Health systems in transition : Uzbekistan

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Table 7.1
Top 10 causes of YLL, 1990 and 2010
Rank
Disorder, 1990
% of total 
YYL, 1990
Disorder, 2010
% of total 
YYL, 2010
1
Lower respiratory infections
25.8
Lower respiratory infections
16.3
2
Ischaemic heart diseases
9.9
Ischaemic heart diseases
16.3
3
Neonatal encephalopathy
8.4
Stroke
7.5
4
Diarrhoeal diseases
6.3
Neonatal encephalopathy
6.5
5
Stroke
5.2
Cirrhosis
4.3
6
Preterm birth complications
3.9
Road injury
3.9
7
Road injury
3.1
Preterm birth complications
2.9
8
Congenital anomalies
2.9
Congenital anomalies
2.4
9
Drowning
2.2
Self-harm
2.2
10
Cirrhosis
1.9
Tuberculosis
2.1
Source
: IHME, 2014. 
When disability is taken into account, conditions such as diabetes, back pain 
and major depressive disorder gain in importance (Table 7.2). 
Table 7.2
Leading causes of DALY and percentage change between 1990 and 2010
Rank
Disorder, 2010
% change, 
1990–2010
(rounded)
1
Ischaemic heart diseases 
60
2
Lower respiratory infections
-40
3
Stroke 40
4
Neonatal encephalopathy
-20
5
Road injury 
20
6
Major depressive disorder
70
7
Cirrhosis
120
8
Lower back pain
50
9
Iron deficiency anaemia
5
10
Diabetes
130
Source
: IHME, 2014. 
However, it is worth noting that these data on YYL and DALY have major 
in-built uncertainties, due to data limitations and the use of assumptions and 
estimates where data were not available (IHME, 2014). In Uzbekistan, national 
data on disease-specific measures mostly include those related to incidence, 
prevalence and mortality. Data reported by Uzbekistan to WHO confirm an 

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Health systems in transition
  
Uzbekistan
116
increasing burden of noncommunicable conditions, such as cardiovascular 
diseases, cancer and diabetes. Unfortunately, these data are now long out of 
date, with the latest data on disease-specific mortality relating to 2005. 
Furthermore, in view of the current set-up of the health system and of data 
collection frameworks, some officially reported data have to be treated with 
caution. For instance, data on conditions that are linked to benefits in the 
public sector, such as cancer, are likely to be more accurate. Some patients 
with cardiovascular conditions or back pain, on the other hand, might entirely 
rely on the private sector, where less strict documentation and data reporting 
measures are in place. 
There is an obvious need for better data. A number of health care 
interventions are shown to reduce mortality, morbidity or disease progression 
and are incorporated into clinical practice guidelines in developed countries 
(Strippoli et al., 2004; Rodbard et al., 2007; Benson et al., 2008; Smith et al., 
2011; AHRQ, 2014). Well-designed and implemented data collection initiatives 
can facilitate informed decision-making and improve the effectiveness and 
efficiency of the health system. 
One of the areas that will need attention is inequities in health outcomes 
across regions. Official statistics on infant mortality indicate substantial 
variation across different parts of the country (Table 7.3).
Table 7.3
Infant mortality per 1 000 live births, 2000–2012 (selected years)