Abstract:
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.