What can be Done with Incomplete Civil Registration Data: Potential and Pitfalls

Kenneth Hill Harvard University Center for Population and Development Studies, 9 Bow Street, Cambridge MA 02138, USA. E-mail: kenneth_hill@harvard.edu

Introduction Complete civil registration, processed in a timely fashion in combination with reasonable accurate population counts from periodic censuses or population registers is the preferred source of information for monitoring population health. However, complete civil registration is limited to developed countries and a small number of generally middle income developing countries. Disappointingly, the number of developing countries with complete civil registration systems, even using the relatively low bar of 90 percent coverage adopted in United Nations publications, has increased only slightly over the last 40 years. Given this situation, the question arises of what can be done with data from incomplete registration systems. The key assumption underlying any systematic use of incomplete registration data is that the events that are registered are approximately representative of all events. Given this assumption and the additional assumption that coverage is not changing substantially over time, the trends in registered events, be they

IPM

sS

essi

ons

B

IPM

sS

essi

ons

births or deaths, can be taken as reflecting true trends, even though levels will be incorrect. However, in general the assumption of constant coverage needs to be evaluated. Given the key assumption, formal and flexible methods have been developed for estimating levels of completeness by comparison with other data sources. For example, births can be compared against changes over time in the number of children women report having given birth to, information often collected in population censuses. Similarly, deaths by age can be compared against intercensal changes in populations by age, again available from successive censuses, though the assumption that registered deaths are representative may be implausible for early childhood. These methods remain valid even if registration completeness is changing, but provide estimates of completeness that refer to an intercensal period, giving information about trends only by repeated application to successive intercensal intervals. These methods are illustrated by application to data from four countries. The Republic of Korea is one country that has improved its registration system from the 1970s to cover all births and deaths. Brazil has achieved complete birth and death registration in most parts of the country, but some poorer areas lag behind. Egypt has a long history of registration, but coverage of deaths in early childhood has been weak. Finally, South Africa has put great emphasis on improving its registration system, providing an example of some of the pitfalls of rapidly-expanding coverage.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Evaluating the Completeness of Birth Registration The completeness of birth registration can be assessed by comparison with two external pieces of information: the numbers of young children recorded in, say, a population census and the number of children women in nationally-representative surveys report having given birth to. The first comparison involves the reverse-projection of the population of young children to birth, which requires estimates of child mortality; it is also sensitive to the quality of census reporting of young children, a group often affected by substantial under-enumeration. I will therefore focus on the second comparison. Brass (1964) first proposed a formal method for comparing current fertility (in the form of age-specific fertility rates, ASFRs) to lifetime fertility (in the form of reports by women of the number of children ever born). If reporting is accurate, fertility is not changing and there are no selection effects operating, the cumulated ASFRs to a given age will be equal to the average number of children ever born (average parity P) by women of that age. Since both ASFRs and average parity are usually tabulated for five-year age groups, cumulated ASFRs indicate lifetime fertility at ages 20, 25, 30, etc., whereas average parities indicate average lifetime fertility for age groups 15-19, 20-24, 25-29, etc. Brass’s P/F Ratio method provided factors based on model age patterns of fertility to obtain average parity equivalents F by interpolating between successive values of cumulated ASFRs; these F’s could then be

IPM

sS

essi

ons

B

IPM

sS

essi

ons

compared to the recorded P’s for 5-year age groups. Brass further argued that the ratios P/F could be used as adjustment factors for the recorded ASFRs: if registration of births does not vary by age of mother, the ASFRs will have the correct age pattern but not necessarily the correct level, and if reporting of children ever born by younger women is correct, but not necessarily the reporting by older women, the P/F ratios for younger women can be used to correct the ASFRs across all age groups. Here we use interpolation factors proposed in United Nations Manual X (1983).

The potential of the method is clear: that birth registration data that are not complete can be used to estimate fertility accurately, with applications to small areas possible. However, the pitfalls are also evident. First, the key assumption, that registered events are representative of all events, is unlikely to be met if registration is highly deficient; it is not possible to set a firm floor on an acceptable minimum level, but it seems likely that, in situations where fewer than 50 percent of births are registered, the pattern of events will be affected by selection biases. The second key assumption, that fertility has been constant, is acceptable for very few countries; under conditions of fertility decline, adjusting current ASFRs by lifetime fertility will over-estimate fertility. Fortunately, if data on children ever born are available for two points in time, lifetime fertility for a synthetic inter-survey cohort can be calculated by differencing cohort P’s (Zlotnik and Hill; 1981), and the effect of changing fertility removed.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

These two techniques are illustrated in Table 1 for the four countries examined. In each case two estimates are shown: a “concurrent” estimate, using average parities from a census (Brazil, Republic of Korea) or nationally-representative survey (Egypt, South Africa) and age-specific fertility rates (ASFRs) obtained from estimates published in the Demographic Yearbook 1997 Historical Supplement Table 6 (except for South Africa, for which the female population is obtained from the large 2007 Community Survey); and a “synthetic cohort” estimate, for which intercensal or intersurvey estimates of “parity” are calculated from cumulated cohort changes in average parity, and ASFRs are obtained by averaging ASFRs at the beginning and end of the period. P/F ratios are shown for age groups 20-24 to 45-49, excluding the age group 15-19 for which the interpolation methods work poorly. The “completeness” estimate in the last line is the average of the P/F ratios for the age groups 25-29 and 30-34. Brazil 1980 and 1991 Birth registration in Brazil is reported as being “incomplete” during the period studied. The “concurrent” P/F ratios rise from 1.56 for the age group 25-29 to 2.44 for the age group 45-49, consistent with declining fertility, but suggesting a completeness of birth registration in 1991 of only 61%. The “synthetic cohort” ratios for the period 1980 to 1991, on the other hand, are basically flat for the age groups 25-29 to 45-49, and suggest a completeness of 73%; the effect of declining fertility on the P/F ratios has been effectively removed by the use of the “synthetic cohort” method. The resulting completeness estimate of 73% is high

IPM

sS

essi

ons

B

IPM

sS

essi

ons

enough to support the assumption that reported events are representative of all events and justify adjustment. The adjusted Total Fertility Rate for the period 1980 to 1991 is 3.22 children per woman. The classification of birth registration in Brazil during this period as “incomplete” seems to be supported.

Table 1: Concurrent and “synthetic cohort” P/F Ratios for Four Countries, 1980s to 2000s.

Age Brazil Egypt Republic of Korea South Africa Group P/F Ratios P/F Ratios P/F Ratios P/F Ratios x,x+4 1991 1980-1991 1992 1988-1992 1990 1985-1990 2007 2001-2007

20-24 1.59 1.52 2.54 2.13 0.90 0.62 1.44 1.4425-29 1.56 1.39 1.65 1.40 1.13 0.92 1.22 1.1630-34 1.69 1.37 1.45 1.20 1.26 0.97 1.24 1.2235-39 1.88 1.37 1.42 1.14 1.48 0.96 1.34 1.2740-44 2.13 1.37 1.49 1.08 1.78 0.97 1.48 1.4045-49 2.44 1.34 1.57 1.07 2.16 0.96 1.54 1.33

Completeness 0.61 0.73 0.64 0.77 0.84 1.06 0.81 0.84TFR (reported) 1.83 2.34 3.85 4.65 1.58 1.62 2.11 2.11TFR (Adjusted)1 2.99 3.22 5.98 6.06 1.89 1.54 2.60 2.52

1 Adjusted by the average P/F ratio for women 25-29 and 30-34

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Egypt 1988 to 1992 Birth registration in Egypt is reported as being “complete” during the period studied. No census estimates of children ever born by age of mother are available for this period, so the average numbers of children ever born from the 1988 and 1992 Demographic and Health Surveys have been used (Sayed et al., 1989; El-Zanaty et al., 1993). The “concurrent” P/F ratios for 1992 show no clear trend, dropping from age group 25-29 to age group 35-39, and then rising again; the estimated completeness is only 64%. The “synthetic cohort” ratios for the period 1988 to 1992 on the other hand drop consistently with age, from 1.40 for women 25-29 to 1.07 for women aged 45-49; the estimated completeness is somewhat higher, at 0.77, but using this estimate to adjust the reported TFR gives an adjusted estimate of 6.06, much higher than the “synthetic cohort” parity for women aged 45-49 of 4.95. The 1988 DHS estimates TFR for the 3 years before the survey as 4.38, whereas the 1992 survey estimates 3.93; the 1992 estimate is almost identical to the estimate from registered births in 1992, whereas the average of the 1988 and 1992 estimates is actually somewhat lower than the estimate from registered births in 1988 and 1992. Something has clearly gone wrong with the P/F ratio method: the age pattern of the ratios suggests that the assumption of representativeness is incorrect, and that births to younger women are less likely to be registered than births to older women.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Republic of Korea, 1985 and 1990 Birth registration in the Republic of Korea is reported as being “complete” at least from 1975 onwards. Column 6 of Table 1 shows concurrent P/F ratios calculated for 1990. The “synthetic cohort” P/F ratios are calculated for 1985 to 1990, with the “synthetic cohort” parities being calculated from parity changes between the 1985 and 1990 censuses, and the ASFRs being averaged between 1985 and 1990. The “concurrent” P/F Ratios rise steeply from the age group 25-29 to 45-49, suggestive of sharply dropping fertility. The “synthetic cohort” P/F Ratios, on the other hand, are basically flat from 25-29 to 45-49, but average a little below 1.0. It seems likely that births are actually recorded slightly more completely than the population census counts in this setting, resulting in a slight upward bias in age-specific fertility rates. Using the small adjustment, the TFR for the period 1985 to 1990 is estimated as 1.54.

South Africa 2001 and 2007 South Africa has made a major effort over the last decade to improve the quality of birth and death registration. No births or birth rates are reported to the United Nations, but unofficial numbers of registered births are available by age of mother for 2005 and 2006. A census in 2001 and a large Community Survey in 2007 recorded data on children ever born; ASFRs were calculated from the registered births in 2006 divided by the female population by age estimated from the 2007 Community Survey, the same ASFR’s being used for both the “concurrent” and the “synthetic cohort” applications. The P/F Ratios for the “concurrent”

IPM

sS

essi

ons

B

IPM

sS

essi

ons

application rise with age from 25-29 to 45-49, consistent with rising fertility; the average ratio for the age groups 25-29 and 30-34 indicates an estimated completeness of birth registration of 81%. The “synthetic cohort” ratios rise by a similar amount from 25-29 to 40-44 as the “concurrent” ratios, though at slightly lower levels, though the 45-49 ratio then drops, largely because the average parity of women aged 45-49 in the 2007 survey is smaller than that of women 40-44 in the 2001 census, resulting in a negative cohort increment; the average ratio for the age groups 25-29 and 30-34 indicates an estimated completeness of birth registration of 84%. Using the average “synthetic cohort” ratio to adjust the 2006 Total Fertility Rate results in an estimate for the period 2001 to 2007 of 2.52. It seems reasonable to conclude that birth registration has improved to close to the “complete” threshold of 90 percent, but not yet quite attained it, at least on average for the period 2001 to 2007. The age pattern of rising “synthetic cohort” P/F ratios may most plausibly be explained in terms of a substantial fertility decline between 2001 and 2007, such that the 2006 rates are well below the average fertility of the intersurvey period.

Summary The analysis of these four data sets suggests that in general the P/F Ratio approach can be used to assess the completeness of birth registration and provide plausible estimates of overall fertility. The assumption of constant fertility can be overcome using the “synthetic cohort” approach as long as two series of average

IPM

sS

essi

ons

B

IPM

sS

essi

ons

parity data are available, though it must be understood that the completeness estimate is then an average over the period between the two series. The key assumption, that registered events are representative of all events in terms of age distribution, is more problematic, though a major deviation from this assumption can be expected to show up in the age pattern of “synthetic cohort” P/F Ratios, as is suspected in the case of Egypt. Evaluating the Completeness of Death Registration A number of methods have been proposed to estimate the completeness of death registration relative to population counts by comparing age distributions of deaths with age distributions of the population using fundamental equations of demographic dynamics. Early methods (Brass 1975; Preston and Hill 1981) assumed population stability, though most developing country populations were by then far from stable. The 1980s saw the development of a number of flexible methods for estimating such coverage, using information on intercensal age-specific growth rates to replace the assumption of stability (Bennett and Horiuchi, 1981; Hill, 1987). The description below is intended to give a broad understanding of how the methods work; for a full description, see Hill et al. (2009) The Bennett and Horiuchi (1981) approach uses age-specific growth rates above age x to expand the number of deaths at each age above x to arrive at an estimate of the population of age x. This approach can be thought of as a “synthetic cohort” analog of Vincent’s (1951) method of extinct generations, and will be described henceforth as the Synthetic Extinct Generations (SEG) method. Heuristically, the deaths at each

IPM

sS

essi

ons

B

IPM

sS

essi

ons

age above x are adjusted for the cumulative population growth rate between x and the ages of the deaths to convert them into a stationary population equivalent. When population coverage is not constant between two censuses, the change in census coverage introduces a constant bias in the estimated growth rates: this can be addressed by adjusting the SEG method for an estimate of census coverage change derived from the GGB method below or as suggested by Bennett and Horiuchi (1981). The methods assume that the population is not affected by migration. Hill’s (1987) General Growth Balance (GGB) method is a generalization of the Brass (1975) Growth Balance method to all populations not affected by migration. The Demographic Balancing Equation expresses the identity that the growth rate of the population is equal to the difference between the entry rate and the exit rate. This identity holds for open-ended age segments x+, and in a population closed to migration the only entries are through birthdays at age x. The “birthday” rate x+ minus the growth rate x+ thus provides a residual estimate of the death rate x+. If the residual estimate can be calculated from population data from two population censuses and compared to a direct estimate using registered deaths, the completeness of death recording relative to population recording can be estimated. The intercept of the straight line fitted to the range of points estimates the constant error in age-specific growth rates resulting from systematic change in census coverage.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

In their simple form, the death distribution methods (DDM’s) make strong assumptions: that the deaths that are registered are approximately representative in terms of age distribution of all deaths; that reporting of age in the censuses and reporting of age in the registered deaths are approximately correct; and that the population is closed to migration. It should also be noted that the methods only provide estimates of adult mortality for intercensal periods. Table 2 shows applications of the GGB and adjusted SEG (SEG-Adj, using the GGB estimate of census coverage change to adjust the population data, and then applying the SEG approach) methods to data by sex for the four countries already examined. In each case a single evaluation (the estimated coverage of registered deaths relative to population) factor is shown based on points for each of two age ranges: 5+ to 65+ and 15+ to 55+; a summary index, the probability of dying between 15 and 60,

45q15, is shown based on each adjustment. Brazil 1980 and 1991 The data for Brazil cover the period 1980 to 1991. For males, the choice of age range for fitting makes no difference regardless of the methodology used; GGB indicates a slight over-registration of deaths relative to population recording of about 1.5%, whereas SEG-Adj indicates a relative under-recording of about 2.5%. GGB reduces the observed 45q15 of 0.251 (25.1%) to 0.247, whereas SEG-Adj increases it to 0.253; the differences are negligible. For females, the story is slightly different: there is a difference of about 5% in the coverage estimate given by GGB depending on the age range of points chosen, from almost exact agreement

IPM

sS

essi

ons

B

IPM

sS

essi

ons

using the age range 5 to 65 to an estimated 4.5% coverage excess of deaths relative to population using the age range 15 to 55. For SEG-Adj, on the other hand, both age ranges give very similar results and indicate almost perfect consistency of reporting between population and registered deaths. As for males, differences in adjusted 45q15 are negligible, ranging from the highest adjusted value of 13.5% to the lowest of 12.9%. Egypt 1986 to 1996 The data for Egypt consist of population censuses carried out in 1986 and 1996, with registered deaths from 1986 to 1992; data from 1993 to 1996 were not readily available. As in the Brazil example, the SEG-Adj estimates are hardly affected by the choice of age range for which coverage is computed; in all cases the estimates are negligibly different from 1.0, indicating a high degree of consistency between the population counts and the registered deaths. The GGB estimates vary more by the age range chosen for fitting, the 5+ to 65+ range indicating lower coverage for males than the 15+ to 55+, and vice versa for females. All the estimates indicate however that registration of adult deaths in Egypt in the late 1980s and early 1990s qualified as “complete” by the 90 percent standard. The range of the estimates of 45q15 is also quite small, from 23.1% to 24.9% for males, and from 15.7% to 18.3% for females; the mid-point of these ranges seems a perfectly acceptable estimate for both males and females.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Table 2: Evaluation (Estimated Coverage of Registered Deaths) and Adjustment of Death Registration Data.

Indicator Brazil Egypt Republic of Korea South Africa 1980-1991 1986-1996 1970-75 2001-2007 GGB SEG-Adj GGB SEG-Adj GGB SEG-Adj GGB SEG-Adj a) Males

Coverage Fitted to: (i) 5 to 65 1.016 0.975 0.946 1.010 0.989 1.003 0.898 0.881

(ii) 15 to 55 1.015 0.976 1.021 1.017 0.913 0.995 0.963 0.912

45q15: Observed 0.251 0.251 0.235 0.235 0.336 0.336 0.536 0.536 Adjusted (i) 0.247 0.253 0.249 0.233 0.333 0.334 0.575 0.589 Adjusted (ii) 0.247 0.253 0.231 0.233 0.361 0.337 0.536 0.569 b) Females

Coverage Fitted to: (i) 5 to 65 0.999 1.003 1.054 1.017 0.779 0.807 0.562 0.543

(ii) 15 to 55 1.045 0.999 0.900 0.984 0.739 0.803 0.598 0.560

45q15: Observed 0.134 0.134 0.167 0.167 0.191 0.191 0.419 0.419 Adjusted (i) 0.135 0.134 0.157 0.163 0.236 0.231 0.620 0.641 Adjusted (ii) 0.129 0.134 0.183 0.169 0.249 0.232 0.583 0.622

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Republic of Korea, 1970 and 1975 Between the 1960s and the 1980s, the Republic of Korea changed the classification of registered deaths from “incomplete” to “complete”. Table 2 examines estimated registration completeness for the period 1970 to 75 to explore whether this change was justified. As in the Brazil example, the SEG-Adj estimates are hardly affected by the choice of age range for which coverage is computed; for males, the estimated completeness estimate is almost exactly 100%, whereas for females it is almost exactly 80%. The GGB estimates vary more by fitting range, and also on average indicate somewhat lower coverage than the SE-Adj estimates. Overall, the estimates agree however that as of the beginning of the 1970s, death registration had reached the threshold of completeness for males but had not at that point reached it for females. Probabilities of dying between 15 and 60 are estimated to be approximately 33.5% for males and approximately 23.2% for females.

South Africa 2001 and 2007 South Africa has invested considerable effort in the era of majority rule in improving its civil registration system. Table 2 shows the evaluation of numbers of registered deaths in 2001 and 2005 in comparison to the 2001 Population Census and a large sample survey, the “Community Survey”, conducted in 2007. Once again, the SEG-Adj methodology shows itself less affected than GGB by choice of fitting range, but in this instance GGB estimates somewhat higher coverage. The registration of male deaths in this period is estimated to be about 90% complete, on the cusp of the 90 percent criterion, whereas completeness of

IPM

sS

essi

ons

B

IPM

sS

essi

ons

registration of female deaths is much lower, only about 57%. The adjusted probabilities of dying between 15 and 60 are very high, about 57% for males and about 60% for females. It is important to note that the South Africa example is not using two population censuses in the analysis, but rather a population census and a large (about 2%) household survey; mixing the information on age distribution from two different types of data collection activity is hazardous, and adds to the caution needed in interpreting results. Summary The application of evaluation methods to assess the completeness of adult death registration appears to be successful in settings where a high proportion of deaths are registered and net migration is negligible, although there is no available “gold standard” against which the adjusted estimates can be compared. In the cases examined, the key assumption (proportionately equal coverage by age) appears to be valid, and net migration does not seem to have had a big effect. Four points should be noted however: first, estimates pertain to average coverage in an intercensal interval, and not to an individual year; second, the estimates presented here are averages, and in practice the full age detail of the estimates should be reviewed for possible evidence that the assumptions are not valid; third, the methods are sensitive to the assumption that net migration is negligible; and fourth, the assumption of proportionate errors may be plausible for deaths of adults, but may not be for deaths of children, for whom coverage errors may be higher. The next section examines this last issue.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Are Estimates of the Completeness of Adult Death Registration Appropriate for Child Deaths? The GGB and SEG-Adj methods applied above compare age patterns of deaths by age to age patterns of population change by age. Deaths of children have little or no influence on the comparison. A pitfall of estimating coverage of deaths after childhood is to assume that the same coverage applies to children. In Table 3, estimates of the Under-5 Morality Rate (U5MR, the probability of dying by age 5) are derived from each of the applications in Table 2, applying the coverage estimate to the observed age specific mortality rate

5M0 for the age group 0 to 4, and then converting that rate into a probability of dying between 0 and 5; the U5MRs are then compared with estimates from other sources for the same time period. These other estimates are generally available for both sexes combined, so the adjusted age-specific rates have been combined assuming a sex ratio at birth of 105 males per 100 females.

In the case of Brazil, the adjusted mortality under age 5 is little more than half the average value from other sources for the same time frame, suggesting lower coverage of child than post-childhood deaths. For Egypt, the adjusted mortality is somewhat lower. For South Africa, the adjusted mortality is much higher than the alternative source of data (an indirect estimate from the 2007 Community Survey). No alternative source was available for the Republic of Korea. On the basis of these comparisons, it appears that adjustment factors derived from the evaluation methods described above should not be used to adjust deaths under age 5. It seems likely that the key assumption – of constant proportionate error – does not hold reliably for young children.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Table 3: Comparison of Under-5 Mortality Rates Derived from the Adjusted Death Rate Under Age 5 with Other National Sources.

Brazil Egypt Republic of Korea South Africa Period: 1980-91 1986-96 1970-75 2001-2007 Males 5M0 observed 0.0107 0.0145 0.0033 0.0179 Coverage Estimate 0.9955 0.9986 0.9751 0.9137 Adjusted 5M0 0.0107 0.0145 0.0034 0.0196 Estimated 5q0 0.0526 0.0703 0.0170 0.0942 Females 5M0 observed 0.0089 0.0152 0.0031 0.0164 Coverage Estimate 1.0114 0.9888 0.7820 0.5657 Adjusted 5M0 0.0088 0.0154 0.0040 0.0290 Estimated 5q0 0.0433 0.0745 0.0199 0.1372 Combined 5q0 0.0481 0.0724 0.0184 0.1152 Estimate from other sources: 0.078 0.082 N/A 0.065

Note: Other sources were (Brazil) DHSs of 1986 and 1996, Census of 1991; (Egypt) DHSs of 1992, 1997 and 1998; (South Africa) Indirect

estimates from the 2007 Community Survey

IPM

sS

essi

ons

B

IPM

sS

essi

ons

Conclusion This paper has examined the potential (and some of the pitfalls) of demographic methods for evaluating the completeness of civil registration systems, and for adjusting the numbers of registered events if necessary. A number of assumptions are made by these methods, including the key one that the recorded events are representative of all events, but often it will be evident from the results that the assumptions do not hold. It is also possible to circumvent some assumptions, such as that of constant fertility in the P/F Ratio method. The pitfalls arise from pushing beyond plausible limits of the assumptions, the assumption of negligible net migration being particularly important for the evaluation of registered deaths. REFERENCES

[1] Bennett, N.G. and S. Horiuchi. 1981. "Estimating the Completeness of Death Registration in a Closed Population." Population Index 47(2):202-221.

[2] Brass W. 1964. Uses of census or survey data for the estimation of vital rates. (E/CN.14/CAS.4V57). Paper prepared for the African Seminar on Vital Statistics, Addis Ababa, 14-19 December 1964.

[3] Brass W. 1975. Methods for Estimating Fertility and Mortality from Limited and Defective Data. Chapel Hill: International Program of Laboratories for Population Statistics.

[4] El-Zanaty F., H.A. Sayed, H.H.M. Zaky, A.A. Way .1993. Egypt Demographic and Health Survey 1992. Columbia MD: Macro International Inc.

[5] Hill, K. 1987. "Estimating Census and Death Registration Completeness." Asian and Pacific Population Forum 1(3):8-13, 23-24.

IPM

sS

essi

ons

B

IPM

sS

essi

ons

[6] Preston, S. and K. Hill .1980. Estimating the Completeness of Death Registration. Population Studies 34(2).

[7] Sayed H.A., M.I. Osman, F. El-Zanaty, A.A. Way .1989. Egypt Demographic and Health Survey 1988. Columbia MD: Institute for Resource Development/Macro Systems Inc.

[8] United Nations .1983. Manual X: Indirect Techniques for Demographic Estimation. ST/ESA/SER.A/81. Population Studies, No. 81. Department of International Economic and Social Affairs. New York: United Nations.

[9] United Nations. 2002. Methods for Estimating Adult Mortality. Department of Economic and Social Affairs, Population Division. ESA/P/WP.175.

[10] United Nations. 2005. World Population Prospects: The 2004 Revision. Sales No. E.01.XIII.20.

[11] Vincent P. 1951. La mortalité des vieillards. Population 6(2): 181-204.

[12] Zlotnik H. and K. Hill .1981. The use of hypothetical cohorts in estimaiting demographic parameters under conditions of changing fertility and mortalitiy. Demography Vol. 18(1): 103-122.

IPM

sS

essi

ons

B

IPM

sS

essi

ons