.37) for Wt decrease; and β of -1.57 (95 % CI: -2.32; -0.83) for WC decrease. However, participants with a diet in the highest quartile for modern diet had a β of 0.29 (95 % CI: 0.12; 0.47) for BMI increase; β of 1.02 (95 % CI: 0.58; 1.46) for Wt increase; and β of 1.44 (95 % CI: 0.78; 2.10) for Wt increase. No significant associations were found between dietary patterns and hypertension., Conclusions: We elucidate the associations between dietary pattern and change in BMI, Wt, WC and hypertension in a 7-year follow-up study. The strong association between favourable body composition and traditional diet, compared with an increase in BMI, WC and Wt with modern diet suggests that there is an urgent need to develop age-specific dietary guideline for older Chinese people.

Background: The primary aim of this study was to evaluate the effectiveness of an intervention to increase the implementation of healthy eating and physical activity policies and practices by centre-based childcare services. The study also sought to determine if the intervention was effective in improving child dietary intake and increasing child physical activity levels while attending childcare., Methods: A parallel group, randomised controlled trial was conducted in a sample of 128 childcare services. Intervention strategies included provision of implementation support staff, securing executive support, staff training, consensus processes, academic detailing visits, tools and resources, performance monitoring and feedback and a communications strategy. The primary outcome of the trial was the proportion of services implementing all seven healthy eating and physical activity policies and practices targeted by the intervention. Outcome data were collected via telephone surveys with nominated supervisors and room leaders at baseline and immediately post-intervention. Secondary trial outcomes included the differences between groups in the number of serves consumed by children for each food group within the Australian Guide to Healthy Eating and in the proportion of children engaged in sedentary, walking or very active physical activity assessed via observation in a random subsample of 36 services at follow-up., Results: There was no significant difference between groups for the primary trial outcome (p = 0.44). Relative to the control group, a significantly larger proportion of intervention group services reported having a written nutrition and physical activity policy (p = 0.05) and providing adult-guided activities to develop fundamental movement skills (p = 0.01). There were no significant differences between groups at follow-up on measures of child dietary intake or physical activity., Conclusions: The findings of the trial were equivocal. While there was no significant difference between groups for the primary trial outcome, the intervention did significantly increase the proportion of intervention group services implementing two of the seven healthy eating and physical activity policies and practices. High levels of implementation of a number of policies and practices at baseline, significant obesity prevention activity in the study region and higher than previously reported intra-class correlation of child behaviours may, in part, explain the trial findings., Trial Registration: Australian Clinical Trials Registry (reference ACTRN12612000927820 ).

Background: Consumption of non-core foods in childhood is associated with excessive weight gain in childhood. Parents play a vital role in establishing healthy diet behaviours in young children. The aim of this study was to assess the effectiveness of a telephone-based intervention in reducing child consumption of non-core foods, and to examine parent and home food environment mediators of change in child consumption., Methods: The 'Healthy Habits' trial utilised a clustered randomised controlled design., Setting/participants: Parents were recruited from 30 preschools (N=394 participants, mean age 35.2±5.6 years). Parents randomized to the intervention group received four telephone contacts and print materials. Parents allocated to the control condition receive generic print materials only. Non-core food consumption was assessed using a validated child dietary questionnaire at baseline, 2 and 6 months post recruitment in 2010., Results: The intervention was effective in reducing child consumption of non-core foods at 2 months (intention to treat analysis: z=-2.83, p<.01), however this effect was not maintained at 6 months. Structural equation modelling using 2 month data indicated that child access to non-core foods in the home and child feeding strategies mediated the effect of the intervention., Conclusion: The telephone-based intervention shows promise in improving short term dietary behaviour in preschool age children, however further development is needed to sustain the effect in the long-term., Trial Registration: Australian Clinical Trials Registry: ACTRN12609000820202.

The same questions about diet were asked in two community-based surveys conducted in the Hunter Region of New South Wales in 1983 and 1994. There were substantial changes in diet over the period; for example, the proportion of respondents who reported using low-fat or skim milk increased from 25 per cent to 51 per cent, the proportion eating meat fewer than five times a week doubled from 21 per cent to 42 per cent and the proportion eating fewer than three eggs per week increased from 55 per cent to 80 per cent. In both surveys, women reported eating a healthier diet than men, and older people and those of higher socioeconomic status reported better diets than younger people or people with less education or lower status occupations. The surprising finding was that over the 11-year period the changes in patterns of food consumption were remarkably similar across all strata of the population. The conclusions are that wide-spread dietary change is possible. However, the changes in the last decade related mainly to reducing the risk of cardiovascular disease; similar behavioural changes to reduce the risk of diet-related cancer are required.

Objective: To illustrate methodological issues involved in estimating dietary trends in populations using data obtained from various sources in Australia in the 1980s and 1990s., Methods: Estimates of absolute and relative change in consumption of selected food items were calculated using national data published annually on the national food supply for 1982-83 to 1992-93 and responses to food frequency questions in two population based risk factor surveys in 1983 and 1994 in the Hunter Region of New South Wales, Australia. The validity of estimated food quantities obtained from these inexpensive sources at the beginning of the period was assessed by comparison with data from a national dietary survey conducted in 1983 using 24 h recall., Results: Trend estimates from the food supply data and risk factor survey data were in good agreement for increases in consumption of fresh fruit, vegetables and breakfast food and decreases in butter, margarine, sugar and alcohol. Estimates for trends in milk, eggs and bread consumption, however, were inconsistent., Conclusions: Both data sources can be used for monitoring progress towards national nutrition goals based on selected food items provided that some limitations are recognized. While data collection methods should be consistent over time they also need to allow for changes in the food supply (for example the introduction of new varieties such as low-fat dairy products). From time to time the trends derived from these inexpensive data sources should be compared with data derived from more detailed and quantitative estimates of dietary intake.

Aim To determine the effects of protein alone (independent of fat and carbohydrate) on postprandial glycaemia in individuals with Type 1 diabetes mellitus using intensive insulin therapy. Methods Participants with Type 1 diabetes mellitus aged 7-40 years consumed six 150 ml whey isolate protein drinks [0 g (control), 12.5, 25, 50, 75 and 100] and two 150 ml glucose drinks (10 and 20 g) without insulin, in randomized order over 8 days, 4 h after the evening meal. Continuous glucose monitoring was used to assess postprandial glycaemia. Results Data were collected from 27 participants. Protein loads of 12.5 and 50 g did not result in significant postprandial glycaemic excursions compared with control (water) throughout the 300 min study period ( P > 0.05). Protein loads of 75 and 100 g resulted in lower glycaemic excursions than control in the 60-120 min postprandial interval, but higher excursions in the 180-300 min interval. In comparison with 20 g glucose, the large protein loads resulted in significantly delayed and sustained glucose excursions, commencing at 180 min and continuing to 5 h. Conclusions Seventy-five grams or more of protein alone significantly increases postprandial glycaemia from 3 to 5 h in people with Type 1 diabetes mellitus using intensive insulin therapy. The glycaemic profiles resulting from high protein loads differ significantly from the excursion from glucose in terms of time to peak glucose and duration of the glycaemic excursion. This research supports recommendations for insulin dosing for large amounts of protein. [ABSTRACT FROM AUTHOR]

Background Oral corticosteroids (OCS) are an efficacious treatment for asthma exacerbations, yet risk of adverse effects may decrease patient adherence to therapy. In particular, changes in appetite and dietary intake, which lead to weight gain and changes in body composition, are considered undesirable. Objective To determine whether 10-day OCS therapy in adults with asthma causes changes in leptin, appetite, dietary intake, body weight and body composition. Methods Double-blinded, placebo-controlled randomized cross-over trial of 10 days prednisolone (50 mg) in adults with stable asthma ( n = 55) (ACTRN12611000562976). Pre- and post-assessment included spirometry, body weight, body composition measured by dual-energy X-ray absorptiometry and bioelectrical impedance analysis, appetite measured using a validated visual analogue scale (VAS) and dietary intake assessed using 4-day food records. Leptin was measured as a biomarker of appetite and eosinophils as an adherence biomarker. Outcomes were analysed by generalized linear mixed models. Results Subject adherence was confirmed by a significant decrease in blood eosinophils (× 109/L) following prednisolone compared to placebo [Coef. −0.29, 95% CI: (−0.39, −0.19) P < 0.001]. There was no difference in serum leptin (ng/mL) [Coef. 0.13, 95% CI: (−3.47, 3.72) P = 0.945] or appetite measured by VAS (mm) [Coef. −4.93, 95% CI: (−13.64, 3.79) P = 0.267] following prednisolone vs. placebo. There was no difference in dietary intake (kJ/day) [Coef. 255, 95% CI: (−380, 891) P = 0.431], body weight (kg) [Coef. −0.38, 95% CI: (−0.81, 0.05) P = 0.083] or body fat (%) [Coef. −0.31, 95% CI: (−0.81, 0.20) P = 0.230]. Symptoms including sleep and gastrointestinal disturbance were reported significantly more often during prednisolone vs. placebo. Conclusions and Clinical Relevance Short-term OCS in stable asthma did not induce significant changes in appetite, dietary intake, body weight or composition, although other adverse effects may require medical management. This evidence may assist in increasing medication adherence of asthmatics prescribed OCS for exacerbations. [ABSTRACT FROM AUTHOR]

Diabet. Med. 29, e21-e24 (2012) Abstract Aim To determine if an insulin dose calculated for a meal containing 60 g carbohydrate maintains postprandial glycaemic control for meals containing 40, 50, 70 or 80 g carbohydrate. Methods Thirty-four young people (age range 8.5-17.7 years) using intensive insulin therapy consumed five test breakfasts with equivalent fat, protein and fibre contents but differing carbohydrate quantities (40, 50, 60, 70 and 80 g of carbohydrate). The preprandial insulin dose was the same for each meal, based on the subject's usual insulin:carbohydrate ratio for 60 g carbohydrate. Continuous glucose monitoring was used to monitor postprandial glucose over 180 min. Results The 40-g carbohydrate meal resulted in significantly more hypoglycaemia than the other meals ( P = 0.003). There was a one in three chance of hypoglycaemia between 120 and 180 min if an insulin dose for 60 g carbohydrate was given for 40 g carbohydrate. The glucose levels of subjects on the 80-g meal were significantly higher than the 60- and 70-g carbohydrate meals at all time points between 150 and 180 min ( P < 0.01). Subjects consuming the 80-g meal were more likely to have significant hyperglycaemia (blood glucose levels ≥ 12 mmol/l) compared with the other meals ( P < 0.001). Conclusions In patients using intensive insulin therapy, an individually calculated insulin dose for 60 g carbohydrate results in postprandial hypoglycaemia or hyperglycaemia for meals containing 40 and 80 g carbohydrate. To calculate mealtime insulin in order to maintain postprandial control, carbohydrate estimations should be within 10 g of the actual meal carbohydrate. [ABSTRACT FROM AUTHOR]

Diabet. Med. 27, 348–353 (2010) Aims Carbohydrate (CHO) counting allows children with Type 1 diabetes to adjust mealtime insulin dose to carbohydrate intake. Little is known about the ability of children to count CHO and whether a particular method for assessing CHO quantity is better than others. We investigated how accurately children and their caregivers estimate carbohydrate, and whether counting in gram increments improves accuracy compared with CHO portions or exchanges. Methods One hundred and two children and adolescents (age range 8.3–18.1 years) on intensive insulin therapy and 110 caregivers independently estimated the CHO content of 17 standardized meals (containing 8–90 g CHO), using whichever method of carbohydrate quantification they had been taught (gram increments, 10-g portions or 15-g exchanges). Results Seventy-three per cent ( n = 2530) of all estimates were within 10–15 g of actual CHO content. There was no relationship between the mean percentage error and method of carbohydrate counting or glycated haemoglobin (HbA1c) ( P > 0.05). Mean gram error and meal size were negatively correlated ( r = −0.70, P < 0.0001). The longer children had been CHO counting the greater the mean percentage error ( r = 0.173, P = 0.014). Core foods in non-standard quantities were most frequently inaccurately estimated, while individually labelled foods were most often accurately estimated. Conclusions Children with Type 1 diabetes and their caregivers can estimate the carbohydrate content of meals with reasonable accuracy. Teaching CHO counting in gram increments did not improve accuracy compared with CHO portions or exchanges. Large meals tended to be underestimated and snacks overestimated. Repeated age-appropriate education appears necessary to maintain accuracy in carbohydrate estimations. [ABSTRACT FROM AUTHOR]