Evidence map›Paper›PMID 37266126›Full record

ArticleFrontiers in nutrition2023

Choosing an effective food classification system for promoting healthy diets in Thailand: a comparative evaluation of three nutrient profiling-based food classification systems (government, WHO, and Healthier Choice Logo) and a food-processing-based food classification system (NOVA).

Sirinya Phulkerd, Sarah Dickie, Natjera Thongcharoenchupong, Sasinee Thapsuwan, Priscila Machado, Julie Woods, Ladda Mo-Suwan, Piyada Prasertsom, Chantana Ungchusak, Chiraporn Khitdee and 1 more

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Public health perspectives on out-of-home food consumption in Thailand.Asia Pacific journal of clinical nutrition · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sirinya PhulkerdInstitute for Population and Social Research, Mahidol University, Salaya, Thailand.
Sarah DickieInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
Natjera ThongcharoenchupongInstitute for Population and Social Research, Mahidol University, Salaya, Thailand.
Sasinee ThapsuwanInstitute for Population and Social Research, Mahidol University, Salaya, Thailand.
Priscila MachadoInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
Julie WoodsInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
Ladda Mo-SuwanFaculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
Piyada PrasertsomBureau of Dental Health, Department of Health, Ministry of Public Health, Mueang, Nonthaburi, Thailand.
Chantana UngchusakThailand Healthy Lifestyle Plan, Thai Health Promotion Foundation, Bangkok, Thailand.
Chiraporn KhitdeeBureau of Dental Health, Department of Health, Ministry of Public Health, Mueang, Nonthaburi, Thailand.
Mark LawrenceInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aimed to assess the nutritional quality of food and beverage products in Thailand by comparing four different food classification systems: the nutrient profiling-based food classification systems by the Department of Health (DOH), the WHO South-East Asia Region (WHO SEA), the Healthier Choice Logo (HCL), and the food-processing-based food classification system, NOVA. Methods: This study used secondary data from the Mintel Global New Products Database ( Results: Of the total sample that could be classified by any of the four classification systems ( Conclusion: A hybrid food classification approach taking both nutrients and food processing into account is needed to comprehensively assess the nutritional quality of food and beverage products in Thailand.

Indexed as

healthy dietsnon-communicable diseasesNOVA food classification systemnutrient profilingThailandultra-processed foods

Identifiers

PMID37266126
PMCPMC10230096

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.