Estimating cause-specific mortality from community- and facility-based data sources in the United Republic of Tanzania: options and implications for mortality burden estimates.
OBJECTIVE
To compare mortality burden estimates based on direct measurement of levels and causes in communities with indirect estimates based on combining health facility cause-specific mortality structures with community measurement of mortality levels.


METHODS
Data from sentinel vital registration (SVR) with verbal autopsy (VA) were used to determine the cause-specific mortality burden at the community level in two areas of the United Republic of Tanzania. Proportional cause-specific mortality structures from health facilities were applied to counts of deaths obtained by SVR to produce modelled estimates. The burden was expressed in years of life lost.


RESULTS
A total of 2884 deaths were recorded from health facilities and 2167 recorded from SVR/VAs. In the perinatal and neonatal age group cause-specific mortality rates were dominated by perinatal conditions and stillbirths in both the community and the facility data. The modelled estimates for chronic causes were very similar to those from SVR/VA. Acute febrile illnesses were coded more specifically in the facility data than in the VA. Injuries were more prevalent in the SVR/VA data than in that from the facilities.


CONCLUSIONS
In this setting, improved International classification of diseases and health related problems, tenth revision (ICD-10) coding practices and applying facility-based cause structures to counts of deaths from communities, derived from SVR, appears to produce reasonable estimates of the cause-specific mortality burden in those aged 5 years and older determined directly from VA. For the perinatal and neonatal age group, VA appears to be required. Use of this approach in a nationally representative sample of facilities may produce reliable national estimates of the cause-specific mortality burden for leading causes of death in adults.
Whiting
David R
DR
MEASURE Evaluation, Carolina Population Center, University of North Carolina at Chapel Hill, NC, USA. david.whiting@ncl.ac.uk
Setel
Philip W
PW
Chandramohan
Daniel
D
Wolfson
Lara J
LJ
Hemed
Yusuf
Y
Lopez
Alan D
AD
D002423:Cause of Death; D002675:Child, Preschool; D006268:Health Facilities / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D009026:Mortality; D012424:Rural Population / Q000706:statistics & numerical data; D018571:Sentinel Surveillance; D013636:Tanzania / Q000453:epidemiology; D014505:Urban Population / Q000706:statistics & numerical data