A systematic review and network meta-analysis

In abstract, our findings counsel that each colour-coded labels and warnings appeared efficient in nudging customers’ behaviour in the direction of extra healthful merchandise by altering the healthfulness notion and eliciting detrimental feelings. Every sort of label could have some completely different attributes, however the distinction between completely different types of labels stays to be demonstrated by additional research. Our research can assist policy-makers to push ahead necessary FOPL insurance policies to utilize the complete potential of FOPL in directing customers’ meals alternative and inspiring reformulation within the meals business.

Supporting data

S1 Fig. Forest plots of community estimates combining direct and oblique results for customers’ notion customers’ notion and attitudes for meals and drinks (secondary outcomes).

CI, confidence interval; HW, well being warning; MD, imply distinction; NS, Nutri-Rating; NW, nutrient warning; OR, odds ratio; TLS, site visitors gentle labelling system.

https://doi.org/10.1371/journal.pmed.1003765.s003

(TIFF)

S2 Fig. Forest plots of community estimates for customers’ goal understanding of colour-coded and warning labels (secondary outcomes).

CI, confidence interval; NS, Nutri-Rating; NW, nutrient warning; OR, odds ratio; TLS, site visitors gentle labelling system.

https://doi.org/10.1371/journal.pmed.1003765.s004

(TIFF)

S3 Fig. Forest plots of community estimates for customers’ subjective understanding, consideration, and notion of colour-coded and warning labels (secondary outcomes).

CI, confidence interval; HW, well being warning; MD, imply distinction; NFt, Vitamin Details desk; NS, Nutri-Rating; NW, nutrient warning; OR, odds ratio; TLS, site visitors gentle labelling system.

https://doi.org/10.1371/journal.pmed.1003765.s005

(TIFF)

S4 Fig. Comparability-adjusted funnel plots for comparability of interventions with management situation for adjustments in customers’ buying and consuming behaviour (major outcomes).

HW, well being warning; MD, imply distinction; NS, Nutri-Rating; NW, nutrient warning; TLS, site visitors gentle labelling system.

https://doi.org/10.1371/journal.pmed.1003765.s006

(TIFF)

S5 Fig. Comparability-adjusted funnel plots for adjustments in customers’ notion and attitudes for meals and drinks (secondary outcomes).

HW, well being warning; MD, imply distinction; NS, Nutri-Rating; NW, nutrient warning; OR, odds ratio; TLS, site visitors gentle labelling system.

https://doi.org/10.1371/journal.pmed.1003765.s007

(TIFF)

S6 Fig. Comparability-adjusted funnel plots for customers’ consideration, notion, and understanding of colour-coded and warning labels (secondary outcomes).

HW, well being warning; NS, Nutri-Rating; NW, nutrient warning; OR, odds ratio; TLS, site visitors gentle labelling system.

https://doi.org/10.1371/journal.pmed.1003765.s008

(TIFF)

S7 Table. Netsplitting of community meta-analysis estimates for the first outcomes into the contribution of direct and oblique proof and take a look at for native inconsistency grouped by age, intercourse, SES, research setting, sort of merchandise, and NFt show.

https://doi.org/10.1371/journal.pmed.1003765.s015

(XLSX)

S8 Table. The netsplitting of sensitivity community meta-analysis in research estimates (together with solely randomised managed trials) for adjustments in customers dietary behaviour into the contribution of direct and oblique proof and take a look at for native inconsistency.

https://doi.org/10.1371/journal.pmed.1003765.s016

(XLSX)

S9 Table. The netsplitting of sensitivity community meta-analysis estimates (eradicating research utilizing NFt management) for adjustments in customers dietary behaviour into the contribution of direct and oblique proof and take a look at for native inconsistency.

https://doi.org/10.1371/journal.pmed.1003765.s017

(XLSX)

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