ADULT MORTALITY DIFFERENTIALS BY GENDER AND REGIONS IN SURINAME IN RECENT YEARS Andrea Idelga Fernand Jubithana Anton de Kom Universiteit Van Suriname Andrea.jubithana-fernand@uvs.edu Bernardo Lanza Queiroz Departament of Demography Universidade Federal de Minas Gerais lanza@cedeplar.ufmg.br Abstract In this paper, we investigate the quality of vital records registration in Suriname and its main regions and investigate mortality differentials by gender and regions in the last two censuses. Suriname is one of the less populated countries in the world and producing adequate mortality estimates for the country is also a challenge. We use data from the 2004 and 2012 censuses and death counts from the Central Bureau of Citizen Issues (CBB). We evaluate quality of mortality data using the Death Distribution Methods. We find that, the urban coastal and rural coastal area have more disadvantage in mortality than the rural interior area and male mortality is almost twice female mortality for all regions. We also show differences in causes of deaths. Keywords: mortality differentials, Suriname, causes of death, data quality 1
Introduction Mortality differentials are present in all societies. Measuring and understanding differentials might help one to investigate trends and the evolution of life expectancy and the health conditions of different population sub-groups. Suriname is a small country and the second less populated in the America´s. There are not, to our knowledge, many studies on mortality and mortality differentials in the country. By being colonized by the Netherlands, some argue that vital records in the country are of good quality. In this paper, we, first, investigate the quality of vital records registration in the country and main regions and, second, analyse mortality differentials by gender and regions in the period between the last two censuses. Studies show that women are healthier than men, however the report of their health is worse on surveys (Case, A; Paxson, C, 2004). But, male mortality is higher than female in several regions of the world. In the first place there may be sex differences in the distribution of chronic conditions as a result of biological, psychosocial or behavioural factors (Verbrugge, 1989; Lawlor et al, 2001; Molarius and Janson, 2002). In the second place women suffer from health conditions that contribute relatively little to mortality risk in relation to men who have health conditions which have large effects on the probability of death (Case, A; Paxson, C, 2004). On the other hand, studies have shown that women make more use of health care than men and that it may be the reason that they know more about their health and thus are more accurate health reporters (Verbrugge 1989, Idler 2003). There is some evidence about the view that men provided more complete information about their health in case of open-ended questions (MacIntyre, Ford and Hunt, 1999). Studies for developed countries have shown that the gap of life expectancy at birth between man and women have been narrowed for recent years (Glei, A; Horiuchi, S, 2007), due to changes in causes of death. In most of the developing countries like Brazil sex differences in mortality does not show reduction (Simoes, 2002; Queiroz et al, 2017). In the study of the United States (Preston, S; Wang, H, 2005) changes in sex mortality differentials is related to histories of cigarette smoking and has a cohort based structure. In most European countries narrowing sex differentials had been observed (Gjonca, et al ., 2005) 2
Mortality differentials exist between and within countries (Kibele, 2012). Even between and within countries large and small differences in life expectancy at birth can be observed (Human Mortality Database 2008b). With respect to the differences in mortality by region the case of Germany (Kibele, 2012) shows variation in regional mortality. Historical studies also present differential mortality of the urban and rural area (Condran, G; Crimmins, E, 1980). For the United States, Fenelon (2012) shows an increasing gap in life expectancy and mortality risks across the northern and southern part of the country. Wilmoth, Boe, and Barbiere (2010) argued that there is a variation in health and mortality by race / ethnicity, socio-economic status, sex and geography in the United States of America. The geographic adult mortality differentials seem to be higher in the USA compared to Western Europe. In the mortality study of the USA (Fenelon, 2013) results show that high mortality is concentrated in space and clustered in the South and that this region is relatively poor with the presence of few health advantage. Suriname has a small scale population (541638 habitants in Census 2012) and differences exist in mortality between the urban coastal area, rural coastal area and the rural interior area. The country consists of ten districts whereby the urban coastal area covers the capital district Paramaribo and district Wanica with about 70% of the population. The rural coastal area (111224 habitants in Census 2012 consists of the districts Para, Commewijne, Saramacca, Nickerie and Coronie. The districts Marowijne, Sipaliwini and Brokopondo are part of the rural interior area (71268 habitants in Census 2012). It is relevant to mention that Suriname is characterized by international and internal migration. According to data of the General Bureau of Statistics (2011) the internal migrants move more from the rural interior area to the urban coastal area, from the rural coastal area to the urban coastal area and from the rural interior to the rural coastal area. The internal migration in 2012 from rural interior area to urban coastal area and from rural coastal area to urban coastal area was 78.04 % and 77.49 % of the internal migrants, respectively. Data and Methods We investigate regional and gender differences in adult mortality in Suriname in the most recent period. The population data is from the Census 2004 and 2012 and the average death counts data between 2004 and 2012 is from the Central Bureau of Citizen Issues (CBB). In 3
order to estimate adult mortality we used traditional demographic methods called Death Distribution Methods (DDM´s): 1) General Growth Balance (GGB) method proposed by Hill (1984); 2) Synthetic Extinct Generation (SEG) method proposed by Benneth and Horiuchi (1981); 3) Combined GGB-SEG method (Hill, You and Choi, 2009). The DDM methods require that assumptions about the population are made regarding the nature of the typical data errors 1) any change in census coverage had been proportionately constant by age, 2) no age misreporting of the population and deaths, and 3) proportionately constant omission of deaths by age (Hill, You, and Choi, 2009). An important assumption in the use of the methods GGB, SEG, and Hybrid GGB-SEG is that the population does not experience net migration. GGB method is a generalization of the Growth Balance method for stable populations proposed by Brass (1975) and it is derived from the population balance equation. The GGB is generalized for non-stable populations when two or more censuses are available (Hill, 1987). The GGB method is mathematically presented by the next equation: 1 k k * k N ( x ) 1 2 D ( x ) 1 1 2 ( ) ln * r x (1) N ( x ) t k C N ( x ) 2 The slope 1 2 k 1 * k 2 of the linear equation estimates the coverage of death recording C relative to an average of the coverage of the two censuses (HILL, 1987; HILL, K., 1987; HILL, K.; You, D.; TIMAEUS, I, 2003; HILL, K.; You, D.; CHOI, Y, 2009). Moreover, the 1 k 1 ln intercept of the linear equation above represents the age invariant change in census t k 2 coverage between two censuses. The SEG method is based on the insight of Vincent (1951) that in a closed population with good reporting of deaths the population of age a at time t could be estimated by accumulating the deaths to that cohort after time t until the cohort was extinct (Hill, You and Choi, 2009). According to Hill, You, and Choi (2009) the SEG method calculates the estimated population that is composed of a sum of those who died multiplied by the sum of the growth rates of the 4
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