Capita Food Consumption Research Articles

Analyzing per capita food consumption patterns in net food-importing developing countries

Net food-importing developing countries, which account for 30% of countries globally, and roughly 20% of the global population, must seek to reduce their vulnerabilities in food production trade shocks. This study investigates per capita food consumption patterns in 60 net food-importing developing countries using ICP 2017 data for eight food categories. Employing the linear approximate, almost ideal demand system model, the research derives marginal shares, income and price elasticities of demand, shedding light on consumption behaviors and responsiveness to changes in income and prices. Results highlight that additional expenditure on per capita food consumption is primarily allocated to fruits, vegetables, meat, and bread and cereals, with considerable variations among countries. At the same time, minimal allocation is observed for sugar and honey, as well as fats and oils. Income elasticities indicate varying degrees of responsiveness across food categories. In contrast, own-price elasticities underscore significant sensitivity to price fluctuations, notably for beverages, milk, cheese, and eggs, meat, fats and oils, and fish and seafood. Moreover, cross-price elasticities suggest predominantly substitution relationships between pairs of food categories, on average. Additionally, a visually informative map displaying estimated marginal shares, income elasticities, and own-price elasticities for the eight food categories was created. These findings offer valuable insights for policymakers and stakeholders in understanding consumption dynamics and formulating effective strategies to address food security and welfare concerns in net food-importing developing countries.

A Study on the Measurement of Relative Poverty in Developing Countries with Large Populations

Under the goal of global poverty eradication, it has become a forward-looking research aim to establish relative poverty criteria and identify people experiencing relative poverty in countries with different demographic characteristics. This paper introduces a new method to measure the relative poverty standard, which is to use the fuzzy decision tree algorithm to objectively estimate the relative poverty standard. The advantage of this algorithm lies in (1) it not only maintaining the regression idea of measuring absolute poverty, but also emphasizing the nonlinearity when the demand is increasing, which can reflect the change in human needs. (2) It overcomes the division of the traditional method which clearly distinguishes between those experiencing poverty and those who are not by means of a subjective threshold, and it also avoids the subjectivity of the selection of multidimensional indicators. (3) It overcomes the problems of data skewness and extreme value issues that traditional methods have, and can exhibit multi-dimensional characteristics. (4) Most importantly, this method can overcome the gap problem caused by the complex population structure in developing countries with huge populations, and is more adaptable under big data conditions than traditional methods. Taking China as an example, using data from the China Household Finance Survey for validation, the validation results show that the relative poverty standard in China in 2019 can be approximately delineated as 5288.5 RMB; this result is higher than the absolute poverty standard line delineated in China in that year, lower than the relative poverty standard line measured using the proportion method, and it can satisfy the average per capita food, tobacco, and alcohol consumption expenditure of Chinese residents in that year. Thus, compared with other methods, the fuzzy decision tree algorithm can better match the identification of relative poverty in developing countries with large populations.

The effect of total factor productivity on the food security and livelihood vulnerability of farm households in Bangladesh

Food security and livelihood vulnerability are important issues for the economic sustainability of developing countries like Bangladesh. This study examines the influence of total factor productivity (TFP) on the livelihood vulnerability and food security of rice farming households in Bangladesh. Data from 1,841 rice farming households were extracted from the Bangladesh Integrated Household Survey (2015 and 2018) conducted by the International Food Policy Research Institute. Various statistical methods, such as the stochastic frontier model, principal component analysis, path analysis using structural equation modeling, and multivariate regression, were employed to analyze the data. The study utilizes a multivariate modeling approach that combines the stochastic frontier model to determine TFP and sophisticated methodologies to estimate the livelihood vulnerability index (LVI) and women’s empowerment in agriculture index (WEAI). The LVI, household dietary diversity Score (HDDS), TFP, and WEAI scores were 0.454, 10.72, 0.703, and 0.717, respectively. The results indicate a significant relationship between TFP and both LVI and HDDS. Higher TFP is associated with lower LVI and higher HDDS among rice farming households, suggesting that improving TFP can enhance food security and reduce vulnerability. The multivariate regression analysis reveals that TFP, household wealth index, women’s empowerment in agriculture index, per capita food expenditure, household level welfare, and household size have a positive significant impact on HDDS, while TFP is negatively associated with LVI, per capita food expenditure and household size. The findings underscore the importance of increasing TFP to improve food security, reduce livelihood vulnerability, and achieve sustainable development goals in countries like Bangladesh. Higher TFP yields positive outcomes regarding household dietary diversity and livelihood vulnerability, highlighting the need for agricultural policies that prioritize TFP enhancement. Policymakers and professionals can use these findings as a roadmap to implement advanced agricultural policies to achieve food security and reduce livelihood vulnerability. Improving household dietary diversity and reducing livelihood vulnerability can be achieved by focusing on increasing TFP, enhancing household wealth, women’s empowerment, per capita food expenditure, household welfare, and household size. Therefore, increasing TFP should be considered in the design of policies aiming to achieve SDGs Goal 2.

Life cycle assessment of food consumption in different cities: Analysis of socioeconomic level and environmental hotspots

This study presents a comprehensive life cycle assessment of the environmental impacts of dietary patterns in different cities, focusing on the correlation between food consumption and environmental impact. The functional unit was the food required to meet one person's yearly needs (1 Inh/year). To determine the quantity and type of food consumed, as well as the income level of the residents, 523 surveys were conducted in households in four cities in Chile (Iquique, Santiago, Temuco, and Coyhaique). Survey data were complemented with secondary information from national statistics and the Ecoinvent database. The environmental impact assessment was carried out using SimaPro, selecting the categories of global warming, terrestrial acidification, terrestrial ecotoxicity, freshwater ecotoxicity, freshwater eutrophication, land use, and fossil resource scarcity. The results show that higher-income households generate greater environmental impacts attributed to higher per capita food consumption. In the global warming category, the environmental impact can range from 1.08 kg CO2 eq/inh/year for the first quintile to 2.15 kg CO2 eq/inh/year for the fifth quintile in Santiago. In this category, the impacts in the highest quintiles can be up to 2.2 times greater than those in the lowest quintiles. Similarly, in acidification, this difference can reach 2.3 times. In the freshwater eutrophication category, the highest-income quintiles can double the environmental impacts compared to the lowest (I and II), mainly due to higher consumption of red meat and dairy products. The food production stage was the environmental hotspot across all evaluated impact categories, accounting for 45%–60% of the impacts in global warming, terrestrial ecotoxicity, and fossil resource scarcity; 74%–78% in terrestrial acidification, freshwater eutrophication, and land use; and 68%–71% in freshwater ecotoxicity. Meat was pinpointed as the primary environmental hotspot in global warming (44%), terrestrial acidification (56%), freshwater eutrophication (50%), land use (35%), and fossil resource scarcity (30%). Conversely, cereals are the primary environmental hotspot in terrestrial ecotoxicity (30%) and vegetables in freshwater ecotoxicity (18%). The geographical location of cities also influenced the environmental impacts of food consumption, primarily due to the types of available foods in regions near each city. Food availability conditions, diets, and quantities consumed, thus influencing environmental impacts. Finally, household incomes, the geographical location of cities, and the food production systems in each city determine the environmental impacts of food consumption. Different configurations of these variables create unique environmental impact profiles for each city. Despite this, typical environmental hotspots in food consumption were identified across all cities, enabling the implementation of strategies to minimize environmental impacts on a national scale. Thus, circular economy strategies linked to food production systems, as well as food loss and waste, could significantly reduce environmental impacts, presenting an intriguing opportunity for future research in this field.

Pengaruh Pengeluaran Pemerintah Sektor Kesehatan, Pengeluaran Makanan Perkapita, dan Rasio Ketergantungan Terhadap Indeks Pembangunan Manusia di Kabupaten Provinsi Lampung

The province of Lampung, strategically located on the island of Sumatra, is facing challenges in improving human development that have yet to meet desired expectations. Data indicates that the Human Development Index (HDI) there is still below the national average and that of Sumatra as a whole. The study was conducted in the 13 districts of Lampung Province during the period 2017-2022 using panel data regression with a Random Effect Model (REM). This research aims to investigate the Human Development Index (HDI) in the districts of Lampung Province, focusing on the dimensions of economics, education, and health. The objective of this study is to analyze the impact of government expenditure on the health sector, dependency ratio, and per capita food expenditure on the HDI. The results show that 1) Government expenditure in the health sector significantly contributes positively to improving the HDI in Lampung Province. Conversely, 2) per capita food expenditure has a significant negative impact, as does 3) the dependency ratio, which also significantly affects the HDI but in a negative direction. Therefore, further attention to these factors is expected to enhance human development in Lampung Province. This study provides deep insights into the challenges and opportunities faced by Lampung District in improving the welfare of its people, and it offers policy recommendations that can lead to inclusive and sustainable development in the future.

The Effectiveness of Conditional Cash Transfer Program: A Case of Rural and Urban Beneficiaries in Philippines

This paper analyzes the effectiveness of the Conditional Cash Transfer (CCT) program in the Philippines in terms of its effect on conditionality goods as reflected by food, health, and education expenditures of households from rural and urban areas that benefitted the program. The CCT program in the Philippines is known as Pantawid Pamilyang Pilipino Program (4Ps) that seeks to address the problem on poverty by improving the socioeconomic status of poor households through targeted investments in health and education. This study used the Propensity Score Matching methodology in estimating the average treatment effect on the treated to capture the effect of CCT on conditionality goods. The study finds that CCT has a significant effect on education for household beneficiaries in rural areas and has improved the quality of food consumed by household beneficiaries in urban areas. Also, a decreased in the per capita total expenditure and per capita food expenditure of the household beneficiaries is revealed in urban areas driven by their improved saving behavior. Thus, the CCT program, at some point, is effective in meeting its short-term goal, but it must be more targeted in order to improve its impact on other conditionality goods.

Metode Geographically Weighted Panel Regression (GWPR) Untuk Menganalisis Faktor Yang Mempengaruhi Kemiskinan Di Provinsi Sumatera Utara

This study aims to analyze the factors of population density, life expectancy, years of schooling, open unemployment rate, per capita monthly food expenditure, population with health complaints, economic growth, human development index, households with access to proper drinking water and households with access to proper sanitation on the percentage of poverty in North Sumatra province. This research is based on secondary data available at the North Sumatra Central Bureau of Statistics in 2017-2021. The factor analysis used in this study is Geographically Weighted Panel Regression (GWPR) which is a combination of the Geographically Weighted Regression (GWR) method with the panel data regression method. The results of the research analysis show that simultaneously the factors of population density, life expectancy, open unemployment rate, monthly per capita food expenditure, population with health complaints, households with access to proper drinking water have no significant effect. If tested simultaneously, only the factor of households having access to proper sanitation has a significant effect on the percentage of poverty. However, partially, these factors have a significant effect on the percentage of poverty.

SDG 2 – ending hunger: the effect of Nigeria’s land titling on production output and food security of farming households

Achieving zero hunger is intricately linked to sustainable agricultural production and the workings of a farming system. With land being the most important resource in smallholder agriculture in developing countries; including Nigeria; the effect of legal land ownership is a sine qua non for the process of achieving zero hunger in Nigeria. This study examined Nigeria’s attempt at making agricultural land both accessible and utilizable for smallholders in Nigeria through the Presidential Technical Steering Committee on Land Reforms in 2009. The aim was to explore the extent to which land ownership had become legalized; so that it had positive investment incentives for smallholder farmers to improve their investment portfolio on their holdings. A secondary dataset of 4,032 respondents obtained from the Living Standard Survey Integrated Survey on Agriculture (LSMS/ISA) of the 2018/2019 season, was used for the study. Data analysis included descriptive statistics and a 2-stage least square model. The apriori being that legal land ownership provided a perception of security that would enhance farm-level investment; which would therefore increase production output and hence food security. The findings revealed that although land titling was low (~12%) within the agricultural system; its return on production output was highly significant (5.3; p < 0.05). The possession of land title would also increase per capita food consumption expenditure (0.35; p < 0.05) among the farming households. On average, households with access to land titles had a significantly higher (at p < 0.01) food expenditure (N9, 868.00) than those without land titles (N6171.72). Other farm-level investment variables such as credit use, and mechanization through tractor use were significant in improving food security amidst the security presented by possession of land title. Thus, expediting the implementation and coverage of formal land registration and titling may be a first step to contributing meaningfully to the food security drive of the SDGs in Nigeria.

Reducing environmental footprints and promoting health: Optimizing dietary structure in China

This paper aims to identify a dietary structure in China that can enhance people's health while significantly reducing environmental footprints. Aligned with the United Nations Sustainable Development Goals, this study incorporates four essential types of footprints associated with food consumption: land, water, CO2 and CH4 footprints, with particular emphasis on the often-overlooked CH4 footprint, whose warming impact is 25 times greater than that of CO2. Employing the structural decomposition analysis method, we find that, the dietary structure had the most contribution in reducing environmental footprints than those of population size, urbanization rate, and per capita food consumption volume in China after 2018. To assess the environmental impacts of different dietary structures, we set three scenarios: the current dietary structure S0, a developing dietary structure S1, and an optimal dietary structure S2 designed through an optimal model based on the dietary guidelines for Chinese residents (DGCR) 2022. We measure the environmental footprints resulting from residents' dietary structure across the three scenarios for the years 2025 and 2030. The optimal dietary structure in S2, which aligns closely with DGCR 2022, features meat and poultry consumption at 3.59 % and 3.26 % of per capita food consumption volume in 2025 and 2030, cereal and tubers at 20.48 % and 21.20 % and milk and dairy products at 24.47 % and 24.40 % in 2025 and 2030. Comparatively, S2 demonstrates significant reductions in environmental footprints when compared to S0. Specifically, the land, water, CO2 and CH4 footprints caused by residents' food consumption in S2 would drop by 10.50 %, 19.01 %, 14.32 %, 14.32 % respectively in 2025, and by 11.14 %, 19.85 %, 15.27 %, 15.27 % in 2030, respectively. Importantly, the reduced environmental footprints achieved in S2 are >1.8 times greater than those in S1. The findings highlight the potential of the dietary structure in S2 to improve residents' health while concurrently reducing environmental footprints. These results offer a basis for designing effective policies that guide both urban and rural Chinese residents towards healthier and environmentally sustainable dietary choices.

Food Insecurity Transition Among Agricultural Households In Nigeria

ABSTRACT: Hunger continues to be on the increase and food crises remain a developmental challenge. The incidence of food insecurity in the country has heightened in recent years due to unprecedented natural hazards, economic shocks and climate change, which have eroded livelihoods and worsened the country’s performance in food security-related indices. We therefore used the panel data from Nigeria to examine the food insecurity transition among agricultural households. The data covered four rounds. The food insecurity status of agricultural households was estimated using the Foster-Greer-Thorbecke measure. We explained the interaction among the states of food security of agricultural households across different periods using the food insecurity transition matrix. The determinants of food insecurity were explored using the dynamic probit model. The model addressed unobserved heterogeneity, state dependency, and serial correlation arising from the data and model. Findings revealed that the mean food expenditure increased across the period. Similarly, mean per capita food expenditure also increased across periods except for the 2012/2013 period where it dropped slightly. We observed a rising incidence of food insecurity across the period from 44.1% in 2010/2011 to 53.4% in 2018/2019 representing a 21.1% increase in food insecurity incidence. Widening inequality exists even among the food insecure. Our findings revealed that 87.6% of households are transitorily food insecure, 5.5% are chronically food insecure and 7% are food secured. The significant factors driving food insecurity across the period were the area of land under cultivation, the fall in the price of outputs, and the increase in the price of major food items. Coping strategies employed were eating less preferred foods, restriction in diversity of foods eaten, limiting food portions, and minimizing the frequency of meal consumption. It is therefore important that the government encourage the adoption of yield-enhancing technologies to ensure household food security. Rising prices of major food items and fall in output price gives a cause for concern over the macroeconomic environment in the country, which fuels rising food prices. Policymakers should exercise caution when implementing exchange rate policies that may affect food and output prices, given the impact they have on the livelihood and household security of smallholders.

Agri-food evolution and carbon emissions in Chinese residential consumption: A life cycle analysis of urban-rural disparities and socioeconomic influences

At present, residential food consumption is not only the main driver of global energy expenditure but also a crucial factor shaping the development of the agri-food system. It is guided by the macro-food paradigm and serves as a cornerstone for ensuring comprehensive food security. This study examines both direct and indirect carbon emissions stemming from urban and rural food consumption in China between 2000 and 2021, employing a life cycle perspective. The research also delves into the associated factors influencing these emissions. Through the utilization of the LMDI (Logarithmic Mean Divisia Index) decomposition method, the study estimates the contributory significance of total carbon emissions attributed to residents' food consumption. Furthermore, the investigation undertakes an in-depth analysis of the disparities in the compositional makeup of food consumption among urban and rural populations, along with an exploration of the pertinent driving forces behind these distinctions. The study's outcomes indicate that, overall, there is a reduction in per capita direct carbon emissions, accompanied by a corresponding rise in per capita indirect carbon emissions. Relative to the index of plant-based food consumption, both the carbon emissions associated with, and the proportion of animal-based food consumption exhibited an ascending trend. The carbon dioxide (CO2) emissions stemming from the dietary patterns of urban inhabitants notably surpass those attributed to their rural counterparts, with a discernible and widening disparity between the two cohorts. Within the context of the life cycle analysis, consumption and production serve as pivotal components of the intricate network of indirect carbon emissions. Notably, the proportion of carbon emissions attributed to urban residents surpasses that of their rural counterparts in both the domains of food production and the subsequent phases of processing and transportation. Owing to the irrational configuration of cooking energy utilization among rural inhabitants, direct carbon emissions within the food consumption continuum, as well as carbon emissions derived from cooking energy usage, surpass corresponding metrics among urban dwellers. This discrepancy can be attributed to the unsystematic nature of the cooking energy framework prevalent in rural contexts. Population growth, per capita food consumption and changes in the structure of food consumption are important factors driving the growth of total food carbon emissions. Within this context, an augmentation in the intake of vegetables, alongside desiccated fruits, and vegetables, exhibits the potential to notably curtail carbon emissions emanating from the dietary practices of rural denizens. Similarly, an elevation in egg consumption emerges as a key determinant in substantially mitigating the carbon emissions stemming from the dietary patterns observed among urban inhabitants. The carbon emissions originating from both animal-based and plant-based food consumption among urban and rural populations are substantially influenced by the intricate interplay of factors such as the demographic composition and the per capita disposable income within both these strata of society.

Evaluating the impact of improved crop varieties in the Sahelian farming systems of Niger

Most people in Niger still rely heavily on agriculture as a source of income. However, low productivity, climate change, soil infertility, pests, and diseases are challenges faced by this sector. As a result, the nation suffers from a severe problem of food insecurity. Many investigations indicate that adopting improved crop varieties(ICVs) increases agricultural productivity. Using information gathered from 1784 farmers, this study assesses the effects of adopting improved crop varieties (ICVs) on household welfare. To analyze the data, we employ endogenous switching regression (ESR) and inverse probability-weighted regression adjustment (IPWRA) techniques. The analysis shows that the ICVs adoption significantly improves household income and food access in Niger's Sahelian region. The ESR model's average treatment effects estimate shows that the ICVs adoption raised per capita income, food expenditure, and household dietary diversity score (HDDS) by 75 %, 1.81 %, and 36.49 %, respectively. The IPWRA model yields similar results.Therefore we conclude that adopting ICVs has substantial dynamic benefits that improve household welfare in Sahel Niger by increasing their probability of escaping poverty, food insecurity, and malnutrition. The farmer's knowledge of improved crop varieties significantly influenced favorably the decision to adopt, suggesting that intensifying dissemination and encouraging the promotion of drought-tolerant crop varieties among farmers, development agencies, researchers, and policymakers could be a crucial plan of action to combat poverty, food insecurity, and malnutrition in the Sahelian region.

A Comparison Small Area Estimation for Skewed Data with EBLUP and Hierarchical Bayes Approaching using Rao-Yu Model

Small Area Estimation (SAE) is a method based on modeling for estimating small area parameters, that applies the Linear Mixed Model (LMM) as its basic. It is conventionally solved with Empirical Best Linear Unbiased Prediction (EBLUP). The main requirement for LMM to produce high precision estimates is normally distributed for its sampling error. However, the researching data namely per capita food expenditure for food crop farmers’ households in Southeast Sulawesi Province has been positively skewed. Applying EBLUP for positively skewed data will produce less accurate estimates. Meanwhile, doing a transformation process will potentially produce biased estimates. The Hierarchical Bayes (HB) approaching often known as Full Bayesian is more flexible regarding normality assumptions and can determine distribution based on data. Because this research will carry out estimates at the district/city level throughout Southeast Sulawesi Province, totaling 17 regions, the efficiency of the estimates can be increased by using the SAE Rao-Yu model which includes area and time random effects. For this reason, this study compares SAE modeling with the EBLUP and HB approaches which are assumed to follow normal, log-normal, and skew-normal distributions. By comparing the Relative Root Mean Square Error (RRMSE), Deviance Information Criterion (DIC), and Coefficient of Variation (CV) values, it is concluded that estimates from the log-normal and skew-normal SAE HB models are more efficient than the SAE EBLUP and normal HB models. However, the SAE estimate that is closer to the direct estimation results is the skew-normal SAE HB.

The impact of adoption of milk safety practices on food and nutrition security: Evidence from smallholder dairy farmers in Ethiopia

Despite the progress observed over the past decades, food and nutritional insecurity remain the prominent challenges in Ethiopia. In this respect, improved farming practices and productivity-enhancing agricultural technologies have been identified as pathways out of these problems; these technologies are the priority agenda of the government policy in Ethiopia. Nonetheless, the impact of the adoption of milk safety practices on dairy farmers’ food and nutrition security has not yet been addressed, especially at the smallholder farmers’ level. The aim of this study was to evaluate the impact of the adoption of milk safety practices on dairy farmers’ food and nutrition security in Ethiopia, using primary data collected from 410 dairy farmers. Generalized propensity score matching was used to evaluate the heterogeneous impact of the adoption of milk safety practices on the household food and nutrition security indicators (per capita food consumption expenditure and food consumption score). The findings reveal that the adoption of milk safety practices had a moderate impact on food consumption expenditure but had no significant impact on food consumption score. An ordered probit endogenous switching regression was also used to account for unobserved bias and check the robustness of the generalized propensity score estimates. Accordingly, the results are similar to the generalized propensity score estimates, and unobserved bias was not a problem. In general, the impact of adoption of milk safety practices on food and nutrition security of smallholder dairy farmers is moderate in Ethiopia. This might be because of the high compliance costs with the adoption of milk safety practices and the lack of quality-based pricing systems. Hence, creating an enabling environment, which in turn, encourages the adoption of milk safety practices would help improve positive effects of the adoption of milk safety practices on food and nutritional security.

Investigating and Quantifying Food Insecurity in Nigeria: A Systematic Review

Given the recent increase in the number of Nigerians estimated to be at risk of food insecurity, it is crucial to explore the array of tools used to quantify food insecurity (FI). This exploration will help determine the prevalence and severity of FI in Nigeria. This review explored the scope of FI research carried out in Nigeria to examine how the design was quantified. A systematic review was performed to compile the accessible Nigerian studies. Seventy-nine studies were reviewed. Eighteen used the Household Food Insecurity Access Scale module (HFIAS) to investigate FI status; thirteen used the recommended daily calorie requirement approach; twelve employed the Household Food Security Survey Module (HFSSM); ten used the food insecurity index (through household per capita food expenditure); seven used the Food Insecurity Experienced Scale (FIES); two used the Food Consumption Score (FCS); and the others employed less standardized or thorough approaches. Different prevalence levels and gravities of FI in the Nigerian populations were documented. The prevalence of FI varied from 12% to 100%, based on the instrument and demography being studied. In accordance with the findings of this review, the authors propose standardization of the FI instrument and highlight the need for a measurement tool that would be appropriate for the Nigerian setting. This will enable researchers to attain a comprehensive knowledge of the occurrence rate of FI in Nigeria, leading to improved food- and nutrition-sensitive policy development.

MAIN PROBLEMS OF FOOD PROCESSING ENTERPRISES AND WAYS TO SOLVE THEM

Ensuring food safety has become one of the priority directions on the world agenda. This issue has become particularly sensitive as a result of the epidemiological situation related to the COVID-19 pandemic, which has clearly shown that it remains the main means of maintaining stability in emergency situations and the continuous supply of quality and safe food to the population. The stability and security of the food system directly affects the socio-economic factors necessary for human survival. The purpose of the study is to present the main mechanisms of its development and effective organization , conducting a scientific study of the actual problems of food processing enterprises of Kazakhstan . Methods: statistical-economic, analytical, comparative analysis methods were used to analyze the current state of development of processing enterprises in our country . In order to summarize the obtained results, analyze, systematize, monographic methods were used. Results: the article analyzed the prices of socially important food products in Kazakhstan in 2016-2022, according to the types of socially important products in 2016-2022. differences between per capita production volume and per capita food consumption rate were studied. In addition, possible ways to solve the food security problem of the country in the coming years were considered. Conclusions: In order to sufficiently provide the population with food of social importance, taking into account the level of specialization of the regions, it is important to strengthen the work of processing enterprises with the support of the state.

WHAT FACTORS INFLUENCE HOUSEHOLDS’ EXPENDITURE ON FISH? EVIDENCE FROM URBAN MALAWI

The purpose of this study was to find the drivers of fish expenditure in urban Malawi using Blantyre as a case study. Previous demand studies on the fisheries sector in Malawi have concentrated on the determinants of consumer choices and demand for tilapia fish thereby making information regarding households’ general consumption pattern of fish scanty. Results show that statistically significant negative determinants of per capita fish expenditure include the price of vegetables, the price of rice, the number of adults in the household, and the household’s per capita food expenditure away from home, while, the price index of food, price of maize, the predicted value of food, and household’s income level are the statistically significant positive drivers of per capita fish expenditure. General policy implications arising from this study are that policymakers need to ensure that households have higher incomes and that food prices are kept low.

Healthy Eating for All? The Challenge of Adhering to Dietary Guidelines for Low-Income Groups in China.

The Chinese Dietary Guidelines propose a balanced diet for healthy living, but the affordability of this diet needs to be considered, especially for low-income households. To investigate the affordability of a healthy diet, this study analyzes the daily retail prices of 46 food items in 36 Chinese cities from 2016 to 2021. This study compares expenditure, diet composition, and nutritional status in two scenarios aligned with the guidelines. The results show that the mean minimum cost of a balanced diet exceeds the current per capita food expenditure for at least 182.85 million urban households. This suggests that low-income people would need to increase their expenditure by at least 20-121% to achieve the recommended diets. This study also identifies affordable and nutrient-dense foods such as standard flour, eggs, black beans, and cabbage, which policymakers should focus on when monitoring food prices. The findings recommend a combination of social and food system policies to reduce prices and make healthy diets accessible. This study identifies the gaps in the Chinese Dietary Guidelines for ensuring accessibility for vulnerable groups and provides a template for policymakers and researchers to track diet affordability using available food price data in China, contributing to China's 2030 Health Plan and the UN's Sustainable Development Goals.

Validity of Food insecurity experience scale (FIES) for use in rural Bangladesh and prevalence and determinants of household food insecurity: An analysis of data from Bangladesh integrated household survey (BIHS) 2018-2019

“Access” dimension of Food insecurity (FI) is directly measured by the Food Insecurity Experience Scale (FIES). The current study assessed the appropriateness of the FIES for measuring FI in rural Bangladesh, followed by an assessment of FI prevalence and its correlates utilizing Bangladesh Integrated Household Survey (BIHS) data. The internal validity of the FIES and the prevalence of FI were investigated using the Rasch modeling approach. We utilized equating procedure to calibrate the study’s result to the global FIES reference scale and determined FI prevalence rates that were comparable across countries. The external validity of the FIES was evaluated by examining its association with other FI measures using Spearman’s rho correlation analysis. With an overall Rasch reliability of 0.84, the FIES met the Rasch model assumptions of conditional independence and equal discrimination, and as well as the fit statistics standards for all eight items. Infit statistics were within the allowed limit for all FIES items indicating good internal validity. However, we noted a high outfit (>2) for the “unable to eat healthy and nutritious food” item indicating the presence of some unusual response patterns. Our analysis found no significant (>0.4) correlation between FIES items. We also found a significant correlation between FIES and other FI proxies, e.g., the Household hunger scale (HHS), Food consumption score (FCS), and Household dietary diversity score (HDDS). Overall, the prevalence of moderate or severe FI was 18.92% in rural Bangladesh. Geographic areas, access to electricity, household ownership, access to sanitation, livestock ownership, family size, education level, and monthly per capita food expenditure significantly explained the variation in FI. Our analyses suggest that the FIES is internally and externally valid for FI measurement in rural Bangladesh. However, FIES questions may need to be reordered to more accurately evaluate lower levels of FI, and the item “unable to eat healthy and nutritious food” may need cognitive testing.

Weather shocks, livelihood diversification, and household food security: Empirical evidence from rural Bangladesh

AbstractExtreme weather events have occurred more frequently because of global climate change. For farmers, diversification, including crop and income diversification, is one of the most effective strategies to improve rural livelihoods by managing risk and coping with weather shocks. We investigate the empirical linkages among weather shocks, livelihood diversification, and household food security, exploiting three waves of nationally representative rural household panel data merged with granular weather data in Bangladesh. Using instrumental variable methods to control for the possible endogeneity of livelihood diversification decisions, we find that weather shocks are significant drivers of crop and income diversification. Moreover, both crop and income diversification are found to impact per capita food expenditure, while their effects on household dietary diversity are not robust. In particular, the distributional effects of income diversification are uniformly positive and significant for all quantiles of a per capita food expenditure distribution but are more sizable for the richest households. The findings, therefore, highlight the unequal effect of livelihood diversification within the context of rural South Asia, suggesting the need for diversification interventions targeting rural low‐income groups with the goal of improving socioeconomic status, institutional conditions, and infrastructure.