In Namibia, non-communicable diseases are on the increase. Statistics on noncommunicable
diseases (cancer, diabetes, cardiovascular diseases, hypertension etc.)
as a cause of morbidity and mortality indicate that it is a public health concern although
population based estimates in the area are lacking. The Ministry of Health and Social
Services stated that between 2004 and 2008, hospital based mortality due to cancer (all
types) increased from 3.2% to 54.7%, cardiovascular diseases (all types) increased
from 5.3% to 21.2% while diabetes mellitus also increased from 1.0% to 14.6%.
To curb the rising trend of the burden of non-communicable diseases in Namibia, the
Ministry of Health and Social Services embarked on several preventive initiatives such
as raising awareness through preventive programmes, passing laws related to the use
of tobacco products, developing national promotion policies as well as health
promoting school initiatives. The programmes however are implemented at national
level but efficient targeting of such programmes requires the identification of high risk
areas of diseases to identify where the disease is most prevalent. The use of disease
maps to identify areas of elevated risk for non-communicable diseases in Namibia
therefore becomes important with the available limited resources. Disease mapping is
one such approach that can serve as a basic tool in planning to optimize the reduction
of non-communicable diseases. Furthermore, mapping of such diseases allows the
study of one disease at a time or multiple disease for comprehensive programming.
The study follows a quantitative cross sectional study design using multiscale disease
modelling methods to describe areas of elevated risk at region, health district and
constituency level in Namibia. The main aim of the study was to fit a multiscale model
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to identify spatial variations of diabetes and hypertension at various geographic levels
in Namibia to guide better planning, monitoring and evaluation and assist in targeting
of resources. The specific objectives were to; Estimate disease risk at health district,
region and constituency level in Namibia; Estimate macro determinants of diabetes
and hypertension; and explore various approaches to model fitting of diabetes and
hypertension in Namibia.
The population for the study was all persons using health facilities from 2008-2014 in
Namibia. A total of 15462 cases of diabetes and 30620 cases of hypertension were
reported from 444 health facilities over a period of seven years. The covariates
considered for the study were safe water, wood/charcoal, main source of income:
wages and salaries, main source of income: pension and education attainment:
incomplete primary education. Covariates for the study were obtained from the 2011
Namibia Population and Housing Census.
The random effects were modelled using a conditional autoregressive prior
distribution. A Fully Bayesian Inference based on Markov Chain Monte Carlo
simulation techniques was used to overcome difficulties in calculating the posterior
distribution.
Results from the study showed that significant spatial variation exist for both diabetes
and hypertension among the different levels considered in the study. The relative risk
for diabetes was found to be highest in Kavango region suggesting an increased risk
for diabetes in the area. At health district and constituency level, the relative risk for
diabetes was found to be highest in Rundu health district and Rundu Urban
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constituency respectively suggesting that the was an increased risk of diabetes in the
area. With respect to hypertension, the relative risk of hypertension was highest in
Khomas region. At health district level, Andara, Rundu, Swakopmund and Windhoek
had the highest relative risk indicating that there was an increased risk of hypertension
in the areas. At constituency level, Rundu Urban constituency was found to exhibit the
highest relative risk of hypertension suggesting an increased risk for hypertension in
the areas.
For the variance components, region had the highest posterior mean (1.0168 and
1.0262 for diabetes and hypertension respectively) suggesting that diabetes and
hypertension was high among the different regions in Namibia compared to health
districts and constituencies.
It is hoped that the study will assist policy makers especially those involved in health
planning to develop comprehensive programmes or targeted interventions in areas that
were found to have elevated risk of diabetes and hypertension, in turn developing
programmes and strategies aiming at improving the health and well-being of the
population. Moreover, the study hopes that considering spatial factors in planning of
health programmes related to diabetes and hypertension could assist in the
achievement of National Development Goals such as those outlined in NDP 4 in line
with the progress towards achieving international goals such as UN Millennium
Development Goals.