Water Footprint of Food Consumption by Chinese Residents

207

143

The last few decades testify that consumers’ concerns for healthier lifestyles and environment care are driving forces for reshaping food buying intentions and their perspectives on food quality. The present study identifies the importance that consumers attach to quality, health, and environment selected cues of purchased food products. More precisely, to elicit preferences for social, environmental, and qualitative food cues, a survey instrument was developed and applied on 797 Belgian and Romanian consumers. Our findings suggest that investigated consumers most frequently use freshness, taste, and appearance to evaluate food quality. The use frequency of food quality cues related to health is primarily influenced by the attention paid to food quality. The most relevant cues of food healthiness are ingredients, nutrition facts, and additives and for food environmental impact are packaging, food origin, and production type. It is concluded that food quality receives high attention both from Belgian and Romanian consumers and health and environment related cues can be used as a means of improving consumer health and environmental protection.

Section: Resultsmentioning

confidence: 99%

Section: Capacity To Maintain Current Health State By Eating the Righmentioning

confidence: 99%

Section: Capacity To Maintain Current Health State By Eating the Righmentioning

confidence: 99%

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Consumer Understanding of Food Quality, Healthiness, and Environmental Impact: A Cross-National Perspective

Petrescu

Vermeir

Petrescu-Mag

2019

207

143

“…The water footprint (WF) is a useful indicator that can reveal the life-cycle water occupation in producing food [11]. An upward trend of water footprint of China's food consumption has been proved by Zhang et al [12]. Although population growth is a great contributor to this growing water footprint [13], the effect of diet transition should also be paid attention to.…”

Section: Introductionmentioning

confidence: 99%

Drivers of the Growing Water, Carbon and Ecological Footprints of the Chinese Diet from 1961 to 2017

Cao

Chai

Yan

et al. 2020

In the past decades, food consumption in China has undergone a rapid increase and a significant structure transition, as a result of population growth and economic development. The food system is increasingly threatening the environment by depleting water resources, deteriorating water bodies, aggravating climate change, degrading ecosystems, etc. It is significant to understand how food consumption affected the environment and how its impacts were driven in the historical period. This study reveals the environmental impacts of China’s food system from 1961 to 2017 from a consumption perspective by assessing water, carbon, and ecological footprints. The logarithmic mean Divisia index method was used to examine the drivers of the growing environmental footprints. The assessment results show that all three environmental footprints have had a drastic increase of more than two times during the studied period, which indicates the high environmental pressure posed by food consumption. We also found that, before the 1980s, the main driving forces of the increasing footprints were population and per capita energy intake. From 1984, the diet pattern started to take a positive effect and then became the dominant driver of the growing environmental footprints after the end of the 1990s.

“…As to food producers and consumers, every aspect of the food life cycle can strive to reduce the impact of food on the environment [ 14 ]. We can advocate a balanced diet structure, reduce food waste, and cut down those unnecessary energy intakes [ 15 , 16 , 17 ]. Today, the global population’s food intake accounts for 19–29% of the total greenhouse gas emissions, 70% of freshwater consumption, and 38% land use [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Using the Machine Learning Method to Study the Environmental Footprints Embodied in Chinese Diet

Liang

Han

Chai

et al. 2020

The food system profoundly affects the sustainable development of the environment and resources. Numerous studies have shown that the food consumption patterns of Chinese residents will bring certain pressure to the environment. Food consumption patterns have individual differences. Therefore, reducing the pressure of food consumption patterns on the environment requires the precise positioning of people with high consumption tendencies. Based on the related concepts of the machine learning method, this paper designs an identification method of the population with a high environmental footprint by using a decision tree as the core and realizes the automatic identification of a large number of users. By using the microdata provided by CHNS(the China Health and Nutrition Survey), we study the relationship between residents’ dietary intake and environmental resource consumption. First, we find that the impact of residents’ food system on the environment shows a certain logistic normal distribution trend. Then, through the decision tree algorithm, we find that four demographic characteristics of gender, income level, education level, and region have the greatest impact on residents’ environmental footprint, where the consumption trends of different characteristics are also significantly different. At the same time, we also use the decision tree to identify the population characteristics with high consumption tendency. This method can effectively improve the identification coverage and accuracy rate and promotes the improvement of residents’ food consumption patterns.