Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Te Morenga LSubject: search.filters.subject.1111 Nutrition and Dietetics

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    Effect of Wholegrain Flour Particle Size in Bread on Glycaemic and Insulinaemic Response among People with Risk Factors for Type 2 Diabetes: A Randomised Crossover Trial
    (MDPI (Basel, Switzerland), 2021-08) Mete E; Haszard J; Perry T; Oey I; Mann J; Te Morenga L
    Wholegrain flour produced by roller-milling is predominantly comprised of fine particles, while stoneground flour tends to have a comparatively smaller proportion of fine particles. Differences in flour particle size distribution can affect postprandial glycaemia in people with type 2 diabetes and postprandial insulinaemia in people with and without type 2 diabetes. No prior studies have investigated the effect of wholegrain flour particle size distribution on glycaemic or insulinaemic response among people with impaired glucose tolerance or risk factors for type 2 diabetes. In a randomised crossover study, we tested the 180-min acute glycaemic and insulinaemic responses to three wholegrain breads differing in flour particle size and milling method: (1) fine roller-milled flour, (2) fine stoneground flour, and (3) coarse stoneground flour. Participants (n = 23) were males and females with risk factors for type 2 diabetes (age 55-75 y, BMI >28 kg/m2, completing less than 150 min moderate to vigorous intensity activity per week). Each test meal provided 50 g available carbohydrate, and test foods were matched for energy and macronutrients. There was no significant difference in blood glucose iAUC (incremental area under the curve) between the coarse stoneground flour bread and the fine stoneground flour bread (mean difference -20.8 (95% CI: -51.5, 10.0) mmol·min/L) and between the coarse stoneground flour bread and the fine roller-milled flour bread (mean difference -23.3 (95% CI: -57.6, 11.0) mmol·min/L). The mean difference in insulin iAUC for fine stoneground flour bread compared with the fine roller-milled flour bread was -6.9% (95% CI: -20.5%, 9.2%) and compared with the coarse stoneground flour bread was 9.9% (95% CI: -2.6%, 23.9%). There was no evidence of an effect of flour particle size on postprandial glycaemia and insulinaemia among older people with risk factors for type 2 diabetes, most of whom were normoglycaemic.
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    Erratum: Estimating Free and Added Sugar Intakes in New Zealand; Nutrients 2017, 9, 1292
    (MDPI (Basel, Switzerland), 2018-05-18) Kibblewhite R; Nettleton A; McLean R; Haszard J; Fleming E; Kruimer D; Te Morenga L
    The authors have requested that the following changes be made to their paper. In Figure 1, the caption was changed to “Figure 1. 10–step method for estimating free sugars content (adapted from Louie et al. 2015 [14])”. In Appendix A, “This appendix details how we used and adapted the 10-step methodology for estimating added sugars described by Louie et al. 2015 [14] to calculate free sugars in the New Zealand food composition database, based on analytical data on total sugars and ingredients in food products. We used the unmodified Louie method to estimate added sugars in the New Zealand food composition database as reported in this paper” [2] was inserted in front of the Appendix A title. Further, “adapted from Louie et al., 2015 [14]” [2] was added after the title. “as per Step 1 of Louie et al., 2015 [14]” [2] was added in Step 1. “as per Step 2 of Louie et al., 2015 [14]” [2] was added in Step 2. “adapted from Step 3 of Louie et al., 2015 [14]” [2] was added in Step 3. “as per Step 4 of Louie et al., 2015 [14]” [2] was added in Step 4a; “adapted from Step 4 of Louie et al.2015 [14]” [2] was added in Step 4b. “as per Step 5 of Louie et al., 2015 [14]” [2] was added in Step 5. “as per Step 6 of Louie et al., 2015 [14]” [2] was added in Step 6. “adapted from Step 7 of Louie et al., 2015 [14]” [2] was added in Step 7. “as per from Step 9 of Louie et al., 2015 [14]” [2] was added as the last sentence of Step 9. “adapted from Step 10 of Louie et al., 2015 [14]” [2] was added as the last sentence of Step 10.
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    Impact of a Modified Version of Baby-Led Weaning on Infant Food and Nutrient Intakes: The BLISS Randomized Controlled Trial
    (MDPI (Basel, Switzerland), 2018-06-07) Williams Erickson L; Taylor RW; Haszard JJ; Fleming EA; Daniels L; Morison BJ; Leong C; Fangupo LJ; Wheeler BJ; Taylor BJ; Te Morenga L; McLean RM; Heath A-LM
    Despite growing international interest in Baby-Led Weaning (BLW), we know almost nothing about food and nutrient intake in infants following baby-led approaches to infant feeding. The aim of this paper was to determine the impact of modified BLW (i.e., Baby-Led Introduction to SolidS; BLISS) on food and nutrient intake at 7⁻24 months of age. Two hundred and six women recruited in late pregnancy were randomized to Control (n = 101) or BLISS (n = 105) groups. All participants received standard well-child care. BLISS participants also received lactation consultant support to six months, and educational sessions about BLISS (5.5, 7, and 9 months). Three-day weighed diet records were collected for the infants (7, 12, and 24 months). Compared to the Control group, BLISS infants consumed more sodium (percent difference, 95% CI: 35%, 19% to 54%) and fat (6%, 1% to 11%) at 7 months, and less saturated fat (-7%, -14% to -0.4%) at 12 months. No differences were apparent at 24 months of age but the majority of infants from both groups had excessive intakes of sodium (68% of children) and added sugars (75% of children). Overall, BLISS appears to result in a diet that is as nutritionally adequate as traditional spoon-feeding, and may address some concerns about the nutritional adequacy of unmodified BLW. However, BLISS and Control infants both had high intakes of sodium and added sugars by 24 months that are concerning.
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    Who We Seek and What We Eat? Sources of Food Choice Inspirations and Their Associations with Adult Dietary Patterns before and during the COVID-19 Lockdown in New Zealand
    (MDPI (Basel, Switzerland), 2021-11-01) Roy R; Gontijo de Castro T; Haszard J; Egli V; Te Morenga L; Teunissen L; Decorte P; Cuykx I; De Backer C; Gerritsen S
    Research shows the shaping of food choices often occurs at home, with the family widely recognised as significant in food decisions. However, in this digital age, our eating habits and decision-making processes are also determined by smartphone apps, celebrity chefs, and social media. The 'COVID Kai Survey' online questionnaire assessed cooking and shopping behaviours among New Zealanders during the 2020 COVID-19 'lockdown' using a cross-sectional study design. This paper examines how sources of food choice inspirations (cooking-related advice and the reasons for recipe selection) are related to dietary patterns before and during the lockdown. Of the 2977 participants, those influenced by nutrition and health experts (50.9% before; 53.9% during the lockdown) scored higher for the healthy dietary pattern. Participants influenced by family and friends (35% before; 29% during the lockdown) had significantly higher scores for the healthy and the meat dietary patterns, whereas participants influenced by celebrity cooks (3.8% before; 5.2% during the lockdown) had significantly higher scores in the meat dietary pattern. There was no evidence that associations differed before and during the lockdown. The lockdown was related to modified food choice inspiration sources, notably an increase in 'comforting' recipes as a reason for recipe selection (75.8%), associated with higher scoring in the unhealthy dietary pattern during the lockdown. The lockdown in New Zealand saw an average decrease in nutritional quality of diets in the 'COVID Kai Survey', which could be partly explained by changes in food choice inspiration sources.
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    No Effect of Added Sugars in Soft Drink Compared With Sugars in Fruit on Cardiometabolic Risk Factors: Results From a 4-Week, Randomized Controlled Trial
    (Frontiers Media SA, 2021-06-30) Te Morenga L; Mallard SR; Ormerod FB
    High intakes of added sugar from soft drinks are associated with negative health outcomes such as the increased risk of gout and type 2 diabetes, weight gain and cardiovascular disease. Fruits are naturally high in sugars but their effect on cardiometabolic risk remains unknown. We examined the effect on cardiometabolic risk factors of consuming natural sugars from fruit or added sugars from sugar-sweetened soft drinks in overweight adults. Forty-eight healthy, overweight (BMI ≥ 28 kg/m2) men (n = 21) and women (n = 20) were randomized to either a fruit (n = 19) or sugar-sweetened soft drink (n = 22) intervention for 4 weeks. The fruit group received 6 items of fresh and dried fruit per day and the sugar-sweetened soft drink group received 955 ml of sugar-sweetened soft drink per day. The interventions were matched for both energy (fruit: 1,800 kJ/d; soft drink: 1,767 kJ/d) and fructose content (fruit: 51.8 g/d; soft drink: 51.7 g/d). The soft drink intervention provided 101 g total sugars, which was all added sugar and the fruit intervention provided 97 g total sugars, which were all natural sugars. Dietary intakes were otherwise ad libitum. Despite being asked to consume additional sugar (up to 1,800 additional kJ/d), there were no changes in weight, blood pressure or other cardiometabolic risk factors, except by uric acid, in any of the intervention groups. In conclusion, our findings do not provide any evidence that short-term regular intake of added sugars is linked to higher cardiometabolic risks, with exception of uric acid in overweight men. Public health interventions to prevent obesity and related diseases should focus on the quality of the whole diet rather than only focusing on reducing sugary drinks or sugar intakes.
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    Co-design of mhealth delivered interventions: A systematic review to assess key methods and processes
    (Springer, 4/07/2016) Eyles H; Jull A; Dobson R; Firestone RT; Whittaker R; Te Morenga L; Goodwin D; Ni Mhurchu C
    Most mobile health (mHealth) programmes are designed with minimal input from target end users and are not truly personalised or adaptive to their specific and evolving needs. This review describes the methods and processes used in the co-design of mHealth interventions. Nine relevant studies of varying design were identified following searches of six academic databases. All employed co-design or participatory methods for the development of a health intervention delivered via a mobile device, with three focusing on health behaviour change (one on nutrition) and six on management of a health condition. Overall, six key phases of design and 17 different methods were used. Sufficiency of reporting was poor, and no study undertook a robust assessment of efficacy; these factors should be a focus for future studies. An opportunity exists to use co-design methods to develop acceptable and feasible mHealth interventions, especially to support improved nutrition and for minority and indigenous groups.