BACKGROUND: For public health purposes, it is important to see whether @entity1 and @entity1 in different age groups die of the same causes in South Africa. OBJECTIVE: We explored sex- and age-specific patterns of causes of @entity204 in a rural demographic surveillance site in northern KwaZulu-Natal in South Africa over the period 2000-2011. DESIGN: Deaths reported through the demographic surveillance were followed up by a verbal autopsy (VA) interview using a standardised questionnaire. Causes of @entity204 were assigned likelihoods using the publicly available tool InterVA-4. Cause-specific mortality fractions were determined by age and sex. RESULTS: Over the study period, a total of 5,416 (47%) and 6,081 (53%) @entity204 were recorded in @entity1 and @entity1 , respectively. Major causes of @entity204 proportionally affecting more @entity1 than @entity1 were (all p<0.0001): @entity1 @entity465 virus/acquired @entity465 ( @entity645 / @entity791 ) (20.1% vs. 13.6%), other and unspecified @entity299 (5.9% vs. 3.2%), @entity64 (4.5% vs. 2.7%), reproductive @entity5 (1.7% vs. 0.4%), @entity6 (2.4% vs. 1.2%), and @entity0 (0.4% vs. 0%). Major causes of @entity204 proportionally affecting more @entity1 than @entity1 were (all p<0.0001) assault (6.1% vs. 1.7%), @entity1907 (34.5% vs. 30.2%), road traffic accidents (3.0% vs. 1.0%), intentional self-harm (1.3% vs. 0.3%), and @entity29773 (2.5% vs. 1.5%). Causes of @entity204 due to @entity166 predominated in all age groups except in older @entity1 . CONCLUSIONS: While mortality during the 2000s was dominated by @entity378 and @entity645 / @entity791 , we found substantial sex-specific differences both for communicable and non-communicable causes of @entity204 , some which can be explained by a differing sex-specific age structure. InterVA-4 is likely to be a valuable tool for investigating causes of @entity204 patterns in other similar Southern African settings.

Who died of what in rural KwaZulu-Natal, South Africa: a cause of XXXX analysis using InterVA-4.

@entity1 :: ('9606', 'Species') :: ['men', 'women', 'human', 'persons'] @entity64 :: ('MESH:D020521', 'Disease') :: ['stroke'] @entity0 :: ('MESH:D001943', 'Disease') :: ['breast neoplasms'] @entity6 :: ('MESH:D003920', 'Disease') :: ['diabetes'] @entity29773 :: ('MESH:D012142', 'Disease') :: ['respiratory neoplasms'] @entity5 :: ('MESH:D009369', 'Disease') :: ['neoplasms'] @entity645 :: ('57667', 'Species') :: ['HIV'] @entity465 :: ('MESH:D007153', 'Disease') :: ['immunodeficiency syndrome', 'immunodeficiency'] @entity299 :: ('MESH:D006331', 'Disease') :: ['cardiac disease'] @entity378 :: ('MESH:D014376', 'Disease') :: ['tuberculosis'] @entity791 :: ('MESH:D000163', 'Disease') :: ['AIDS'] @entity166 :: ('MESH:D003141', 'Disease') :: ['communicable diseases'] @entity204 :: ('MESH:D003643', 'Disease') :: ['death', 'deaths'] @entity1907 :: ('MESH:D014397', 'Disease') :: ['pulmonary tuberculosis']
@entity204 :: (MESH:D003643,Disease) :: ['death']
