This cross-sectional study was conducted in Bogor Regency, Indonesia, from September to October 2022. The 2020 Indonesian Population Census revealed that Java Island holds the highest population share in Indonesia at 56.1%, with nearly one-third (31.8%) residing in West Java [13], making it the largest consumer of food in Indonesia. Within West Java, Bogor Regency has the largest population, totaling 5,473,476 people.
2.2 Sample size and sampling techniqueThe sample size was determined following the Indonesian National Standard (SNI) 19–3964-1994 for the collection and measurement of samples of urban waste generation and composition. The sample size considered the population size, number of households, and average number of household members in the two selected sub-districts (Cibinong and Sukajaya Sub-district). Sample size formulation:
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Note: K = Number of household samples (household); S = Number of samples (people); N = Number of family members Cd = Housing coefficient (metropolitan and big cities = 1); Ps = Population (people).
The total population in Sukajaya Sub-district is 66,922 people, and in Cibinong Sub-district, it is 363,424 people [13], with an average of 4.03 people per household in Bogor Regency, [14]. Therefore, the total sample size for this study was 215 households, which were collected from 24 neighborhood associations or the smallest administrative units in Bogor Regency (Rukun Tetangga/RT). Multistage random sampling was conducted to collect data from the two sub-districts and 24 RTs, which were selected from a total of 102 RTs in the study location.
2.3 Household food waste measurementHousehold food waste was measured using two methods: Waste Composition Analysis (WCA) for solid FW (food) and a diary for liquid FW (drink). The WCA method was used following the SNI 19–3964-1994 to collect and measure samples of urban waste generation and composition. FW was collected for eight consecutive days for each household, with FW from the home trash bin being sorted and weighed daily according to the food type. FW collection was carried out every morning until the afternoon by waste collectors. Each household was supplied with 8 pre-coded plastic trash bags.
For liquid waste, measurements were conducted using a diary method for seven consecutive days, following The Waste and Resources Action Program (WRAP) guidelines for measuring household food and drink waste disposed of down the drain [15]. The recording completed independently by one of the family members at home who is responsible for food preparation (typically the housewife). The diary form and recording guidelines were provided one day in advance, with recording procedures directly explained by the study coordinators to participants (housewives). Diaries were then collected on the final day of food waste collection.
Total FW is the sum of food and drink waste and is divided into two types: edible and inedible FW. Edible FW is food still fit for consumption, such as meat cuts, bread crumbs, apples, etc. Meanwhile, inedible FW is food that is not fit for consumption or is not consumed under normal conditions, such as fish bones, eggshells, fruit peels, etc.
2.4 Food security measurementHousehold food security was assessed by examining the dimension of food access, measured using the Food Insecurity Experience Scale (FIES) questionnaire. Additionally, household income and the proportion of food expenditure were considered as confounding factors in this study. Household income (per capita per month) was categorized based on its data distribution: quartile 1 (< IDR 400,000), quartile 2 (IDR 400,000 to less than IDR 875,000), quartile 3 (IDR 875,000 to less than IDR 1,375,000), and quartile 4 (> IDR 1,375,000).
The FIES is an instrument for measuring food security, which serves as a proxy for food access and was developed by the FAO [16]. Data was collected using the FIES with a 30-day reference period, assessing household food insecurity experienced in the past 30 days. The FIES consists of three domains that define the food insecurity construct: uncertainty or worry about food sufficiency, inadequate food quality, and inadequate food quantity. These domains were described using eight questions related to the experience of hunger or food insecurity felt by family members due to a lack of money or other resources.
The eight questions were framed with a Yes or No response and addressed the following experiences: (1) worrying about not having enough food; (2) Not being able to eat healthy and nutritious food; (3) eating only a few types of food; (4) not eating breakfast, lunch, or dinner (skipping meals); (5) eating less than they should; (6) running out of food; (7) feeling hungry but not eating; and (8) not eating all day.
There were three levels of food insecurity severity: mild, moderate, and severe. Households that experienced uncertainty or worry about food sufficiency and inadequate food quality were classified as mildly food insecure (answered "yes" to questions 1–3). Households experiencing inadequate food quantity were classified as moderately food insecure (answered yes to questions 4–6) and finally households experiencing hunger were classified as severely food insecure (answered yes to questions 7–8) [16]. The prevalence of food insecurity was determined based on moderate and severe food insecurity.
Data collection on household characteristics (household size, expenditure, and the husband’s and wife’s occupation and education level) was conducted using a structured questionnaire. Interviews were conducted in participants' homes by trained interviewers who had graduated from nutrition and public health programs. The training of interviewers was carried out prior to the data collection.
2.5 Statistical analysisThe association between household food security status and household characteristics was analyzed using the Maximum Likelihood Ratio Chi-Square test due to the unmet expected cell requirements. Spearman's Rank Test was employed to examine the association between household income, food expenditure proportion, and household food waste. Additionally, the association between household food security status and food waste was evaluated using Kendall Tau-b. Ordinal logistic regression was conducted to further explore the association between household food security status and food waste while adjusting for household characteristics, income, and the proportion of food expenditure. The threshold for statistical significance was set at α = 0.05. All inferential analyses were performed using IBM SPSS version 21.
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