Food Accessibility and Nutrition Status of Tenant Women of Reproductive Age and Under-Five Children on Smallholder Tobacco Farms in the Northern Malawi

Dissertation (MSc)--University of Pretoria, 2017.Introduction: Lack of evidence-based information is an impediment to improve the food security and nutrition status of vulnerable tobacco tenant women and their children on smallholder farms in Malawi. Aim: To assess and describe the food accessibility and nutrition status of the tobacco tenant women of reproductive age and their under-five children on smallholder farms, as well as to determine and report correlational relationships amongst demographic and socio-economic factors, food accessibility measurements and nutrition status indicators. Design: Quantitative cross-sectional descriptive correlational study. Setting: Bwengu, Engucwini and Njuyu Extension Planning Areas, Mzimba North district, Malawi. Sample: 110 women of reproductive age sampled through a proportional systematic random sampling technique, and their 139 under-five children. The sample size was calculated using nQuery version 7 software based on 47% prevalence of malnutrition among under-five children in Malawi, estimated at 95% CI to the accuracy of 10%. Methodology: Data were captured through face-to-face interviews during the hunger season. Food accessibility was captured using the Household Food Insecurity Access Scale (HFIAS), Household Hunger Scale (HHS), Months of Adequate Household Food Provisioning (MAHFP) and Individual Dietary Diversity Scale (IDDS). Nutrition status was measured using anthropometry according to standard protocol. WHO Anthro software was used to compute Z-scores (W/A, H/A, W/H and BMI/A) for children, based on WHO standards. Microsoft Excel was used to calculate BMI for women, based on WHO cut-off points. Stata software was used to compute regression analyses to establish correlational relationships between independent and dependent variables. Ethical approval was obtained from the University of Pretoria, Natural and Agriculture Science Committee (Number EC151215- 028), as well as from the Mzuzu Agriculture Development Division in Malawi. Results: Mean age of the women was 27.3 ± 6 years and 28.8 ± 15 months for the children. The experience of food insecurity access was severe for 75% of the households. Nearly onefifth of households were severely hungry, and had adequate food for only about eight months of the year. The women and their children consumed a mean of two food groups in the previous 24 hours. For the women, 21% were malnourished. For the children, 20% were wasted, 31.3% were stunted and 34% were underweight. More male children were malnourished. For food accessibility measurements, the multivariable linear regression analysis was used. The significant factors influencing the severity of the experience of food insecurity access were loan access (P = 0.015) and household size (P = 0.000). For the prevalence of hunger, the significant factors were food security and nutrition training (P = 0.046), marital status (P = 0.045) and household size (P = 0.000). For the annual prevalence of hunger, the significant factors were labour (P = 0.038), income (P = 0.008) and household size (P = 0.001). For the dietary diversity, the significant factors were labour (P = 0.001), food security and nutrition decisions (P = 0.004), mother’s age (P = 0.033) and income (P = 0.000). Using the multivariable IV regression analysis, the significant factors influencing the BMI of the women were their age (P = 0.054), loan access (P = 0.004), HFIAS scores (P = 0.007) and HHS scores (P = 0.001). For the children’s weight-for-age, the significant factors were the mother’s BMI (P = 0.014), child’s sex (P = 0.005), assets (P = 0.014), mother’s age (P = 0.001) and child’s age (P = 0.015). Using the multivariable random-effects GLS regression analysis, the significant factors influencing the children’s height-for-age were the mother’s age (P = 0.004), child’s sex (P = 0.005), assets (P = 0.028) and HFIAS scores (P = 0.006). For the children’s weight-forheight, the significant factors were the mother’s BMI (P = 0.032), MAHFP scores (P = 0.029), child’s age (P = 0.008) and income (P = 0.001). For the children’s BMI-for-age, the significant factors were the mother’s BMI (P = 0.030), mother’s age (P = 0.029), income (P = 0.002) and assets (P = 0.047). Conclusion: The food accessibility and nutrition status of the tobacco tenant women and their children were seriously poor. The significant factors influencing food accessibility and nutrition status were loan access, household size, food security and nutrition training, marital status, labour, income, assets, food security and nutrition decisions, mother’s BMI, mother’s age, child’s age, child’s sex, HFIAS scores, HHS scores and MAHFP scores. The study findings offer clues to policy makers on where to direct interventions to improve food accessibility and nutrition status of the tobacco tenant women and their children in Malawi.Human NutritionMScUnrestricte