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STS489 Danielle J.R. et al.
2. Methodology
 Study Area and Data
This study uses data collected in the Demographic and Health Surveys
(DHS) and Malaria Indicator Surveys (MIS) carried out in Kenya, Malawi,
Tanzania and Uganda between 2015 and 2017, namely the 2015 Kenya Malaria
Indicator Survey (KMIS2015), the 2017 Malawi Malaria Indicator Survey
(MMIS2017), the 2015-2016 Tanzania Demographic and Health Survey and
Malaria Indicator Survey (TDHS2015) and the 2016 Uganda Demographic and
Health Survey (UDHS2016). These four countries are situated on the east of
sub-Saharan Africa and together form one contiguous region. The surveys
were nationally represented and utilised a stratified two-stage cluster design.
Three questionnaires, the household, women and men questionnaires, were
carried out in the selected households. These questionnaires were designed
to collect information regarding the characteristics of the household and
eligible women and men. All children under the age of five years old in the
selected households were tested for malaria and anaemia, with the consent of
a parent or guardian.
 Outcome Variable
In all the surveys, a child’s haemoglobin concentration was measured by
finger- or heel-prick blood specimens using a portable HemoCue analyser. For
this study, a binary response variable was used, indicating whether the child
was anaemic if their altitude adjusted Hb level was less than 11 g/dL, or not
anaemic if their altitude adjusted Hb level was greater than or equal to 11
g/dL.
 Explanatory Variables
The explanatory variables considered in this study comprised of a number of
demographic, socioeconomic and environmental factors. These potential risk
factors are shown in Figure 1. Such factors included the gender and age of the
child, number of members in the household (size of the household), mother’s
highest education level, the child’s malaria Rapid Diagnostic Test (RDT) result,
type of place of residence: rural or urban; cluster altitude, household wealth
index, type of toilet facility, and the age and gender of the head of the
household. In addition, certain geospatial covariates were also considered. As
no information regarding intestinal parasites was collected in the surveys used
in this study, certain geospatial covariates were used as a proxy. Specifically,
the cluster level average day land surface temperature (LST) and the cluster
level average Enhanced Vegetation Index (EVI) for 2015.
Furthermore, the spatial variation of childhood anaemia across the
administrative levels of the countries was investigated. The administrative levels
of each of the countries were chosen based on the levels for which public health
decisions are made. Accordingly, administrative level 1 (called “counties” or
“districts”) for Kenya, which consisted of all 47 counties; administrative level 2

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