Data for: Global food waste across the income spectrum: Implications for food prices, production and resource use

Here we develop a new panel database on household food waste at the national level based on the Energy Balance equation, including adjustments for changes in body weight over time. Since food waste at the country level is not directly observed at present, we must infer this from other observables, including food availability (FA), estimates of physical activity levels (PAL) and basal metabolic rates (BMR), and changes in Body Mass Index (BMI). This leads to the following system of equations for deducing food waste: Energy expenditure = Physical activity level*Basal Metabolic Rate (1) Food Intake = 𝛥 𝐵𝑜𝑑𝑦 𝑤𝑒𝑖𝑔ℎ𝑡*𝜌 + 𝐸𝑛𝑒𝑟𝑔𝑦 𝐸𝑥𝑝𝑒𝑛𝑑𝑖𝑡𝑢𝑟𝑒 (2) Food Waste = 𝐹𝑜𝑜𝑑 𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒 − 𝐹𝑜𝑜𝑑 𝐼𝑛𝑡𝑎𝑘𝑒 (3) Where 𝜌 is a convertor of changes (of increases) in body weight to excessive intake of calories based on the energy balance equations (Hall et al. 2011). Following this approach, the uneaten calories at household level are quantified as the difference between the available calories (kcal/cap/day) and the caloric intake (kcal/cap/day). Country-specific food availability (kcal/cap/day) is obtained from the FAO Food Balance Sheets (FAO/WHO 2017) over the period 1975-2013. The country-specific average Energy Expenditure are calculated from the product of country-specific BMR and the country-specific PAL. The composite BMR, for an average person in each country, is a function of countries’ demographics (age, average weight, and sex) retrieved from World Bank Database (World Bank 2018). PAL based on different lifestyles retrieved from (FAO/WHO 2004). We extend Verma et al. (2017) by incorporating the increment of body weight into this equation. The country-specific average increase 𝛥𝐵𝑜𝑑𝑦 𝑤𝑒𝑖𝑔ℎ𝑡 (𝐵𝑊) was obtained from the differences in BMI reported for the years 1975, 85, 95, 2005, and 2014 (Abarca-Gómez et al. 2017) and country-specific average height for male and female from NCD Risk Factor Collaboration (Risk and Collaboration 2016). The increment in body weight is converted to energy (Kcal/cap/day) by applying a weight change model (Hall et al. 2011). Finally, by assuming a uniform intertemporal distribution of changes on energy expenditure due to changes on average weight, we can calculate country-specific average annual energy daily intake for the period 1975-2013. The final dataset contains average daily households’ uneaten calories for 158 countries (95% of the overall population) for the period 1975-2013. This dataset was used for the paper “Global food waste across the income spectrum: Implications for food prices, production and resource use” (Lopez Barrera and Hertel).本研究基于能量平衡方程（Energy Balance equation）构建了一套全新的国家级家庭食物浪费面板数据库，并纳入了随时间变化的体重调整项。由于当前无法直接观测国家级层面的食物浪费数据，我们需通过其他可观测指标进行推导，包括食物可得性（Food Availability, FA）、身体活动水平（Physical Activity Levels, PAL）与基础代谢率（Basal Metabolic Rates, BMR）的估算值，以及身体质量指数（Body Mass Index, BMI）的变化情况。由此得到如下用于推导食物浪费的方程组： 能量消耗 = 身体活动水平 × 基础代谢率 (1) 食物摄入量 = Δ体重 × ρ + 能量消耗 (2) 食物浪费 = 食物可得性 − 食物摄入量 (3) 其中，ρ为基于能量平衡方程（Hall等，2011）的体重（增量）变化向超额热量摄入的转换系数。基于该方法，家庭层面未被食用的热量可通过可获得热量（千卡/人·天）与热量摄入量（千卡/人·天）的差值进行量化。1975-2013年期间，各国专属的食物可得性（千卡/人·天）数据取自联合国粮食及农业组织食物平衡表（FAO/WHO，2017）。各国平均能量消耗通过各国专属基础代谢率（BMR）与身体活动水平（PAL）的乘积计算得到。各国平均人口的综合基础代谢率（BMR）为各国人口统计特征（年龄、平均体重与性别）的函数，相关数据取自世界银行数据库（World Bank Database，2018）。身体活动水平（PAL）基于不同生活方式设定，数据取自FAO/WHO（2004）。本研究将体重增量纳入该方程，拓展了Verma等（2017）的研究框架。各国平均体重变化量（ΔBW）取自1975年、1985年、1995年、2005年及2014年报告的身体质量指数（BMI）差值，各国男女平均身高数据取自非传染性疾病风险因素协作组（NCD Risk Factor Collaboration，2016）。体重增量通过体重变化模型（Hall等，2011）转换为热量单位（千卡/人·天）。最后，假设平均体重变化带来的能量消耗变化在时间维度上均匀分布，我们可计算得到1975-2013年期间各国专属的年均每日热量摄入量。最终数据库涵盖1975-2013年期间158个国家（覆盖全球95%的总人口）的家庭日均未食用热量数据。该数据集已应用于论文"Global food waste across the income spectrum: Implications for food prices, production and resource use"（Lopez Barrera与Hertel）。