In:
Public Health Nutrition, Cambridge University Press (CUP), Vol. 24, No. 5 ( 2021-04), p. 1117-1128
Abstract:
A high-fibre diet is associated with a lower risk for diseases. However, few adults meet the dietary fibre recommendation. Therefore, the effects and acceptance of an algorithm-generated personalised dietary advice (PDA) compared with general advice (GA) on fibre intake were investigated. Design: A 6-week, single-blind randomised controlled trial with a 3-month follow-up. Setting: PDA was based on habitual intake and provided fibre-rich alternatives using a website; GA contained brochures. Dietary intake was assessed at baseline, week 1, week 6 and 3-month follow-up. Both groups evaluated their advice at week 6. All participants had access to PDA from week 7 until 3-month follow-up. Participants: Two groups of healthy adults: PDA ( n 34) and GA ( n 47). For 3-month follow-up analysis, participants were re-divided into visitors ( n 52) and non-visitors ( n 26) of the PDA. Results: At week 6, energy intake remained stable in both groups, but fibre intake per 1000 kcal increased non-significantly in both groups (PDA = Δ0·5 ± 2·8; GA = Δ0·8 ± 3·1, P = 0·128). Importantly, a significantly higher percentage of PDA participants adhered to the recommendation compared with week 1 (PDA = 21 % increase; GA = 4 % increase, P ≤ 0·001). PDA participants evaluated the advice significantly better compared with GA participants. At 3-month follow-up, fibre intake increased compared with baseline (visitors = Δ2·2 ± 2·6, P 〈 0·001; non-visitors = Δ1·5 ± 1·9, P = 0·001), but was insignificantly different between groups. Visitors had a decrease and non-visitors had an increase in energy intake (visitors =Δ − 132 ± 525; non-visitors = Δ109 ± 507, P = 0·055). Conclusions: The algorithm-generated PDA was well accepted and stimulated adherence to the recommendations more than GA, indicating to be a suitable and cost-efficient method for improving dietary fibre intake in healthy adults.
Type of Medium:
Online Resource
ISSN:
1368-9800
,
1475-2727
DOI:
10.1017/S1368980020002980
Language:
English
Publisher:
Cambridge University Press (CUP)
Publication Date:
2021
detail.hit.zdb_id:
2016337-X
SSG:
21
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