[Analysis of food carbon footprint and its socio-demographic disparities in China in 2018].

ABSTRACT

OBJECTIVE: To analyze food carbon footprint and its socio-demographic disparities among adults in China. METHODS: A total of 12 777 adults aged 18 years and above from the China Health and Nutrition Survey in 2018 who have completed dietary and socio-demographic data were analyzed. The information of food intake were collected by 24 h recalls combined with the weighing of household seasonings. Food consumption was converted into energy intake by the China Food Composition Table. Carbon footprint of 26 food groups were calculated by the food carbon footprint database based on life-cycle assessment(LCA), multinomial logit model was used to analyze the association of socio-demographic factors and food carbon footprint. RESULTS: Average food carbon footprint were decreased with increasing age while increased with increasing income and education levels, and was higher among male than that among female, was higher among urban residents than that among rural residents, was higher in the south than that in the north. Multinomial logit analysis showed that compared with people aged 18-44, the likelihood of occurring high carbon footprint in 60y and above group were 29%(OR=0.71, 95%CI 0.61-0.83) lower than that occurring low carbon footprint. Women were 11%(OR=0.89, 95%CI 0.81-0.99) and 25%(OR=0.75, 95%CI 0.67-0.84) less likely to appear medium and high carbon footprint than low carbon footprint, compared with their male counterparts. In comparison to people living in cities, rural dwellers were 24%(OR=0.76, 95%CI 0.69-0.85) and 38%(OR=0.62, 95%CI 0.55-0.70) less likely to appear medium and high carbon footprint than low carbon footprint. People in the south were 3.89 times(95%CI 3.52-4.30) and 11.35 times(95%CI 10.01-12.88) more likely to occur medium and high carbon footprint than low carbon footprint, compared with people in the north. Participants were more likely to occur medium carbon footprint and high carbon footprint with the increasing income level(OR>1), and were more likely to occur high carbon footprint with the increasing education level(OR>1). CONCLUSION: The food carbon footprint of adults in China in 2018 show different socio-demographic disparities, gender, income and education level are significant factors.