A cross-sectional study conducted in rural Uganda has identified that households’ perceived minimum necessary income is a stronger predictor of food security status than their actual reported income. The research, published in Agriculture & Food Security, surveyed 173 households in Sembabule District to examine the determinants of household food security. By combining standardized quantitative indicators with open-ended qualitative data, the study reveals that subjective assessments of financial needs and specific household challenges offer greater explanatory power for food security outcomes than many traditional socioeconomic variables.
The study was designed to address a gap in existing research, which often relies on isolated or context-specific indicators that limit comparability across studies. The researchers employed two widely recognized metrics: the Food Consumption Score (FCS) and the Months of Adequate Household Food Provisioning (MAHFP). The FCS measures short-term dietary diversity and consumption frequency over a seven-day recall period, while the MAHFP captures long-term seasonal food availability over a twelve-month period. This dual-indicator approach allows for a more comprehensive assessment of both immediate consumption and year-round resilience.
Data collection took place in two phases between February and October 2022. The initial phase involved structured questionnaires and open-ended interviews to gather information on household characteristics, socioeconomic status, and self-reported challenges. The second phase focused specifically on calculating the FCS and MAHFP scores. The sample consisted of households with children attending a local primary school in Kenziga village, representing a non-probability convenience sample. This method was selected to facilitate access to a diverse cross-section of rural families while ensuring feasibility and trust in the data collection process.
The two indicators produced contrasting classifications of food security among the participating households. According to the FCS, 41.5% of households were classified as food insecure, whereas the MAHFP indicated that 68.9% were food insecure. This divergence highlights the different dimensions of food security captured by each metric. The FCS reflects recent consumption patterns, which may be influenced by the timing of data collection shortly after the harvest season. In contrast, the MAHFP summarizes the cumulative effects of food shortages experienced throughout the agricultural year, providing a broader view of chronic deficits.
Binary logistic regression models were used to identify the key determinants of food security for each indicator. The models identified perceived minimum necessary income as a significant predictor, rather than actual income. For the FCS-based model, each unit increase in perceived necessary income was associated with a 32% increase in the odds of being classified as food secure. This finding suggests that in rural contexts where income sources are often informal or irregular, subjective estimations of financial strain may offer a clearer sense of economic pressure than objective income figures.
Variables derived from open-ended questions emerged as the most influential predictors in the models. Complaints about hunger, lack of clothing, and insufficient farmland were strongly associated with food insecurity. Specifically, households reporting a lack of clothing had their odds of being food secure reduced by approximately 56%, while those citing insufficient farmland saw a 61% reduction in their odds of food security. These qualitative variables consistently showed stronger explanatory power than many traditional socioeconomic factors, underscoring the value of integrating perception-based data into quantitative analysis.
Interestingly, concerns about lack of access to drinking water were inversely related to food insecurity in the FCS model, showing 2.76 times higher odds of being food secure. This counterintuitive result may reflect higher expectations or awareness among better-off households, rather than actual differences in water access. Similarly, in the MAHFP model, complaints related to poverty or financial difficulties were positively associated with food security. These patterns suggest that self-reported complaints may capture perceived gaps or shifting expectations rather than absolute material deficits.
The study also found that larger household sizes were associated with greater food security, contrary to the common assumption that larger households face greater consumption demands. Food-secure households had an average of 7.89 members, compared to 6.73 in food-insecure households. This may be attributed to labor-sharing dynamics, where more working-age members contribute to cultivation and income-generating activities, enhancing household resilience. Additionally, food-secure households were more likely to own larger land areas and engage in the sale of agricultural surplus, which contributes to both food availability and economic access.
The regression models demonstrated adequate goodness of fit and discriminatory capacity. The FCS model had an area under the ROC curve of 0.762, indicating good ability to distinguish between food-secure and food-insecure households. The MAHFP model showed an AUC of 0.715, reflecting acceptable discriminatory capacity. Internal validation through repeated random subsampling confirmed the stability of both models, with limited overfitting. These results support the robustness of the identified predictors in this specific rural context.
Limitations of the study include the non-probability sampling approach, which may introduce selection bias, and the cross-sectional nature of the data, which identifies statistical associations rather than causal relationships. The sample size, while sufficient for the models used, may limit the statistical power to detect all potential predictors. Furthermore, the reliance on self-reported data for both objective and subjective variables requires careful interpretation, particularly regarding the inverse relationship between water complaints and food security.
The findings highlight the multidimensional nature of food insecurity and the importance of combining standardized indicators with open-ended, perception-based data. Improving access to cultivable land and safe water, as well as integrating local perspectives into rural development strategies, may enhance the effectiveness of food security interventions. The strong predictive power of perceived needs suggests that policies should go beyond income generation to include financial literacy and resource management support.
This study supports the use of participatory approaches that give voice to lived experiences and help uncover priority needs often overlooked in conventional assessments. By identifying perceived needs as key predictors, the research offers a new perspective for policymakers and practitioners aiming to design more effective and contextually relevant food security interventions in rural Sub-Saharan Africa.
The study was conducted in Sembabule District, a predominantly rural area in central Uganda where agricultural systems are largely rain-fed and rely on low-input practices. This region, part of Uganda’s dry corridor, is characterized by limited crop diversification and a heavy dependence on maize, which serves as the primary dietary staple. Such reliance exposes communities to recurrent food crises during periods of drought, a vulnerability that was particularly acute during the 2022 agricultural season. According to the World Meteorological Organization, both the March–May and October–December rainy seasons recorded below-average precipitation, contributing to the most prolonged drought in over four decades. This climatic context is critical for interpreting the study’s findings, as the timing of data collection shortly after the harvest may have temporarily improved short-term food availability, potentially softening the impact of the drought on immediate consumption metrics.
Water access in the study area is a significant structural constraint, with 90.8% of surveyed households collecting water from unprotected surface ponds or waterholes. The average daily time spent on this task was 70 minutes, a substantial labour burden that contrasts sharply with national statistics. Uganda Bureau of Statistics data indicate that most agricultural households rely on protected sources such as public boreholes, protected wells, or public taps, with only 13% using unprotected wells or springs. This disparity places the study area among the most water-deprived rural settings in the country. The heavy time cost of water collection has direct implications for household labour allocation, affecting time available for childcare, income-generating activities, and agricultural production. The study notes that time-saving interventions, such as the installation of protected water points or communal storage systems, could substantially reduce this burden and potentially improve food security outcomes by freeing up labour for other essential tasks.
The demographic profile of the respondents also offers insight into the dynamics of household food management. Women emerged as the primary respondents in 98.2% of cases, a pattern that likely reflects prevailing gender roles in rural Uganda. In these communities, women are typically responsible for food preparation, resource management, and child care, giving them the most accurate knowledge of household food consumption and access. This gender distribution presents a specific opportunity for policy intervention, as prioritizing women through tailored extension services could enhance the effectiveness of food security programs. The study suggests that gender-responsive training on integrated crop-livestock systems, home-gardening, and food preparation could support the adoption of resilient practices and improve household nutrition outcomes, aligning with broader national development goals.
Land tenure and fragmentation represent another critical dimension of the findings. More than 90% of Uganda’s farm output is produced on plots under five hectares, and customary land systems have increasingly undergone subdivision and individualization. This fragmentation constrains the ability of households to expand cultivation or adopt long-term investments such as crop rotation and perennial crops. The study connects these local constraints to wider regional debates on the “East African land rush,” where competition for land and boundary disputes can limit smallholders’ secure access to cultivable acreage. Households reporting insufficient farmland consistently exhibited lower levels of food security, suggesting that limited land access is not merely a local constraint but part of a structural landscape of tightening land availability. Strengthening security of tenure under customary systems could encourage longer-term investments in soil fertility and perennial crops, thereby enhancing household resilience.
The study’s methodological approach also highlights the importance of integrating qualitative insights into quantitative analysis. By using open-ended questions, the researchers captured respondents’ self-reported needs and household challenges in a way that standardized surveys often miss. This participatory approach allowed for the integration of perception-based qualitative information into the statistical models, providing a richer and more contextualized understanding of the drivers of food insecurity. The findings suggest that allowing respondents to express their own concerns provides valuable insights into the contextual realities shaping food security, which can significantly improve the legitimacy and applied relevance of research for policy and programming. This method underscores the value of giving voice to lived experiences to uncover priority needs that might otherwise be overlooked in conventional assessments.
Subject of Research: Determinants of household food security in rural uganda: perceived needs as key predictors
Article Title: Determinants of household food security in rural uganda: perceived needs as key predictors
Article References: Solano-Jiménez, J., Abadía, R., Palleja, R. P., & Martínez-Carrasco, L. (2026). Determinants of household food security in rural uganda: perceived needs as key predictors. Agriculture & Food Security, 15(1), Article 14. https://doi.org/10.1186/s40066-025-00594-5
Image Credits: AI Generated
DOI: 10.1186/s40066-025-00594-5
Keywords: Determinants, household, food, security, rural, uganda, perceived, needs, predictors, scientific research
News Source: Alan Morgan. (November 12, 2026). Perceived Needs Predict Food Security in Rural Uganda. Scienmag.
