Comparison of fruit and vegetable intakes during weight loss in males and females

Fruit and vegetable consumption in relation to primary headaches: the MEPHASOUS study

BACKGROUND

Fruit and vegetable consumption may beneficially affect the odds of primary headaches due to their antioxidant contents. However, no study has examined the association between fruit and vegetable consumption and primary headaches among university students.

AIM

To assess the relation between fruit and vegetable intakes and primary headaches among Iranian university students.

METHODS

Overall, 83,214 university students with an age range of ≥ 18 years participated in the present study. Dietary intakes and also data on confounding variables were collected using validated questionnaires. Data on dietary intakes were collected using a validated dietary habits questionnaire. We used the International Classification of Headache Disorders-3 (ICHD-3) criteria to define primary headaches.

RESULTS

Fruit consumption was negatively associated with primary headaches; such that after controlling for potential confounders, greater intake of fruits was associated with 30% lower odds of primary headaches (OR: 0.70, 95% CI 0.58-0.84). Such an inverse association was also found for vegetable consumption. In the fully adjusted model, students in the top category of vegetable consumption were 16% less likely to have primary headaches compared with those in the bottom category (OR: 0.84, 95% CI 0.74-0.95). Subgroup analysis revealed that fruit consumption was inversely associated with primary headaches in females, unlike males, and vegetable consumption was inversely associated with these headaches in males, as opposed to females. Moreover, fruit and vegetable consumption was related to lower odds of primary headaches in normal-weight students.

CONCLUSION

Fruit and vegetable intakes were associated with reduced odds of primary headaches.

LEVEL OF EVIDENCE

Level III, cross-sectional analytic studies.

The Relationship between Dietary Polyphenol Intakes and Urinary Polyphenol Concentrations in Adults Prescribed a High Vegetable and Fruit Diet

Urinary polyphenol metabolites are potential biomarkers of dietary polyphenol intake. The current study aims to evaluate associations between total diet, vegetable and fruit polyphenol intakes with urinary polyphenol metabolite concentrations in a sample of adults prescribed a diet rich in vegetables and fruit. Thirty-four participants completed a 10-week pre-post study. Participants were asked to consume Australian recommended daily vegetable and fruit serves and attend measurement sessions at baseline and at weeks 2 and 10. Two 24-h diet recalls were collected at each time-point and polyphenol intakes were calculated using the Phenol-Explorer database. Spot urine samples, collected at each time-point, were analyzed for 15 polyphenol metabolites using liquid chromatography-mass spectroscopy. Spearman’s correlation analyzes assessed the strength of relationships between urinary and dietary polyphenols. Linear mixed models were used to investigate relationships between polyphenol excretion and intake. Total urinary polyphenols were significantly correlated with total polyphenol intakes at week 10 (r_s = 0.47) and fruit polyphenols at week 2 (r_s = 0.38). Hippuric acid was significantly correlated with vegetable polyphenols at baseline (r_s = 0.39). Relationships were identified between individual polyphenol metabolites and vegetable and fruit polyphenols. Linear mixed model analyzes identified that for every 1 mg increase in polyphenol intakes, urinary polyphenol excretion increased by 16.3 nmol/g creatinine. Although the majority of relationships were not sufficiently strong or consistent at different time-points, promising relationships were observed between total urinary polyphenols and total polyphenol intakes, and hippuric acid and vegetable polyphenols.

Changes in vegetable and fruit intakes and effects on anthropometric outcomes in males and females

AIM

To investigate associations between changes in vegetable and fruit (V&F) intakes and anthropometric indices (weight, BMI, % body fat, waist circumference), including differences by sex, during a dietary weight-loss intervention.

METHODS

Adults (18-45 years) with overweight/obesity (BMI 25-35 kg/m² ) entered a 10-week pre-post study, receiving individualised consults with an Accredited Practising Dietitian targeting increased V&F intakes. Dietary intake was assessed using 24-hour recalls and food frequency questionnaires. Linear mixed models were used to examine how much of the changes in anthropometric indices were explained by changes in V&F intakes. Sex differences were assessed by Wilcoxon rank sum tests.

RESULTS

Of the 43 participants enrolled, 34 completed the study (53% female). Significant differences in energy intake and anthropometric indices were observed between males and females at baseline. After 10 weeks, females significantly reduced their weight (-2.9%, P < .01), BMI (-0.82 kg/m² , P < .01), waist circumference (-1.70 cm, P < .01), energy intake (-824 kJ/day, P = .01) and improved diet quality (-14.0% energy-dense, nutrient-poor foods, P < .01). Males significantly reduced weight (-2.5%, P = .04), BMI (-0.76 kg/m² , P = .03), waist circumference (-2.40 cm, P = .02), energy intake (-2875 kJ/day, P < .01), increased fruit intake (+0.89 serves/day, P = .02) and improved diet quality (-6% energy-dense, nutrient-poor foods, P < .01). Compared to the other sex, greater reductions were observed in energy intake in males and energy-dense, nutrient-poor foods in females. Linear mixed models identified that changes in V&F intakes did not explain the variation in anthropometric measures.

CONCLUSION

Future interventions may benefit from trialling sex tailored messages to enhance effects on anthropometric changes.

Exploring dietary changes in an interdisciplinary intervention trial: Application of a dietary guidelines food composition database

BACKGROUND

Consumption of food groups aligning with dietary guidelines is advised for obesity management and was used in a recent lifestyle intervention trial, the Health Track study. We have conducted a number of dietary pattern analyses on this trial but, with recent access to the new Australian Dietary Guidelines (ADG) food composition database, we can now assess ADG adherence, with the advantage of categorising mixed dishes. The present study aimed to compare changes over time in consumption of ADG food groups.

METHODS

Secondary analysis of baseline and three-month diet history data was conducted. Participants received individualised dietary advice (I), individualised dietary advice plus 30 g of walnuts per day (IW) or usual care (C). The ADG database was used to determine food group servings with changes in five food groups used as a measure of dietary quality.

RESULTS

Fruit and vegetable intakes increased in the IW (+0.4 and +1.1 serves, P < 0.05) and I (+0.5 and +0.4 serves, P > 0.05) arms. Consumption of meat/protein foods increased in the IW arm (+0.3 serves, P > 0.05) but decreased in the I and C arms (both - 0.4 serves, P < 0.05). Consumption of grains and milk/alternatives decreased in all study arms (P < 0.05). Greater improvements in grain and dairy food quality were observed in the intervention arms.

CONCLUSIONS

The ADG database enabled ADG specific food group analysis, addressed food quality and showed the HealthTrack intervention increased adherence to dietary guidelines compared to usual care.

A Comprehensive Critical Assessment of Increased Fruit and Vegetable Intake on Weight Loss in Women

No previous reviews or meta-analyses have specifically assessed the effects of increased fruit and vegetable (FV) intake on weight loss with a primary focus on women. Several studies show differences between men and women in how increased FV intake affects their weight loss and maintenance, risk of becoming overweight or obese, and the influence of eating speed and frequency on weight control. This analysis provides a comprehensive and visual assessment of the effects of increasing FV intake and long-term weight change from observational studies and weight loss from randomized controlled trials (RCTs) in women. Consistent evidence from prospective studies and RCTs shows that increased intake of FV is a chief contributor to weight loss in women. This effect is enhanced with concurrent dietary restriction of high energy density (ED) or high-fat foods. Yet, the type of FV differentially impacts weight loss in women. Whole FV intake may influence weight through a variety of mechanisms including a reduction in eating rate, providing a satisfying, very-low to low energy density, low glycemic load or low-fat content. Also, FV are the primary source of dietary fiber, which can provide additional support for weight loss in women when consumed at adequate levels.

The comparative validity of a brief diet screening tool for adults: The Fruit And Vegetable VAriety index (FAVVA)

BACKGROUND & AIMS

A brief assessment tool on frequency and variety of fruit and vegetable intake could provide a cost-effective and sustainable approach to improving diet. The primary aim was to evaluate the comparative validity of a brief index of Fruit And Vegetable VAriety (FAVVA) relative to food and nutrient intakes derived from a comprehensive food frequency questionnaire (FFQ). The secondary aim was to evaluate the FAVVA index in relation to fasting plasma carotenoid concentrations.

METHODS

Dietary intakes and fasting plasma carotenoid concentrations of 99 overweight and obese adults (49.5% female; 44.6 ± 9.9 years) were assessed at baseline and 3-months. Food and nutrient intakes were assessed using the Australian Eating Survey (AES) FFQ. The FAVVA index was derived from a sub-set of 35 AES questions related to fruit and vegetable intake frequency and variety. Associations were assessed using Spearman's correlation coefficients and linear regression analysis, and agreement using weighted kappa (K_w).

RESULTS

Total FAVVA score demonstrated moderate to strong, significant (all p < 0.01) correlations with total daily intakes of vegetables (r = 0.75), vitamin C (r = 0.71), fruit (r = 0.66), vitamin A (r = 0.49), fibre (r = 0.49), potassium (r = 0.46), magnesium (r = 0.39), iron (r = 0.26), riboflavin (r = 0.24), calcium (r = 0.23), zinc (r = 0.20) and niacin equivalent (r = 0.20). These associations remained significant in the adjusted regression analyses and agreement testing. Total FAVVA was significantly correlated with plasma carotenoid concentrations (μg/dL) of α-carotene (r = 0.22, p < 0.01), β-carotene (r = 0.26, p < 0.001), β-cryptoxanthin (r = 0.22, p < 0.01) and total carotenoids (r = 0.18, p < 0.05). The associations with α-carotene (β = 0.09, p < 0.001), β-carotene (β = 0.42, p < 0.05) and total plasma carotenoids (β = 0.85, p < 0.05) remained significant in the adjusted regression analyses and for agreement testing.

CONCLUSIONS

FAVVA is suitable as a brief tool to rank frequency and variety of fruit and vegetable intake.

Comparison of Australian Recommended Food Score (ARFS) and Plasma Carotenoid Concentrations: A Validation Study in Adults

Diet quality indices can predict nutritional adequacy of usual intake, but validity should be determined. The aim was to assess the validity of total and sub-scale score within the Australian Recommended Food Score (ARFS), in relation to fasting plasma carotenoid concentrations. Diet quality and fasting plasma carotenoid concentrations were assessed in 99 overweight and obese adults (49.5% female, aged 44.6 ± 9.9 years) at baseline and after three months (198 paired observations). Associations were assessed using Spearman’s correlation coefficients and regression analysis, and agreement using weighted kappa (K_w). Small, significantly positive correlations were found between total ARFS and plasma concentrations of total carotenoids (r = 0.17, p < 0.05), β-cryptoxanthin (r = 0.18, p < 0.05), β-carotene (r = 0.20, p < 0.01), and α-carotene (r = 0.19, p < 0.01). Significant agreement between ARFS categories and plasma carotenoid concentrations was found for total carotenoids (K_w 0.12, p = 0.02), β-carotene (K_w 0.14, p < 0.01), and α-carotene (K_w 0.13, p < 0.01). In fully-adjusted regression models the only signification association with ARFS total score was for α-carotene (β = 0.19, p < 0.01), while ARFS meat and fruit sub-scales demonstrated significant relationships with α-carotene, β-carotene, and total carotenoids (p < 0.05). The weak associations highlight the issues with self-reporting dietary intakes in overweight and obese populations. Further research is required to evaluate the use of the ARFS in more diverse populations.