Variety Predicts Discretionary Food and Beverage Intake of Australian Adults: A Cross-Sectional Analysis of an Online Food Intake Survey

BACKGROUND

Variety has been used as a strategy for increasing intakes of healthy foods, but has not been well explored with respect to discretionary food/beverages. The diverse sensory properties of these foods suggests that variety could play an important role in total intake.

OBJECTIVE

This study explored variety as a predictor of intake of discretionary food/beverages, and described the variety of these items consumed by Australian adults.

DESIGN

Secondary analyses of cross-sectional data from a validated, online survey that assesses participants' dietary intake using frequency and portion-based questions. Discretionary food/beverages are grouped into 11 categories.

PARTICIPANTS/SETTING

Participants included 235,203 Australian adults, aged 18 years or older, who provided data from May 2015 to November 2020.

OUTCOME MEASURES

Variety was the number of categories of discretionary food/beverages consumed. Servings were estimated from usual intake questions, and percent contribution summarized by category. Consumption prevalence was the proportion of the sample/subgroup consuming each category. Consumption was calculated as the mean of the sample and per capita in servings.

STATISTICAL ANALYSES PERFORMED

Descriptive statistics were used to present variety and percent contribution to total intake across the sample and subgroups, and multiple regression was used to examine whether or not variety predicted intake of discretionary food/beverages.

RESULTS

Participants consumed a median of 8 categories of discretionary food/beverages, with every additional category associated wit h an increase in intake of half a serving of discretionary food/beverages per day (B = 0.48; P < 0.001). Alcohol, cakes and cookies, takeaway, and confectionary collectively contributed around two-thirds of total daily intake of discretionary food/beverages, with alcohol contributing the largest proportion (28.3% of total daily intake).

CONCLUSIONS

Variety is related to total intake of discretionary food/beverages. Intervention approaches targeting a reduction in variety, as an alternative to a focus on portion size or frequency of intake, would be a novel way of addressing overconsumption of discretionary food/beverages in future research.

Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial

BACKGROUND

The effect of personalised nutrition advice on discretionary foods intake is unknown. To date, two national classifications for discretionary foods have been derived. This study examined changes in intake of discretionary foods and beverages following a personalised nutrition intervention using these two classifications.

METHODS

Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomised to receive generalised dietary advice (control) or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Dietary intake was derived from an FFQ. An analysis of covariance was used to determine intervention effects at month 6 between personalised nutrition (overall and by levels) and control on i) percentage energy from discretionary items and ii) percentage contribution of total fat, SFA, total sugars and salt to discretionary intake, defined by Food Standards Scotland (FSS) and Australian Dietary Guidelines (ADG) classifications.

RESULTS

Of the 1607 adults at baseline, n = 1270 (57% female) completed the intervention. Percentage sugars from FSS discretionary items was lower in personalised nutrition vs control (19.0 ± 0.37 vs 21.1 ± 0.65; P = 0.005). Percentage energy (31.2 ± 0.59 vs 32.7 ± 0.59; P = 0.031), percentage total fat (31.5 ± 0.37 vs 33.3 ± 0.65; P = 0.021), SFA (36.0 ± 0.43 vs 37.8 ± 0.75; P = 0.034) and sugars (31.7 ± 0.44 vs 34.7 ± 0.78; P < 0.001) from ADG discretionary items were lower in personalised nutrition vs control. There were greater reductions in ADG percentage energy and percentage total fat, SFA and salt for those randomised to L3 vs L2.

CONCLUSIONS

Compared with generalised dietary advice, personalised nutrition advice achieved greater reductions in discretionary foods intake when the classification included all foods high in fat, added sugars and salt. Future personalised nutrition approaches may be used to target intake of discretionary foods.

TRIAL REGISTRATION

Clinicaltrials.gov NCT01530139 . Registered 9 February 2012.