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Clustering of adherence to personalised dietary recommendations and changes in healthy eating index within the Food4Me study – CORRIGENDUM

Published online by Cambridge University Press:  12 June 2019

Katherine M Livingstone
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle upon TyneNE4 5PL, UK
Carlos Celis-Morales
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle upon TyneNE4 5PL, UK
Jose Lara
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle upon TyneNE4 5PL, UK
Clara Woolhead
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
Clare B O’Donovan
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
Hannah Forster
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
Cyril FM Marsaux
Affiliation:
Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre, Maastricht, The Netherlands
Anna L Macready
Affiliation:
Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, UK
Rosalind Fallaize
Affiliation:
Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, UK
Santiago Navas-Carretero
Affiliation:
Center for Nutrition Research, University of Navarra, Pamplona, Spain CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
Rodrigo San-Cristobal
Affiliation:
CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
Silvia Kolossa
Affiliation:
ZIEL Research Center of Nutrition and Food Sciences, Biochemistry Unit, Technical University of Munich, Munich, Germany
Lydia Tsirigoti
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
Christina P Lambrinou
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
George Moschonis
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
Agnieszka Surwiłło
Affiliation:
National Food & Nutrition Institute (IZZ), Warsaw, Poland
Christian A Drevon
Affiliation:
Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
Yannis Manios
Affiliation:
Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
Iwona Traczyk
Affiliation:
National Food & Nutrition Institute (IZZ), Warsaw, Poland
Eileen R Gibney
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
Lorraine Brennan
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
Marianne C Walsh
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
Julie A Lovegrove
Affiliation:
Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, UK
J Alfredo Martinez
Affiliation:
CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
Wim HM Saris
Affiliation:
Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre, Maastricht, The Netherlands
Hannelore Daniel
Affiliation:
ZIEL Research Center of Nutrition and Food Sciences, Biochemistry Unit, Technical University of Munich, Munich, Germany
Mike Gibney
Affiliation:
UCD Institute of Food and Health, University College Dublin, Dublin, Republic of Ireland
John C Mathers
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle upon TyneNE4 5PL, UK
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Abstract

Type
Corrigendum
Copyright
© The Authors 2019 

Original text and corrections:

ORIGINAL TEXT (page 3296, Abstract)

Subjects: Adults aged 18–79 years (n 1480).

CORRECTION

Subjects: Adults aged 18-79 years at baseline (n 1480).

ORIGINAL TEXT (page 3298, Results)

Of the 5562 individuals who registered on the Food4Me website, 1607 were randomised into the study and a total of 1480 provided baseline data on dietary intakes(17).

CORRECTION

Of the 5562 individuals who registered on the Food4Me website, 1607 were randomised into the study. A total of 1480 participants provided baseline data on dietary intakes (15). Following exclusion of missing data for covariates the baseline sample was 1285. A total of 1147 participants provided complete follow up data.

ORIGINAL TEXT (page 3300, Results)

There were no significant differences in changes in HEI between clusters when PN was stratified by Level 1, Level 2 or Level 3 (data not shown).

CORRECTION

The results for when PN was stratified by L1, L2 or L3 are presented in Supplementary Table 5. For participants in L2, there were bigger improvements in HEI for participants in C4 compared with C1 (P<0.001) and in C3 and C2 compared with C1 (<0.05). For participants in L3, there were bigger improvements in HEI for participants in C4 compared with C1 and C2 (P<0.05) (Supplementary Table 5). There were no significant differences for participants in L1.

ORIGINAL TEXT (page 3300, Results)

Exclusion of participants with reported intakes more than 3 SD above or below the mean dietary intakes of whole grains, oily fish, red meat and fruit and vegetables revealed similar clusters (see online supplementary material, Supplemental Table 5).

CORRECTION

Exclusion of participants with reported intakes more than 3 SD above or below the mean dietary intakes of wholegrain, oily fish, red meat and fruit and vegetables revealed similar clusters (Supplementary Table 6).

ORIGINAL TEXT (page 3302, Discussion)

We observed that individuals in the cluster where the fewest recommendations were met (C4) reported the biggest improvement in HEI following PN intervention but there were no differences between clusters in response to conventional, non-personalised dietary advice.

CORRECTION

We observed that individuals in the cluster where the fewest recommendations were met (C4) reported the biggest improvement in HEI following PN intervention.

ORIGINAL TEXT (page 3302, Discussion)

Fig. 1 Changes from baseline to month 6 in Healthy Eating Index 2010 (HEI) score by cluster of adherence to dietary recommendations at baseline among adults aged 18–79 years (n 1480), Food4Me study.

CORRECTION

Figure 1 Changes from baseline to month 6 in Healthy Eating Index by clusters of adherence to recommendations at baseline among adults aged 18–79 years (n 1,147), Food4Me study.

ORIGINAL TEXT (page 3300, Results)

Table needed

CORRECTION

Table 1 Food and nutrient and intakes by participants by clusters of adherence to recommendations at baseline among adults aged 18–79 years (n 1285), Food4Me study

Values represent means and SD.

†, P values are also adjusted for total energy intake.

*ANOVA were adjusted for age, sex, BMI, PAL, smoking habits and country; Posthoc Tukey tests were performed to test for significant differences between clusters Superscript numbers denote where the differences lie across the clusters. For example, 1 means significantly different from cluster 1.

ORIGINAL TEXT (page 3301, Discussion)

Table needed

CORRECTION

Table 2 Socio-demographic characteristics of participants by clusters of adherence to recommendations at baseline among adults aged 18–79 years (n 1285), Food4Me study

Values represent means and SD or percentages; PAL, physical activity level; SB, sedentary behaviour

*ANOVA and logistic regression were used to test for significant differences across clusters in continuous and categorical variables, respectively. Analyses were adjusted for age, sex, BMI, PAL, smoking habits and country. Post hoc Tukey tests (continuous data) and logistic regression (categorical) were used to test for significant differences between clusters. Superscripts denote where the differences lie across the clusters. For example, 2 means significantly different from cluster 2.

ORIGINAL TEXT (page 3302, Discussion)

Table needed

CORRECTION

Table 3 Healthy Eating Index (HEI) score and its constituents at baseline and month 6 by clusters of adherence to recommendations among adults aged 18–79 years Food4Me study

Values represent means and SD.

*Fatty acid ratio is the ratio of unsaturated fatty acids (mono- and polyunsaturated fatty acids) to saturated fatty acids

†ANOVA were used to test for significant differences across clusters. Models were adjusted for age, sex, body mass index, physical activity level, smoking habits and country. Posthoc Tukey’s tests used to test for significant differences between clusters. Superscript numbers denote where the differences lie across the clusters relative to the reference category (1). For example, 2 means significantly different from cluster 2.

ORIGINAL TEXT (Supplementary Materials)

The table below was previously omitted.

CORRECTION

Supplemental Table 5. Changes from baseline to month 6 in Healthy Eating Index 2010 (HEI) score by cluster (C) of adherence to dietary recommendations at baseline among adults aged 18–79 years in the Food4Me study stratified by level of personalised nutrition advice.

Values are predicted means and standard errors. ANOVA were used to test for significant differences across clusters. Models were adjusted for age, sex, BMI, physical activity level, smoking habits and country. Level 1 received personalised dietary advice on how their intakes of these food groups at baseline compared with guideline amounts. Level 2 received advice based on their dietary intake (as for Level 1) and also on their baseline phenotypic data. Level 3 received advice based on their dietary intake, phenotypic and genotypic data collected at baseline. Posthoc Tukey’s tests used to test for significant differences between clusters. Superscript numbers denote where the differences lie across the clusters relative to the reference category. For example, 2 means significantly different from cluster 2.

References

Livingstone, KM, Celis-Morales, C, Lara, J, Woolhead, C, O’Donovan, CB, Forster, H, et al. Clustering of adherence to personalised dietary recommendations and changes in healthy eating index within the Food4Me study. Public Health Nutrition, 19(18), 32963305. doi:10.1017/S1368980016001932 CrossRefGoogle Scholar

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