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Revista Brasileira de Epidemiologia

Print version ISSN 1415-790XOn-line version ISSN 1980-5497

Rev. bras. epidemiol. vol.20  supl.1 São Paulo May 2017 


Completeness of death-count coverage and adult mortality (45q15) for Brazilian states from 1980 to 2010

Bernardo Lanza QueirozI 

Flávio Henrique Miranda de Araujo FreireII 

Marcos Roberto GonzagaII 

Everton Emanuel Campos de LimaIII 

IDepartment of Demography and Center for Regional Development and Planning of the Universidade Federal de Minas Gerais - Belo Horizonte (MG), Brazil.

IIDepartment of Demography and Actuarial Sciences of the Universidade Federal do Rio Grande do Norte - Natal (RN), Brazil.

IIIDepartment of Demography and Elza Berquó Population Studies Center of the Universidade Estadual de Campinas - Campinas (SP), Brazil.



Assess the completeness of the DataSUS SIM death-count registry, by sex and Brazilian state, and estimate the probability of adult mortality (45q15), by sex and state, from 1980 to 2010.


The study was based on mortality data obtained in the DataSUS Mortality Information System, from 1980 to 2010, and on population data from the 1980, 1991, 2000, and 2010 demographic censuses. The quality assessment of the registry data was conducted using traditional demographic and death distribution methods, and death probabilities were calculated using life-table concepts.


The results show a considerable improvement in the completeness of the death-count coverage in Brazil since 1980. In the southeast and south, we observed the complete coverage of the adult mortality registry, which did not occur in the previous decade. In the northeast and north, there were still places with a low coverage from 2000 to 2010, although there was a clear improvement in the quality of data. For all Brazilian states, there was a decline in the probability of adult mortality; we observed, however, that the death probability for males is much higher than that for females throughout the whole analysis period.


The observed improvements seem to be related to investments in the public health care system and administrative procedures to improve the recording of vital events.

Keywords: Brazil; Mortality; Demography; Underregistration


The study of the mortality levels and standards as well as the attaining of reliable estimates are very important in the understanding of demographic dynamics and in fiscal planning and social policies. AbouZahr and Boerma1 argue that appropriate decisions for public health only occur when there is good information on health-related events, such as mortality, morbidity, and causes of death, which depend on the good coverage of the health information system.

In many countries, estimating mortality is a challenge, as the quality of information is generally unsatisfactory, and limitations on mortality and population data have persisted over time2,3. However, efforts in many of them resulted in the improvement of health and mortality information in recent decades3. In Brazil, for example, the completeness of coverage of the death records of adult males went from 83.2% in the 1980-1991 period to 89.7% in the 2000-2010 period4.

These results indicate that, despite advances in information quality, efforts still need to be undertaken to assess the quality of data and, where necessary, to adjust the under-enumeration of deaths so that mortality estimates become more reliable. There is a number of methods that permit circumventing these problems and measure mortality indirectly or via demographic relations5,6,7,8,9.

This study is part of this discussion by assessing the quality of mortality data obtained by DataSUS SIM, presenting estimates of adjustment factors for the under-registration of the declaration of death, by sex and period, and producing estimates of adult mortality (45q15) for Brazil from 1980 to 2010. In the Burden of Disease Project10, the assessment of the quality of mortality data and the attaining of proper mortality estimates are fundamental for proper investigation of the observed advances in Brazil and in its states over the last years. Problems regarding under-reporting of death have a direct impact on the calculation of the mortality envelope, the basis of all the measures of the Burden of Disease Project10,11, and affect how the evolution and trends of morbidity and mortality occur in the country. This article uses the same demographic methods used in the Global Burden of Disease Study, with minor adjustments and changes to the application. Therefore, this study presents a systematic assessment of the quality of data on death in Brazil and in its states and enables comparative studies with project results.


The study makes extensive use of the Ministry of Health database, DataSUS1. The system provides information on deaths and causes of death by age and sex at state level. Data have been available since 1979, but the information used was from 1980 to 2010. Mortality data are organized according to the Revision of the International Classification of Diseases (ICD) codes (9th, from 1980 to 1995, and 10th, from 1996 onwards). For the models used, the simplified average of the number of deaths per age in each intercensal period was calculated. Population by age and sex was obtained from the Brazilian censuses (1980, 1991, 2000, and 2010). The geometric mean of the population from each pair of census was used to obtain an estimate of the intercensal population. The intercensal population is used in the methods to estimate death counts under-registration.

The article uses formal demographic techniques to assess the quality of mortality data and estimate the completeness of coverage of mortality information. Several methods have been developed based on equation models for population dynamics to analyze the death coverage in comparison to the population9. Death-distribution methods are most commonly used to estimate the completeness of coverage of adult mortality in non-stable populations8,9. These methods compare death distribution by age to the age distribution of the population, providing the age standard of mortality for a determined period. There are three main methods to assess coverage in death records: general growth balance (GGB), proposed by Hill7, synthetic extinct generation (SEG), proposed by Bennett and Horiuchi6, and adjusted synthetic extinct generations (SEG-adj), proposed by Hill et al9. There are method requirements related to the following recent demographic dynamics:

  1. the population is closed, that is, not subject to migration;

  2. the completeness of death coverage remains constant by age;

  3. the completeness of population-count coverage remains constant by age; and

  4. the ages of the living and deaths are declared without errors.

The advantage of these three methods compared to previous formulations for the adjustment of death under-registration5,8 is to introduce flexibility to the requirements of the stable population11, that is, they do not require that population growth rates to be constant by age.

The GGB method is derived from the basic demographic balancing equation that defines the growth rate as the difference between the population birth rate and death rate. This relation also occurs for any age group with an x+ open interval (people aged x and over). Otherwise speaking, in a population without migration, birth occurs as birthdays in x ages. Thus, the difference between the birth rate at x+ and the population growth rate at x+ yields a residual estimate of the mortality rate at x+. If the residual mortality estimate can be estimated from two population censuses and compared to a direct mortality estimate using the death registry or enumeration of the demographic census, the completeness of coverage of the death registry can be estimated from the relationship between these two quantities7,8,9.

Therefore, from a linear regression of the difference between the birth rate and the growth rate in each age group relative in comparison with the age-specific mortality rate in each age group, it is possible to estimate an intercept that captures any coverage variation between the two censuses, as it is also possible to estimate a slope which serves as an indicator of the completeness of coverage of the death registry compared with the average coverage of both censuses7,8,9. The method contrasts the age distribution of deaths (average in the intercensal period) with intercensal population. The estimate specifically refers to registry coverage between censuses, not to a particular date.

Bennett and Horiuchi’s method6, known as a method of extinct generations (SEG), using specific growth rates by age to convert deaths by age in population age distribution. As the observed deaths from an age x in a population are equal to the x-age population, adjusted by the population growth rate by age interval, the deaths of a population at the x+ age provide an estimate of the age x population. The completeness of coverage of the death registry is calculated by the ratio between the population estimated from the deaths above x and the population observed above x + years of age.

Hill et al.9 suggest the combination of Hill’s7 and Bennett and Horiuchi’s6 methods can be more robust than the application of these two methods separately. The adjusted method consists in applying the GGB to obtain estimates of the change in the relative coverage of the demographic censuses, use that estimate to adjust one of the demographic censuses (population enumeration) and then apply the SEG method using the adjusted population to obtain the completeness of mortality data coverage.

The three methods require a closed population or small migration flows to improve the use of estimates. There are methodologies in the literature that allow dealing with this problem12,13. A simpler alternative, suggested by Hill et al.9, is to consider only age groups that are not greatly influenced by migration flows. The most appropriate way of deciding which age interval to use in the production of under-registration estimates should involve the assessment of diagnostic charts produced by the GGB method.

It is important to emphasize that, as there is no standard model, all methodological alternatives should be considered obtaining better estimates of data quality and mortality tendencies in Brazil and its regions. Thus, results of under-registration estimates are presented based on the three methods. Estimates of death probability between the ages of 15 and 59 years (45q15) are presented using the adjusted SEG method, which combines GGB information with SEG results. Estimates were produced using the adult coverage package, developed by Lima, Riffe, and Queiroz for the R-Cran software2. Regarding the problem of populations with migration flows, the solution proposed by the package was accepted, that is, the best age group in each period and unit of analysis.


The evaluation of the performance for the death-distribution methods is best observed in charts. Figures 1 and 2 show the GGB results for two states in the 2000-2010 period. The first, Maranhão, has a high under-registration level, and the second, São Paulo, shows a death-coverage rate of 100%. To simplify the analysis, we present only results for males, which are quite similar to those for females. The x-axis shows mortality rates observed for the x+ ages, and the y-axis represents mortality rates observed for the x + ages derived as a residue of the growth and birth rates at x+ ages. The estimate of the completeness of coverage is obtained from an orthogonal regression in the points for the considered age groups. The slope of the line estimates the adjustment factor needed to adjust observed mortality rates. The intercept of the estimated line provides an estimate of the relative coverage between the two censuses used in the analysis4,8,9,14. The analysis of the dispersion chart confirms the concern with the requirement of closed population in these states. The points at younger ages, especially for males, present greater distance from the estimated line.

Figure 1: Diagnostic charts, general growth balance (GGB), males, São Paulo, 2000-2010. 

Figure 2: Diagnostic charts, general growth balance (GGB), males, Maranhão, 2000-2010 intercensal estimate. 

For São Paulo, the observed curve is practically on the observed data, and the estimates obtained from the differences between the birth rates and the growth rates are practically the same as the observed rates. In any case, there is still greater variation in ages with higher migration flows and in more advanced ages. The results for Maranhão show a high level of death under-registration in the state. The observed curve shows estimates of mortality rates, calculated based on the difference between birth and population growth rates, well above the observed mortality rates. The result also indicates that estimating the adjustment factor using the entire age distribution can be problematic, and it is preferable to use the ages over 35 years and under 65 years. The results suggest that the age declaration is reasonable, and the GGB method requirements, except for the closed population, are partially met.

Tables 1 and 2 present the estimates of the completeness of coverage obtained between 1980 and 2010 for each state by the three methods, for males and females, respectively. The results show a considerable improvement in the death coverage in Brazil since 1980. In almost all states of the south and southeast between 1991 and 2000, we observed a complete coverage of the adult mortality registry, which was not observed in the period between 1980 and 1991. Although there are still places with a low completeness of coverage in north and northeast states, as in Maranhão, there has been a clear improvement in the quality of mortality information.

Table 1: Coverage completeness of the male death registry by period and different methods, Brazilian states, 1980-2010. 

Source: Mortality Information System (SIM), DataSUS. GGB: general growth balance; SEG-adj: adjusted synthetic extinct generation.

Table 2: Coverage completeness of the female death registry by period and different methods, Brazilian states, 1980-2010. 

Source: Mortality Information System (SIM), DataSUS. GGB: general growth balance; SEG-adj: adjusted synthetic extinct generation.

The under-registry adjustment estimates allow correcting the number of deaths recorded and producing proper life tables for the Brazilian population and states. Table 3 shows the adult mortality estimates for males and females between 1980 and 2010, corrected by the adjusted synthetic extinct generations (SEG-adj) method. Adult mortality is represented by the probability of death between ages 15 and 60 years (45q15). We chose to use this measure for its simplicity and the possibility of comparing estimates of under-registration and adult mortality with other studies. We consider that the entry into adulthood occurs at age of 15 years; at that age, there is the inflection point in which the declining of childhood mortality risks is replaced by increased mortality risks for young adults and adults. In addition, this measure covers a substantive age interval - up to the age of 60 years - and avoids problems inherent in estimates of mortality at more advanced ages. In all states, there has been a decline in the probability of adult mortality. Males’s death rates are much higher than those of females, and there has been a stagnation in the decline rate in male mortality in the last decade. As a result, we observe great male over-mortality in all regions of Brazil.

Table 3: Corrected adult death probabilities (45q15), men and females, Brazilian states, 1980-2010. 

Source: Mortality Information System (SIM), DataSUS.


In developing countries, in general, infant deaths have a greater under-registration than adult deaths15,16,17,18,19. Still, estimates of adult mortality in the developing world are less satisfactory than those of infant mortality for two main reasons. First, there are no longitudinal data, such as birth history, to calculate infant mortality from household surveys. Second, indirect estimation techniques for adult mortality do not seem as robust as indirect estimates for infant mortality8,9,20. As a result, much of what we know about adult mortality in developing countries is based on assessed civilian records and, if necessary, adjusted by death distribution methods.

In recent decades, the quality of mortality data in Brazil has shown significant progress, but with large regional variability21,22,23. For the states, some studies for specific points in time enable an analysis of the evolution of data quality4,24,25. However, these studies do not use the same methodology, which makes comparability of results difficult. Thus, it is important to assess and adjust data from the mortality information system, obtain proper estimates for the states in the last decades and analyze the evolution of mortality records. Nevertheless, adopting one single analysis methodology facilitates an appropriate comparison of the evolution of data quality as well as the levels and tendencies of mortality in time and space, with coverage of the death records for both males and females, above 95%4,23,24. States in the south and southeast regions have records of 100% of deaths, for both sexes. Some states in the northeast and north regions present lower quality of information, but they have shown recent significant advances compared to the 1991-2000 period4,21,24,25. In 2010, all states in the south and southeast regions, as well as some in the northeast and Midwest regions, had complete coverage of the death registry. In addition, there was great progress in the quality of mortality information in poorer states in the northeast and north regions, especially those that had the worst record quality in previous periods.

Although presenting different levels of coverage estimates, other authors’ results demonstrate improvements in the quality of mortality data in Brazil in recent decades23,24. The differentials of the levels of coverage of death records in each states and period indicated by different studies are due to the adoption of different methods and/or procedures. The comparison of different studies is complicated by method non-uniformity. Other studies use one of the methods of death distribution for one point in time and one region and another for a different state. In addition, the choice of method may vary over time and across regions.9,24,25.

Regarding mortality estimates for Brazilian regions, the results indicate an improvement in health conditions, as measured by adult mortality. A highlight that needs to be studied further is the non-reduction of the mortality differential between males and females in this period, for which the main reason is deaths caused by violence and traffic accidents26,27,28. There is a probability of adult mortality above 0.200 for males and around 0.120 for females. The highest death risks in the most recent period were observed in Rio de Janeiro, Espírito Santo, Alagoas, and Pernambuco. The sharpest declines in adult mortality were observed in the states with the highest mortality rates in 2000. Female adult mortality is much lower than that of males, and the difference between sexes remained practically constant between 2000 and 2010.

Regarding the application of different methods, there were not many surprises. The results were very close to the problems found in simulation exercises developed by Hill et al9. Both the GGB and the variations of the SEG method work very well, when the errors to which they were developed are the only ones in the data, although it is difficult to identify which errors may occur. The GGB offers a certain advantage as it enables the adjustment of a systematic additional error: coverage changes between censuses. A pronounced age pattern of the population coverage (primarily for young adults) has a major adverse effect on GGB results; however, it has a minor impact on the SEG. Therefore, overall, the SEG is less sensitive to the age coverage differential than the GGB. The major problem in the application of methods, especially for the states, is migration flows. In the two cases presented, and for the other states, the analysis of the diagnostic charts shows the effects of migration in the application of methods. Moreover, we must carefully assess the evolution of some states, such as Acre and Rondônia, which have a completeness of coverage greater than 100%. This may indicate serious data problems and limitations derived from the requirements of the applied methods.

Death distribution methods generally work well, but researchers should be aware of model requirements and the most appropriate ways of estimating under-registration, especially when analyzing smaller areas with large migration flows. Murray et al.11 evaluated variants of death distribution methods in different scenarios, concluding that those presented in this paper are the ones that produce better results.

Studies that assess the quality of mortality data in Brazil and its regions over time are important to evaluate health care policies, but also to analyze the results of the Disease Burden Project10. By using methodological alternatives, this study enable future comparative studies on mortality estimates with those used by the project as well as the evaluation of the trend of Brazilian data quality.

The results point to a series of future researches: studies that seek to better understand social and economic determinants of the mortality differential in Brazil, offer more in-depth studies on data quality in the states and provide methodological and substantive studies on the mortality differential between males and females.


The results on the evolution of coverage of adult death and mortality records in Brazil show remarkable regional differences regarding quality evolution and trend in time and space. For both sexes, the northeast and north presented the greatest progress in the coverage of the death registry in the last three decades. The areas closer to the capitals had greater coverage throughout the whole period (the results are not shown in this text). The improvements observed appear to be related to investments in the public health care system and administrative procedures to improve the recording of vital events. Thus, the quality of data on adult mortality appears to have improved significantly over the years and in many parts of the country. The analysis suggests that the efforts of central, state, and local governments to improve the quality of vital statistics in Brazil are being successful and will allow a better understanding of the dynamics of health and mortality transition in the country. Ongoing investments in the Family Health Program may have a significant impact on improving the quality of mortality data in Brazil as the program works closely with the community and monitors the health status of several individuals in each location.


1. AbouZahr C, Boerma T. Health information systems: the foundations of public health. Bulletin of the World Health Organization 2005; 83: 578-83. [ Links ]

2. Luy M. Estimating Mortality Differences in Developed Countries From Survey Information on Maternal and Paternal Orphanhood. Demography 2012; 49(2): 607-27. [ Links ]

3. Setel PW, Macfarlane SB, Szreter S, Mikkelsen L, Jha P, Stout S, et al. A scandal of invisibility: making everyone count by counting everyone. Lancet 2007; 370(9598): 1569-77. [ Links ]

4. Lima EEC, Queiroz BL. Evolution of the deaths registry system in Brazil: associations with changes in the mortality profile, under-registration of death counts, and ill-defined causes of death. Cad Saúde Pública 2014; 30(8): 1721-30. [ Links ]

5. Preston S, Coale AJ, Trussell J, Weinstein M. Estimating the Completeness of Reporting of Adult Deaths in Populations That Are Approximately Stable. Popul Index 1980; 46(2): 179-202. [ Links ]

6. Bennett NG, Horiuchi S. Estimating the Completeness of Death Registration in a Closed Population. Popul Index 1981; 47(2): 207-21. [ Links ]

7. Hill K. Estimating census and death registration completeness. Asian Pac Popul Forum East-West Popul 1987; 1(3): 8-13, 23-24. [ Links ]

8. Hill K, Choi Y, Timaeus IM. Unconventional approaches to mortality estimation. Demogr Res 2005; 13: 281-300. [ Links ]

9. Hill K, You DZ, Choi YJ. Death distribution methods for estimating adult mortality: sensitivity analysis with simulated data errors. Demogr Res 2009; 21: 235-54. [ Links ]

10. Wang H et al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388: 1459-544. [ Links ]

11. Murray CJL, Rajaratnam JK, Marcus J, Laakso T, Lopez AD. What Can We Conclude from Death Registration? Improved Methods for Evaluating Completeness. PLoS Med 2010; 7(4): e1000262. [ Links ]

12. Hill K, Queiroz B. Adjusting the general growth balance method for migration. Rev Bras Estud Popul 2010; 27(1): 7-20. [ Links ]

13. Bhat PNM. General growth balance method: a reformulation for populations open to migration. Popul Stud 2002; 56(1): 23-34. [ Links ]

14. Queiroz BL, Sawyer DOT. What can the mortality data from the 2010 Census tell us? Rev Bras Estud Popul 2012; 29(2): 225-38. [ Links ]

15. Ahmed S, Hill K. Maternal mortality estimation at the subnational level: a model-based method with an application to Bangladesh. Bull World Health Organ 2011; 89: 12-21. [ Links ]

16. Alkema L, You D. Child Mortality Estimation: a Comparison of UN IGME and IHME Estimates of Levels and Trends in Under-Five Mortality Rates and Deaths. PLoS Med 2012; 9(8): e1001288. [ Links ]

17. Hill K, You D, Inoue M, Oestergaard MZ. Child Mortality Estimation: Accelerated Progress in Reducing Global Child Mortality, 1990-2010. PLoS Med 2012; 9(8). [ Links ]

18. Szwarcwald CL, Leal MC, Andrade CLT, Souza Jr. PRB. Estimação da mortalidade infantil no Brasil: o que dizem as informações sobre óbitos e nascimentos do Ministério da Saúde? Cad Saúde Pública 2002; 18(6): 1725-36. [ Links ]

19. Frias PG, Szwarcwald CL, Souza Junior PRB, Almeida WS, Lira PIC. Correção de informações vitais: estimação da mortalidade infantil, Brasil, 2000-2009. Rev Saúde Pública 2013; 47(6): 1048-58. [ Links ]

20. Hill K, Trussell J. Further Developments in Indirect Mortality Estimation. Popul Stud 1977; 31(2): 313-34. [ Links ]

21. Agostinho CS, Queiroz BL. Estimativas da mortalidade adulta para o Brasil no período 1980/2000: uma abordagem metodológica comparativa. ABEP 2008. [ Links ]

22. Paes NA. Quality of death statistics by unknown causes in Brazilian states. Rev Saúde Pública 2007; 41(3): 436-45. [ Links ]

23. França E, Abreu DX, Rao C, Lopez AD. Evaluation of cause-of-death statistics for Brazil, 2002-2004. Int J Epidemiol 2008; 37(4): 891-901. [ Links ]

24. Paes NA. Avaliação da cobertura dos registros de óbitos dos estados brasileiros em 2000. Rev Saúde Pública 2005; 39(6): 882-90. [ Links ]

25. Paes NA, Albuquerque MEE. Evaluation of population data quality and coverage of registration of deaths for the Brazilian regions. Rev Saúde Pública 1999; 33(1): 33-43. [ Links ]

26. Moura EC, Gomes R, Falcão MTC, Schwarz E, Never ACM, Santos W. Gender inequalities in external cause mortality in Brazil, 2010. Ciênc Saúde Coletiva 2015; 20(3): 779-88. [ Links ]

27. Pereira FNA, Queiroz BL. Diferenciais de mortalidade jovem no Brasil: a importância dos fatores socioeconômicos dos domicílios e das condições de vida nos municípios e estados brasileiros. Cad Saúde Pública 2016; 32(9). [ Links ]

28. Abreu DMX, César CC, França EB. Diferenciais entre homens e mulheres na mortalidade evitável no Brasil (1983-2005). Cad Saúde Pública 2009; 25(12): 2672-82. [ Links ]

Financial support: Bill & Melinda Gates Foundation (GBD Global) and Ministry of Health (GBD 2015 Brazil-states), through the National Health Fund (Process No. 25000192049/2014-14). Project for mortality estimates and construction of life tables for small regions in Brazil (1980-2010) - Ministry of Science, Technology, Innovation and Communications (MCTI)/National Council for Scientific and Technological Development (CNPq)/Ministry of Education (MEC)/ Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES)/Applied Social Sciences (Process No. 470866/2014-4) and MCTI/CNPq/Universal 14/2014 (Process No. 454223/2014-5).

Received: December 13, 2016; Accepted: March 06, 2017

Corresponding author: Bernardo Lanza Queiroz. Departamento de Demografia e Centro de Desenvolvimento e Planejamento Regional. Universidade Federal de Minas Gerais. Avenida Antônio Carlos, 6.627, Campus da Pampulha, CEP: 31270-901, Belo Horizonte, MG, Brasil. E-mail:

Conflict of interests: nothing to declare

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