Evaluation tool development for food literacy programs

Food literacy is described as the behaviours involved in planning, purchasing, preparing, and eating food and is critical for achieving healthy dietary intakes. Food literacy programs require valid and reliable evaluation measures. The aim of this paper is to describe the development and validation of a self-administered questionnaire to measure food literacy behaviours targeted by the Food Sensations® for Adults program in Western Australia. Validity and reliability tests were applied to questionnaire item development commencing with (a) a deductive approach using Australian empirical evidence on food literacy as a construct along with its components and (b) adapting an extensively-tested food behaviour checklist to generate a pool of items for investigation. Then, an iterative process was applied to develop a specific food literacy behaviour checklist for program evaluation including exploratory factor analysis. Content, face, and construct validity resulted in a 14-item food behaviour checklist. Three factors entitled Plan & Manage, Selection, and Preparation were evident, resulting in Cronbach’s alpha 0.79, 0.76, and 0.81, respectively, indicating good reliability of each of these factors. This research has produced a validated questionnaire, is a useful starting point for other food literacy programs, and has applications globally

Independent external validation of cardiovascular disease mortality in women utilising Framingham and SCORE risk models: a mortality follow-up study

Background - We conducted an independent external validation of three cardiovascular risk score models (Framingham risk score model and SCORE risk charts developed for low-risk regions and high-risk regions in Europe) on a prospective cohort of 4487 Australian women with no previous history of heart disease, diabetes or stroke. External validation is an important step to evaluate the performance of risk score models using discrimination and calibration measures to ensure their applicability beyond the settings in which they were developed. Methods - Ten year mortality follow-up of 4487 Australian adult women from the National Heart Foundation third Risk Factor Prevalence Study with no baseline history of heart disease, diabetes or stroke. The 10-year risk of cardiovascular mortality was calculated using the Framingham and SCORE models and the predictive accuracy of the three risk score models were assessed using both discrimination and calibration. Results - The discriminative ability of the Framingham and SCORE models were good (area under the curve>0.85). Although all models overestimated the number of cardiovascular deaths by greater than 15%, the Hosmer-Lemeshow test indicated that the Framingham and SCORE-Low models were calibrated and hence suitable for predicting the 10-year cardiovascular mortality risk in this Australian population. An assessment of the treatment thresholds for each of the three models in identifying participants recommended for treatment were found to be inadequate, with low sensitivity and high specificity resulting from the high recommended thresholds. Lower treatment thresholds of 8.7% for the Framingham model, 0.8% for the SCORE-Low model and 1.3% for the SCORE-High model were identified for each model using the Youden index, at greater than 78% sensitivity and 80% specificity. Conclusions - Framingham risk score model and SCORE risk chart for low-risk regions are recommended for use in the Australian women population for predicting the 10-year cardiovascular mortality risk. These models demonstrate good discrimination and calibration performance. Lower treatment thresholds are proposed for better identification of individuals for treatment

A Western Australian Survey of Breastfeeding Initiation, Prevalence and Early Cessation Patterns

Objective: This paper reports on current initiation and prevalence rates, in Western Australia, differentiating ‘any’ breastfeeding with ‘exclusive’ breastfeeding whilst exploring patterns and reasons for stopping breastfeeding. The results presented are part of a larger study examining women’s perceptions of care and wellbeing in the early postnatal period. Methods: A cross sectional survey was used to examine infant feeding practices during the hospital stay and at 9 weeks post birth from Western Australian women with a registered live birth between February and June 2006. Results: Data obtained from 2,669 women revealed a 93% (n = 2,472) initiation rate of any breastfeeding. More multiparous women (73.5%) were exclusively breastfeeding in hospital compared to primiparous women (65.2%), which decreased to 57.1 and 49.2%, respectively at 9 weeks. Of those who had ceased by 9 weeks, more multiparous women (71.1%) ceased before 3 weeks. Reasons cited for ceasing in order of frequency were insufficient milk supply, infant related reasons, pain and discomfort and emotional reasons. Younger maternal age, primiparous women, lower maternal education levels, offering a combination of breast milk and formula in hospital and caesarean birth were significant independent predictors of early cessation. Conclusions: Although initiation rates including “any” breast milk are meeting NHMRC dietary guidelines of 90%, the 60% target of exclusive breastfeeding is not being achieved for 3 months or in fact at 9 weeks. Targeted support for at risk groups such as younger, less well-educated, primiparous women must continue. Evidence based policies to protect breastfeeding must address the practice of offering formula to breastfed infants in hospital and the impact of increasing interventions such as caesarean births

Effects of whey protein isolate on body composition, lipids, insulin and glucose in overweight and obese individuals

The health benefits currently associated with increased dairy intake may be attributable to the whey component of dairy proteins. The present study evaluated the effects of whey protein supplementation on body composition, lipids, insulin and glucose in comparison to casein and glucose (control) supplementation in overweight/obese individuals for 12 weeks. The subjects were randomised to whey protein, casein or glucose supplementation for 12 weeks according to a parallel design. Fasting blood samples and dual-energy X-ray absorptiometry measurements were taken. Seventy men and women with a mean age of 48•4 (SEM 0•86) years and a mean BMI of 31•3 (SEM 0•8) kg/m2 completed the study. Subjects supplemented with whey protein had no significant change in body composition or serum glucose at 12 weeks compared with the control or casein group. Fasting TAG levels were significantly lowered in the whey group compared with the control group at 6 weeks (P=0•025) and 12 weeks (P=0•035). There was a significant decrease in total cholesterol and LDL cholesterol at week 12 in the whey group compared with the casein (P=0•026 and 0•045, respectively) and control groups (P<0•001 and 0•003, respectively). Fasting insulin levels and homeostasis model assessment of insulin resistance scores were also significantly decreased in the whey group compared with the control group (P=0•049 and P=0•034, respectively).The present study demonstrated that supplementation with whey proteins improves fasting lipids and insulin levels in overweight and obese individuals

Low carbohydrate meals or a small dose of insulin normalises one-hour blood glucose in a woman with normal glucose tolerance and elevated one-hour postload glucose: A case report

Diabetes is diagnosed by 2-hour BGL ≥ 11.1 mmol/L on OGTT, fasting BGL ≥ 7.0 mmol/L or HbA1C ≥ 6.5%. IFG and IGT are similarly diagnosed by elevated fasting and 2-hour BGLs. Although-hour BGL is routinely measured, results are classified as NGT if fasting and 2-hour levels are normal, irrespective of elevation at 1 hour. It has, however, been shown that 1-hour postload BGL is a strong predictor of future risk for type 2 diabetes and vascular disease, even in those with NGT. Additionally Meisinger et al. identified 1-hour postload glycaemia as a long-term predictor for all-cause mortality in men without diabetes. There is no normal range for 1-hour glucose, but ≥ 8.6 mmol/L has been identified as a cut-off marking increased cardiovascular and diabetes risk. It has been suggested that recognition and management of those with NGT and 1-hour glucose ≥ 8.6mmol/L may reduce incidence of diabetes and vascular events

Anthropometric measurements of general and central obesity and the prediction of cardiovascular disease risk in women: a cross-sectional study

Objectives: It is important to ascertain which anthropometric measurements of obesity, general or central, are better predictors of cardiovascular disease (CVD) risk in women. 10-year CVD risk was calculated from the Framingham risk score model, SCORE risk chart for high-risk regions, general CVD and simplified general CVD risk score models. Increase in CVD risk associated with 1 SD increment in each anthropometric measurement above the mean was calculated, and the diagnostic utility of obesity measures in identifying participants with increased likelihood of being above the treatment threshold was assessed. Design: Cross-sectional data from the National Heart Foundation Risk Factor Prevalence Study. Setting: Population-based survey in Australia. Participants: 4487 women aged 20–69 years without heart disease, diabetes or stroke. Outcome measures: Anthropometric obesity measures that demonstrated the greatest increase in CVD risk as a result of incremental change, 1 SD above the mean, and obesity measures that had the greatest diagnostic utility in identifying participants above the respective treatment thresholds of various risk score models.Results: Waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-stature ratio had larger effects on increased CVD risk compared with body mass index (BMI). These central obesity measures also had higher sensitivity and specificity in identifying women above and below the 20% treatment threshold than BMI. Central obesity measures also recorded better correlations with CVD risk compared with general obesity measures. WC and WHR were found to be significant and independent predictors of CVD risk, as indicated by the high area under the receiver operating characteristic curves (>0.76), after controlling for BMI in the simplified general CVD risk score model. Conclusions: Central obesity measures are better predictors of CVD risk compared with general obesity measures in women. It is equally important to maintain a healthy weight and to prevent central obesity concurrently

Vision self-management for older adults: a randomised controlled trial

Background/aims: Ageing of the population will result in unprecedented numbers of older adults living with age-related vision loss (ARVL). Self-management models improve health outcomes and reduce healthcare costs; however, the principles have rarely been applied in low vision services. Methods: A two-armed randomised controlled trial of older adults (n=77) with ARVL compared ‘usual care’ provided by a not-for-profit community agency with an extended model of care (usual care+self-management group intervention). The primary outcome variable (participation in life situations) was measured using the Activity Card Sort. Secondary outcome measures examined general health and vision-specific domains.Results: The intention-to-treat analysis demonstrated that the extended model produced significantly better participation in life situations at post-test when compared with the usual care only group. Gains were made regardless of whether participants were, or were not, depressed at baseline. The addition of the self-management group was also successful in significantly reducing depression, increasing physical and mental health, generalised and domain-specific self-efficacy, and adjustment to ARVL. With the exception of adjustment and mental health, differences were still apparent at 12 weeks' follow-up. Conclusion: Addition of self-management significantly improved general health and vision-specific rehabilitation outcomes for older adults with ARVL

Does an Adolescent’s accuracy of recall improve with a second 24-h dietary recall?

The multiple-pass 24-h dietary recall is used in most national dietary surveys. Our purpose was to assess if adolescents’ accuracy of recall improved when a 5-step multiple-pass 24-h recall was repeated. Participants (n = 24), were Chinese-American youths aged between 11 and 15 years and lived in a supervised environment as part of a metabolic feeding study. The 24-h recalls were conducted on two occasions during the first five days of the study. The four steps (quick list; forgotten foods; time and eating occasion; detailed description of the food/beverage) of the 24-h recall were assessed for matches by category. Differences were observed in the matching for the time and occasion step (p < 0.01), detailed description (p < 0.05) and portion size matching (p < 0.05). Omission rates were higher for the second recall (p < 0.05 quick list; p < 0.01 forgotten foods). The adolescents over-estimated energy intake on the first (11.3% ± 22.5%; p < 0.05) and second recall (10.1% ± 20.8%) compared with the known food and beverage items. These results suggest that the adolescents’ accuracy to recall food items declined with a second 24-h recall when repeated over two non-consecutive days

Omitting follow-up food after initial hypoglycaemic treatment does not increase the likelihood of repeat hypoglycaemia

Introduction: Guidelines for self-treatment of hypoglycaemia specify initial treatment with quick-acting carbohydrate until blood glucose levels normalize and then follow-up with longer-acting carbohydrate. The few studies investigating follow-up show 29–57% omission or undertreatment with follow-up carbohydrate but do not investigate the association of this with repeat hypoglycaemia. This study aimed to develop, validate and administer a questionnaire to delineate this association. The timeframe targeted was 2 h post primary hypoglycaemic event (PPHE), the time influenced by long-acting carbohydrate. Methods: A questionnaire was generated, test–retest reliability assessed, and it was piloted on convenience samples from the target population. The final version was administered to all insulin-treated individuals attending an outpatient diabetes clinic over 4 weeks (169).Results: Questionnaire development: readability (69.6—standard/easy), test–retest reliability (Cohen’s kappa 0.57–0.91) and return rate (72.2%) were all acceptable. Questionnaire data: questionnaires were returned by 122 participants (63 males/59 females). Method of insulin administration was subcutaneous insulin injections (91%) and continuous subcutaneous insulin infusion (CSII) (9%). Repeat hypoglycaemia within 2 h PPHE was reported by 8.2% of respondents. There was no significant difference for age, gender and diabetes duration between those reporting repeat hypoglycaemia and those without. Consumption of follow-up longer-acting carbohydrate was reported by 58.2% of responders with 48% of these using long-acting and 52% medium-acting carbohydrate foods. Method of insulin administration and consumption of follow-up food were significantly associated with repeat hypoglycaemia (P = 0.015, 0.039) but presence or absence of symptoms and duration of action of carbohydrate were not significantly associated (P = 0.103, 0.629). Hierarchical logistic regression analysis showed omission of follow-up food PPHE was not a significant predictor of increased likelihood of repeat hypoglycaemia within 2 h PPHE, irrespective of method of insulin administration (P = 0.085). Conclusion: This study supports guidelines that recommend judicious, rather than routine use of follow-up longer-acting carbohydrate PPHE

Misinterpreting P-Values in Research

The overuse of p-values to dichotomize the results of research studies as either being either significant or non-significant has taken some investigators away from the main task of determining the size of the difference between groups and the precision with which it is measured. Presenting the results of research as statements such as “p 0.05”, “NS” or as precise p-values has the effect of oversimplifying study findings. Further information regarding the size of the difference between groups is required. Presenting confidence intervals for the difference in effect, of say two treatments, in addition to p-values, has the distinct advantage of presenting imprecision on the scale of the original measurement. A statistically significant test also does not imply that the observed difference is clinically important or meaningful