Cause of death during 2009–2012, using a probabilistic model (InterVA-4): an experience from Ballabgarh Health and Demographic Surveillance System in India

Abstract

ObjectivesThe present study aimed to estimate the age and cause-specific mortality in Ballabgarh Health and Demographic Surveillance System (HDSS) site for the years 2009 to 2012, using a probabilistic model (InterVA-4).MethodsAll Deaths in Ballabgarh HDSS from January 1, 2009, to December 31, 2012, were included in the study. InterVA-4 model (version 4.02) was used for assigning cause of death (COD). Data from the verbal autopsy (VA) tool were extracted and processed with the InterVA-4 model. Cause-specific mortality rate (CSMR) per 1,000 person-years was calculated.ResultsA total of 2,459 deaths occurred in the HDSS during the year 2009 to 2012. Among them, 2,174 (88.4%) valid VA interviews were conducted. Crude death rate ranged from 7.1 (2009) to 6.4 (2012) per 1,000 population. The CSMR per 1,000 person-years over the years (2009–2012) for non-communicable diseases, communicable diseases, trauma, neoplasm, and maternal and neonatal diseases were 1.78, 1.68, 0.68, 0.49, and 0.48, respectively. The most common causes of death among children, adults, and the elderly were infectious diseases, trauma, and non-communicable diseases, respectively.ConclusionsOverall, non-communicable diseases constituted the largest proportion of mortality, whereas trauma was the most common COD among adults at Ballabgarh HDSS. Policy-makers ought to focus on prevention of premature CODs, especially prevention of infectious diseases in children, and intentional self-harm and road traffic accidents in the adult population.

Cause-Specific Mortality Fraction (CSMF) of adult mortality in Butajira, South Central Ethiopia

“…Similarly, tuberculosis is the leading CoD in several HDSS sites; 15.9% from Kilite Awlaelo [18] and 19.7% from Dabat HDSS [19] in Ethiopia, 26.9% [33] and 16% [34] in Kenya, and 18.5% in South Africa [35]. However, a lower proportion of deaths due to tuberculosis were registered from Ballabgarh in India (7.3%) [36], Dodowa in Ghana (9.7%) [37], Taabo in Cote d'Ivoire (6.4%) [38] and Matlab in Bangladesh (6.1%) [39]. The disparity may be associated with variation in the surveillance years and its duration and HDSS site dissimilarity [40] like disparities in socioeconomic status, exposure risk difference [41], including the way individuals live, work and interact, and the healthcare system capacity in managing tuberculosis cases [42].…”

A prospective study of causes of death in rural Gadchiroli, an underdeveloped district of India (2011-2013)

“…For example, in a study from a rural part of northern India where causes of deaths were determined between 2009-2012 maternal deaths accounted for 2.3% of all deaths among females aged 15-49. 29 In a study from southern India conducted in 2003-2004 maternal deaths accounted for 1% of all female deaths. 8 In our study deaths due to infectious, perinatal and maternal conditions, which are the current health priorities of the government healthcare system in rural areas 30 , were outnumbered by the deaths due to NCDs and injuries in rural Gadchiroli.…”

A prospective study of causes of death in rural Gadchiroli, an underdeveloped district of India (2011-2013)

“…This number is not very far off from the percentage of maternal deaths among females reported from other studies on mortality surveillance from relatively affluent rural parts of India. For example, in a study from a rural part of northern India where causes of deaths were determined between 2009-2012 maternal deaths accounted for 2.3% of all deaths among females aged 15-49 (29). In a study from southern India conducted in 2003-2004 maternal deaths accounted for 1% of all female deaths (8).…”