Dataset Information

Spatial-Temporal Footprints Assessment and Driving Mechanism of China Household Diet Based on CHNS.

ABSTRACT: Food consumption is closely associated with resource consumption and environmental sustainability. An unreasonable dietary pattern would cause great pressure or damage to resources and the environment. It is particularly important to reduce the negative impact of household food consumption on resources and the environment while simultaneously ensuring people's nutrient intake and health. This study applied the China Health and Nutrition Survey (CHNS) database to quantitatively study the spatial-temporal analysis of multiple footprints of household food consumption at multiple scales and explored the driving mechanism of the multiple footprints. The results showed that, except land footprint (LF), the other four types of footprints all decreased at varying degrees; the water footprint (WF), carbon footprint (CF), nitrogen footprint (NF) and energy footprint (EF) decreased by 18.24%, 17.82%, 12.03% and 20.36%, respectively, from 2000 to 2011; multiple footprints of food consumption of household in Guizhou was the highest among the 12 provinces involved in the study; this shows that resource consumption (water, energy and land resource) and environmental influences (CO₂ emissions and nitrogen emissions) brought by food consumption of per household in Guizhou are much greater than in other provinces, which has a negative influence on sustainable development; by analyzing the driving factors of multiple footprints, it is shown that nutrient intake, household attributes, educational level and health conditions were significantly correlated to multiple footprints. Among them, nutrient intake has greater impact on the multiple footprints of Chinese household food consumption. By comparing multiple footprints of different dietary patterns, it was found that the current Chinese dietary pattern would cause excessive resource consumption, which would bring more pressure on resources and the environment. Adjusting household living habits would possibly reverse the unsustainable situation, such as reducing the consumption of animal-derived foods and adjusting the dietary pattern of households with a higher educational level and income status. Chinese Dietary Guidelines 2016 has better sustainability; the promotion of this dietary pattern across the country would help China to relieve the pressure on resources and environment from the consumer side, promoting the realization of sustainable development.

SUBMITTER: Long Y

PROVIDER: S-EPMC8391238 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Arable land is the lifeblood of food production, it is of great significance to promote the protection of arable land and ensure national food security by accurately understanding the change law of cultivated land and its driving mechanism. This study takes the Weibei dry plateau region of China as an example, explores its spatial and temporal change characteristics through the center of gravity shift and land use shift matrix, and couples the geographic probe model to reveal the driving mechanisms affecting arable land change. The results show that in the past 25 years, the total arable land area in the Weibei Dry Plateau Region of China has decreased by 5.58%, and the stability of arable land resources in the whole region has weakened. The center of gravity of arable land shifts to the northeast, and the standard deviation ellipse of arable land mainly undergoes the change process of "increase (1995-2015)-decrease (2015-2020)", and the spatial distribution of arable land tends to be dispersed. In the LISA frequency mapping, the proportion of stable constant and low-frequency areas is as high as 89.58%, and the spatial pattern of cultivated land is relatively stable. Medium and high frequency areas. The transformation mode is mainly "low-low" aggregation, "low-high" aggregation is not significant, and the decline of cultivated land in the study area is more obvious. In the past 25 years, a total of 1017.26 km2 of arable land was converted to construction land. The explanatory power of the influencing factors varies in each period (0.299 to 0.731), with total agricultural machinery power has the strongest explanatory power of 0.694, 0.592, and 0.731, respectively. The interaction between slope and annual average temperature and other factors being the highest, both greater than 0.8. Through the construction of LISA frequency mapping, combined with the center of gravity model and standard deviation ellipse, the spatial evolution trend of regional arable land is more comprehensively and dynamically grasped. By using the geodetector model, the driving mechanism of the changes of arable land is revealed comprehensively, which provides a theoretical basis for the scientific management and effective protection of arable land resources and a basis for decision-making.

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Spatial-Temporal Footprints Assessment and Driving Mechanism of China Household Diet Based on CHNS.

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