Development of a database for estimation of the nut content of Australian single-ingredient and multi-ingredient foods

Nikodijevic, Cassandra J.; Probst, Yasmine; Neale, Elizabeth P.

doi:10.1016/j.jfca.2019.103236

Cited by 7 publications

(10 citation statements)

References 13 publications

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“…Assumptions made for country-specific databases are described in Supplemental Table 1. Specifically, the Australian Health Survey-Australian Dietary Guidelines database [30], Australian nut database [31], and the AUSNUT 2011-2013 food recipe file [32] were utilised to calculate the FVNLO content of Australian foods. In the UK context, the FSA Standard Recipes Database 1992-2012 [33] was used in conjunction with the NDNS Nutrient Databank to calculate the FVNLO content of foods.…”

Section: Application Of the Original Nutri-score Algorithmmentioning

confidence: 99%

Aligning nutrient profiling with dietary guidelines: modifying the Nutri-Score algorithm to include whole grains

et al. 2021

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Purpose Whole grains, generally recognised as healthy choices, are not included in most nutrient profiling systems. We tested modifications to the Nutri-Score algorithm to determine whether including whole grains would provide an improved measure of food, and overall diet quality. Methods The whole-grain content of food, with a minimum cut-point of 25%, was added to the algorithm, following similar methods used to score other health-promoting components such as fibre. We applied and compared the original and the modified Nutri-Score to food composition and dietary intake data from Australia, France, the United Kingdom, and the United States. Results At the food level, correlations between whole-grain content and food nutritional score were strengthened using the modified algorithm in Australian data, but less so for the other countries. Improvements were greater in grain-specific food groups. The largest shift in Nutri-Score class was from B to A (best score). At the dietary intake level, whole-diet nutritional scores for individuals were calculated and compared against population-specific diet-quality scores. With modifications, correlations with diet-quality scores were improved slightly, suggesting that the modified score better aligns with national dietary guidelines. An inverse linear relationship between whole-diet nutritional score and whole-grain intake was evident, particularly with modifications (lower whole-diet nutritional score indicative of better diet quality). Conclusion Including a whole-grain component in the Nutri-Score algorithm is justified to align with dietary guidelines and better reflect whole grain as a contributor to improved dietary quality. Further research is required to test alternative algorithms and potentially other nutrient profiling systems.

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Section: Application Of the Original Nutri-score Algorithmmentioning

confidence: 99%

Aligning nutrient profiling with dietary guidelines: modifying the Nutri-Score algorithm to include whole grains

et al. 2021

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“…To determine nut consumption during the 2011-2012 NNPAS, the nut-specific database developed by our team (12) was applied to 24-h recall data. For the purpose of this research, the term 'nuts' was used to include tree nuts, peanuts, mixed nuts, tree nut products and peanut products and excluded coconut, coconut products, peanut oil, tree nut oils and nut milks.…”

Section: Methodsmentioning

confidence: 99%

“…To accurately estimate nut consumption, a systematic method of quantifying the amount of nuts in mixed dishes is required. We have recently developed a nut-specific database for application to Australian dietary data (12) . In addition, currently available data on nut consumption from the 2011-2012 NNPAS are based on a single day's dietary recall.…”

mentioning

confidence: 99%

Nut consumption in a representative survey of Australians: a secondary analysis of the 2011–2012 National Nutrition and Physical Activity Survey

Nikodijevic

Probst

Batterham

et al. 2020

Public Health Nutr.

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Objective: Nut consumption is associated with a range of health benefits. The current study aimed to examine nut consumption in the 2011–2012 National Nutrition and Physical Activity Survey (NNPAS) and to investigate associations between nut intake, nutrient intake and anthropometric and blood pressure measurements. Design: Secondary analysis of the 2011–2012 NNPAS. Usual consumption of nuts in the 2011–2012 NNPAS was determined, and nut consumption was compared with population recommendations of 30 g nuts per day. The relationship between nut consumption and intakes of key nutrients, anthropometric outcomes (weight, BMI and waist circumference) and blood pressure was examined using linear regression for participants aged over 18 years. Setting: Australia. Participants: Australians (2 years and older, n 12 153) participating in the representative 2011–2012 NNPAS. Results: Mean nut intake was 4·61 (95 % CI: 4·36, 4·86) g/d, with only 5·6 % of nut consumers consuming 30 g of nuts per day. Nut consumption was associated with significantly greater intakes of fibre, vitamin E, Fe, Mg and P. There was no association between nut consumption and body weight, BMI, waist circumference, or blood pressure. Conclusions: Exploration of nut consumption in a representative sample of Australians identified that nut intake does not meet recommendations. Higher nut consumption was not adversely associated with higher body weight, aligning with the current evidence base. Given the current levels of nut consumption in Australia, strategies to increase nut intake to recommended levels are required.

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“…All of the food matching was performed using the VLOOKUP function in Microsoft Excel (Microsoft Corporation, 2010, version 14.0.7). In order to determine walnut consumption, a nut-specific food composition database ( 42 ) was applied to the dietary intake data. Walnuts are commonly consumed alone or as part of mixed foods, such as carrot cake and brownies ( 42 ).…”

Section: Methodsmentioning

confidence: 99%

“…In order to determine walnut consumption, a nut-specific food composition database ( 42 ) was applied to the dietary intake data. Walnuts are commonly consumed alone or as part of mixed foods, such as carrot cake and brownies ( 42 ). The detailed food intake data preparation process has been reported elsewhere ( 23 ).…”

Section: Methodsmentioning

confidence: 99%

Identifying Usual Food Choice Combinations With Walnuts: Analysis of a 2005–2015 Clinical Trial Cohort of Overweight and Obese Adults

et al. 2020

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Consumption of nuts has been associated with a range of favorable health outcomes. Evidence is now emerging to suggest that walnuts may also play an important role in supporting the consumption of a healthy dietary pattern. However, limited studies have explored how walnuts are eaten at different meal occasions. The aim of this study was to explore the food choices in relation to walnuts at meal occasions as reported by a sample of overweight and obese adult participants of weight loss clinical trials. Baseline usual food intake data were retrospectively pooled from four food-based clinical trials (n = 758). A nut-specific food composition database was applied to determine walnut consumption within the food intake data. The a priori algorithm of association rules was used to identify food choices associated with walnuts at different meal occasions using a nested hierarchical food group classification system. The proportion of participants who were consuming walnuts was 14.5% (n = 110). The median walnut intake was 5.14 (interquartile range, 1.10-11.45) g/d. A total of 128 food items containing walnuts were identified for walnut consumers. The proportion of participants who reported consuming unsalted raw walnut was 80.5% (n = 103). There were no identified patterns to food choices in relation to walnut at the breakfast, lunch, or dinner meal occasions. A total of 24 clusters of food choices related to walnuts were identified at others (meals). By applying a novel food composition database, the present study was able to map the precise combinations of foods associated with walnuts intakes at mealtimes using data mining. This study offers insights into the role of walnuts for the food choices of overweight adults and may support guidance and dietary behavior change strategies.

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Development of a database for estimation of the nut content of Australian single-ingredient and multi-ingredient foods

Cited by 7 publications

References 13 publications

Aligning nutrient profiling with dietary guidelines: modifying the Nutri-Score algorithm to include whole grains

Aligning nutrient profiling with dietary guidelines: modifying the Nutri-Score algorithm to include whole grains

Nut consumption in a representative survey of Australians: a secondary analysis of the 2011–2012 National Nutrition and Physical Activity Survey

Identifying Usual Food Choice Combinations With Walnuts: Analysis of a 2005–2015 Clinical Trial Cohort of Overweight and Obese Adults

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