ArticleScientific data2026
A long-term dataset of dietary patterns and associated environmental effects in China from 1987 to 2023.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
- A long-term dataset of dietary patterns and associated environmental effects in China from 1987 to 2023.Scientific data · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
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Abstract
The global food system is undergoing a profound transformation, with significant implications for human health and environmental sustainability. Systematic analysis of dietary evolution and its environmental effects is essential for sustainable food system development. Existing research, however, typically emphasized short-term dynamics or isolated environmental factors, neglecting a thorough analysis of the long-term, multidimensional effects of dietary transformation on water, land, and carbon resources. This study constructed a long-term dataset from 1987 to 2023 on the evolution of dietary patterns in China and their associated environmental effects, based on data from the National Bureau of Statistics of China. The dataset established a framework that links diet to water use, land requirement, and carbon emissions. It covers nine food categories: cereals, vegetables, fruits, oilseeds, sugar, eggs, milk, meat, and aquatic products. The dataset comprised long-term time series, multidimensional characteristics, and granularity, providing essential data to support the development of sustainable dietary transition strategies tailored to China's national conditions and to optimize regional resource allocation.
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