Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
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php/jkki eISSN 2503-2801, pISSN 2985-3435 Determinants of Food Security in Rural Households: An Analysis of Dietary Diversity.
Land Ownership, and Socioeconomic Factors Fitrio Deviantony1* .
Erti Ikhtiarini Dewi1 .
Yeni Fitria1 .
Enggal Hadi Kurniyawan1 1 Department of Mental Health Nursing.
Faculty of Nursing.
Universitas Jember.
Indonesia Article History Submitted: 27-06-2024 Revised: 28-07-2024 Accepted: 13-08-2024 org/10.
58545/jkki.
Copyright .
2024 Authors This is an open-access article under the CC-BY-SA License.
Abstract Background: Food security is a critical issue in rural areas, influenced by various socioeconomic factors, dietary practices, and resource Understanding the determinants of food security can help in designing effective interventions to improve the well-being of rural Purpose: This study aims to identify and analyze the key determinants of food security among rural households, focusing on dietary diversity, land ownership, and other socioeconomic factors.
Methods: The dataset used in this study includes variables such as gender, marital status, education, land ownership, food crop cultivation, meal frequency, age, food source.
Food Security Index (FSI), and Household Dietary Diversity Score (HDDS).
Multiple linear regression analysis was conducted to explore the relationships between these variables and the FSI.
Additionally, a Random Forest Regressor model was employed to predict the FSI and to determine the importance of each feature.
Results: The multiple linear regression analysis revealed that HDDS has a significant positive relationship with the FSI .
<0.
indicating that higher dietary diversity is associated with higher food security levels.
Other variables, such as education and food source, showed weaker correlations with food security.
The Random Forest Regressor model achieved an R-squared value of 0.
495, with feature importance analysis indicating that HDDS, food source, and age are the most influential factors in determining food security.
The Mean Squared Error (MSE) of the model was 10.
Conclusion: This research highlights the crucial role of dietary diversity and socioeconomic conditions in shaping food security outcomes in rural areas.
The findings provide valuable insights for policymakers and stakeholders aiming to enhance food security and dietary quality in rural Further studies are recommended to explore the complex interactions between these variables and to develop targeted interventions to improve food security.
Keywords: Food Security.
Rural Households.
Dietary Diversity.
Socioeconomic Factors Correspondence Fitrio Deviantony Faculty of Nursing.
Universitas Jember Jl.
Kalimantan No.
Sumbersari.
Kabupaten Jember.
East Java 68121 Indonesia Email: fitrio.
psik@unej.
How to cite:
Deviantony.
Dewi.
Fitria.
, & Kurniyawan.
Determinants of Food Security in Rural Households: An Analysis of Dietary Diversity.
Land Ownership, and Socioeconomic Factors.
Jurnal Kesehatan Komunitas Indonesia, 4.
, https://doi.
org/10.
58545/jkki.
Deviantony .
Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 Dietary diversity, which measures BACKGROUND Food security remains a significant the variety of foods consumed, serves as a challenge in rural areas, where access to key indicator of nutritional quality and diverse and nutritious food is often limited food security.
A diverse diet is typically by various constraints (Mekonnen et al.
associated with better health outcomes, as These constraints include economic it ensures the intake of essential nutrients instability, lack of education, inadequate required for growth, development, and land ownership, and limited access to disease prevention.
In many rural areas, markets and agricultural resources.
In rural settings, the ability to secure a stable and nutritious food supply is not only a matter availability and economic constraints, of immediate survival but also a critical leading to poor nutritional outcomes and increased vulnerability to food insecurity long-term productivity, and social stability (Bilali, (FAO, 2.
Understanding interactions between these socioeconomic education, land ownership, and income factors and dietary diversity is essential for levels, are crucial determinants of food developing effective strategies to enhance food security in rural communities.
This educational attainment often have better study aims to explore these interactions by access to information and resources, analyzing a comprehensive dataset that enabling them to make informed decisions includes variables such as gender, marital about food production and consumption.
status, education, land ownership, food Land ownership is another significant crop cultivation, meal frequency, age, food factor, as it provides the means for source.
Food Security Index (FSI), and households to cultivate their own food and Household reduce dependency on external food (HDDS) (Briones Alonso et al.
, 2.
examining these variables, the research Furthermore, income levels influence a seeks to identify the key determinants of household's ability to purchase diverse and food security and provide insights that can nutritious foods, impacting overall dietary inform policy and intervention programs aimed at mitigating food insecurity in rural Socioeconomic Households (Oyo Kalema.
Determinants of Food Security in Rural Households Dietary Diversity Score Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 The findings of this study are The dataset was first cleaned and expected to contribute to a deeper preprocessed to ensure accuracy and understanding of the multifaceted nature of food security and highlight the handled appropriately, and categorical variables were encoded as necessary.
socioeconomic and dietary factors in Descriptive statistics were calculated to efforts to improve the well-being of rural households (Baliwati et al.
, 2.
distribution and central tendencies.
Missing To understand influence food security, policymakers and between the Food Security Index (FSI) and the various independent variables, a interventions that promote sustainable multiple linear regression analysis was food systems, enhance dietary diversity, conducted (Ningtyas et al.
, 2.
This and ultimately improve the quality of life statistical technique helps to quantify the for rural populations.
effect of each independent variable on the dependent variable (FSI) while controlling for the influence of other variables.
The METHODS This study employs a quantitative regression model included the following approach to analyze the determinants of independent variables: gender, marital food security among rural households.
The status, education, land ownership, food dataset used in this research includes a crop cultivation, meal frequency, age, food variety of variables, such as gender, marital source, and HDDS.
The model was status, education, land ownership, food evaluated based on R-squared, adjusted R- crop cultivation, meal frequency, age, food squared, and the significance of individual source.
Food Security Index (FSI), and Score In addition to linear regression, a (HDDS)(Mahmudiono et al.
, 2.
These Random Forest Regressor was employed to variables were collected from a sample of predict the Food Security Index (FSI) and identify the most important factors comprehensive overview of the factors influencing food security.
Random Forest is an ensemble learning method that builds Household Dietary Diversity multiple decision trees and merges them to improve predictive accuracy and control Deviantony .
Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 The dataset was split into correlation analysis, this study provides a training and testing sets .
% training, 20% testin.
to evaluate the model's determinants of food security in rural The model's accuracy was The methods employed ensure assessed using metrics such as Mean a robust analysis, allowing for a deeper Squared Error (MSE) and R-squared (RA).
understanding of the complex interactions The Random Forest model provides between socioeconomic factors, dietary an assessment of feature importance, diversity, and food security.
indicating which variables have the most significant impact on predicting the FSI.
This analysis helps to identify the key
RESULTS
The analysis conducted in this study determinants of food security and provides insights into which factors should be regarding the determinants of food security prioritized in policy and intervention among rural households.
The results are summarized below, focusing on the A correlation analysis was conducted outcomes of the multiple linear regression, to examine the pairwise relationships Random Forest regression, and correlation between all variables in the dataset.
This multicollinearity issues and provides a The multiple linear regression model associations between different factors was used to explore the relationships influencing food security.
between the Food Security Index (FSI) and Data Multiple Linear Regression Analysis various independent variables, including gender, marital status, education, land importance plots, were created to facilitate ownership, food crop cultivation, meal the interpretation of the results.
These frequency, age, food source, and Household visualizations provide a clear and concise Dietary Diversity Score (HDDS).
(RA):
The between variables and the impact of 1% of the variance in the different factors on food security.
FSI, with an adjusted R-squared value of regression.
Random Forest regression, and Determinants of Food Security in Rural Households Significant Predictors: The HDDS emerged Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 as a significant predictor of the FSI, with a results from the multiple linear regression strong negative relationship .
< 0.
(Table.
This suggests that higher included food source and age, while dietary diversity is associated with lower variables such as gender, marital status, food security levels.
Other variables, such education, land ownership, and meal as education and food source, showed frequency had relatively lower importance.
confidence level.
Other Correlation Analysis The correlation analysis provided insights into the pairwise relationships between variables.
Random Forest Regression Analysis A Random Forest Regressor model Key Correlations: The HDDS showed was employed to predict the FSI and a strong negative correlation with the FSI determine the importance of each feature.
(-0.
, reinforcing the finding that higher Model Performance: The Random Forest dietary diversity is associated with lower model achieved an R-squared value of food security levels.
The FSI also had negative correlations with education and 5% of the variance in the FSI was food source, although these were weaker.
explained by the model.
The Mean Squared Positive Error (MSE) was 10.
between HDDS and education, as well as between HDDS and food source, indicating importance analysis revealed that HDDS that higher education levels and diverse food sources are associated with better Feature Importance:
The most influential factor predicting the FSI, aligning with the dietary diversity.
Table 1.
Multiple Linear Regression Results Variable Constant Gender Marital status Education Land ownership Food crops Meal frequency Age Food Source HDDS Coefficient Std.
Error t-value p-value <0.
<0.
95% C.
406, 43.
[-0.
266, 0.
[-0.
642, 0.
[-0.
314, 0.
[-0.
232, 0.
[-1.
048, 0.
[-0.
295, 1.
[-0.
028, 0.
[-0.
419, 0.
[-1.
629, -1.
Deviantony .
Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 Figure 1.
Correlation Matrix of Variables Figure 2.
Feature Importances from Random Forest Regressor
DISCUSSION
The findings of this study provide significant insights into the determinants of food security among rural households.
variables that influence the Food Security Determinants of Food Security in Rural Households Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 Index (FSI)(Cordero-Ahiman Education, while showing a weak negative correlation with FSI, had a analysis revealed that the Household positive correlation with HDDS.
This Dietary Diversity Score (HDDS) is a suggests that more educated households significant predictor of the FSI, with a tend to have a more diverse diet, which strong negative relationship.
This indicates that higher dietary diversity is associated education improves awareness and access with lower food security levels, suggesting to nutritional information.
However, the that households consuming a more varied weak correlation with FSI indicates that diet may face greater challenges in securing education alone may not be sufficient to enough food(Kishore et al.
, 2.
This enhance food security significantly.
Land- counterintuitive result could be explained ownership, another critical factor, did not by the possibility that households striving show a strong correlation with FSI.
This for a more diverse diet may encounter might be due to the fact that owning land higher costs, leading to financial strain and does not necessarily translate into effective reduced food security.
Other variables such utilization or productivity, especially in as education, food source, and age, rural areas where access to resources and although not statistically significant in the agricultural inputs may be limited.
The multiple linear regression model, showed results of this study have important policy some level of importance in the Random implications(Nandi et al.
, 2.
Firstly.
Forest regression analysis (Mehraban & interventions aimed at improving food Ickowitz, 2.
Specifically, the feature security should consider the complexity of importance analysis from the Random dietary diversity and its impact on Forest model highlighted that HDDS, food household food security.
Efforts to enhance source, and age are the most influential dietary diversity need to be accompanied factors in predicting the FSI.
This by measures to reduce the financial burden underscores the complexity of food on households, such as subsidies for security, where multiple factors interplay nutritious foods or support for home The outcomes(Oyo Kalema.
The Secondly, correlation analysis provided additional nutrition and food security awareness insights into the relationships between should be strengthened, particularly in various socioeconomic factors and food rural areas (Alhogbi et al.
, 2.
These Deviantony .
Jurnal Kesehatan Komunitas Indonesia (JKKI) Volume 4 Issue 2.
August 2024, pp 179-188 https://ebsina.
id/journals/index.
php/jkki eISSN 2503-2801, pISSN 2985-3435 programs can empower households to AUTHOR CONTRIBUTIONS make informed decisions about their diets Substantial and resource utilization.
Lastly, policies conceptualization, data curation, analysis:
should focus on improving the productivity Fitrio Deviantony.
Erti Ikhtiarini Dewi, and sustainability of land use in rural areas.
Yeni Fitria and Enggal Hadi Kurniawan.
Providing access to agricultural inputs.
Supervision Writing-review & editing:
training, and support services can help Fitrio landowners optimize their land for food Manuscript revisions: Fitrio Deviantony.
Deviantony.
Yeni Fitria.
security (Weiss et al.
, 2.
ACKNOWLEDGMENT