Hong Xi, Li Weiyi, Wang Liusen, Jiao Yingying, Liu Mengran, Zhang Jiguo, Wang Huijun, Zhang Bing, Jiang Hongru, Wang Zhihong
National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Center for Disease Control and Prevention of Hancheng City, Weinan 715400, China.
Wei Sheng Yan Jiu. 2024 May;53(3):403-409. doi: 10.19813/j.cnki.weishengyanjiu.2024.03.010.
To analyze food carbon footprint and its socio-demographic disparities among adults in China.
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.
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).
The food carbon footprint of adults in China in 2018 show different socio-demographic disparities, gender, income and education level are significant factors.
分析中国成年人的食物碳足迹及其社会人口统计学差异。
对2018年中国健康与营养调查中12777名18岁及以上且已完成饮食和社会人口统计学数据的成年人进行分析。通过24小时回顾法结合家庭调味品称重收集食物摄入量信息。根据《中国食物成分表》将食物消费量转化为能量摄入量。基于生命周期评估（LCA）的食物碳足迹数据库计算26类食物的碳足迹，采用多项logit模型分析社会人口统计学因素与食物碳足迹的关联。
食物碳足迹平均水平随年龄增长而降低，随收入和教育水平提高而增加，男性高于女性，城市居民高于农村居民，南方高于北方。多项logit分析显示，与18 - 44岁人群相比，60岁及以上人群出现高碳足迹的可能性比出现低碳足迹的可能性低29%（OR = 0.71，95%CI 0.61 - 0.83）。与男性相比，女性出现中碳足迹和高碳足迹的可能性分别比出现低碳足迹的可能性低11%（OR = 0.89，95%CI 0.81 - 0.99）和25%（OR = 0.75，95%CI 0.67 - 0.84）。与城市居民相比，农村居民出现中碳足迹和高碳足迹的可能性分别比出现低碳足迹的可能性低24%（OR = 0.76，95%CI 0.69 - 0.85）和38%（OR = 0.62，95%CI 0.55 - 0.70）。与北方人群相比，南方人群出现中碳足迹和高碳足迹的可能性分别是出现低碳足迹可能性的3.89倍（95%CI 3.52 - 4.30）和11.35倍（95%CI 10.01 - 12.88）。随着收入水平提高（OR > 1），参与者出现中碳足迹和高碳足迹的可能性增加，随着教育水平提高（OR > 1），出现高碳足迹的可能性增加。
2018年中国成年人的食物碳足迹存在不同的社会人口统计学差异，性别、收入和教育水平是重要因素。
