Household Food waste in Delhi, India
Description
The data pertains to a physical waste survey undertaken in Urban areas in South Delhi District, Delhi, India. The physical waste survey was undertaken to quantify avoidable food waste (AFW) and explore and understand the drivers of AFW at the household level. Household waste was collected for seven consecutive days from each of the 56 households. Subsequently, one participant from each of the 17 high AFW-generating households was engaged in a semi-structured interview to uncover the drivers of household AFW. A mixed methods approach was employed to understand the phenomenon of AFW in urban households. Descriptive and inferential analysis was undertaken on the physical waste data. The interview data was analyzed through thematic analysis. The following data files are attached 1. Physical waste survey data 2. Food categories: The FW items were categorized into 14 food categories. 3. Participant and household data (Anonymized) 4. Semi-structured interview guide/protocol
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Steps to reproduce
For the physical waste survey, household waste, including kitchen waste, was collected from 56 households. The survey was held in 10 phases. During these phases, the number of participating households ranged from two to nine households. Each household provided the waste for seven consecutive days, from Tuesday to Monday. The waste generated on Monday was collected on Tuesday. Likewise, the waste generated on Sunday was collected on Monday. The participant households were given waste bags for keeping their household waste. Following collection, the household waste was sorted into avoidable food waste (AFW), unavoidable FW (UAFW), and miscellaneous waste, including paper waste, cardboard waste, plastic waste, and glass waste. However, the current data focuses on AFW and UAFW. Subsequently, interviews were undertaken with the participants responsible for food-related activities in their households to unearth drivers underlying household food waste behaviors. SPSS was used for descriptive and inferential analysis of survey data. NVIVO was used for reflexive thematic analysis of the interview data.