Evidence map›Paper›PMID 30603270›Full record

ArticleDiabetology international2016

Validating the use of photos to measure dietary intake: the method used by DialBetics, a smartphone-based self-management system for diabetes patients.

Shigeko Kato, Kayo Waki, Sadako Nakamura, Sanae Osada, Haruka Kobayashi, Hideo Fujita, Takashi Kadowaki, Kazuhiko Ohe

Abstract read
In one paragraph

Article in Diabetology international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2021
    Article
  4. Review
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

8 authors.

Shigeko Kato1Department of Ubiquitous Health Informatics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655 Japan.
Kayo Waki1Department of Ubiquitous Health Informatics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655 Japan.
Sadako Nakamura3Institute of Food, Nutrition and Health, Jumonji University, 2-1-28 Sugasawa, Niiza-Shi, Saitama 352-8510 Japan.
Sanae OsadaJunior College, Department of Food and Nutrition, Kagawa Education Institute of Nutrition, 3-24-3, Komagome, Toshima-ku, Tokyo, 170-8481 Japan.
Haruka Kobayashi6Business Department of Healthcare Business Smart-life Solutions Department, NTT DOCOMO, Inc., 2-11-1 Nagatacho, Chiyoda-ku, Tokyo, 100-6111 Japan.
Hideo Fujita1Department of Ubiquitous Health Informatics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655 Japan.
Takashi Kadowaki2Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655 Japan.
Kazuhiko Ohe7Department of Medical Informatics, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655 Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe accuracy of estimating nutritional intake and balance from photos of meals has not been well documented. However, DialBetics (DB)-our diabetes self-management support system, which is based on information and communication technologies-relies on the photos that type 2 diabetes patients take of their meals with smartphones. Therefore, we designed a study to evaluate this accuracy.

methodsWe prepared 61 dishes whose actual amount/value of total energy and each nutrient were known: protein, fat, carbohydrates, dietary fiber and salt. Their balance-the protein-fat-carbohydrate ratio-was also known, constituting the weighed food record (WFR). Smartphone photos of those dishes were taken, and three registered dietitians evaluated each dish from those photos, naming the dish and estimating the amount of each nutrient in it, plus the dish's balance. These estimated DB and WFR values were compared using the Wilcoxon matched-pairs rank-sum test; intraclass correlation coefficients (ICCs) were calculated. Agreement between the two values for each dish was assessed by Bland-Altman analysis.

resultsThere were significant ICCs-0.84 for fat (95 % confidence interval 0.75-0.90) and 0.93 for carbohydrates (0.88, 0.96)-but no statistically significant differences between DB and WRF for other nutrients or balance. Bland-Altman analysis showed that differences between the two values were random and not biased against nutrient intake; 95 % limits of agreement were acceptable although wide (energy -198 to 210 kcal/dish; carbohydrates -22.7 to 25.8 g/dish).

conclusionDB's diet evaluation by photos is reliable with apparent potential for assessing diets.

Indexed as

Dietary intakeDish photographSelf-managementTelemedicineType 2 diabetes

Identifiers

PMID30603270
PMCPMC6224981

What OpenQuestion holds

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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.