Evidence map›Paper›PMID 30836654›Full record

ArticleInternational journal of environmental research and public health2019

Adaptation and Validation of the Chinese Version of the Nutrition Environment Measurement Tool for Stores.

Yang Liu, Shenzhi Song, Joel Gittelsohn, Nan Jiang, Jiajin Hu, Yanan Ma, Deliang Wen

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Food Environment Assessment in Two Socioeconomic Contexts in Queensland, Australia.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2026
    Article
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  3. Article
  4. Article
  5. Article
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  8. Characterizing Retail Food Environments in Peri-Urban Pakistan during the COVID-19 Pandemic.International journal of environmental research and public health · 2022
    Article
  9. Article
  10. Review
  11. Article
  12. 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

7 authors.

Yang LiuInstitute of Health Sciences, China Medical University, Shenyang 110122, China. yliu0568@cmu.edu.cn.
Shenzhi SongInstitute of Health Sciences, China Medical University, Shenyang 110122, China. szsong@cmu.edu.cn.
Joel GittelsohnDepartment of International Health, Center for Human Nutrition, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205-2179, USA. jgittel1@jhu.edu.
Nan JiangInstitute of Health Sciences, China Medical University, Shenyang 110122, China. ndjiang@live.ca.
Jiajin HuInstitute of Health Sciences, China Medical University, Shenyang 110122, China. jjhu@cmu.edu.cn.
Yanan MaInstitute of Health Sciences, China Medical University, Shenyang 110122, China. ynma@cmu.edu.cn.
Deliang WenInstitute of Health Sciences, China Medical University, Shenyang 110122, China. dlwen@cmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in lifestyle and food environment have created a heavy burden of obesity and chronic disease in China. However, measurements of the food environment have been rarely reported in China or other countries with similar food cultures; this measurement shortage is partially due to the lack of valid and reliable measurement tools. The aim of the present study was to adapt and validate a Chinese version of the Nutritional Environment Measurement Survey for Stores (C-NEMS-S). Categories and items of the NEMS-S were culturally adapted to fit the Chinese population and included grains, dry beans, starchy tubers, vegetables, fruits, seafood, meat and poultry, dietary oils, milk, bread, instant noodles, and beverages. A scoring sheet for each food category was created to measure availability, quality, and pricing. Then, the C-NEMS-S was validated in 10 large-sized supermarkets and 10 convenience stores in Shenyang, China. Two trained raters performed their evaluations separately at the same store. The intra-class correlation coefficient (ICC) of the availability composite score was 0.98. All food measures had a moderate or good ICC (0.41 to 1.00). The kappa for each food measure ranged from 0.52 to 1.00. C-NEMS-S was able to show the difference in healthy food availability between large-sized supermarkets and convenience stores, as well as the price differences between healthier options and regular options. Large-sized supermarkets had a significantly higher total score (

Indexed as

Nutrition SurveysChinaCommerceConsumer BehaviorFoodHumansNutritional StatusReproducibility of ResultsChinafood environmentNutritional Environment Measurement Survey-Stores (NEMS-S)

Identifiers

PMID30836654
PMCPMC6427157

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Registered trials

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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.