Human Nutrition

Permanent URI for this community

https://scholar.sun.ac.za/handle/10019.1/100754

Browse

Browsing Human Nutrition by Subject "Agrobiodiversity -- Kenya"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    The role of agricultural biodiversity, dietary diversity, and household food security in households with and without children with stunted growth in rural Kenya
    (Stellenbosch : Stellenbosch University, 2014-04) M'Kaibi, Florence K.; Steyn, Nelia; Ochola, Sophie; Du Plessis, Lisanne; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Interdisciplinary Health Sciences. Division of Human Nutrition.
    ENGLISH ABSTRACT: Research aim The study aimed to explore the associations between agricultural biodiversity, household food security and dietary diversity in households with children aged 24 to 59 months in two rural areas of Kenya, of which one had higher rainfall and agricultural biodiversity than the other. Methods Study sample and location The study adopted a cross-sectional analytical approach to investigate the associations in resource in poor households in two rural areas; Akithii and Uringu of Kenya. Of the 525 households randomly selected, 261 were from Uringu division and 264 from Akithii division. Two independent cross-sectional surveys were conducted; Phase one in September to October 2011 (during the dry season) while Phase 2 took place in March 2012 (during the rainy season). A questionnaire was developed to gather information on the socio-demographics of the household, breastfeeding and infant feeding practices, immunization and childhood illnesses. Dietary intake was measured during each season by conducting a repeated 24-hour recall (24-hr recall) with the mother/care giver of the household. A nutrient adequacy ratio (NAR) was calculated for each nutrient as the percent of the nutrient meeting the recommended dietary intake (RDI) value for that nutrient. A mean adequacy ratio (MAR) was calculated for 11 nutrients as the mean of the NARs of these nutrients. Dietary diversity was measured using data from the 24-hour recalls and classifying it into nine food groups. A dietary diversity score (DDS) was calculated based on each different food group which was consumed during the period of recall up to a maximum of nine if the food had been consumed from each of the nine groups. Household food security (HFS) was measured using the Household Food Insecurity Access Scale (HFIAS). The agricultural biodiversity was calculated by counting the number of different crops and animals eaten either from domestic sources or from the wild. Weight and height measurements of children and their mothers/care givers were taken. Weight for age (WAZ), height for age (HAZ) and weight for height z (WHZ) scores were determined for children, while body mass index (BMI) measurements were calculated for the adult women. The relationships between continuous response variables and nominal input variables were analyzed using appropriate analysis of variance (ANOVA) or pooled, paired and independent mean T-tests when only two groups were involved. Results Dietary intake was low with the majority of households not meeting the RDIs for most nutrients. The MAR was 61.3%; 61.8% for Phase 1 and 2 respectively. The DDS was low at 3.3 ±1.2 for both Phases. The majority of households were food insecure with a HFIAS mean of 12.8 ± 6.19 and 10.9 ± 7.49 for Phase 1 and 2 respectively. Agricultural biodiversity was low with a total of 26 items; 23 domesticated and 3 from the natural habitat. Two food items from the natural habitat originated from plants and one from animals. Exclusive breastfeeding up to the recommended six months was practiced at low rates of 23.4% while 39.3% of mothers in both divisions introduced complementary foods before 6 months of age. Stunted growth among the children was high at a mean of 30.5% (n=291). Boys had higher stunted growth rates in both divisions compared to the girls. A significant positive relationship was established between the number of contributors to household income with height for age z-scores (HAZ) scores of the children (Spearman r=-0.15, p=0.02). The number of household assets also significantly influenced HAZ scores (Spearman r=-0.17, p=0.01), the higher the number of household assets, the lower HAZ scores were. During Phase 1 (dry season) (pooled t-test, p<0.001), levels of food insecurity were higher compared to Phase 2 (wet season) (pooled t-test, p<0.001); showing the influence of season on food security. Phases 1 & 2 showed that Akithii had a significantly higher level of food insecurity (Mann-Whitney U; p<0.01), and a lower DDS (chi-square test, p<0.001) compared to Uringu. Children in Akithii consumed a less diversified diet than those in Uringu. Agricultural biodiversity was positively and significantly related to: HFIAS (Spearman r=-0.10, p=0.02); DDS (ANOVA, p<0.001); all NARs (Spearman, p<0.05) and MAR (Spearman, p<0.001).This implies that households with higher agricultural biodiversity were more likely to be food secure, have higher dietary diversity levels and a diet comprising a higher nutritional value. DDS was significantly correlated to MAR and NARs of all the nutrients studied in this study. Findings showed that DDS was also consistently significantly inversely correlated to Household Food Insecurity Access Prevalence (HFIAP) (R =-0.185, t (N-2)-3.889), p=0.0001). This correlation showed that an increase in dietary diversity inversely affected HFIAS. A significant relationship was found between HFIAP and MAR (ANOVA, p=0.00268); indicating that households with a higher MAR were more likely to be food secure. There was a significant correlation between the BMI of the mother/care giver and the WAZ scores of the children (r=0.1410, p<0.001); indicating that higher HAZ scores were found in mothers with higher mean BMI values. There was a significant difference between households with and without children with stunted growth in DDS (ANOVA; p=0.047) and HFIAS (ANOVA; p=0.009) but not with agricultural biodiversity score (ANOVA; p=0.486). The agricultural biodiversity mean score for households with children presenting with stunted growth were, however, lower at 6.8, compared to 7.0 for those with normal growth however the p value was not significant. This indicates that households with children with stunted growth and those without are significantly different in DDS and HFIAS but not regarding agricultural biodiversity. This further implies that the potential of DDS and HFIAS to be used as proxy measures for stunting be further explored. Conclusion Agricultural biodiversity has a positive impact on household food security, dietary diversity, dietary adequacy and child growth. Food security is closely linked to dietary diversity and dietary adequacy; therefore improving one is likely to improve the other two and impact positively on child growth status. Interventions to improve child health and food security in resource poor rural households should aim at increasing dietary diversity through agricultural biodiversity.