Factors That Determine the Dietary Diversity Score in Rural Households: The Case of the Paute River Basin of Azuay Province, Ecuador

Cordero-Ahiman, Otilia Vanessa; Vanegas, Jorge Leonardo; Franco-Crespo, Christian; Beltrán-Romero, Pablo; Quinde-Lituma, María Elena

doi:10.3390/ijerph18042059

Cited by 35 publications

(42 citation statements)

References 59 publications

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“…The low consumption of animal products could be due to higher prices attached to such commodities compared to vegetables and other food items. This result was similar to [38,43] who also found that consumption of food rich in micronutrients such as milk/dairy products and fish and seafoods is low in the study area. Meanwhile, the frequency of vegetables' consumption in the study area is high.…”

Section: Discussionsupporting

confidence: 89%

“…The results of the study show that the diet of the sample UIVs producers in the study area is based on starch. This result is consonant with [38,43], who also reported a cereal-based diet for the sample respondent. It is noteworthy that the diets of the UIVs producers lacked protein-source products (such as eggs (1.5), milk and dairy products (2.1), fish and other seafoods (5.5), and meats (5.7)), which was an indicator that the households' diets lacked the important nutrients requirement by the body.…”

Section: Discussionsupporting

confidence: 75%

“…Usually, the reference period varies depending on the focus of the study, but, generally, the previous day or week was used by [24,25,43]. This study adopted a 7-day reference period preceding the survey following [38,41]. Fourteen different standardized food groups were included in the questionnaire for scoring (Table 1).…”

Section: Analytical Techniques 241 Measuring Dietary Diversity Of the Householdmentioning

confidence: 99%

“…The variables included were UIVs diversity (number of UIVs cultivated), age of the head of the household (years), years of formal education of the head of household, marital status of the head of household (the marital status of the head of household was registered according to the options: single, married), number of UIVs farm plots, farm distance from home (km), area of cultivated land to UIVs (ha), access to extension agent (yes or no), off-farm income in naira, gross margin generated from UIVs in naira (gross margin from immediate past UIVs cultivated before the survey), monthly food expenditure per capita, location (Oyo, Ondo, and Ekiti). Therefore, 12 explanatory variables were selected for the estimation of the model following [2,38]. The parameters and values chosen to rule that an association is or is not statistically significant were realized according the significance levels: * p < 0.10, ** p < 0.05, and *** p < 0.01.…”

Section: Empirical Modelmentioning

confidence: 99%

“…Cordero-Ahiman et al [38] analysed the factors that determine the household dietary diversity score (HDDS) in the rural area of the Paute River Basin, Azuay Province, Ecuador. The HDDS was measured through 12 food groups consumed over a recall period of 7 days, and a Poisson regression model was used to determine the relationship between the HDDS and sociodemographic variables.…”

Section: Introductionmentioning

confidence: 99%

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Underutilised Indigenous Vegetables for Household Dietary Diversity in Southwest Nigeria

et al. 2021

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The diets of many households in developing countries are monotonous and starch-based. Integrating underutilised indigenous vegetables (UIVs) to cropping systems can contribute to both crop and dietary diversities, thereby improving rural households’ nutrition and boosting food security. Therefore, this study established a link between the UIVs’ diversity and the household dietary diversity (HDD) of the UIVs producers in the rural area of Southwest Nigeria. A multistage sampling technique was used to select 191 UIV-producing households in the region. Their HDD was measured based on the 12 unique food groups consumed by households over a 7-day reference period preceding the survey, and negative binomial Poisson regression analysis was used to determine the relationship between UIV diversities, other sociodemographic characteristics, and the HDD score of the UIV-producing households in the area. The results showed that only about four groups of food contributed greatly to the HDD score. The result of the negative binomial Poisson regression analysis showed UIVs diversity as a significant variable that increased the HDD score in the study area. Other factors that determined the HDD score of UIV-producing households were the marital status of the household head, farm distance from the home, UIVs land area, off-farm income, UIVs gross margin, per capita food expenditure, and Oyo location. The study concluded that the inclusion of diverse underutilised indigenous vegetables into cropping systems in rural areas and vegetable home gardening practices in the rural and urban areas of developing countries could alleviate the challenge of nutrition insecurity.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 75%

Section: Analytical Techniques 241 Measuring Dietary Diversity Of the Householdmentioning

confidence: 99%

Section: Empirical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Underutilised Indigenous Vegetables for Household Dietary Diversity in Southwest Nigeria

et al. 2021

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Food Security

Vuppalapati

2022

International Series in Operations Research &Amp; Management Science

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Investigating food insecurity, health and environment-related factors, and agricultural commercialization in Southwestern Nigeria: evidence from smallholder farming households

Otekunrin

2022

Environ Sci Pollut Res

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Hunger and food insecurity remained some of the serious challenges facing our world in present time with great concerns from Sub-Saharan Africa especially countries like Nigeria. This study investigates food insecurity (FI), health and environment-related factors, and agricultural commercialization among smallholder farm households. This study was conducted in Southwestern Nigeria utilizing cross-sectional survey data from 352 farm households and employed multi-stage sampling procedure. The household FI levels was determined using food insecurity access scale (HFIAS), crop commercialization index (CCI) was used to compute each household’s CCI (four levels), while ordered logit model was used to analyse factors influencing FI. Health and environment-related factors’ access were assessed across each FI category. The results indicated that about 13% of cassava farm households are non-participant in the marketing of their produce. The findings revealed that less than 20%, 30%. and 40% of households in all four FI categories had access to piped water, improved toilet facilities, and electricity respectively. The ordered logit regression analysis indicated that age, gender, education level, farm experience, nonfarm income, and ownership of motorcycle significantly influencing FI in the study areas. Therefore, this study stressed the implementation of policy actions capable of promoting rural infrastructure development that will lead to increased agricultural production, marketing, and improved quality of life of rural dwellers.

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Factors That Determine the Dietary Diversity Score in Rural Households: The Case of the Paute River Basin of Azuay Province, Ecuador

Cited by 35 publications

References 59 publications

Underutilised Indigenous Vegetables for Household Dietary Diversity in Southwest Nigeria

Underutilised Indigenous Vegetables for Household Dietary Diversity in Southwest Nigeria

Food Security

Investigating food insecurity, health and environment-related factors, and agricultural commercialization in Southwestern Nigeria: evidence from smallholder farming households

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