metadata: authors: 0: author: Bulatao, Rodolfo A.
1: author: Stephens, Patience W.
docna: 0: docna: Global estimates and projections of
            mortality by cause, 1970-2015
docty: Policy Research Working Paper
subtopic: Population & Development,Disease Control & Prevention,Reproductive Health,Cancer,Law and Justice Institutions
teratopic: Health, Nutrition and Population
abstracts: cdata!: The authors report estimates and
            projections of deaths by cause for major world regions,
            based on data from country reports to the World Health
            Organization and regression models. They report mortality
            rates for seven major causes: infectious and parasitic
            diseases, neoplasms, circulatory system diseases,
            complications of pregnancy, certain perinatal conditions,
            injury and poisoning, and other causes. Some more specific
            causes are reported on. They give estimates for six age
            groups by sex for four years (1970, 1985, 2000, and 2015)
            and six country groups: industrial market economies,
            industrial nonmarket economies, Latin America and the
            Caribbean, sub-Saharan Africa, the Middle East and North
            Africa, and Asia and the Pacific. Among their findings: The
            population over 45 in developing countries is projected to
            more than double between 1985 and 2015, rising from 17 to 24
            percent of the population. Causes of death, which are
            closely related to age at death, must change accordingly.
            Infant mortality in developing countries is projected to
            fall from 78 per thousand in 1985 to 43 per thousand in 2015
            and life expectancy at birth in developing countries is
            projected to rise by five years. The leading causes of death
            for the world as a whole for both 1970 and 1985 were
            infectious and parasitic diseases and circulatory system
            diseases - with the first more important in developing
            countries, and the second more important in developed
            countries. Certain perinatal conditions were also more
            important for developing countries, but accounted for only a
            fourth or a fifth as many deaths in 1985. Neoplasms were
            more important in developed than in developing countries.
            Deaths from infectious diseases are expected to decline as a
            percentage of deaths; proportionate deaths from diseases of
            the circulatory system are expected to rise. The greatest
            number of deaths will continue to be in Asia, where almost
            half of all deaths in the world take place. This proportion
            is not projected to change. Better data on causes of death
            are essential. The World Health Organization is working with
            countries to strengthen their cause-of-death information
            systems as an essential support for health monitoring.
repnme: repnme: Global estimates and projections of
            mortality by cause, 1970-2015
display_title: Global estimates and projections of
            mortality by cause, 1970-2015
listing_relative_url: /research/1992/10/699559/global-estimates-projections-mortality-cause-1970-2015
topicv3: Emergency Obstetric Care m1326113 1454,Cancer m1326342 1431,Injury m1327524 1428,Life Expectancy m1504363 2666,Mortality m1504365 3661
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Health, Nutrition and Population
origu: Pop & Human Resources Department
no_of_pages: 92
model_extractions: <!-- Start of picture text --> Policy Research<br>Population, Health, and Nutrition<br>WPS 1007<br><!-- End of picture text --> This paper- a product of the Population Policy and Advisory Service, Population and Human Resources - Department was prepared as background for the Health Sector Priorities Review. Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Otilia Nadora, room S6-065, extension 31091 (October 1992, 83 pages).

Bulatao and Stephens report estimates and projections of deaths by cause for major world regions, based on data from country reports to the World Healt, Organization and regression models. They report mortality rates for seven major causes: infectious and parasitic diseases, neoplasms, circulatory system diseases, complications of pregnancy, certain perinatal conditions, injury and poisoning, and other causes. Some more specific causes are reported on. They give estimates for six age groups by sex for four years (1970, 1985, 2000, and 2015) and six country groups: industrial market economies, industrial nonmarket economies, Latin America and the Caribbean, Sub-Saharan Africa, the Middle East and North Africa, and Asia and the Pacific.

# Among their findings:

* The populadon over 45 in developing countries is projected to more than double between 1985 and 2015, rising from 17 to 24 percent of the population. Causes of death, which are closely related to age at death, must change accordingly.

* Infant mortality in developing countries is projected to fall from 78 per thousand in 1985 to 43 per thousand in 2015 and life expectancy at

birth in developing countries is projected to rise by five years.

> * The leading causes of death for the world as a whole for both 1970 and 1985 were infectious and parasitic diseases and circulatory system diseases - with the first more important in developing countries, and the second more important in developed countries. Certain perinatal conditions were also more important for developing countries, but accounted for only a fourth or a fifth as many deaths in 1985. Neoplasms were more important in developed than in developing countries.

* Deaths from infectious diseases are expected to decline as a percentage of deaths; proportionate deaths from diseases of the circulatory system are expected to rise.

* The greatest number of deaths will continue to be in Asia, where almost half of all deaths in the world take place. This proportion is not projected to change.

* Better data on causes of death are essential. The World Health Organization is working with countries to strengthen their cause-of-death information systems as an essential support for health monitoring.

ThePolicy Research Working Paper Series disseminates thefindings of work under way in the Bank. Anobjectiveofthe series is to get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy.

Produced by the Policy Research Dissemination Center
# GLObAL ESTIMATES **AND** PROJECTIONS OF MORTALITY BY CAUSE, 1970-2015

_RWolfo A. Bulatao and Patience W. Stephens_
# Contents

AcInowledg!nents ........ ............................. iv Background .... .............. .........................

1

|M ethod ...................................................<br>2|
|---|
|Groupingcausesof<br>death.................................<br>2|
|Dataoncaes of<br>death..................................<br>3<br> <br>|
|Estimating<br>andprjectting<br>nwtaity<br>.............<br>.....<br>4|
|Predictmortaityrates<br>bycause<br>..............................<br>4|
|Results<br>.......................................<br>5<br>|
|Thedemnographic<br>backgrmd.. ............................<br>.<br>5|
|<br>Cunrentcauses<br>of<br>death<br>...................................<br>6|
|Trendsinmajor<br>cauesof<br>death .......................<br>........<br>13|
|Age-sexspecfic<br>patemns ...........<br>.................<br>17|
|Discsson<br>..<br>.........................................<br>18|
|AnnexA. MeIthodakqy<br>............<br>.......................<br>21|
|Dataoncauses<br>ofdeat ...............................<br>23|
|Projectinug<br>nrtaiy.......................<br>..........<br>23|
|<br>Predicft<br>deafs bynajor<br>caue..<br>...........................<br>26|
|Estimatn<br>deahis<br>byspecific<br>nue ............<br>.<br>.<br>27|
|<br>Redasifying<br>deaths onunspefed causes<br>.. ..................<br>.<br>28.8|
|Annex B. Suppleenmtay<br>Tabls .................................. 28|
|Annex<br>C. ExpertAessmens...........<br>..<br>.................<br>68|
|Diardea.<br>........................................<br>69|
|Polio<br>........................................<br>.<br>.<br>.<br>76|
|Yelow fever,<br>degue, andencephalts<br>. .......................<br>77|
|<br> <br>Malaia<br>..........................................<br>78|
|Schistosontiasis<br>and ffialasis<br>.... ...........................<br>79|
|Complications<br>ofpregnancy<br>..................<br>80|
|<br> <br>Diabtes.<br>........................................<br>81|
|References<br>...........................................<br>81|
# List of Tables

|Table 1.<br>Table 2.<br>Table 3.<br>Table 4.<br>Table 5.<br>Table 6.<br>Table 7.<br>Table 8.<br>Table 9.<br>Table 10.<br>|Classification of causes of death and corresponding International<br>Classification of Diseases, Injuries, and Causes of Death (ICD)<br>categories ...........................................<br>Estimated and projected mortality rates (per 100,000), by major<br>cause, sex, and region, 1970-2015.....................<br>.<br>Deaths by major and specific cause (in thousands), by region,<br>1985 ..............................................<br>Age-standardized mortality rates (per 100,000) for major and<br>specific causes, by region, 1985.......................<br>Comparison of regression estimates of mortality rates and deaths<br>from particular causes and expert assessments, all developing<br>countries, 1985.................. .............<br>Ratio of deaths from circulatory system diseases to deaths from<br>infectious and parasitic diseases, by region, 1970-2015.... ..<br>Percentage distribution of deaths by major cause in 1985 and<br>incremental changes expected by 2000 and 2015 from three<br>factors, world and developed and developing countries ...<br>.....<br>Percentage distribution by major cause of all deaths, deaths under<br>65, and potential years of life lost, world and developed and<br>developing countries, 1970-2015.............<br>Percentage of regional population covered by reports to WHO or<br>sample surveys, by year ................................<br>Predicted and reported percentage distributions of deaths by<br>cause for reporting countries grouped by region, 1985.... ..<br>|2<br>...<br>7<br>10<br>....<br>11<br>.......<br>12<br>.....<br>15<br>..<br>16<br>19<br>.....<br>20<br>|
|---|---|---|
|Table Al.<br>Table A2.<br>Table A3.<br>TableB1<br>Table B2.<br>Table B3.<br>Table B4.<br>Table B5.<br>Table B6.|Regional grouping of countries and territories .................<br>Countries or territories with reliable reports on causes of death,<br>and year of data used, by region ..........<br>..<br>..............<br>Countries or territories with less reliable reports on causes of<br>death, year of data used, and indices of coverage and data<br>quality, by region .................<br>.PopulationiLmillions by age and sex, major world regions, 1970-<br>2015 ......................<br>..................<br>Estimates and projections of fertility, mortality, and population<br>growth for major regions in selected quwnquennia .....<br>.........<br>Mortality rates per 100,000 from major causes, by age, sex, and<br>region, 1970-2015................<br>............<br>Mortality rates per 100,000 from major causes, by age, sex, and<br>region, 1970-2015................................<br>Mortality rates per 100,000 from specific causes by age, sex, and<br>region,1985<br>.................**.**...............<br>Deaths in thousands from specific causes by age, sex, and region,<br>1985.........................................|22<br>24<br>25<br>......<br>29<br> <br>31<br>.32<br>....<br>44<br>......<br>56<br>.....<br>62|

ii
|Table Cl. Comparison of esfimated deaths<sup>from certain specific causes in</sup><br>developing countries around 1985 with Walsh<sup>assessment ....</sup><br>...<br>Table C2. Expert assessments of mortality rates<sup>(per 100,000) and deaths (in</sup><br>thousands) for some specific causes, by age,<sup>sex, and region,</sup><br>1985 ..............................................|.. 68<br>70|
|---|---|
|List of Figures||
|Figure 1. Life expectancyby region ...............................<br>Figure 2. Wfant mortality by region<sup>...............................</sup>|6<br>6<br>|
|<br>Figure 3. Mortality by cause, world, 1970-85<sup>.........................</sup><br>Figure 4. Deaths by cause, developed countries,<sup>1970-2015....</sup><br>.....<br>Figure 5. Deaths by cause, developing<sup>countries, 1970-2015....</sup><br>.....|9<br>......<br>13<br>.....<br>14|

iii
# Acknowledgments

Alan D. Lopez conrtribted the base data and his Isights, critquing the argument and suggeswt imptant poinb. Expert assesmet for specific diseases or comments on the regression estimates were provided by David Dunlop, Richard Feachem, B. Robert Greenberg, Scott B. _Haistead,_ Dean T. Jamison, Berrihard Liese, Jose Martinez, Alberto Tones, and Patck Vaughn, as well as by other participants at meetings for the World Bank health sector priorties review. However, they are not responsible for the specific figures reported here, which have been reVsed for consistency with the present hamework.

IV
Estimates and projections of deaths by cause for major world regions are reported here. The sources for these estimates are country reports to the World Health Organization (WHO) and regression models.

Mortality rates will be reported for seven major causes-infectious and parasitic diseases, neoplasms, circulattty system diseawes, complications of pregnancy, certain perinatal conditions, injurv and poisoning, and other causes-and for more specific causes under some headings. For the major causes, predictive equations depending on the overall mortality level were previously estimated to supplement reported data; for the specific causes, WHO data and some new equations will be the basis.

Estimates were made for six age groups (0, 1-4, 5-14, 15-44, 45-64, and 65 and older) by sex for four years (1970, 1985, 2000, and 2015) and six country groupsindustrial market economies, industial nonmarket economies, Lafin America and the Caribbean (LAC), Sub-Saharan Afica, the Middle East and North Africa (IMENA), and Asia and the Pacific. Clsfication of countries as industral or developing (Annex A) is as of 1985.

The objective, approach, and background of the exercise are discussed; the methodology is described; current and projected distrbutions of death by cause are presented and contrasted among regions; and the reasonableness of and possible biases in the estimates are assessed.

# Background

The main objective of this exercise is to provide a comprehensive picture of the dsriution of deaths by underlying cause for 1985 and a gerneral perspective on how the distribution can be expected to change. We attempt to classify current deaths by both maor and specific cause, but project only the major causes into the future.

The approach is to summarize reports of causes of death to WHO and supplement these with regression estimates for nonreporting countries. An alternative would have been to consider diseases or disease groups one by one, building up a composite picture from the epidemiologicalliterature. Though disease experts have been canvassed for information on this literature, we do not rely primarily on this approach because it would lead to inconsistencies between estimates for different diseases and would provide overaU mortality rates at odds with other mortality data.

The approach taken follows work initiated by Preston (1976) and continued by Hakulinen and others (1986a, 1986b), whose age-sex specific equations for major causes of death are used here. This regression-based approach has also been applied to partcular areas, such as cancer deaths (Parkdn and others 1988).

Hakulinen and others estimated the distrbution of deaths by major cause as of 1980. We update their estimates to 1985, incorporate new data not available to them, attempt a more detailed clasification of causes, and provide perspectives on possible future trends.
2 _Estimates and PAijections of Mortality by Cause_

# Method

This section covers categories of causes of death; the nature and quality of the base data; the estimation and projection of mortality; the equations used to disaggregate mortality by major cause; and procedur; - for subdividing major causes into specific categories.

## _Grouping causes of death_

The categories for major causes of death shown in Table 1 are identical to those used by Hakulinen and others to permit the application of their equations. These categories require some explanation. Bronchitis, emphysema, and asthma are included among the infectious and parasitic diseases because of the important infectious bronchitis component, which was not separable from the others because of the way the Table 1. Classificatlon of causes of death and corresponding International Classificatlon of Diseases, Injuries, and Causes of Death (lCD) categories

|_Cau_|_si. of death category_|_ICD-8 (List A)_|_ICD-9 (Basic_<br>_tabulation list)_|
|---|---|---|---|
|_Maj_|_or CAUses_|||
|1|Infectious and parasitic diseases|A1-44, A99, A90-93|01-07, 320-323|
|2|Neoplasms|A45-61|08-17|
|3|<br>Circulatory system and certain degenerative<br>diseases|A80-88, A64, A98, A102,<br>A105-106|25-30, 181, 341,<br>347, 350|
|4|Complications of pregnancy|A112-118|<br>38-39, 41|
|5|<br>Perinatal conditions|A131-135|45|
|6|Injury and poisoning|AE138-150|E47-E56|
|7|<br>Other causes|Other codes|Other codes|
|_Spec_|_fc causes_|||
|<br>1.1|<br>Diarrhea|Al-5|01|
|1.2|Tuberculosis|A6-10|02|
|1.3|Acute respiratory infection|A15-17, A89-92|033-035, 320-322|
|<br>1.4|<br>Measles|<br>A25|<br>042|
|1.5|Chronic obstructive pulmonary disease (COPD)|A93|323-325|
|<br>1.6|<br>Polio|A22-23|040, 078|
|1.7|Yellow fever, dengue, and encephalitis|A26-27|<br>044-045|
|<br>1.8|<br>Malaria|A31|052|
|1.9|Schistosomiasis and filariasis|A39, A41|072, 074|
|1.10|Intestinal parasltes|A42-43|075076|
|<br>3.1|<br>Ischernc heart disease|A83|27|
|3.2|Cerebrovascular disease|A85|29|
|3.3|Other cardiovascular diseases|A80, A82, A84, A86-88|25, 26, 28, 30|
|3.4|Diabetes|<br>A64|<br>181|
|3.5|Certain degenerative diseases (nephrltis, cirrhosis of<br>the liver, ulcers of the stomach and duodenum)|A98, A102, A105, A106|341,347, 350|
|7.1|<br>Mental disorders|A69|210**-**212|
|7.2|Oral health diseases|A97|330|
|7.3|Mlcronutrient disorders|A62-63, A67|180, 193, 200|
|7.4|Malnutrition|A65|190-192|

Note: The specific diseases listed under infectious and parasitic diseases (1.1-1.10) and under other causes (7.1-7.4) are not meant to be comprehensive.
_Mdhad_ _3_ data were reported. Diabetes, nephritis, cirrhosis of the liver, and ulcers of the stomach and duodenum have been included among circulatory system diseases not because of any presumed simaty in etiology or pathogenesis but to keep the number of categories manageable by combining the degenerative diseases other than cancer.

Hakulinen and others also included in their analysis two subcategories for infectious and parasitic diseases: diarhea, gastritis, and enteritis; and influenza, pneumonia, and bronchitis. Only the diarrhea subcategory is maintained as a specific cause. The second subcategory is further refined into infectious and chronic components. Other subcategories for specific causes of death (Table 1) were chosen to break up the three largest of the major categories-infectious and parasitic diseases, circulatory system diseases, and other causes. Subcategories were chosen mainly for substantive interest. The diarrhea subcategory is duplicated among these specific causes, but the influenza, pneumonia, and bronchitis subcategory is replaced by otheis somewhat more specific. These breakdowns also allow distinction of the specific causes just noted that fit awkwardly into the major categories.

Among the specific causes, not all could be defined witS precision. For micronutrient disorders, for instance, the codes selected from the revision currently in use (the ninth) of the International Statistical Classification of Diseases, Injuries, and Causes of Death (ICII-9; VHO 1977) were thfose for disorders of hie thyroid gland, aneemias, and avitamntosis. This group of causes may be both too broad and too narrow in different ways, but further specification was not possible.

# _Data on causes of death_

Statistics on causes of death, by sex and age, based on the International Class-5cation of Diseases are provided annually to WHO by some 70 countries or territories. In principle, the cause of death returns should be comparable between countries since they are based on a common set of procedures for coding and certifying the cause of death. In practice, however, the comparability of data across countries is affected by variations in diagnostic preferences, cultural factors, medical training, the availability of diagnostic aids, and other factors.

In addition, the reliability of national cause of death statistics is a matter of concern. Broadly speaking, reliability depends on coverage and quality. Deaths not covered by the vital registration system are most likely those in more remote areas with a cause of death structure typical of high mortality populations. Thus countries with incomplete coverage are likely to report a cause of death structure biased towards the chronic diseases pattem more commonly found in urban areas; the greater the incompleteness, the more biased the data are likely to be. However, of even greater significance with respect to reliability is the extent of medical certification of the cause of death, which ensures data qualty. In remote areas with few if any physicians, cause of death is frequently certified by lay personnel who have little or no medical training. Diagnosis is uncertain and many deaths may be coded to symptoms and ill-defined conditions.
4 _Esffmatme and Poetios of Morality by Cause_

# Further details about the reliability of the data and the incorporation of estimates from subnationai information can be found in Annex A.

The reports on cause of death will be used as they are in tis paper, without attempdng corrections such as regrouping codes or reallocating the undefined causes. We rely on the original WHO procedures for scrutinizing the data before including them in their mortality database, and do not attempt any reclassification. Nor do we attempt the adjustments that might be needed to take associated or contributory conditions into account. It is difficult to nredict how the importance of associated causes will alter as countries progress throur,t the epidemiological transition. Certainly under the regime of infectious diseases, malnutrition will frequently underlie many deaths from diarrheel diseases or acute respiratory infections. On the other hand, as death Is increasingly postponed to older ages, multiple pathologies at or near the time of death become relatively common. As a result, this paper can only concem itself with reported distributions of underlying causes of death.

## _Estimating and projecting mortality_

Before estimating deaths by cause, overall mortality must be estimated and projected. This was done country by country, for 187 countries, territories, or groups of small countries or territories covering the entire world (but only aggregate results are reported). Life expectancy and infant mortality estimates for the 1985-90 quliquennium were obtained from the best available sources; adjustments were made as needed for agreement with other demographic parameters; and both forward and backward population projections were made.

Each country's experience with mortality change is used to project its mortality over the next three quinquennia (1990-2005), after which each country reverts to the average mortality trend for the world as a whole. This average trend involves slower improvements as life expectancy rises. The procedure involves separate projections of life expectancy (for each sex) and infant mortality (for both sexes combined), the imposition of nonlinear trends on both, and the choice of "split' life tables. Further description of the procedures is provided in Annex A.

The projections using these mortality trends are the 'standard' Bank projections (see Bulatao and others 1990). Two types of alternative projections were also run: 'fixed mortality' projections, in which age-specific mortality rates (for five-year age groups) are taken as fixed at 1985-90 levels throughout the projection period; and 'fixed distriution' projections in which mortality changes as in the standard projections, but the distribution of deaths by cause within each of the six larger age groups does not change from 1985. These alternative projections allow some decomposition of projected changes in the cause of death structure.

# _Predicting mortality rates by cause_

The equations for major causes of death predict mortality rates by cause from age and sex specific mortality rates for all causes. These equations are all lnear. Because some of the age groups covered a broad range of ages, slight variations in the equations
_Mdhod_ S were produced to take into account differences among 24 world regions in age structure within these age groups. This was not necessary for age groups 0 and 14, for which therefore only world equations are available. The derivatlon of these equations is explained in Hakulinen and others (1986a), and they are further described in Annex A.

These equations were used to predict mortality rates by cause wherever repoited data were not available. The reported data themselves were adjusted proportionally where necessary to provide the overall mortality levels estimated by the Bank.

New regression equations were estimated for mortality rates from 21 specific causes, using the rate for the major cause under wllch each falls as the predictor. These 21 causes include the 19 listed in the second part of Table 1 and two 'other' subcategories, under infectious and parasitic diseases and under other causes, estimates for which were obtained as residuals from the major causes. No 'other' subcategory is needed under circulatory system diseases because the subcateores are already comprehensive. The regression procedure is explained in Annex A.

As was done for the major causes, the equations were first used to estimate mortality rates by cause, age, sex, and country, and for each age-sex group in each country, rates were adjusted proportionally if necessary to provide the expected totals. Deaths from ill-defined causes were not reclassified under other categories, but estimates were made of the maximum possible increase in each category from such reclassification. Annex A provides details.

Some of the equations were clearly less robust than those for the major causes. They appear especially unreliable for various tropical diseases prevalent In regions that are poorly represented in the WHO database. Experts on partcur diseases were shown the regression estimates and asked about appropriate adjustments. The responses varied from acceptance of the estimates to detailed recommendations for revision, based on survey evidence of cases and case-fatality rates and on individual judgments. Since the recommendations sometimes appeared considerably at variance with reported deaths and regression estimates, they are presented and discussed separately.

# Results

The demographic background and projecied trends in overall morlity will be described, and then estimates of current mortality by canse will be presented. Next, trends in the major causes of death will be considered, and patterns of causes of death by age and sex will be discussed.

## _lhe demographkc background_

Population estimates and vital rates for each of the six regions, drawn from the Bank projections, are provided in Annex B. As will be shown, demographic variables contribute to important dhanges in cause of death dist butions. For instance, the population in deveilping countries over 45 is projected to more than double between 1985 and 2015, rising from 17 to 24 percent of the population. Causes of death, which
_6_ _Edstlatt and Projecdions of Mortality by Cause_ are dosely related to age at death, must change accordingly. Mortality from all causes will change, with infant mortality in developing countries projected to fall from 78 per thoand in 1985 to 43 per thousand in 2015 and life expectancy at birth in developing countries projected to rise by five years. This too implies changes in causes of death, which vary, by mortality level.

Projected trends in life expectancy and infant mortality, both showing continual improvement, are represented in Figures 1 and 2. Based on worldwide and individual country experience of mortality change, these projections effectively assume that factors that have produced improvement in the past, whether socioeconomic or medical, will continue to produce improvement in the future. No country was allowed to retrogress in these projections, although retrogression is of course possible. Even with projected improvements, however, regional differentiation will remain sharp: by 2015, life .:xpectancy in Sub-Saharan Africa will have barely caught up with 1985 life expectancy in the Middle East and North Africa, and will not have caught up with 1985 life expectancy in any other region.

Current regional crude death rates vary as one would expect, beirg dearly highest in Sub-Saharan Africa and lowest in Latin America and the Caribbean. The latter region has more young people than the developed country regions, which accounts for its lower risk of death. With the projected improvements in life expectancy, the crude death rate is not expected to fall monotonically. Once the rate reaches a point around 5 to 10 per thousand. regions generally experience a bottoming out of decline and then a slight increase in deaths as their elderly populations increase. Given these trends, variability across regions in crude death rates is projected to diminish considerably by 2000 and 2015.

# _Current causes of death_

Estimated mortality rates by major cause are shown in Table 2 by sex and region, but wnthout age breakdowns. (Three Asian subregions-India, China including Taiwan, Hong Kong, and Macao, and other Asia are also shown.) Patterns for 1970 and 1985 will be considered first. The leading causes of death for the world as whole for both 1970 Figure 1. U* expectancy by region Figure 2. Infant mortality by region <!-- Start of picture text --> 60 1480<br>Is. .s<br>S.~~~~~~~~~~~~~~~~~~~~~~~~o<br>50,<br>450<br>40 1067 "" "6f i- 106-70- 18540 200o-0 iou-a<br><!-- End of picture text -->
_References_ _7_ Table 2. EstImated and projected mortality rates (per 100,000), by major cause, sex, and region, 1970-2015

||_1_<br>|_970_<br>|_1_<br>|_9850_<br>|0<br>|<br>|20<br> <br>|15|
|---|---|---|---|---|---|---|---|---|
|_Region and cau_|_Male_|_Female_|_Male_|_Female_|_Mak_|_Femak_|<br>_Male_|_Female_|
|_World_|||||||||
|AU causes<br>|1293<br>|1281|<br>1064|1004|<br>863|802|880|<br>776|
|Infections|449|449|318|294|176|179|140|<br>133|
|Neoplasms<br>|95<br>|96<br>|108<br>|96<br>|108<br>|98<br>|128<br>|<br>114<br>|
|Circulatory<br>|297<br>|324|262|286|292|283|339|<br>314|
|Pregnancy|0|13|0|9|0|9|0|7|
|<br>Perinatal|<br>86|<br>70|<br>79|<br>59|<br>48|<br>36|<br>37|27|
|lijury<br>|93<br>|40<br>|97<br>|56|78|31|79|32|
|Other|273|289|201|204|161|167|157|<br>150|
|_Developed_<br>**_Countries_**|||||||||
|<br>AU causes|1054|1069|<br>1W|1013|997|963|1161|<br>1059|
|Infections|146|112|109|74|78|59|90|63|
|Neoplasms<br>|167<br>|163<br>|203<br>|172<br>|182<br>|170<br>|213<br>|188<br>|
|Circulatory|463|552|473|563|486|536|575|597|
|<br>Prepancy|0|2|0|1|0|<br>1|<br>0|1|
|<br>Perinatal|26|10|15|10|13|9|13|7|
|Injury|99|51|87|40|77|37|80|39|
|Other<br>|153|180|161|154|160|152|191|163|
|_Develping Conties_|||||||||
|<br>All causes|1383|1373|<br>1070|1001|830|759|823|714|
|Infections|564|595|382|368|200|211|150|148|
|Neoplasms<br>|68<br>|68<br>|78<br>|70<br>|90<br>|79<br>|111<br>|98<br>|
|CIrculatory|234|225|198|192|244|216|291|252|
|<br>Pregnancy|0|18|0|12|0|<br>11|<br>0|9|
|<br>Perinatal|109|96|98|75|56|43|42|31|
|Injury|91|35|100|62|78|29|79|30|
|Other|318|336|213|221|162|171|150|147|
|_Indusal Aiaet_|||||||||
|All causes|1036|1021|986|950|1007|943|1173|<br>1045|
|Infections<br>|106|85|82|66|64|47|68|38|
|Neoplasms<br>|186<br>|169<br>|240<br>|192<br>|196<br>|171<br>|236<br>|200<br>|
|Circulatory|500|567|461|518|513|551|615|639|
|<br>Pregnancy|0|0|0|0|0|0|0|0|
|<br>Perlnatl<br>|21|7|8|5|10|6|10|5|
|Injury|98|58|74|40|70|36|74|40|
|Other|125|135|120|128|154|131|171|123|
|_Nonmarkd_|||||||||
|All causes|1089|1155|1162|1126|980|1000|1139|1082|
|Infections|224|159|158|88|103|79|128|106|
|Neoplasms|129|152|136|135|158|169|173|168|
|<br>Crculatory|392|524|495|644|437|509|505|526|
|<br>Pregnancy|0|4|0|3|0|2|0|2|
|Perinata<br>|37<br>|15|28|17|20|13|19|11|
|Injury|100|40|109|39|90|38|90|37|
|<br>Other|209|260|237|200|172|189|225|231|
|_Latin Amerio_**_a_**_nd C_<br>_Jbe_|_m_||||||||
|All causes|1097|903|883|706|677|557|722|594|
|Infections|366|301|211|177|100|86|67|55|
|Neoplasnms|79|76|76|70|<br>94|<br>86|<br>122|109|
|<br>Circulatory|238|214|228|1%|242|215|306|275|
|<br>Pregancy|0|12|0|6|0|4|0|3|
|Perinatal<br>|61<br>|42<br>|65<br>|44<br>|40<br>|28<br>|30<br>|20<br>|
|Injury|98|31|90|29|76|28|78|29|
|<br>Other|<br>255|<br>227|<br>213|<br>184|<br>124|<br>111|<br>119|102|
_8_ _Edbnate and Projectiom of Mortality by Cause_ Table 2 (continued)

||_1_<br>|_970_<br>|_1_<br>|_985_<br>|_20_<br>|_00_<br>|_20_<br>|_1_<br>|
|---|---|---|---|---|---|---|---|---|
|_Region and ease_|_Male_|_emal_|_Male_|_Fmale_|_Male_|_Femae_|_Male_|_Femaje_|
|_Sub-Snm_<br>_Afice_|||||||||
|ADl caues|2163|1882|<br>1727|1448|1196|<br>1024|<br>947|<br>785|
|Infections|1070|937|817|683|498|430|346|<br>286|
|Neoplasns|52|57|52|55|54|55|60|60|
|<br>Circulatory|243|226|2D9|<br>191|182|169|180|<br>162|
|<br>Pregnay|0|27|0|21|0|17|0|14|
|Perinata|200|157|167|129|119|90|82|61|
|Injury|108|39|96|34|86|30|82|28|
|<br>Other<br> <br>|491|438|386|334|258|233|1%|174|
|_Mlk_<br>_Eastand North Aftia_|||||||||
|<br> <br>All causes|1563|152)|1184|1121|775|733|691|<br>624|
|Infections|624|<br>653|459|473|2D9|<br>237|142|<br>164|
|Neoplasms|60|56|65|60|69|62|81|70|
|<br>Crcuatory|250|224|200|183|191|171|209|176|
|<br>Pregnancy|0|21|0|13|<br>0|<br>12|<br>0|10|
|<br>Perlnata|140|126|120|97|73|57|52|39|
|Injury|90|37|80|32|75|28|76|28|
|<br>Other<br>|400|404|260|263|157|<br>166|<br>131|137|
|_Ada_|||||||||
|AMl causes|1280|1342|963|946|784|736|833|734|
|hnfecdons|506|577|319|323|149|176|110|119|
|Neoplasms|70|70|85|74|101|87|130|113|
|<br>Crculatory|<br>230|<br>227|<br>191|<br>194|<br>268|<br>235|<br>338|292|
|<br>Pregnany|0|17|0|11|0|10|0|8|
|<br>Pednatal|98|91|88|67|42|32|30|22|
|Injury|87|34|105|78|77|29|79|31|
|<br>Other<br>_bdia_|289|327|175|199|147|167|145|149|
|All causes|1491|1575|1158|1165|879|790|846|745|
|Irdections|600|707|478|476|215|239|152|175|
|Neoplasms|70|66|43|<br>51|<br>88|<br>74|<br>108|91|
|<br>Cin~uLatory|270|249|145|126|253|2D4|295|239|
|<br>Pregnanc|0|27|0|22|0|12|0|10|
|<br>Perinatal|123|122|168|132|60|48|40|30|
|Injury|96|35|85|65|82|28|84|29|
|Other|332|369|239|293|180|185|167|171|
|All causes|978|1115|777|793|700|693|W|738|
|Infections<br>|354<br>|449<br>|186<br>|2D4<br>|63|104|48|46|
|Neoplasms|76|78|_126_|98|123|103|167|144|
|<br>CIrculatory|205|224|216|249|306|276|417|368|
|<br>Pregnacy|0|8|0|2|0|7|0|4|
|<br>Pelnata|63|60|34|22|23|17|18|13|
|Injury|78|34|127|111|71|30|72|34|
|<br>Other|203|263|87|106|114|156|125|129|
|_her Asia_|||||||||
|Al causes|1603|1482|_1W_|938|802|739|793|715|
|Ifections|686|657|354|338|206|213|150|158|
|Neoplasms|<br>59|<br>59|<br>67|<br>63|<br>79|<br>76|<br>102|95|
|<br>Ciulatory|228|<br>2D6|<br>2D4|<br>182|<br>226|<br>209|<br>274|246|
|<br>Pregnancy|0|21|0|14|0|13|0|10|
|<br>Perinatal<br>|133<br>|110<br>|81|62|49|36|35|25|
|Injury|94|35|90|36|81|28|84|29|
|<br>Oher|<br>403|<br>394|<br>251|<br>244|<br>160|<br>163|<br>149|152|
_Ruudis_ 9 and 1985 were infectious and parasitic diseases and circulatory system diseases, the first more important in developing countries and the second more important in developed countries. Like infectious and parasitic diseases, certain perinatal conditions were much more important for developing countries, but over all countries accounted for only a fourth or a fifth as many deaths in 1985. Like circulatory system diseases, neoplasms were more important in developed than in developing countries, but over all countries accounted for only a third as many deaths. The other causes category and injury and poisoning provide weak contrasts between developed and developing countries, and complications of pregnancy accounts for a small proportion of deaths.

Figure 3 compares these results with estimates that Hakulinen and others (1986a) made for 1980. Although the equations were the same, Hakulinen and others incorporated earlier reported data for fewer countries. Nevertheless, results are generally consistent, with their estimated rates for 1980 usually being intermediate between our 1970 and 1985 estimates. Comparisons for specific regions are complicated by some differences in country groupings, but also show general agreement. For SubSaharan Africa, Hakulinen and others did assume slightly higher overall mortality levels than we use, but their distribution of deaths across causes is still similar to ours.

Taken at face value, these estimates also indicate that substan' _A_ change can take place in a short period. For developing countries, the mortality rme for infectious and parasitic diseases is estimated to have declined 17 percent from 1970 to 1980, and 22 percent from 1980 to 1985.

Breakdowns for 1985 of the three largest categories of major causes are summarized in Table 3, which gives numbers of deaths for both major and specific causes. Table 4 provides mortality rates standardized using the 1985 world age structure. (Annex B gives rates and deaths by sex, age, and region.) Figure 3. Mortality by cause, world, 1970-85 <!-- Start of picture text --> 400<br>40<br>40<br>o 1<br>Eol l |<br>so,<br>WuIi_ Naqu s | uI k~<br><!-- End of picture text -->
_Estimates and Projectioms of Mortality by Cause_ 10 Table 3. Deaths by major and specific cause (in thousands), by region, 1985

|_Cause_|_World_|_Devel-_<br>_oped_|_Devel-_<br>_oping_|_Indus-_<br>_trial_|_Non-_<br>_market_|_LAC_|_Sub-S_<br>_haran_<br>_Africa_|_Middle_<br>_East_<br>_a- and_<br>_North_<br>_Africa_|_Asia_|
|---|---|---|---|---|---|---|---|---|---|
|All causes|49899|12047|37852|<br>7313|<br>4735|3183|<br>7203|<br>4314|23151|
|Infectious, parasitic|14764|<br>1061|13704|<br>558|503|778|<br>3403|1743|<br>7780|
|<br>Diarrhea|2997|20|2977|5|15|201|<br>1158|<br>507|<br>1q11|
|Tuberculosis|844|39|805|13|25|48|119|76|<br>562|
|Acute respiratory|5549|422|5127|271|151|286|<br>1407|<br>741|<br>2693|
|<br>Measles|421|1|420|0|1|16|196|87|<br>121|
|COPD|1943|334|1608|248|87|113|<br>226|160|<br>1110<br>|
|Polio|25|1|25|0|0|2<br>|3<br>|2<br>|18<br>|
|Yellow fever|8|0|8|0|0|0|2|1|5<br>|
|Malaria|146|0|146|0|0|6|20|16|<br>105|
|Schistosoniiasis|12|0|12|0|0|0|0|1|10|
|Intestinal parasites|133|3|130|0|2|7|41|18|<br>65|
|<br>Other Infectious|2686|240|2446|20|221|99|230|135|<br>1981|
|Neoplasrns|4903|2190|2714|1629|<br>560|294|<br>242|235|<br>1943|
|<br>Circulatory|13208|<br>6075|7133|3704|2371|848|<br>909<br>|715<br>|<br>4661<br> <br>|
|<br>Ischemnic<br>heart|3948|2426|1522|1407|<br>1019|213|<br>216|19G|<br>904|
|Cerebrovascular|3813|1547|2266|873|674|176|<br>193|158<br>|<br>1738<br> <br>|
|Other cardiovascular|3705|1603|2103|1075|<br>527|302|<br>347|254|<br>1199|
|Diabetes|507|159|348|129|30|62|55|42|<br>189|
|Certain degenerative|1235|340|895|220|120|96|97|70|<br>631|
|<br>Pregnancy|225|8|218|0|7|12|48|23|<br>134|
|<br>Perinatal|3321|143|3178|51|92|218|<br>672|408|<br>1880|
|Injury, poisoning|3694|729|2965|429|299|239|<br>294|212|<br>2220|
|<br>Other|9784|1842|7941|941|902|795|<br>1635|<br>978|<br>4534|
|Mental disorders|95|46|50|36|10|5|4|3|38|
|Oral health diseases|3|1|2|0|0|1|0|0|1|
|Micronutrient|252|42|210|20|23|23|45|27|115|
|Malnutrition|372|26|346|6|20|24|67<br>|37|<br>218<br>|
|Unspecified|9061|1728|7333|879|849|742|<br>1519|911|<br>4162|

As noted earlier, chronic obstructive pulmonary disease, though it is not infectious, was **included** for convenience among the infectious and parasitic diseases. This is one of the four specific causes that dominate this major category. The other three are diarrhea, acute respiratory infections (pneumonia, influenza, acute bronchitis, whooping cough, and diphtheria, but not measles, which has been separated), and other infectious and parasitic diseases. In every region, these four account for<sup>at least</sup> nine out of ten **deaths** from **this** major cause. Tuberculosis and measles account for a few percent more, and the remaining categories are quite rare. Among<sup>the four</sup> dominant causes, the balance varies considerably across regions. A major contrast<sup>is the</sup> greater importance of chronic obstructive pulmonary disease in developed regions<sup>and</sup> the greater importance of diarrhea in developing regions. Acute respiratory<sup>infections,</sup> being important in both developed and developing regions, overall is responsible for a larger share of deaths than either of these two causes. The predominance of these four specific causes in these estimates accurately reflects the data reported to WHO.<sup>For</sup> instance, for reporting Latin American countries, acute respiratory infections<sup>account</sup> for a quarter to a half of all deaths due to infectious diseases in each age-sex group,<sup>and</sup>
_Reslts_ _11_ Table 4. Age-standardized mortality rates (per 100,000) for major and specific causes, by region, 1985

|_Cause_|_World_|_Devel-_<br>_oped_|_Devel-_<br>_oping_|_Indus-_<br>_trial_|<br>_Non-_<br>_market_|_LAC_|_Sub-Sa_<br>_haran_<br>_Afr*a_|_Middle_<br>_East_<br>_- and_<br>_Noith_<br>_Afr*a_|_Asia_|
|---|---|---|---|---|---|---|---|---|---|
|AlU causes<br>|1046<br>|692|1147|<br>578|894|901|<br>1621|<br>1243|1077|
|Infectious, parasitic|308|77|386|43|126|199|<br>658|422|350|
|Diarrhea|62|2|78|1|5|48|221|114|47|
|Tuberculosls<br>|18|3|25|1|5|14|<br>33|24|25|
|Acute respiratory<br>|116<br>|29|141|20|40|72|258|173|120|
|Measles<br>|9|0|10|0|0|4|31|17|5|
|COPD<br>|41|18|54|18|16|33|54|49|56|
|Polio<br>|1|0|1|0|0|0|0|0|1|
|Yellow fever|0|0|0|0|0|0|0|0|0|
|Malaria|3|0|4|0|0|1|3|4|5|
|Schistosomiasis|0|0|0|0|0|0|0|0|0|
|Intestinal parasltes|3|0|3|0|1|2|7|4|3|
|Other infectious|56|24|69|3|59|26|50|35|88|
|Neoplasms<br>|103|117|92|125|97|91|86|92|93|
|Clculatory<br>|280|298|255|260|381|272|328|297|237|
|Ischemicheart<br>|84|119|55|99|164|69|85|82|46|
|Cerebrovascular<br>|81<br>|74|84|59|106|57|74|68|91|
|Other cardiovascular<br>|<br>78|78|73|75|86|97|119|103|59|
|Diabetes|11|8|12|9|5|20|20|18|10|
|Certain degenerative|26|19|30|17|21|29|30|26|30|
|Pregnancy|5|1|6|0|2|3|11|7|5|
|Perinatal|69|20|77|12|32|48|89|76|79|
|Injury, poisoning|77|56|83|51|67|64|71|61|94|
|Other|205|123|248|87|189|223|377|288|219|
|Mental disorders|2|2|2|2|2|2|2|1|2|
|Oralhealth diseases|0|0|0|0|0|0|0|0|0|
|Mlcronutrient|5|3|6|2|4|7|12|9|5|
|Malnutrition<br>|8|3|9|0|6|6|11|8|9|
|Unspecified|190|115|231|83|177|209|352|269|202|

Note: Rates are standardized using the 1985 world age structure.

acute respiratory infections and diarrhea combined account for three-fourths of deaths under five.

Among circulatory system diseases, ischemic heart disease, cerebrovascular disease, and other cardiovascular diseases are nearly equal in importance for the world as a whole. Regionally, ischemic heart disease is responsible for the largest share of circulatory system disease deaths in developed regions; cerebrovascular disease has the largest share in Asia; and other cardiovascular diseases have the largest share in the remaining developing regions. All these categories are important everywhere, however: each always accounts for a fifth or more of the deaths under the major category. Diabetes is of lesser importance in these estimates, with less than 5 percent of deaths under the major category, and nephritis, cirrhosis of the liver, and ulcers of the stomach and duodenum account for roughly twice this proportion.
_12_ _Estimates and Projections of Mortality by Cause_ For the other causes category, an attempt was made to distinguish mental disorders, oral health diseases, micronutrient deficiencies, and malnutrition. Combined these accounted for under 10 percent of. other causes, however, leaving a large remainder unspecified.

Experts were asked to comment on the regression estimates. For some causes, they provided their own assessments or suggested useful data. Mainly they recommended increases in deaths from particular causes of 130 to 270 percent. The largest of these increases was for malaria, and progressively smaller increases were recommended for yellow fever, polio, schistosomiasis, and complications of pregnancy (rable 5). For diabetes, a reduction of 6 percent was recommended. For diarrhea, a proportionally trivial reduction was recommended, but with a substantial shift in deaths toward younger ages. On the order of 700 thousand deaths could be moved, per the expert assessments, from over age five to under age five. Although the recommended change in the total number of deaths from all these causes combined is modest, substantial shifts do occur for particular age groups.

Could the regression estimates be too low because all causes of death are underreported? This cannot be the explanation for the discrepancies in Table 5 because the regression estimates have been adjusted to provide the correct overall mortality levels.

If deaths from ill-defined causes were reclassified under other headings, could the regression estimates be raised to the level of the expert assessments? The answer depends on how the ifl-defined deaths are redistributed. If they are simply redistributed proportionally across all other categories, each category would increase only about 10 percent, well below the increase required to match the expert assessments. On the other hand, the ill-defined deaths might be assigned to only a few categories, on the assumption that the accuracy of reporting varies. We estimated the maximum number of deaths in each category if as many of the ill-defined deaths as possible were included in it. (These maximum estimates are not consistent, since they add up to substantially Table 5. Comparison of regression estimates of mortality rates and deaths fro= particular causes and expert assessments, all developing countries, 1985

||_Rates pe_|_r 100.000_||_Deaths (000_|_)_|_Ratio:_<br>|_Recommend-_<br>|
|---|---|---|---|---|---|---|---|
|_Cause_|_Regres-_<br>_sion_|_Expert_|_Regres-_<br>_sion_|_Maxi-_<br>_mum_|_Expert_|_Regression_<br>_Expert_|_l ed change in_<br>_deaths (000)_|
|Diarrhea<br>|81.2|78.4|2977|na|2876|1.0|-101|
|Polio|0.7|2.1|25|143|77|3.1|52|
|Yellow fever|0.2|0.7|8|54|26|3.3|18|
|Malaria|4.0|14.6|146|557|537|3.7|390|
|Schistosomiasis|<br>0.3|0.9|12|92|34|2.9|22|
|Pregnancy|5.9|13.4|218|403|492|2.3|274|
|Diabetes|9.5|8.7|348|na|319|0.9|-29|

na - not applicable.

Note: Maximum deaths are obtained by adding to the initial esdmates all possible deaths from il-defined causes.
_Resul_ _13_ more than the total deaths.) The column of maximum estimates in Table 5 shows the results. In principle, the expert assessments could be attained if substantial numbers of deaths from il-defined causes were reclassified under these specific categories. This does not hold in one case: for pregnancy complications, the number of ill-defined deaths among women 15-44 is too small to allow the regression estimates to be adjusted upward sufficiently. In this case, the expert assessments could be correct only if deaths from complications of pregnancy are misclassified under other defined causes.

This does not establish that the expert assessments are correct-it merely shows one way most of them could be made consistent with the WHO database. Essentialy the assessments were based on estimates of numbers of cases, whether from survey data or from informed judgments. Different sources of error are attached to reports of cause of death and to estimates from surveys focusing mainly on morbidity. Surveys may allow greater care in identifying cases, but typicaUy often require additional assumptions, generaUy from inadequate data, about case-fatality rates. Therefore, choosing between the regression estimates and the expert assessments is difficult, and details of each are provided separately-the latter in Annex C, which discusses them further.

# _Trends in major causes of death_

Given uncertainties in figures for specific causes, only the major causes are projected into the future. Figures 4 and 5 shows how the actual numbers of deaths are expected to change for developed and developing countries. The two most important major causes show opposite trends, infectious diseases declining from causing 35 percent of deaths in 1970 to causing 16 percent of deaths in 2015, while diseases of the circulatory system rise, from causing 24 percent of deaths in 1970 to causing 39 percent of deaths in 2015. The infectious disease trend is mainly due to lower mortality from this cause in developing countries, whereas the circulatory disease trend is due to higher mortality from this cause in both developed and developing countries. A Figure 4. Deaths by cause, developed countries, 1970-2015 <!-- Start of picture text --> CL<br>In.<br>14.<br>M1170 II1BS M2000 lO015<br><!-- End of picture text -->
_14_ _Estimates and Projections of Mortality by Cause_

# Figure 5. Deaths by cause, developing countries, 1970-2015

<!-- Start of picture text -->
[-90=E 1~985 M 2000 2015<br><!-- End of picture text --> convenient inidex for sumnun ig these changes is the ratio of deaths from circulatory system diseases to deaths ftom infectious and parasitic diseases. For the world as a w.hole, this ratio is estimated at 0.7 for 1970, 0.9 for 1985, 1.6 for 2000, and 2.4 for 2015.

Of the remaiIiing five major causes of death, two follow the trends for these first two causes, certain perinatal conditions showing a decline parallel decline to that for inlfectious and parasitic diseases and neoplasms showing an increase parallel to that for rcliatrysystem diseases. The other causes category is responsible for more deaths than either of these causes and is expected to decline, but somewhat gradually, and possibly because of better reporting rather than actual change. Injury arnd poisoning, accounting for 5 to 10 percent of deaths, and complicadtons of pregnancy, accounting for under 1 percent of deaths, show no clear trend. All regions exhibit the same basic trends, the differences among them having to do rnairly with being more or less advanced in the process of epidemiological transition. Patternis and trends for Asia, the region with the largest population, are closest to those for the world as a whole, with Latin America and the Ca^ribean, indstralnonmarket econornies, and industria market econonmies successivelv more advanced, on the one hand, and the Middle East and North Africa and Sub-Saharan Africa successively less advanced, on the other. Table 6 gives the ratios of circulatory system deaths to infectious and parasitic disease deaths, which effectively summarize the regional contrasts.

The greatest numbers of deaths will continue to be in Asia, where ahnost half of all deaths in the world take place. This proportion is not projected to change. For all causes cornbined, in fact, each region will contribute about the same proportion of deaths in 2015 as in 1985. For particular causes, some changes are projected, however, with Asia contibuting smaller proportions of deaths from unfectious and parasitic diseases and perinatal conditions and larger proportions of deaths from circulatory system diseases and neoplasms. Sub-Saharan African deaths will increase in proportion for the first two of these causes, and industria market economy deaths will decrease
_15_ _Results_ Table 6. Ratio of deaths from circulatory system diseases<sup>to</sup> deaths from Infectious and parasitic diseases, by region, 19702015

|_Region_|_1970_|_1985_|2000|_2015_|
|---|---|---|---|---|
|World|0.69<br>|0.89<br>|1.62<br>|2.39<br>|
|Developed countries|3.98|5.73<br>|7.52<br>|7.69<br>|
|Developing countries|0.40|0.52<br>|1.12<br>|1.82<br>|
|Industrial market|5.63|6.64<br>|9.61<br>|11.88<br>|
|Induswtrial<br>nonmarket|2.44<br>|4.72<br>|5.24<br>|4.41<br>|
|Latin America and Caribbean|0.68|1.09|2.46|4.74<br>|
|Sub-Saharan Africa|0.23|0.27|0.38<br>|0.54<br>|
|Middle East and North Africa|0.37|0.41<br>|0.81<br>|1.26<br>|
|Asia|0.42|0.60<br>|1.55<br>|2.75<br>|
|India|0.40<br>|0.29<br>|1.01<br>|1.64<br>|
|China|0.53<br>|1.19<br>|3.52<br>|8.37<br>|
|Other Asia|0.32|0.56|1.04|1.69|

in proportion for the last two of these causes.

The projections of mortality by cause are not straightforward extrapolations<sup>from</sup> past experience, but involve a combination of population<sup>projections with predictive</sup> equations for mortality rates by cause. An alternative, much<sup>simpler, procedure would</sup> have been to take the change in percentage of deaths due<sup>to a given cause from 1970</sup> to 1985 and extrapolate this linearly into the future. This<sup>alternative procedure would</sup> have given quite different results: for the world as a whole<sup>by 2000, a larger share of</sup> deaths due to infectious and parasitic diseases (24<sup>instead of 21 percent), a</sup> correspondingly lower share due to circulatory system<sup>diseases (29 instead of 35</sup> percent), and smaller variations for the other causes. For specific<sup>regions, the differences</sup> would have been greater: for the Middle East and North Africa<sup>by 2015, for instance,</sup> a linear extrapolation would give 39 percent of deaths due<sup>to infectious and parasitic</sup> diseases, whereas the regression-based procedures give<sup>only 23 percent.</sup> Some insight into why the calculations come out as they do<sup>can be obtained by</sup> decomposing future changes in the distribution of deaths.<sup>Such changes maybe related</sup> to changes in the age-sex structure of the population, changes<sup>in mortality levels from</sup> all causes within age-sex groups, or changes in the distribution<sup>of deaths by cause</sup> within age-sex groups. Projections with fixed mortality or<sup>fixed distributions of deaths</sup> by cause can help distinguish these components of change,<sup>if one accepts the necessary</sup> assumptions: for instance, that mortality can change without<sup>a simultaneous change in</sup> the distribution of deaths by cause, or, in other words,<sup>that a similar proportional</sup> change in deaths across causes is conceivable. Table 7<sup>shows, first, the percentage of</sup> deaths due to each cause in 1985; second, the projected increase<sup>or decrease in this</sup> percentage (by 2000 and 2015) due to contemplated changes<sup>in the age-sex structure,</sup> assuming fixed mortality; third, the further projected increase<sup>or decrease in this</sup> percentage if mortality is allowed to decline but the distibution<sup>of deaths by cause is</sup> fixed within age-sex groups; and fourth, the further projected<sup>increase or decrease due</sup> to changes in the distribution of deaths by cause within<sup>age-sex groups. Totaling the</sup> components for 2000 for any given cause and adding the<sup>1985 figure gives the projected</sup> percentage of deaths due to that cause by 2000.
_16_ _Estimates and Projections of Mortality by Cause_ Table 7. Percentage distrihution of deaths by major cause in 1985 and incremental changes expected by 2000 and 2015 from three factors, world and developed and developing countries

||_1985_|_Perc_<br>|_entage_<br>_point c_<br>_by 2000 due t_|_hange_<br>_o_|_Perc_<br>|_entage_<br>_point c_<br>kg_2015 due t_|_hange_<br>_o_|
|---|---|---|---|---|---|---|---|
|_p_<br>_Region and cause di_|_ercentage_<br>_sttibution_|_Age-sex_<br>_structure_|_Mortality_<br> <br>_change_|_Distrtiu-_<br>_tion change_|<br>_Age-sex_<br>_stmeture_|<br>_Mortality_<br>_change_|_Distdbu-_<br>_tion change_|
|_World_||||||||
|Infections|29.6|-1.1|-2.0|-5.2|-1.4|-3.3|-8.4|
|Neoplasms|9.8|0.6|0.8|1.1|1.1|1.1|2.6|
|<br>Circulatory|26.5|2.2|2.9|2.9|3.3|4.4|5.3|
|<br>Pregnancy|0.5|0.1|-0.1|0.0|0.1|-0.2|0.0|
|<br>Perlnatal|6.7|0.8|-1.2|0.3|-1.8|-1.6|0.6|
|Injury|7.4|-0.8|-0.4|0.4|-1.1|-0.7|1.1|
|<br>Other|19.6|-0.3|0.0|0.4|-0.1|0.2|-1.2|
|_Developed_<br>_Countries_||||||||
|<br>Infections|8.8|-1.1|-0.2|-0.6|-1.1|-0.2|-0.6|
|Neoplasms|18.2|0.6|0.0|-0.9|0.8|-0.2|-0.7|
|<br>Clrculatory|50.4|2.5|1.1|-1.8|2.8|1.5|-1.8|
|<br>Pregnancy|0.1|0.0|0.0|0.0|0.0|0.0|0.0|
|<br>Perlnatal|1.2|-0.3|-0.2|0.4|-0.4|-0.2|0.3|
|Injury|6.1|-05|-0.6|0.9|-0.9|-0.8|1.0|
|<br>Other|15.3|-1.2|-0.1|2.0|-1.2|-0.1|1.9|
|_Devlopig Countne_|_s_|||||||
|<br>Infections|<br>36.2|-1.9|-1.8|-6.6|-3.0|-3.0|-10.8|
|Neoplasms|7.2|1.0|0.7|1.7|1.8|1.0|3.6|
|<br>Crculatory|18.8|3.2|2.6|4.3|5.2|3.9|7.4|
|<br>Pregnancy|0.6|0.1|-0.1|0.0|0.1|-0.2|0.0|
|<br>Perlnatal|8.4|-1.1|-1.3|0.3|-2.6|-1.8|0.7|
|Injury|7.8|-0.9|-0.3|0.2|-1.2|-0.6|1.1|
|<br>Other|21.0|-0.3|0.2|-0.1|-0.2|0.6|-2.1|

Table 7 indicates that the three components can operate in the same or in opposite directions. For instance, population aging, lower mortality (especially at younger ages), and changes in the distribution of deaths all contribute to the decline in infectious diseases. On the other hand, population aging and lower mortality reduce the importance of injury and poisoning, but distribution change raises their importance in relation to other causes of death.

WWch of the three components exerts the greatest effect varies considerably from cause to cause. The largest effect overall is that of distrbutional change on infectious and parasitic diseases, but in this case the other two components mostly operate in the same direction, namely to reduce the proportion of deaths from this cause. The three components are also consistent in their effect on raising the importance of circulatory system diseases in developing countries, but in developed countries the components work in opposite directions. Therefore, both demographic and epidemiological change will have roles in modifying mortality by cause in the future.
_Results_ _17_

# _Age-sex specific patterns_

Patterns by age and sex are roughly similar across regions, but also different in many details. (Annex B gives all the estimates.) Between men and women, differences are small, except with regard to complications of pregnancy. Across ages, mortality is lowest at 5-14 and 15-44, about five times as high at 1-4 and 45-64, and about fifty times as high at 0 and 64 and above. Concerning the percentage of deaths from each cause at each age, the patterns are roughly as follows. Infectious and parasitic diseases decline in importance with age (though they are more prominent at age 1-4 than at 0, give the predominance of certain perinatal causes among infant deaths), whereas circulatory system diseases and neoplasms increase in importance with age. Other causes are essentially stable across ages. Injury and poisoning is most prominent at age 15-4, perinatal conditions of course significant at age 0, and complications of pregnancy notable at age 15-44.

Over time, mortality rates by cause show variable changes. For infectious and parasitic diseases and for the other causes category, reductions are fairly constant across age groups, except for being somewhat smaller at 65 and above. In contrast, for circulatory system diseases and for injury and poisoning, reductions over time are strongly linked to age, being much greater at younger ages. For neoplasms, increases over time are actually more frequent than reductions, and are expected to occur in all regions, but most notably in Sub-Saharan Africa.

To obtain the previously reported estimates for all ages, deaths were simply added up across age groups. Should deaths at different ages be given equal weight? Several arguments to the contrary are possible. For instance, fewer deaths at the oldest ages are iikely to be 'premature' than at younger ages, and from the perspective of prevention, deaths at the oldest ages might therefore deserve less attention. Also, deaths at younger rather than older ages might be seen as depriving individuals of a larger number of potential years of life. To illustrate the effects of alternative weightings, Table 8 compares the percentage d - ' ition of deaths by cause with the percentage distribution of deaths under 65 and **.** .'.. the percentage distribution across causes of potential years of life lost by death. Years lost are calculated under the simplifying assumptions that life expectancy is 75 and that deaths in each age group from each cause occur at the mean for that age group from all causes in the world as a whole in 1985.

Weighting deaths at younger ages more heavily increases the prominence of infectious and parasitic diseases, perinatal conditions, and injury and poisoning (the latter mainly in developed countries) and reduces the prominence of circulatory system diseases and neoplasms. The effects on the remaining causes are weak or inconsistent. Thus infectious and parasitic diseases account for a little over a third of deaths in developing countries in 1985 but a half of all potential years of life lost. In comparison to infectious and parasitic diseases, circulatory system diseases will account for more deaths by 2000, but not for as many deaths under 65 until 2015, and even by 2015 for less than half as many potential years of life lost. Nevertheless, whether weighted or unweighted, the percentages mostly shuw similar trends, especially in decreases for infectious and parasitic diseases and increases for circulatory system diseases.
_18_ _Estimates and Projections of Mortality by Cause_ Table **8.** Percentage distribution by major cause of all deaths, deaths under 65, and potential years of life lost, world and developed and developi-. countries, 1970-2015

|_Region and_<br>_cause_|_19_<br>_All_<br>_deaths_|_70: Perc_<br>_Deaths_<br>_under_<br>_65_|_ent of_<br>_Life_<br>_years_<br>_lost_|_198_<br>_All_<br>_deaths_|_5: Pcent_<br>_Deaths_<br>_under_<br>_65_|_of_<br>_Life_<br>_yeats_<br>_lost_|_200_<br> <br>_All_<br>_deaths_|_0: Perce_<br>_Deaths_<br>_under_<br>_65_|_nt of_<br>_Life_<br>_years_<br>_lost_|_20_<br>_All_<br>_deaths_|_15: Perc_<br>_Deaths_<br>_under_<br>_65_|_ent of_<br>_Life_<br>_years_<br>_lost_|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|_World_|||||||||||||
|Infectious|35|<br>45|50|<br>30|39|44|21|30|37|<br>16|<br>23|32|
|Neoplasms|7|5|2|10|8|4|12|12|6|15|<br>15|9|
|<br>CIrculatory|<br>24|<br>12|6|26|13|7|35|20|10|<br>39|<br>25|14|
|Pregnancy|1|1|1|0|1|1|1|1|1|0|1|1|
|Perlnatal|6|9|12|<br>7|11|15|5|10|16|4|9|15|
|Injury|5|7|6|7|10|10|7|10|9|7|12|11|
|<br>Other|22|21|23|20|19|20|20|17|20|19|<br>16|18|
|_Developed Co_|_untries_||||||||||||
|Infectlous|12|16|20|9|13|18|7|4|5|7|3|3|
|Neoplasms|16|18|12|18|21|14|18|27|21|18|<br>29|24|
|Circulatory|<br>48|28|16|50|29|17|52|39|29|53|41|32|
|Pregnancy|0|0|0|0|0|0|0|0|0|0|0|0|
|Perinatal|2|6|11|1|4|8|1|5|14|1|5|14|
|Injury|7|17|21|6|15|17|6|16|20|5|15|19|
|Other|16|16|20|15|19|25|16|9|10|16|7|9|
|_Developing C_|_ountrks_||||||||||||
|Infectious|42|49|53|36|42|46|26|33|39|19|26|34|
|Neoplasmis|<br>5|4|_2_|7|6|3|11|10|5|14|14|8|
|Circulatory|<br>17|10|5|19|11|6|29|17|9|35|23|13|
|Pregnancy|1|1|1|1|1|1|1|1|1|1|1|1|
|Perlnatal|7|10|12|8|12|16|6|10|16|5|9|16|
|Injury|5|5|4|8|10|9|7|10|9|7|11|10|
|Other|24|22|23|21|19|20|21|18|20|19|17|19|

# Discussion

Since the expert assessments imply that at least some of the regression estimates are too low, we now consider the quality of these estimates and the biases that may exist in them.

The source of particular estimates should be borne in mind. For several regions, the current and past estimates are based substantially on data reported to WHO. Table 9 shows the proportions of regional populations covered by reported data. (The U.S.S.R. is not counted as covered, but China and rural India are.) The 1970 and 1985 estimates for industrial market economies are drawn almost entirely from reports. This is true to a lesser extent for Latin America and the Caibbean and industrial nonmarket economies. The situation for Asian data is more ambiguous because of reliance on special survey data for China and India. For Sub-Saharan Africa and North Africa and the Middle East, on the other hand, practically all the 1970 and 1985 figures are produced from the regression models.

As noted earlier, estimates based entirely on reports to WHO are not free from potential bias. The general issues of reliability and comparability have already been noted, but in addition some aspects of the coding appear not to conform with expert
_Discussion_ _19_ Table 9. Percentage of **regional** population covered by reports to WHO or sample surveys, by year

|_Region_|_1970_|_1985_|
|---|---|---|
|World<br>|28|59|
|Developed countries<br>|74|76|
|Developing countries<br>|10|53|
|Industrial market economies<br>|98|100|
|Industrial nonmarket econo-<br>mies<br>|29|32|
|Latin America and Caribbean<br>|62<br>|53|
|Sub-Saharan Africa<br>|0<br>|0|
|Middle East an( North Africa<br>|14<br>|2<br>|
|Asia|2|71|

Note: For 1985, the U.S.S.R. is not counted as covered. China and rural India in 1985 are the only cases covered by sample surveys rather than registration. Urban India is not counted as covered.

expectations. For example, substantial deaths from diarrhea at older ages were judged improbable. Nevertheless, on the average across reporting countries in 1985, 40 percent of all deaths from this cause occurred at age 65 and older, and the proportion exceeded 80 percent in countries like Norway and Japan, with presumably reliable reports. Misclassification cannot be excluded as an explanation, but cannot be confirmed with available data.

Further potential problems exist with the regression-based estimates, where they are used for 1970 and 1985 for countries with no reported data, as well as for 2000 and 2015 for all countries. Both statistical and substantive criteria could be applied in assessing these results.

Statistically, the equations for major causes of death produced patterns for 1970 and 1985 consistent with those produced by Hakulinen and others (1986a) for 1980, using the same equations but different life tables and regional groupings. Hakulinen and others argued that their results had many similarities to previous results by Preston (1976), who estimated equations that were not age-specific. They also argued that the procedure was insensitive to choice of life tables, which appears borne out by the similarities between their results and these.

To assess the regression procedure, the equations were applied to the reporting countries for 1985 to see whether predictions would match reports. This comparison is permissible because the equations for major causes had been separately estimated (by Hakulinen and others) with other data; the procedure is less informative regarding the equations for specific causes, which were estimated using the reported data in the comparison. Table 10 shows, however, that the reported distribution by major causes is more doselv approximated by predictions than is the distribution by specific causes. For the major causes, indices of dissimilarity between percentage distributions range from 5 to 13 among the four regions in Table 10. For specific causes under infectious diseases, these indices range from 12 to 34; for specific causes under circulatory system
_20_ _Estimates and Projections of Mortality by Cause_ Table 10. rredlcted and reported percentage distributions of deaths by cause for reporting countries grouped by region, 1985

||_Indust_|_rial (24Y_|_Nonm_|_arket (8)._|_LA_|_C (26)_|_As_|_ia (7)_|
|---|---|---|---|---|---|---|---|---|
|_Cause_|<br>_Predicte_|<br>_d Reporte_|<br>_d Predicte_|<br>_d Repored_|<br>_Predicte_|<br>_d Reporte_|<br>_d Predicte_|<br>_d Reported_|
|Percent of all causes|||||||||
|Infections<br>|8<br>|8<br>|20<br>|11<br>|23<br>|20<br>|31<br>|32|
|Neoplasms<br>|17<br>|22|12|12|11|11|9|9|
|Circulatory|51|51|38|50|31|32|25|20|
|Pregnancy|0|0|0|C|0|0|1|1|
|Perinatal|1|1|2|2|7|7|6|8|
|Injury|6|6|6|6|7|10|6|11|
|<br>Other|17|13|22|19|21|b|22|19|
|Percent of infections|||||||||
|Diarrhea|7|1|16|3|22|28|25|9|
|Tuberculosis<br>|4|2|8|5|6|6|5|8|
|Acute respiratory|42|49|43|30|41|31|43|33|
|Measles|1|0|2|0|2|1|3|1|
|COPD|33|45|19|17|16|b|12|16|
|Polio|0|0|0|0|0|b|0|0|
|Yelow fever|0|0|0|0|0|0|0|0|
|Malaria|0|0|1|0|1|0|1|2|
|Schistosomiasis<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0|
|Entestinalparasites|0|0|1|0|1|1|1|1|
|Other Infections|12|4|10|44|12|17|9|31|
|Percent of circulatory|||||||||
|Ischemnlc<br>heart|30|38|29|43|29|28|27|17|
|Cerebrovascular|24|24|24|28|23|19|23|42|
|Other cardiovascular|<br>34|29|34|22|34|37|34|23|
|Diabetes|6|3|6|1|6|8|6|3|
|Certain degenerative|<br>7|6|7|5|9|13|9|15|
|<br>Percent of other causes|||||||||
|Mentaldisorders|2|4|1|1|1|c|1|1|
|Oralhealth diseases|0|0|0|0|0|c|0|0|
|hicronutrient|3|2|3|3|3|c|3|2|
|Malnutrition<br>|1|1|2|2|2|c|3|5|
|Unspecified|94|93|94|94|94|c|93|91|

unumber of countries included in the comparison. "With no reported data for this category, it was assumed to be equal to the predicted value to permit comparisons for other categories.

'No data.

diseases, they range from 8 to 24; and for specific causes under other causes, they range from 1 to 3. Generally, the distributions for nonmarket economieF are more poorly predicted than those for other regions.

fwor particular causes, predicted percentages are higher than reported percentages in some regions, lower in others. For circulatory system diseases, for instance, predictions are too high in Asia, too low in nonmarket economies. One might draw implications from such comparisons about the possible directions of bias in the estimates for nonreporting countries, but only if one assumes similar mortality patterns in nonreporting as in reporting countries.
_Dbsussion_ 21 For the specific causes, the statistical adequacy of the equations varies by cause, as indicated earlier using coefficients of determination. Those causes of death that have distinctive patterns in Africa and the Middle East, and possibly in Asia, may be poorly estimated for these regions. This does not mean that diseases especially prevalent in these regions are underestimated: their prevalence might still be properly represented by extension of pattems across developed and Latin American countries. Rather it means that causes of death that show important discontinuities between reporting countries and nonreporting countries may be poorly estimated for the nonreporting countries. Unfortunately, without reports for all regions, one cannot tell defiritively which causes of death these are.

Even if the equations were entirely accurate for the present, projecting them into the future would still raise several issues. Future estimates also depend on assumptions about age structure, about current vital rates, and about trends in these variables. Furthermore, other unexpected changes could alter the outlook. Estimates for new causes of death cannot be generated by this procedure. For Human Immunodeficiency Virus (HIV) infection, in particular, this limitation may have significance for the broader picture. Besides changes in diseases, changes in medical technology, in life styles, in health and safety measures, and in the delivery of health services, as well as in the nature and quality of cause of death reports, could change the picture. All that the projections provide is a hypothetical picture based on somewhat contradictory assumptions: that mortality decline will be extended into the future, extending past trends, but that historical patterns associating particular disease categories with particular mortality levels will remain as they are.

Despite these caveats and uncertainties, the broad patterns in the estimates and projections are certainly plausible: the regional contrasts and the way some of them persist over time; the expected increase in circulatory system diseases as a cause of death; and the separate contributions of age structures, mortality levels, and epidemiological change to variation in distribution of deaths by cause. The implications worth drawing from these broad patterns depend on the questions one asks. As Table 8 showed with alternative percentage distributions, from different perspectives the figures reveal different patterns. One clear implication from any perspective, however, is that better data on cause of death are essential. In this regard, WHO is working with countries to strengthen their cause of death information systems as an essential support for health monitoring.

# Annex A. Methodology

This annex provides more detail about the data on causes of death, the projection of mortality levels, and the regressions to decompose overall mortality into major and specific causes. The reclassification of deaths from unspecified causes is also discussed.

## Table Al shows how countries are classified.
_Estimates and Projections of Mortality by Cause_ _22_

# Table Al. Regional grouping of countries and territories

_Industrial Market_ Brazil Gabon Qatar _Economies_ Chile Gambia, The Saudi Arabia Australia Colombia Ghana Syrian Arab Rep. Austria Costa Rica Guinea Tunisia Belgium Cuba Gulnba-Bissau Turkey Canada Dominica Kenya United Arab Emirates Channel Islands Dominican Rep. Lesotho West Bank Cyprus Ecuador Liberia Yemen, People's Dem. Denmark El Salvador Madagascar Rep. of Finland Grenada Malawi Yemen Arab Rep. France Guadeloupe Mall Other North Africa Germany, Fed. Rep. of Guatemala Mauritania Greece Guyana Mauritius _Asia and the Pacfikc_ Iceland Haiti Mozambique Bangladesh Ireland Honduras Namibia Bhutan Italy Jamaica Niger Brunei Japan Martinique Nigeria Cambodia Luxembourg Mexico Reunion China (excluding Malta Montserrat Rwanda Taiwan) Netherlands Netherlands AntiUes Sao Tome and Principe Fiji New Zealand Nicaragua Senegal French Polynesia Norway Panama SeycheUes Guam Portugal Paraguay Sierra Leone Hong Kong Spain Peru Somalla India Sweden Puerto Rico South Africa Indonesia Switzerland St. Kitts and Nevis Sudan Kiribati United Kingdom St. Liiu.a Swaziland Korea, Dem. People's United States of St. Vincent and Tanzania Rep. of America the Grenadines Togo Korea, Rep. of Other Europe Suriname Uganda Lao People's Dem. Rep. Other North America Trinidad and Tobago Zaire Macao Uruguay Zambia Malaysia _Industrial Nonmarket_ Venezuela Zimbabwe Maldives _Economies_ Virgin Islands (U.S.) Other West Africa Mongolia Albania Other Latin America Myanma Bulgaria _Middle East and_ Nepal Czechoslovakia _Sub-Saharan Africa North Africa_ New Caledonia German Dem. Rep. Angola Afghanistan Pacific Islands Hungary Benin Algeria Papua New Guinea Poland Botswana Bahrain Philippines Romania Burkina Faso Egypt, Arab Rep. of Singapore U.S.S.R. Burundi Gaza Strip Solomon Il4ands Yugoslavia Cameroon Iran, LIslamic Rep. of SriLanka Cape Verde Iraq Taiwan _Latin America and_ Central African Rep. Israel Thailand _the Cribbean_ Chad Jordan Tonga Antigua and Barbuda Comoros Kuwait Vanuatu Argentina Congo, People's Rep.of Lebanon Viet Nam Bahamas C8te d'Ivoire Libya Western Samoa Barbados Djibouti Morocco Other Micronesia Bellze Equatorial Guinea Oman Other Polynesia _Industrial Nonmarket_ Venezuela Zimbabwe _Economies_ Virgin Islands (U.S.) Other West Africa Albania Other Latin America Bulgaria _Middle East and_ Czechoslovakia _Sub-Saharan Africa North Africa_ German Dem. Rep. Angola Afghanistan Hungary Benin Algeria Poland Botswana Bahrain Romania Burkina Faso Egypt, Arab Rep. of U.S.S.R. Burundi Gaza Strip Yugoslavia Cameroon Iran, LIslamic Rep. of Cape Verde Iraq _Latin America and_ Central African Rep. Israel _the Cribbean_ Chad Jordan Antigua and Barbuda Comoros Kuwait Argentina Congo, People's Rep.of Lebanon Bahamas C8te d'Ivoire Libya Barbados Djibouti Morocco Bellze Equatorial Guinea Oman Bolivia Ethiopia Paldstan
_Annex A. Methodology_ _23_

# _Data on causes of death_

The cause of death data for countries and territories used in this analysis can be divided into two groups. Table A2 lists those countries, mostly developed, for which the cause of death data are reasonably reliable, although comparability may still be uncertain. Table A3 lists those countries for which the data are less reliable and presents two indicators of reliability: coverage, as computed from the annual estimated number of deaths, and quality, as measured by the proportion of deaths coded as due to illdefined conditions. Some countries that report data have been exduded because coverage and qualicy are sufficiently poor to render the data unusable.

Of the countries included, China, India, and the U.S.S.R. have data with special characteristics. The Chinese data are from a survey covering 57 million urban residents and 42 million rural residents spread over the eastern part of the country. The 580 thousand deaths recorded, though only 7 percent of estimated annual Chinese deaths, should be reasonably indicative of the mortality pattern for 70-80 percent of the population. ICD-9 codes were used, and all the major causes and the majority of specific causes can be identified. Sample deaths were weighted to reflect the total population.

The Indian data are from a 1986 cause of death survey of 1,200 rural primary health care centers spread throughout India, and covered 10,075 male and 8,187 female deaths (0.2 percent of estimated Indian deaths). Coding was idiosyncratic, but the major causes and some of the specific causes were still distinguishable. Without the base population, mortality rates could not be calculated from the survey. We arbitrarily assumed that age-specific urban mortality rates were fixed percentages of rural rates (at age 1-4, 37.5 percent; at ages 0, 5-14, and 15-44, 67 percent; at age 45-65, 75 percent; and at age 65 and above, 100 percent). With the rural population at 74.5 percent of the total and with a particular age structure of mortality for the country as a whole drawn from Bank projections (see below), we then generalized the survey results to cover the rural population and estimated urban deaths by cause from the regression equations dussed below.

For the U.S.S.R., the data reported to WHO permitted identification of deaths due to diarrhea, most circulatory system diseases (exduding cirrhosis of the liver) and measles. Regression estimates were used to fill in the other causes.

For most other countries, data were available on each cause of death. The major exceptions were the Latin America and Caribbean countnes, for which 1970 but not 1985 data were available on other causes and four specific causes (chronic obstructive pulmonary disease, polio, mental disorders, and micronutrient disorders). Again, regression estimates filled in for the missing data.

# _Projecting mortality_

As noted above, the projection of mortality involved separate projections of life expectancy and infant mortality and the selection of 'split' life tables.
_24_ _Estimates and Projections of Mortality by Cause_ Table A2. Countries or territories with reliable reports on causes of death, and year of data used, by region

|_Country or territory_|_Year_|_County or territory_|_Year_|
|---|---|---|---|
|_Industria market economies_<br>|<br>|_Industrial nonmarket economies_<br>||
|Australia<br>|1985<br>|Bulgaria|1985|
|Austria<br>|1985|Czechoslovakia|1985|
|Belgium<br>|1986|German Dem. Rep.|1985|
|Canada<br>|1985<br>|Hungary|1985|
|Denmark<br>|1985|Poland|1985|
|Finland<br>|1985|Romanla|1984|
|France<br>|1985|U.S.S.R.|1986|
|Germany, Federal Rep. of<br>|1985<br>|Yugoslavia|1985|
|Greece<br>|1985|||
|Iceland<br>|i985|_Latin America and the Caribbea_|_n_|
|Ireland<br>|1985|Argentina|1985|
|Italy<br>|1985<br>|Chile<br>|1985|
|Japan<br>|1985<br>|Costa Rica<br>|1985|
|Luxembourg<br>|1985<br>|Cuba|1985|
|Malta<br>|1985|Uruguay|1985|
|Netherlands<br>|1985|||
|New Zealand<br>|1985|_Middk East and North Africa_||
|Norway<br>|1985<br>|Israel|1985|
|Portugal<br>|1985|||
|Spain<br>|1985|_Asia_||
|Sweden<br>|1985|Hong Kong|1985|
|Switzerland<br>|1985<br>|Singapore|1985|
|United Kingdom<br>|1985<br>|||
|United States of America|1985|||

Note: Data for around 1970 for all these countries or territories except the German Democratic Republic, the U.S.S.R., and Israel were also used. The U.S.S.R. data, though considered reliable, could not provide estimates for many of the specific causes used here.

Life expectancy is assumed to rise over time following a logistic curve that has a minimum of 20 and a maximum of 75.8 for males or 82.5 for females. The slope of the curve is estmated using a regression equation that has on the right-hand side the slope over the previous quinquennium and the female secondary enrolment ratio (or the percent urban, in the few cases where this is not available). In comparisons among a variety of countries, the median slope in the past, applying the logistic curve, was -.035, and the quartiles were -.017 and -.053. To eliminate extreme trends-including a few increases in mortality-no country is allowed to have a slope falling outside these quartiles. The estimated slope, or the quartile value if appropriate, is assumed to apply for three quinquennia, after which all countries are assumed to revert to the median slope.

Infant mortality is assumed to fall over time also following a logistic curve, from a maximum of 200 per thousand to a minimum of 4 per thousand. The median slope across a variety of countries with data was .052, with the quartiles being .025 and .120. A slope is estimated for each country from its performance in the preceding quinquennium, and applied for three quinquennia, unless this slope falls outside the quartiles, in which case the appropriate quartile value is used.
_Anne A. Methodology_ _25_ Table A3. Countries or territories with less reliable reports on causes of death, year of data used, and indices of coverage and data quality, by region

||||_Reporte_|_d deaths_<br>|
|---|---|---|---|---|
|||||_Percent due_|
||||_Pt_|<br>_illd_|
||||_ercen o_|_to -e-_|
|_Country or territory_|_Year of_<br>_data used_|_Number_|<br>_estimated total_<br> <br>_deaths_|<br>_fined_<br>_conditions_|
|_Latin Amenca and the Caribbean_<br>|||||
|Antigua and Barbuda<br>|1983<br>|300<br>|na|na<br>|
|Bahamas<br>|1985|1200|na|<5|
|Barbados<br>|1984<br>|2000<br>|95|<5<br>|
|Belize<br>|1984<br>|700<br>|na|15|
|Dominica<br>|1984<br>|400<br>|na<br>|na|
|Dominican Rep.<br>|1985<br>|28000<br>|62<br>|15<br>|
|Ecuador<br>|1985<br>|51000|70|15|
|El Salvador<br>|1984<br>|29000<br>|62<br>|20-25<br>|
|Guatemala<br>|1984|66500|86|10|
|Guyana<br>|1984<br>|4800<br>|91<br>|10<br>|
|Martdnique<br>|1985|2200|88|10|
|Mexico<br>|1983<br>|410000<br>|85<br>|5<br>|
|Panama<br>|1985|9000|80|5-10|
|Paraguay<br>|1985<br>|12600<br>|50<br>|20-25<br>|
|Peru<br>|1983|94000|50|5-10|
|Puerto Rico<br>|1985<br>|23200<br>|100|<5|
|St. Kitts and Nevls<br>|1984<br>|500|na|15|
|St. Vincent and the Grenadines<br>|1985<br>|700<br>|na<br>|10<br>|
|Suriname<br>|1985<br>|2300<br>|95<br>|15<br>|
|Trinidad and Tobago<br>|1983<br>|7600<br>|95|<5|
|Venezuela<br>|1983|77000|81|5|
|_Sub-Sahamn Africa_<br>|||||
|Mauritius<br>|1985<br>|6600<br>|100|<5|
|Sao Tom6 and Principe<br>|1985<br>|1100|na|20|
|Seychelles<br>|1985|500|na|10|
|_Middk East and North Afnica_<br>|||||
|Bahrain<br>|1985<br>|1600|90|20|
|Kuwait|1985|4300|85|5|
|_Asia_|||||
|China<br>|1985|580000|7|<5|
|India<br>|1986|18000|0.2|na|
|Korea, Rep. of<br>|1985<br>|192000<br>|75|15|
|Sri Lanka<br>|1983|96000|96|30|
|Thailand|1985|218000|57|50|

na - not ascertained.

Note: Data for around 1970 were also used for these countries except for Guyana, Seychelles, Sao Tome, Bahrain, Israel, China, India, the Republic of Korea, and Sri Lanka. In addition, 1970 data were used for five additional countries: Colombia, the Arab Republic of Egypt, Honduras, Nicaragua, and St. Lucia. The quality indices, in ten cases, are for a later data year, either 1986 or 1987. The data used for China and India were sample survey data.

For each country for the first three quinquennia, life tables are chosen from the Coale-Demeny set. The first step is to select that family of life tables (North, South, East, or West) for which the ratio of life expectancy to infant mortality is as close as
_Estimates and Projections of Mortality by Cause_ _26_ possible to the ratio for that country. The second step is to make up composite or 'split' life tables from life tables for different levels of the selected family: the infant mortality rate is used to select levels to apply up to age 14, and the life expectancies are used in conjunction with the first selection to select levels to apply from age 15 on. By the thirteenth quinquennium, all countries are assumed to have reverted to West model life tables, with levels chosen according to the median trend in life expectancies and infant mortality determined entirely by the choice of levels. Between the third and the thirteenth quinquennium, life tables are interpolated to provide a smooth transition.

Single-year deaths by age and sex are obtained by interpolation from the quinquennial estimates normally provided in the projections, taking migration into account.

For more detail and justification of these procedures, a background paper on the World Bank projection procedures (Bulatao and Bos 1989) can be consulted.

# _Predicting deaths by major cause_

The equations for major causes of death show mortality rates by cause increasing with overall mortality for all causes except neoplasms. The increases are greatest for infectious and parasitic diseases (slopes around 0.5, meaning that half of an increase in deaths is attributable to this major cause), followed by other and unknown causes (slopes around 0.25) and perinatal conditions (slope of 0.22, for age group 0 only). Slopes vary considerably by age group: for infectious and parasitic diseases, they vary from 0.7 for those 14 years old to 0.4 for those 65 and older. Slopes also vary by sex: for neoplasms among those 65 and older, the slope for males is -0.13 and for females -0.04. Nevertheless, the trend across age groups is essentially similar between males and females. In contrast, slopes vary very little across regions, with the largest gap between regions for a given cause and sex and age group being around 0.04. The equations for lower-mortality, more developed regions do appear to diverge more often from the norm, though ordy minimally. Considering the number of regions and the rarity of even small differences in the equations, the case for distinct cause of death structures across regions is weak.

Where reported data were not available, the equations specific to each of the 24 regions were applied (though the world equations would produce similar results). For 2000 and 2015, we maintained the same region-specific equations for the industrial market economnies but allowed each other country to switch from its region-specific set of equations to the equations for developed countries as a whole if its mortality level had declined sufficiently, as indicated by a crude death rate, standardized using the 1985 age structure for the world as a whole, below 6. (The industrial market economies as a group have a standardized crude death rate of 5.8, as contrasted, for example, with 9.0 for Latin America and the Caribbean.) The few negative estimates of mortality rates (e.g., because of the negative slopes for neoplasms) were set to zero case by case, and rates for other disease categories adjusted proportionally.
_27_ _Annex A. Mehodology_

# _Estimating deaths by specific cause_

To estimate new regressions for 22 specific causes of death, data for around 1970 and around 1985 were pooled. As noted earlier, Latin America and Caribbean countries had no data for some causes for 1985, requiring the inclusion of 1970 data. Altogether, 1970 data for 65 countries (34 of them developing, mostly Latin American) and 1985 data for 69 countries (38 developing) were used. Because of the number of causes for which estimates could not be produced, the U.S.S.R. and India were excluded, but China was included. Data quality varies for the countries included, but imposing a more rigorous standard would bias the sample strongly toward developed countries.

For each country, mortality rates by cause were first adjusted to correspond to overall mortality levels in the World Bank estimates and projections. Rates based on fewer than 10,000 people in the age-sex group were excluded. Three equations were then estimated for each disease in each age-sex group: a quadratic specification, where the rate for the specific cause depended on the rate for the major cause and the square of this rate, as well as on a dummy variable for data year; a corresponding linear specification; and a specification in which the rate for the specific cause depended only on two, dummy variables, for developing country status and data year.

If the quadratic term achieved a 5 percent level of significance, the quadratic equation was chosen; if not, and the linear term achieved a 5 percent level of significance, the linear equation was chosen; and in all remaining cases, the dummy variable equation was chosen. Of the 264 final equations, half were quadratic, a third linear, and the remainder dummy variable equations. The dummy vanable for data year had a significant effect in 20 percent of the equations chosen.

Mortality rates for some specific causes of death were predicted better than rates for others. R<sup>2</sup> did vary much more by cause than by age-sex group, permitting the grouping of equations by cause:

- a. mean 12 over .70: diarrhea, acute respiratory infection, other cardiovascular diseases, and unspecified causes

- b. mean _11_ between .35 and .60: tuberculosis, measles, chronic obstructive pulmonary disease, other infectious and parasitic diseases, cerebrovascular disease, nephritis/cirrhosis/ulcers, miaonutrient disorders, and malnutrition

- c. mean R<sup>2</sup> between .20 and .25: intestinal parasites, ischemic heart disease, and diabetes

- d. mean R<sup>2</sup> below .20: polio, malaria, yellow fever/dengue/encephalitis, schistosomiasis/filariasis, mental disorders, and oral health diseases.

The last group also accounted for almost all the dummy variable equations. Mortality rates for causes in this group did not covary with mortality levels for broader categories, and developed or developing country averages were essentially applied for these causes.
_Estimates and Projections of Mortality by Cause_ _28_

## _Reclassifying deaths from unspecified causes_

The subcategory of unspecified causes of death indudes particular causes that we cannot treat individually-meningitis, appendicitis, kidney infections, congenital anomalies, indirect obstetric causes, etc.-as well as vague and ill-defined conditions. Particularly for developing countries, where ill-defined conditions may be numerous (see the last column in Table A3), it is useful to determine the potential effect of reclassifying these deaths under other categories.

The appropriate procedure would be to use as a guide empirical studies that reclassify under other headings deaths reported as due to ill-defined conditions. Not having located such studies, we propose an alternative requiring no special information. This alternative involves, first, determining the number of such deaths, and second, calculating the maximum potential increase in deaths in every other category from reclassifying deaths from ill-defined conditions.

The deaths in the unspecified causes subcategory set an upper limit on the deaths we need to reclassify. We reduce the number by assuming that mortality rates for this subcategory for developed countries reflect properly diagnosed miscellaneous causes, and that only rates for developing countries that exceed these developedcountry rates reflect deaths from ill-defined causes. The latter can thus be estimated for each age-sex group in each developing country region.

These deaths might simply be distributed proportionally across all other cause of death categories. However, we do not wish to exdude the possibility that proportionally more deaths are misdiagnosed for some causes than for others. Therefore, we set a maximum possible increase for each category from reclassifying deaths from ill-defined causes. These maximum increases are determined under two assumptions: that they are proportional to the square root of p; (1- p,), where pi is the proportion of deaths initially in category i; and that the largest possible maximum increase for any category (by the previous assumption, this would be for a category with exactly half of all deaths) is the total estimated deaths from ill-defined causes.

These maximum potential increases should total more than the ill-defined deaths, and maximum increases for subcategories should total more than the maximum increase for the major category of which they are a part. This is as it should be. The maximum increases only indicate how much larger each category might be, but do not indicate that it should be larger, and not all categories can simultaneously be much larger.

# Annex B. Supplementary Tables

The tables in this annex provide demographic parameters by region (B1 and B2); mortality rates and deaths for major causes by age, sex, and region from 1970 to 2015 (B3 and B4); and mortality rates and deaths for specific causes by age, sex, and region for 1985 (B5 and B6). The estimates in the latter two tables are the regression estimates, and have not incorporated expert assessments, which appear in the following annex.
_29_ _Annex B. Suppkmentary Tableo_ Table **B1.** Population in **millions** by **age** and sex, major<sup>world regions, 1970-2015</sup>

|_Regon, age_|_1_|_970_|_1_|_985_|2|000|_2_|_015_|
|---|---|---|---|---|---|---|---|---|
|<br>_and gax_|_Mak_|_Femal_|_Mae_|_Femae_|_Male_|_Femak_|_Male_|_Female_|
|<br>World|||||||||
|Total|1848|1853|2438|2406|3128|3075|3801|3745|
|0|57|53|62|59|70|68|74<br>|71<br>|
|1-4|212|201|232|222|2n|263|287|278<br>|
|5-14|434|419|542|516|641|622|691<br>|669<br>|
|15-44|797|m|1117|1076|1461|1402|1746|1687|
|45-64|257|276|363|368|500|498|748|738|
|65+|92|134|122|165|183|224|256|303|
|Developed|||||||||
|Total|507|560|570|606|618|645|647|670|
|0|9|8|9|9|8|8|9|8|
|1-4|37|35|35|34|33|32|34|32|
|<br>5-14|98|94|89|85|87|83|84|80|
|15-44|227|230|266|260|276|268|261|253|
|45-64|92|116|121|136|146|153|175<br>|180<br>|
|65+|44|76|51|83|67|100|84|117|
|Developing|||||||||
|Total<br>'|1341|1293|1868|1800|2510|2430|3154|3075|
|<br> <br>0|<br>48|<br>45|<br>53|51|62|60|65|63|
|<br>1-4|<br>174|<br>165|197|189|238|231|253|245|
|5-14|336|325|453|432|554|539|607|589|
|<br>15-44|<br>569|541|851|816|1185|1133|1484|1434|
|<br>45-64|<br>165|<br>160|<br>242|232|355|344|573|558|
|<br>65+|<br>48|58|72|81|116|123|172|186|
|Industral|||||||||
|Total|334|360|371|389|398|412|411|424|
|<br>0|<br>6|<br>6|<br>5|5|5|5|5|5|
|<br>1-4|24|23|20|19|20|19|20|19|
|<br>5-14|62|59|55|52|52|50|50|47|
|1C-44|146|146|174|171|176|170|160|154|
|45-64|65|75|79|84|98|101|116|118|
|65+|32|51|37|57|47|67|60|81|
|Nonmarket|||||||||
|Total|173|200|199|217|220|233|236|246|
|0|3|3|4|4|3|3|4|3|
|1-4|13|12|15|14|13|13|14|13|
|5-14|37|35|34|32|35|34|34|33|
|<br>15-44|<br>81|84|91|89|100|98|101|99|
|<br>45-64|<br>27|<br>41|43|51|48|52|59|62|
|<br>65+|<br>12|<br>25|<br>13|<br>27|20|33|24|36|
|<br>LAC|||||||||
|Total|142|142|201|201|264|265|319|322|
|<br>0|<br>5|<br>4|<br>6|<br>6|6|5|6|6|
|<br>1-4|<br>18|<br>17|<br>22|21|23|22|23|22|
|<br>5-14|<br>38|37|49|48|57|55|55|53|
|15-44|59|59|92|91|129|128|156|153<br>|
|45-64|17|17|24|25|37|40|62|65|
|65+|6|7|8|10|12|1S|18|24|
_30_ _Estimates and Projections of Mottality by Cause_

**Table 8l.** Population in mlllions (continued)

|_Region, age_|_1_|_970_|_1_|_985_|_2_|_000_|_2_|_015_|
|---|---|---|---|---|---|---|---|---|
|_and sex_|_Male_|_Female_|_Male_|_Female_|_Male_|_Female_|_Male_|_Female_|
|Sub-Sahara|||||||||
|Total|146|150|226|230|358|362|539|545|
|0|6|6|9|9|14|14|17|17|
|1-4|21|21|33|33|49|49|65|64|
|5-14|39|39|62|62|100|99|142|140|
|15-44|60|62|93|94|152|153|245|246|
|45-64|15|16|22|24|34|37|56|60|
|65+|4|5|6|7|9|11|15|18|
|MENA|||||||||
|Total|128|122|193|183|293|280|411|394|
|0|5|5|7|7|9|9|11|10|
|1-4|17|17|25|24|35|34|41|39|
|5-14|35|33|51|47|76|74|94|91|
|15-44|52|50|84|78|131|123|194|185|
|45-64|15|14|21|20|32|31|57|53|
|65+|5|5|6|6|9|10|15|15|
|Asia|||||||||
|Total|924|880|1248|1186|1595|1523|1885|1815|
|0|33|30|31|29|<br>33|32|32|30|
|1-4|118|110|117|111|131|126|125|121|
|5-14<br>|225<br>|216<br>|291<br>|274<br>|321<br>|311<br>|316<br>|305<br>|
|15-44|398|371|583|552|774|730|890|851|
|45-64|117|112|175|162|251|237|397|380|
|65+|33|41|52|58|85|87|125|128|
|India|||||||||
|Total|286|266|395|370|519|491|631|605|
|o|10|9|12|11|12|11|11|11|
|1-4|35|32|45|43|46|45|45|43|
|5-14|68|65|97|92|113|110|116|112|
|15-44|123|115|173|161|251|234|310|298|
|45-64|38|34|53|47|73|70|114|105|
|65+|11|11|16|16|24|22|35|36|
|China|||||||||
|Total|427|402|550|515|669|629|753|714|
|0|15|14|10|9|12|11|11|10|
|1-4|54|51|37|35|47|45|43|41|
|5-14|<br>101|<br>96|<br>117|<br>108|<br>116|<br>112|<br>108|103|
|15-44|188|167|275|255|324|303|331|313|
|45-64|55|54|86|77|125|113|195|183|
|65+|15|22|26|31|46|46|65|63|
|Other Asia|||||||||
|Total|211|212|303|301|407|403|502|495|
|0|8|7|9|9|10|9|10|9|
|1-4|29|27|35|33|38|37|38|36|
|5-14|56|56|78|74|92|89|93|90|
|15-44|87|88|135|136|199|194|249|239|
|45-64|25|24|36|37|53|54|89|92|
|65+|7|8|10|12|16|19|24|29|
_Annex B. Suppkementary Tables_ _31_ Table B2. Estimnates and projections of fertility, mortality, and population growth for major regions in selected quinquennia

|_Quinquen._|_Births_|_Deaths_|_Growth_|_Total_|_Life exp_<br>_-at b_|_eetancy_<br>_irth_|_Mo_|_rtality_|
|---|---|---|---|---|---|---|---|---|
|<br>_nium and_|||_rate_|_fertility_|||_Infant_|_Under 5_|
|_reglon_|_Crude ra_|_te per 1000_|<br>_(percent)_|<br> <br>_rate_|_Males_|_Female_|<br>_s (1000 qO_|<br>_) (1000 q5)_|
|_1970-75_|||||||||
|World|31|12|1.9|4.3|60|63|83|122|
|Developed|16|10|0.7|2.2|69|76|24|28|
|<br>Developing|37|12|2.4|5.2|57|58|93|138|
|Industrial|16|10|0.7|2.1|71|78|15|17|
|Nonmarket|18|11|0.7|2.4|64|<br>73|<br>38|47|
|LAC|34|9|2.4|4.8|60|65|63|85|
|Sub-Sahara|48|20|2.8|6.6|43|47|138|<br>231|
|MENA|42|15|2.7|6.3|52|54|116|<br>169|
|Asia|35|11|2.3|4.9|59|59|84|119|
|_1985-90_|||||||||
|World|27|10|1.7|3.4|63|67|70|96|
|Developed|15|10|0.5|1.9|70|77|15|18|
|<br>Developing|31|10|2.1|<br>3.9|<br>61|<br>63|<br>78|108|
|<br>Industrial|13|9|0.5|1.7|73|79|9|10|
|Nonmarket|17|11|0.7|2.3|66|74|24|28|
|LAC|29|7|2.0|3.6|64|69|56|69|
|Sub-Sahara|46|15|3.1|6.4|50|53|111|171|
|MENA|40|10|3.0|5.6|59|61|90|121|
|Asia|27|9|1.8|3.3|63|65|68|90|
|_2000-05_|||||||||
|World|23|8|1.4|2.9|66|70|50|67|
|<br>Developed|<br>13|<br>10|<br>0.3|<br>1.9|<br>73|<br>79|<br>11|12|
|<br>Developing|25|8|1.7|3.1|65|67|55|74|
|<br>Industrial|12|10|0.3|1.8|75|81|7|7|
|Nonmarket|15|10|0.4|2.1|70|76|17|20|
|LAC|21|6|1.4|2.5|68|<br>73|37|44|
|Sub-Sahara|40|11|2.9|5.4|55|59|83|122|
|MENA|32|8|2.4|4.3'|64|65|56|73|
|Asia|21|8|1.3|2.6|67|69|45|56|
|_2015-20_|||||||||
|World|20|8|1.1|2.6|68|72|40|53|
|Developed|13|11|0.2|2.0|73|80|10|11|
|<br>Developing|<br>21|8|<br>1.3|<br>2.6|<br>67|<br>70|<br>43|58|
|<br>Industrial|12|11|0.1|2.0|75|81|<br>7|7|
|Nonmarket|14|11|0.3|2.1|71|78|14|17|
|LAC|18|7|1.1|2.2|70|75|29|34|
|Sub-Sahara|32|9|2.3|4.0|59|63|64|93|
|MENA|26|7|1.9|3.1|66|69|44|57|
|Asia|17|8|0.9|2.2|69|71|34|42|
_Estimates and Proictions of Mortality by Cause_ 32 Table **B3.** Mortality rates per 100,000 from **_major_**<sup>auses, by age, sex, and</sup><sup>_region,_1970-2015</sup>

|_Re8ion_|_1_|_970_|_19_|_85_|_2_|_000_|_2_|_015_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Femak_|_Male_|_Femade_|_Male_|_Femeak_|_Male_|_Female_|
||||All C|auses|||||
|World|||||||||
|Total<br>|1293<br>|1281<br>|1064<br>|1004<br>|863<br>|802<br>|880<br>|776<br>|
|0|9135|8647|8550|6955|5759|4581|4656<br>|3538<br>|
|1-4|1730|1845|1380<br>|1291<br>|444<br>|390<br>|362<br>|281<br>|
|5-14|222|238|165|154|118|103|104|87|
|15-44|384|346|270<br>|244<br>|222<br>|204<br>|201<br>|172<br>|
|45-64<br>|1521<br>|1024<br>|1294<br>|904<br>|1097<br>|774<br>|1019<br>|678<br>|
|65+|7979|6847|7463|6497|6901|6048|6880|5845|
|Developed|||||||||
|Total|1054|1069|1047|1013|997|963|1161|1059|
|0|3477|1417|1920|1379|1392|988|1268|775<br>|
|1-4|703|681|785|805|53|90|54|75<br>|
|5-14|72|20|39|17|27|11|25|9|
|15-44|188|75<br>|181<br>|55<br>|125<br>|41<br>|108<br>|33<br>|
|45-64|1160|605<br>|1112<br>|517<br>|904<br>|395<br>|882<br>|368<br>|
|65+|7612|6355|7474|6015|6655|5482|6755|5471|
|Developing|||||||||
|Total|1383|1373|1070|1001|830<br>|759<br>|823<br>|714<br>|
|0|10169<br>|9995<br>|%71<br>|7902<br>|6341<br>|5053<br>|5098<br>|3894<br>|
|1-4|1952<br>|2097<br>|1486<br>|1378<br>|499<br>|432<br>|403<br>|308<br>|
|5-14|265|301|189|181<br>|132<br>|118<br>|115<br>|98<br>|
|15-44<br>|462<br>|461<br>|298<br>|305<br>|245<br>|243<br>|217<br>|197<br>|
|45-64|1723|1330|1385|1130|1177|942|1061|778|
|65+|8310|7503|7454|6993|7043|6511|6941|6080|
|Industri1|||||||||
|Total|1036|1021|986|950|1007|943|1173|1045<br>|
|0|2275|890|1222|880|935<br>|671<br>|908<br>|533<br>|
|1-4|907|957|428|492|46<br>|91<br>|27<br>|54<br>|
|5-14|44|9|20|6|14|3|15|3<br>|
|15-44|128|44|112|32|87|23|79<br>|19<br>|
|45-64<br>|1000<br>|480<br>|926<br>|399<br>|775<br>|298<br>|778<br>|293<br>|
|65+<br>|7270|5980|7084|5711|6615|5330|6408|5073|
|Nonmarket|||||||||
|Total|1089|1155|1162|1126|980|1000|1139|1082|
|0|5828|2452|2931|2082<br>|2078<br>|1461<br>|1m<br>|1113<br>|
|1-4|319|162|1291|1239|63|89|92|103|
|5-14|119|39|70|35|45|22|38|16<br>|
|15-44|295|128|314|99|191|72|155|55|
|45-64|1540|831|1455|72|1169|588|1088|513|
|65+|8551|7111|8593|6661|6748|5786|7606|6372|
|LAC|||||||||
|Total|1097|903|883|706|677|557|722|594|
|0|7886|5789|6365<br>|5050<br>|4244<br>|3322<br>|3370<br>|2466<br>|
|1-4|1039|918|749|77|314|289|137|109|
|5-14|173|136|107|82|67|46|55|34<br>|
|15-44<br>|348<br>|266<br>|246<br>|144<br>|173<br>|99<br>|150<br>|81<br>|
|45-64|1553|1068|1351|779|1083|605|993|527|
|65+|8132|7019|7925|6441|7052|5742|6702|5415|
_Annex B. Supplementary Tables_ _33_ Table DS. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|_2_|_000_||_2015_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Femak_|_Mak_|_Female_|_Male_|_Femak_|_Male_|_Femak_|
|Sub-Sahara|||||||||
|Total|2163|1882|1727|1448|1196|1024|947|785|
|0|17653|14573|14128|11476|9935|8003|7557|5856|
|1-4|2774|2424|2215|1675|1094|852|925|604|
|5-14|679|683|439|430|306|284|238|211|
|15-44|838|736|654|564|517|440|406|330|
|45-64|2202|1746|1995|1537|1691|1315|1444|1061|
|65+|9108|8382|8589|7738|<br>7905|<br>7114|<br>7461|6516|
|MlENA|||||||||
|Total|1563|1520|1184|1121|775|733|691|624|
|0|13275|12850|11330|9237|6589|5278|5150|3978|
|<br>1-4|<br>1451|<br>1667|<br>1554|<br>1574|<br>370|<br>356|<br>300|305|
|5-14|306|357|213|206|125|114|105|91|
|15-44|565|571|295|326|265|296|216|223|
|45-64|2016|1588|1429|1182|1285|1101|1157|898|
|65+<br>|8947|8002|7934|7505|7400|6953|7086|6439|
|Asia|||||||||
|Total|1280|1342|963|946|784|736|833|734|
|0|8627|(2r:#|8552|6999|5138|4034|4047|3026|
|14|2017|2287|1402|1374|343|315|215|188|
|5-14|203|252|146|138|91|78|74|60|
|15-44|410|431|250|284|201|218|177|173|
|4564|1649|1279|1307|1118|1108|920|1004|759|
|-S5+|8148|7418|7191|6939|6910|6516|6899|6099|
|||<br>Infec|<br>tlous and|<br>Parasitic Di|<br>seases||||
|World|||||||||
|Total|449|449|318|294|176|179|140|133|
|0|3913|3926|3537|2990|2195|1809|1629|1277|
|1-4|1148|1248|775|735|272|246|215|170|
|514|113|146|78|88|49|54|41|44|
|15-44|153|166|84|93|57|81|43|60|
|4564|332|216|262|195|118|ill|71|63|
|65+|1209|948|1223|928|841|741|77|619|
|Developed|||||||||
|Total|146|112|109|74|78|59|90|63|
|0|953|355|306|234|126|86|66|20|
|1-4|172|165|274|276|3|31|9|26|
|5-14|17|4|6|3|1|0|0|0|
|15-44|29|9|24|2|6|0|0|0|
|45-64|148|52|85|21|46|0|32|0|
|65+|885|606|659|366|591|367|629|363|
|Developing|||||||||
|Total|564|595|382|368|200|211|150|148|
|0|4453|4592|4083|3457|2471|2036|1833|1439|
|1-4|1359|1482|864|817|310|276|242|188|
|5-14|141|187|92|105|57|62|47|50|
|15-44<br>|202<br>|233<br>|103<br>|122|69|100|51|70|
|45-64|436|335|351|297|147|161|84|83|
|65+|1501|1404|1620|1506|986|<br>1046|<br>842|780|
_Estimates and Projections of Mortality by Cause_ _34_ Table B3. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|2|000|_2_|_015_|
|---|---|---|---|---|---|---|---|---|
|<br>_and age_|_Mae_|_Female_|_Male_|_Female_|_Male_|_Female_|_Male_|_Female_|
|Industrlal|||||||||
|Total|106|85|82|66|64|47|68|38|
|<br>0|<br>341|<br>138|<br>55|<br>39|<br>0|<br>2|<br>0|0|
|1-4|187|229|37|46|5|33.|2|19|
|5-14|3|1|1|0|0|0|0|0|
|15-44|6|3|4|1|0|0|0|0|
|<br>45-64|<br>75|<br>28|<br>43|<br>17|<br>0|<br>0|<br>0|0|
|<br>65+|<br>736|<br>442|<br>700|<br>412|<br>556|<br>285|<br>477|201|
|<br>Nonmarket|||||||||
|Total|224|159|158|88|103|79|128|106|
|<br>0|<br>2150|<br>781|<br>671|<br>509|315|213|157|48|
|<br>1-4|<br>143|<br>44|611|594|0|28|19|35|
|<br>5-14|<br>40|8|<br>13|<br>6|2|0|0|0|
|15-44|70|20|64|5|16|0|0|0|
|45-64|319|97|163|26|142|1|95|u|
|65+|1295|938|544|267|674|531|1002|729|
|LAC|||||||||
|Total|366|301|211|177|100|86|67|55|
|0|3962|2957|2339|2010|1402|1151|952|710|
|1-4|671|611|390|385|175|172|47|43|
|5-14|79|72|36|35|15|13|8|6|
|15-44|99|93|53|40|13|15|7|9|
|45-64|3O0|200|206|105|65|24|22|10|
|65+|1306|1076|1083|847|825|615|670|455|
|Sv'-sSahara|||||||||
|Total|1070|937|817|683|498|430|346|286|
|o|8286|6949|6473|5350|4318|3557|3095|2449|
|1-4|1972|1734|1564|1186|746|584|622|402|
|5-14|414|456|257|280|170|178|126|127|
|15-44|466|416|341|306|246|226|170|155|
|45-64|742|540|617|440|435|335|286|214|
|65+|1900|1828|1681|1578|1393|1337|1205|1105|
|MENA|||||||||
|Total|624|653|459|473|209|237|142|164|
|<br>o|<br>5806|<br>5856|<br>5034|<br>4194|<br>2599|<br>2152|1859|1481|
|<br>1-4|<br>973|<br>1147|<br>1081|<br>1111|<br>215|221|164|184|
|5-14|160|218|109|124|52|60|38|43|
|15l-|256|285|94|153|74|134|43|86|
|<br>45-64|<br>584|<br>432|<br>280|<br>277|<br>195|<br>239|<br>116|142|
|<br>65+|<br>1594|<br>1425|<br>1299|<br>1409|<br>1088|<br>1207|<br>955|1010|
|Asia|||||||||
|Total|506|577|319|323|149|176|110|119|
|0|3603|4164|3465|2960|1852|1509|1291|992|
|1-4|14"'|1623|707|726|196|191|108|104|
|5-14|101|154|63|75|31|35|21|24|
|<br>15-44|<br>170|<br>217|<br>75|49|42|83|28|53|
|45-64|396|314|345|309|114|146|60|66|
|<br>65+|<br>1472|<br>1404|<br>1736|<br>1620|953|1065|811|767|
_35_

**_Annex_** _B. Suppimentary_ **_Tables_**

Table B3. MortaUty rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|_2_|_000_|_2_|_015_|
|---|---|---|---|---|---|---|---|---|
|<br>_and age_|_Mak_|_Female_|_Male_|_Female_|_Mak_|_Female_|_Male_|_Female_|
||||Neo|piasms|||||
|World|||||||||
|Total|95|96|108|96|108|98|128|114|
|0|9|8|11|8|9|9|10|9|
|1-4|16|18|22|20|9|9|9|9|
|5-14|7|7|6|6|8|8|8|8|
|15-44|17|21|20|22|17|20|17|21|
|45-64|241|216|270|215|251|217|256|219|
|65+|1055|738|1127|748|1009|721|1039|746|
|Developed|||||||||
|Total|167|163|203|172|182|170|213|188|
|0|10|5|8|8|8|8|8|7|
|1-4|60|66|31|35|7|9|6|7|
|5-14|8|4|6|4|6|4|6|3|
|15-44|18|18|18|17|16|13|15|11|
|45-64|256|193|296|196|246|178|249|172|
|65+<br>|1275|831|1503|880|1096|797|1091|800|
|Developing|||||||||
|Total<br>|68<br>|68<br>|78<br>|70<br>|90<br>|79<br>|_1ll_<br>|98<br>|
|0|9|8|11|8|10|9|10|9<br>|
|1-4|7|8|20|18|9|9|9|9|
|5-14|6|7|6|6|8|9|8|9|
|15-44|16|22|20|23|17|22|17|23|
|45-64|233|232|257|226|252|234|257|234|
|65+|857|614|862|613|958|658|1013|712|
|Industrw|||||||||
|Total|186|169|240|192|196|171|236|200|
|0|10|4|6|6|7|7|7|6|
|1-4|82|92|45|52|6|8|4|6|
|5-14|7|2|4<br>|1|4|2|4|2|
|15-44|16|12|15|10|14|8|13|7|
|45-64|250|172|309|178|247|153|249|152|
|65+|1337|882|1679|1030|1109|814|1123|824|
|Nonmarket|||||||||
|Total|129|152|136|135|158|169|173|168|
|0|11|8|10|9|10|9|10|9|
|1-4|17|16|11|12|9|9|9|10|
|5-14|10|9|9|8|9|8|8|6|
|19-.4|22|29|25|30|19|22|18|18|
|S5-64|271|232|272|225|244|226|248|211|
|<br>65+|<br>1103|<br>727|<br>998|<br>560|<br>1067|<br>764|<br>1012|744|
|LAC|||||||||
|Total|79|76|76|70|94|86|122|109|
|0|8|7|9|8|10|9|10|9|
|1-4|14|12|9|9|10|10|10|9|
|5-14|6|6|7|7|9|9|9|9|
|15-44|16|22|15|19|18|20|17|19|
|45-64|221|222|223|204|265|219|268|210|
|65+|1021|_m_|998|702|1032|728|1063|758|
_36_ _Estimates and Projections of Mortality by Cause_ Table B3. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|_2_|_000_||_2015_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Mak_|_Femak_|_Mak_|_Femak_|_Male_|_Female_|<br>_Male_|_Female_|
|Sub-Sahara|||||||||
|Total|52|57|52|55|54|55|60|60|
|0|9|3|9|8|9|9|10|9|
|1-4|5|7|6|8|8|9|8|9|
|5-14<br>|2<br>|5<br>|5<br>|7<br>|6<br>|8<br>|7<br>|9<br>|
|15-44|12|24|14|23|16|23|17|22|
|45-64|213|236|222|235|234|234|244|233|
|<br>65+|<br>796|<br>569|833|<br>593|<br>882|<br>617|914|640|
|MENA|||||||||
|Total|60|56|65|60|69|62|81|70|
|0|8|7|9|9|10|9|10|9|
|14|7|7|7|8|10|10|10|10|
|5-14|6|7|7|8|8|9|9|9|
|15-44|18|23|18|22|18|22|18|22|
|45-64|206|212|244|234|251|233|257|232|
|<br>65+<br>|<br>737|510|925|625|956|644|979|664|
|Asia|||||||||
|Total|70|70|85|74|101|87|130|113|
|0|10|9|13|8|10|9|10|9|
|14|6|7|29|25|10|10|9|9|
|5-14<br>|7<br>|8<br>|5<br>|6<br>|9<br>|9<br>|8<br>|9<br>|
|15-44|17|22|22|24|17|22|17|24|
|45-64<br>|241<br>|235<br>|268|227<br>|253<br>|236<br>|258|238|
|65+|852|605|837|599|956|653|1021|719|
||<br>Circ|<br>ulatoy Sys|<br>tem and C|<br>=tidn Dege|<br>nerative D|<br>iseases|||
|World|||||||||
|Total|297|324|262|286|292|283|339|314|
|0|<br>124|121|99|82|62|45|42|26|
|1-4|33|35|25|22|8|7|7|5|
|5-14|14|15|10|9|7|6|6|5|
|15-44|54|46|41|34|38|31|37|29|
|45-64|579|372|488|318|494|299|481|275|
|65+|3798|3396|3364|3245|3376|3070|3437|3108|
|Developed|||||||||
|Total|463|552|473|563|486|536|575|597|
|0|40|9|26|19|0|0|0|0|
|14|19|21|11|17|1|2|1|1|
|5-14|4|1|1|1|1|0|1|0|
|15-44|40|17|32|11|30|11|28|9|
|45-64|530|253|506|216|443|169|440|157|
|65+|4170|3691|4064|3793|3485|3225|3507|3234|
|Developing|||||||||
|Total|234|225|198|192|244|216|291|252|
|0|139|142|111|93|71|51|47|30|
|14|36|38|28|23|9|8|7|6|
|5-14|17|19|11|10|8|7|7|6|
|15-44<br>|60<br>|58<br>|44<br>|41<br>|40<br>|35<br>|39<br>|32<br>|
|45-64|606|459|479|377|516|357|494|314|
|65+|3462|3005|2872|2682|3313|2943|3402|3028|
_Annex B. Suppkmentary Tables_ _37_ Table B3. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|_2_|_000_|2|015|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Mae_|_Fenmal_|_Mal_|_Female_|_Male_|_Femal_|_Male_|_Female_|
|Induswtrial|||||||||
|Total<br>|500<br>|567<br>|461<br>|518<br>|513|551|615|639|
|0|30|11|34|25|0|0|0|0|
|1-4<br>|26<br>|29<br>|17|26|1|2|0|1|
|5-14|2|1|1|0|0|0|0|0|
|15-44<br>|29<br>|10<br>|22<br>|6<br>|21<br>|6<br>|19<br>|5<br>|
|45-64<br>|502<br>|203<br>|417<br>|142|410|123|412|121|
|65+|4193|3754|3689|3394|3501|3258|3466|3228|
|Nonmarket|||||||||
|Total|392|524|495|644|437|509|505|526|
|0<br>|60<br>|5<br>|14<br>|11<br>|0<br>|0|0|0|
|1-4<br>|7<br>|4<br>|2<br>|4|1|2|2|2|
|5-14<br>|7<br>|3<br>|2<br>|2<br>|3<br>|1<br>|2|1|
|15-44<br>|58<br>|31|51|19|47|20|42|16|
|45-64<br>|595<br>|343<br>|670<br>|338<br>|510<br>|260<br>|497<br>|225<br>|
|65+<br>|4105|3562|5140|4642|3447|3159|3610|3247|
|LAC<br>|||||||||
|Total<br>|238<br>|214<br>|228<br>|196<br>|242|215|306|275|
|0<br>|81<br>|55<br>|79<br>|63<br>|27<br>|14<br>|12<br>|3|
|1-4<br>|20|16|14|14|6|5|3|2|
|5-14<br>|9<br>|8<br>|6<br>|6<br>|4<br>|3<br>|3<br>|2<br>|
|15-44<br>|50<br>|39<br>|40|26|35|20|34|18|
|45-64<br>|561<br>|376<br>|554|312|517|259|497|228|
|65+<br>|3468|3116|3449|2960|3470|3002|3424|3028|
|Sub-Sahara<br>|||||||||
|Total<br>|243<br>|226<br>|209<br>|191<br>|182<br>|169<br>|180<br>|162<br>|
|0|291|236|221|173|138|102|90|59|
|1-4<br>|51|44|41|30|20|16|17|11|
|5-14<br>|42|41|27|26|19|17|15|13|
|15-44<br>|90<br>|83<br>|75<br>|67<br>|64<br>|54<br>|55<br>|44<br>|
|45-64|677|580|648|524|602|463|**565**|394|
|65+<br>|3654|3135|3562|3047|3430|2948|3348|2860|
|MENA|||||||||
|Total|250|224|200|183|191|171|209|176|
|0<br>|192<br>|191<br>|166<br>|128<br>|72|49|44|26|
|1-4|26|30|29|29|7|6|6|6|
|5-14<br>|24<br>|27<br>|13<br>|12<br>|8<br>|7<br>|7<br>|5<br>|
|15-44<br>|78<br>|81<br>|45<br>|43<br>|43<br>|41<br>|38<br>|34<br>|
|45-64|669|552|563|421|540|398|522|343|
|65+|3498|2909|3518|3089|3419|3013|3365|2942|
|Asia|||||||||
|Total|230|227|191|194|268|235|338|292|
|0<br>|111<br>|128<br>|71<br>|64<br>|50<br>|36<br>|31<br>|19<br>|
|1-4|37|41|26|22|6|6|4|3|
|5-14<br>|13<br>|15<br>|8<br>|7<br>|6<br>|5<br>|4<br>|4|
|15-4<br>|55<br>|53<br>|40<br>|39<br>|36<br>|33<br>|36<br>|31<br>|
|45-64|596|443|438|360|501|351|479|312|
|65+|3431|2982|2625|2546|3267|2924|3410|3063|
_Estimates and Projections of Mortality by Cause_ _38_ Table 83. Mortality rates per 100,000 (continued)

|_Region_|_19_|_70_|_19_|_85_|_20_|_00_|_2015_|
|---|---|---|---|---|---|---|---|
|<br>_and age_|_Male_|_Femae_|_Male_|_Femae_|_Male_|_Female_|_Male_<br>_Female_|
|||Co|mplication|s of Pregna|ncy|||
|World|||||||<br>|
|Total|0<br>|13<br>|0<br>|9<br>|0<br>|9<br>|0<br>7<br> <br>|
|0|0|0|0|0|0<br>|0<br>|0<br>0<br> <br>|
|1-4|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|5-14|0|0|0|0|0|0|0<br>0<br>|
|15-44|0|30|0|20|0<br>|18<br>|0<br>15<br> <br>|
|45-64|0|4|0|2|0|3|0<br>3<br>|
|65+|0|0|0|0|0|0|0<br>0|
|Developed|||||||<br>|
|Total|0|2|0|1|0|1<br>|0<br>1<br> <br>|
|0|0|0|0|0|0|0<br>|0<br>0<br> <br>|
|1-4|0|0|0|0|0|0<br>|0<br>0<br> <br>|
|5-14|0|0|0|0|0|0|0<br>0<br> <br>|
|15-44|0|4|0|3|0<br>|2<br>|0<br>1<br> <br>|
|45-64|0|1<br>|0<br>|1<br>|0<br>|1<br>|0<br>1<br> <br>|
|65+|0|0|0|0|0|0|0<br>0|
|Developing|||||||<br>|
|Total|0<br>|18<br>|0<br>|12<br>|0<br>|11<br>|0<br>9<br> <br>|
|0|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|1-4<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|5-14|0|0|0|0|0|0<br>|0<br>0<br> <br>|
|15-44|0|41|0|26|0|21|0<br>17<br> <br>|
|45-64|0|6|0|2|0|4|0<br>3|
|65+|0|0|0|0|0|0|0<br>0|
|Industrial|||||||<br>|
|Total|0|0|0|.0|0|0|0<br>0|
|0|0|0|0|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|1-4|0|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|5-14|0|0|0|0|0|0|0<br>0<br> <br>|
|15-"4|0|1|0|0|0|1|0<br>0|
|45-64|0|0|0|0|0|1<br>|0<br>1<br> <br>|
|65+|0|0|0|0|0|0|0<br>0|
|Nonmarket|||||||<br>|
|Total|0|4|0|3|0<br>|2<br>|0<br>2<br> <br>|
|0|0|0|0|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|1-4|0|0|0|0|0|0|0<br>0<br> <br>|
|5-14|0|0|0|0|0|0|0<br>0|
|15-44|0|9|0|7|0|5|0<br>3|
|45-64|0|2|0|2|0|2|0<br>2|
|65+|0|0|0|0|0|0|0<br>0|
|LAC||||||||
|Total|0|12|0|6|0|4|0<br>3|
|0|0|0|0|0|0<br>|0<br>|0<br>0<br> <br>|
|1-4|0|0|0|0|0|0|0<br>0|
|5-14|0|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>0<br> <br>|
|15-44<br>|0<br>|27<br>|0<br>|13<br>|0<br>|8<br>|0<br>6<br> <br>|
|45-64|0|4|0|2|0|2|0<br>2|
|65+|0|0|0|0|0|0|0<br>0|
_Annex B. Supplmentary Tables_ _39_

|Table B3. Mort<br>|ality rates pe<br>|r 100,000 (c<br>|ontinued)<br>||||||
|---|---|---|---|---|---|---|---|---|
|_Region_|_1_|_970_|_1_|_85_|_2_|_000_|_2_|_015_|
|<br>_and age_|<br>_Male_|<br>_Female_|<br>_Mak_|<br>_Femak_|<br>_Mak_|<br>_Femak_|_Mak_|_Femak_|
|Sub-Sahara<br>|||||||||
|Total<br>|0<br>|27<br>|0<br>|21<br>|0<br>|17|0|14|
|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|1-4<br>|0|0|0|0|0|0|0|0|
|5-14<br>|0<br>|0<br>|0<br>|0|0|0|0|0|
|15-44<br>|0|64|0|49|0|38|0|29|
|45-64<br>|0<br>|8<br>|0<br>|7<br>|0<br>|6<br>|0<br>|5|
|65+<br>|0|0|0|0|0|0|0|0|
|MENA<br>|||||||||
|Total|0|21|0|13|0|12|0|10|
|0<br>|0|0|0|0|0|0|0|0|
|1-4<br>|0|0|0|0|0|0|0|0|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|0<br>|49<br>|0<br>|29<br>|0|26|0|20|
|45-64<br>|0<br>|8<br>|0<br>|5<br>|0<br>|5<br>|0<br>|4<br>|
|65+<br>|0|0|0|0|0|0|0|0|
|Asia<br>|||||||||
|Total|0|17|0|11|0|10|0|8|
|0<br>|0<br>|0<br>|0<br>|0|0|0|0|0|
|1-4<br>|0|0|0|0|0|0|0|0|
|5-14<br>|0<br>|0<br>|0|0|0|0|0|0|
|15-44|0|38|0|24|0|19|0|15|
|45-64<br>|0<br>|6<br>|0<br>|2<br>|0|4|0|3|
|65+|0|0|0|0|0|0|0|0|
|||Cer|tin Peinat|<br>Condti|ons||||
|World<br>|||||||||
|Total<br>|86|70|79|59|48|36|37|27|
|0<br>|2778<br>|2421<br>|3095<br>|2375<br>|2129<br>|1632<br>|1889<br>|1396|
|1-4|1|1|1|1|0|0|0|0|
|5-14<br>|0<br>|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64<br>|0<br>|0<br>|0|0|0|0|0|0|
|65+<br>|0|0|0|0|0|0|0|0|
|Developed<br>|||||||||
|Total<br>|26|10|15|10|13|9|13|7|
|0<br>|1511|647|940|656|1004|705|976|616|
|1-4<br>|0<br>|1<br>|5<br>|4|0|0|0|0|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
|Developing<br>|||||||||
|Total|109|96|98|75|56|43|42|31|
|0<br>|3009|2752|3459|2667|2279|1753|2009|1496|
|1-4<br>|1<br>|1<br>|1<br>|1<br>|0<br>|0<br>|0|0|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0|0|0|
|15-44<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
_ESWmata and Projections of Mortali4y by Cause_ _40_ Table 3. Mortaity rates per 100,000 (continued)

|_Rclon_|_1_|_970_|_1_|_985_|_2_|_000_|_2_|_015_|
|---|---|---|---|---|---|---|---|---|
|_and 4e_|_Male_|_Female_|_Mal_|_Femal_|_Male_|_Fcmale_|_Male_|_Femalk_|
|Industral|||||||||
|Total|21|7|8|5|10|6|10|5|
|0|1201|451|551|387|798|558|785|463|
|1-4|0|1|7|5|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|
|<br>45-64|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|65+|0|0|0|0|0|0|0|0|
|Nonmarket|||||||||
|Total|37|15|28|17|20|13|19|11|
|0|2117|1030|1505|1035|1313|924|1243|828|
|1-4|0|0|1|2|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-4|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
|LAC|||||||||
|Toud|61|42|65|44|40|28|30|20|
|<br>0|<br>1870|<br>1314|<br>2223|1572|<br>1817|1369|1629|1175|
|1-4|1|0|0|0|0|0|0|0|
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|<br>65+|<br>0|<br>0|<br>0|<br>0|<br>0|0|0|0|
|Sub-Sahara|||||||||
|Total|200|157|167|129|119|90|82|61|
|0|4734|3843|3970|3165|3062|2406|2547|1936|
|1-4|2|2|1|1|1|1|1|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|<br>65+|0|0|0|0|0|0|0|0|
|bMA|||||||||
|Total|140|126|120|97|73|57|52|39|
|0|3668|3350|3360|2672|2336|1808|2023|1520|
|1-4|1|1|1|1|0|0|0|0|
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|15-4|0|0|0|0|0|0|0|0|
|<br>45-64|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|65+|0|0|0|0|0|0|0|0|
|Asia|||||||||
|Total|98|91|88|67|42|32|30|22|
|0|2749|2654|3558|2719|2017|1527|1778|1300|
|<br>1-4|<br>1|<br>2|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|5-14|0|0|0|0|0|0|0|0|
|<br>15-44|<br>0|<br>0|<br>0|<br>0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|<br>65+|0|0|0|0|0|0|0|0|
_Annex_ **_B._** _Suppkmentary Tablks_ _41_ Table B3. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|2|000||_2015_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Female_|<br>_Male_|_Female_|_Male_|_Female_|_Male_|_Female_|
||||Injury an|d Poisonng|||||
|World|||||||||
|Total|93|40|97|56|78|31|79|32|
|0|108|97|142|114|83|66|74|58|
|1-4|100|86|209|171|45|34|43|31|
|5-14|31|14|32|17|24|11|23|10|
|15-44|100|22|86|37|82|20|79|19|
|45-64|124|32|110|47|109|29|106|29|
|65+|217|153|209|157|<br>201|<br>144|205|151|
|Developed|||||||||
|Total|99|51|87|40|77|37|80|39|
|0|82|36|52|37|42|31|41|27|
|1-4|263|223|136|130|30|28|26|23|
|5-14|27|6|16|5|13|4|13|4|
|15-44|78|15|79|14|62|10|58|8|
|45-64|103|30|97|27|97|23|96|22|
|65+|226|176|200|142|209|163|210|164|
|Developing|||||||||
|Total,|91|35|100|62|78|29|79|30|
|0|113|108|157|127|88|71|79|61|
|1-4|65|56|222|178|47|35|45|32|
|5-14|33|16|35|19|25|12|24|11|
|15-44.|109|25|88|44|86|23|82|21|
|45-64|136|33|117|58|113|31|108|31|
|65+|208|122|216|171|197|128|202|142|
|Industrial|||||||||
|Total|98|58|74|40|70|36|74|40|
|0|79|30|41|28|34|24|33|20|
|1-4|368|316|168|170|25|26|17|18|
|5-14|24|3|11|2|8|2|9|2|
|15-44|63|11|58|10|49|7|45|6|
|45-64|89|28|78|24|87|19|87|19|
|65+<br>|225|187|195|150|210|167|209|168|
|Nonmarket|||||||||
|Total|100|40|109|39|90|38|90|37|
|0|88|48|69|50|54|40|51|36|
|1-4|64|49|89|75|38|30|39|31|
|5-14|32|11|26|10|21|8|19|7|
|15-44|105|20|119|21|86|15|78|12|
|45-64|137|33|133|32|118|30|115|28|
|65+|230|155|214|125|208|155|213|156|
|LAC|||||||||
|Total|98|31|90|29|76|28|78|29|
|0|74|56|88|73|72|57|65|49|
|1-4|67|45|49|37|46|34|43|30|
|5-14|32|13|27|13|22|10|21|10|
|15-44|119|24|103|21|83|20|76|17|
|45-64|157|35|153|32|113|29|108|28|
|65+|258|133|259|132|205|145|203|152|
42 _Estimates and Projections of Mortality by Cause_ Table 83. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|2|000||_2015_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Female_|<br>_Male_|_Female_|<br>_Male_|_Female_|<br>_Male_|_Female_|
|Sub-Sahara|||||||||
|Total|108|39|96|34|86|30|82|28|
|0|174|150|147|125|115|96|97|78|
|1-4|74|60|67|51|54|41|52|38|
|5-14|50|22|39|18|33|15|30|14|
|15-44|133|26|120|25|111|24|103|23|
|45-64|149|33|143|32|133|32|125|32|
|65+|210|118|206|119|202|120|199|121|
|MENA|||||||||
|Total|90|37|80|32|75|28|76|28|
|0|130|126|126|106|90|73|79|62|
|1-4|54|47|59|50|46|34|46|34|
|5-14|36|19|29|14|25|12|25|12|
|15-44|113|30|94|23|92|23|86|23|
|45-64|135|34|124|32|120|32|116|31|
|65+<br>|197|110|206|129|201|128|200|129|
|Asia|||||||||
|Total|87|34|105|78|77|29|79|31|
|0<br>|104<br>|105<br>|181<br>|143<br>|79<br>|63<br>|70<br>|54<br>|
|1-4|65|59|334|272|45|34|42|29|
|5-14|29|15|37|21|23|11|22|10|
|15-44<br>|104|24|79|55|81|23|77|21|
|45-64|131|32|108|69|110|31|105|31|
|65+|200|122|211|189|195|126|202|145|
||||<br>Ote|<br>Causes|||||
|World|||||||||
|Total|273|289|201|204|161|167|157|150|
|0|2204|2075|1666|1386|1280|1019|1013|m|
|1-4|432|457|349|342|109|93|88|66|
|5-14|57|57|39|35|29|24|26|20|
|15-44|60|61|39|39|29|34|25|28|
|45-64<br>|245|186<br>|163|128|126|115|105|90|
|65+<br>|1700|1612|1539|1419|1473|1373|1428|122|
|Developed|||||||||
|Total|153|180|161|154|160|152|191|163|
|0|881|365|587|425|213|159|177|105|
|1-4|190|206|329|344|12|21|12|17|
|5-14|16|5|10|4|5|2|5|1|
|15-44|23|12|28|8|11|4|8|3|
|45-64|124|76|128|57|72|24|65|16|
|65+|1057|1051|1047|834|1273|929|1317|911|
|Developing|||||||||
|Total|318|336|213|221|162|171|150|147|
|0|2446|2394|1849|1550|1422|1133|1122|858|
|1-4|484|511|352|341|123|103|99|73|
|5-14|69|72|45|41|33|27|29|22|
|15-44|75|82|42|48|33|41|28|33|
|45-64|312|266|181|169|149|156|118|113|
|65+|2282|2358|1884|2020|1589|1736|1482|1417|
_Annex B. Supplementary_ **_Tables_** 43 Table B3. Mortality rates per 100,000 (continued)

|_Region_|_1_|_970_|_1_|_985_|2|000||_2015_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Femal_|_Male_|_Femalk_|<br>_Male_|_Femae_|_Male_|_Female_|
|Industdil|||||||||
|Total|125|135|120|128|154|131|171|123|
|0<br>|614<br>|255<br>|535<br>|395|97|80|82|43|
|1-4<br>|244<br>|289<br>|154<br>|193<br>|10<br>|21<br>|4|11|
|5-14<br>|8<br>|2<br>|4<br>|1<br>|2<br>|0|2|0|
|15-44|14|7|14|4|3|1|2|1|
|45-64<br>|84<br>|49<br>|80|38|31|1|30|0|
|65+<br>|779|715|821|725|1239|806|1133|653|
|Nonmarket<br>|||||||||
|Total<br>|209<br>|260<br>|237|200|172|189|225|231|
|0<br>|1402<br>|580<br>|663<br>|467<br>|386<br>|276|311|192|
|1-4<br>|87|49|577|553|15|21|23|25|
|5-14<br>|29<br>|9<br>|20<br>|9<br>|11|4|9|3|
|15-44<br>|40|20|55|16|24|9|17|6|
|45-64<br>|218<br>|124|217|89|155|69|133|47|
|65+<br>|1819|1729|16%|1066|1352|1177|1769|1495|
|LAC<br>|||||||||
|Total<br>|255<br>|227<br>|213<br>|184<br>|124<br>|111<br>|119|102|
|0<br>|1891<br>|1400<br>|1627<br>|1323|915|723|703|518|
|1-4<br>|265<br>|234<br>|286<br>|273<br>|78<br>|69<br>|34<br>|26<br>|
|5-14|47|38|31|22|17|10|13|7|
|15-44|63|61|36|26|22|16|16|12|
|45-64|306|232|215|125|123|71|97|50|
|65+|2078|1921|2135|1799|1520|1253|1342|1022|
|Sub-Sahara|||||||||
|Total<br>|491|438|386|334|258|233|1%|174|
|0<br>|4159<br>|3388<br>|3306<br>|2655<br>|2292<br>|1833<br>|1718<br>|1324<br>|
|1-4<br>|670<br>|577<br>|536|399|266|203|225|144|
|5-14<br>|171<br>|158|111|100|77|66|60|49|
|15-4|135|123|104|94|80|74|61|56|
|45-64<br>|420|350|366|299|287|245|223|184|
|65+<br>|2548|2732|2307|2401|1997|2091|1795|1790|
|MENA<br>|||||||||
|Total<br>|400<br>|404<br>|260<br>|263|157|166|131|137|
|0<br>|3470|3320|2636|2129|1483|1187|1135|879|
|1-4<br>|391|435|377|376|92|85|75|73|
|5-14|80|87|54|48|32|26|26|21|
|15-44<br>|100<br>|103<br>|44|55|39|50|30|38|
|45-64<br>|422<br>|350<br>|218<br>|214<br>|180<br>|194|146|145|
|65+<br>|2921|3048|1986|2253|1736|1960|1587|1695|
|Asia<br>|||||||||
|Total<br>|289<br>|327<br>|175<br>|199|147|167|145|149|
|0|2051|2199|1265|1105|1131|890|867|651|
|1-4<br>|498<br>|555|307|329|85|75|53|44|
|5-14|53|60|32|29|23|18|18|13|
|15-44<br>|64<br>|76|33|43|24|37|20|29|
|45-64|286|249|148|152|130|151|102|109|
|65+|2193|2305|1783|1985|1539|1748|1454|1405|
_Estimates and Projetions of Mortality by Cause_ _44_ Table 84. MotalIty rates per 100,000 from major c _.s,_ by **age, sexc,** and region, 1970-

|2015||||||_|||
|---|---|---|---|---|---|---|---|---|
|_Region_<br>_and age_|_197_<br>_Malc_|_0_<br>_Female_|_198_<br> <br>_Male_|_5_<br>_Female_|200<br> <br>_Male_|0<br>_Femak_|_201_<br>_Male_|_5_<br>_Female_|
||||All|Causes|||||
|World|||||||||
|Total|23778|23614|25842|24057|26900|24576|33323|28950|
|0|5205|4607|5282|4111|4035|3092|3431|2512|
|1-4|3630|3666|3186|2854|1202|1022|1036|779|
|5-14|962|995|892|795|753|642|720|584|
|15-44|3052|2659|3011|2627|3247|2855|3499|2902|
|<br>45-64|<br>3875|<br>2808|<br>4666|<br>3307|<br>5461|3834|7582|4983|
|<br>65+|<br>7053|<br>8878|<br>8806|<br>10363|<br>12203|<br>13129|<br>17055|17190|
|Developed|||||||||
|Total|5323|5953|5941|6106|6132|6181|7470|7053|
|0|306|119|171|118|115|77|108|63<br>|
|1-4|262|241|274|269|18|29|18|24|
|5-14|71|19|35|14|23|9|21|7|
|15-44|427|171|481|143|344|109|283|83|
|45-64|1063|699|1340|700|1313|604|1540|661|
|65+|3194|4704|3640|4862|4319|5354|5501|6216|
|Developing|||||||||
|Total|18455|17661|19901|'17951|20769|18394|25853|21896|
|0|4899|4488|5111|3993|3920|3015|3323|2449|
|1-4|3369|3425|2913|2585|1184|994|1018|755|
|5-14|891|976|857|781|730|633|699|578|
|15-44|2625|2488|2529|2485|2902|2746|3216|2818|
|45-64|2813|2109|3326|2607|4148|3230|6042|4323|
|<br>65+|<br>3859|<br>4174|<br>5165|<br>5501|<br>7884|<br>7775|<br>11555|10974|
|Industrial|||||||||
|Total|3448|3657|3640|3672|3988|3864|4795|4410|
|0|132|49|65|44|46|32|45|25|
|1-4|221|221|88|96|9|17|5|10|
|5-14|27|5|11|3|7|2|8|2|
|15-44|187|64|195|54|153|38|126|29|
||644|358|723|335|757|301|902|346|
|45-64|||||||||
|65+|2236|2960|2558|3140|3015|3474|3709|3998|
|Nonmarket|||||||||
|otal|1875|2296|2301|2434|2144|2318|2675|2643|
|0|173|69|107|74|68|46|63|38|
|<br>1-4|<br>41|<br>20|<br>186|<br>174|<br>8|11|13|14|
|<br>5-14|<br>44|<br>14|<br>24|<br>11|<br>16|<br>7|<br>13|5|
|<br>15-44|240|107|286|88|192|70|156|54|
|<br>45-64|<br>419|<br>342|616|365|555|303|638|315|
|<br>65+|<br>958|<br>1744|<br>1082|<br>1722|1304|1880|1792|2217|
|LAC|||||||||
|Total|1557|1274|1768|1416|1778|1474|2294|1907|
|<br>0|<br>365|<br>259|<br>370|<br>285|<br>243|183|195|137|
|<br>1-4|185|159|163|152|72|64|31|24|
|5-14|65|50|52|39|38|25|30|18|
|<br>15-44|205|156|226|132|222|126|233|124|
|45-64|265|184|326|197|403|239|610|341|
|65+|4n|466|631|611|800|837|11%|1264|
_45_ _Annex B. Supplmentary Tables_ Tablo 4. Mortality rates per 100,000 (continued)

|_Region_|_197_|_0_|_198_|_5_|_200_|_0_|_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Mae_|_Female_|<br>_Mal_|_Femae_|_Mae_|_Femae_|_Mak_|_Female_|
|<br>Sub-Sahara|||||||||
|Total|313B|2796|3885|3318|4257|3697|5093|4264|
|0|1078|**884**|1337|1072|1370|1084|1309|994|
|1-4|**583**|**505**|733|551|536|414|595|385|
|5-14|263|266|273|267|305|281|337|?46|
|<br>15-44|<br>501|<br>455|<br>603|<br>531|<br>781|<br>670|991|809|
|45-64|336|281|444|368|568|482|807|631|
|<br>65+|<br>376|<br>405|<br>495|<br>529|<br>697|<br>767|<br>1053|1149|
|MtENA|||||||||
|Total|1993|1843|2272|2042|2264|2046|2831|2454|
|0|644|586|778|610|605|465|543|402|
|1-4|252|274|387|373|128|119|122|119|
|5-14|107|117|107|97|95|84|98|82|
|15-44|291|282|246|255|347|362|418|413|
|45-64|292|215|291|238|412|339|658|477|
|65+|407|370|462|468|677|676|992|960|
|Asia|||||||||
|Total|11768|11747|11976|11175|12469|11177|15634|13272|
|0|2811|2759|2626|2025|1702|1284|1277|916|
|1-4|2349|2487|1630|1510|448|397|270|227|
|5-14|456|544|424|378|291|243|233|181|
|15-44|1628|1595|1454|1567|1553|1588|1574|1473|
|45-64|1920|1429|2265|1804|2766|2171|3967|2874|
|65+|2604|2933|3577|3892|sno|5495|8313|7600|
|||<br>Infe|<br>cdous and|<br>Parasitic D|<br>iseases||||
|World|||||||||
|Total|8255|8280|7725|7039|5491|5495|5300|4957|
|<br>0|<br>2229|<br>2092|<br>2185|<br>1767|<br>1538|<br>1221|<br>1200|907|
|1-4|2409|2479|1788|1624|737|646|615|470|
|5-14|490|610|422|456|316|336|285|293|
|15-44|1213|1278|942|998|828|1133|755|1007|
|45-64|846|591|945|713|585|552|531|460|
|65+<br>|1068|1230|1444|1480|1487|1608|1914|1819|
|Developed|||||||||
|Totd|737|621|616|444|479|376|577|422|
|0|84|30|27|20|10|7|6|2|
|1-4|64|58|96|92|1|10|3|8|
|5-14|17|3|5|2|1|0|0|0|
|15-44|66|21|65|6|16|0|0|0|
|45-64|135|61|102|28|67|1|56|0|
|65+|371|449|321|295|384|358|512|412|
|Developing|||||||||
|Total|7518|7658|7109|6595|5013|5119|4723|4535|
|<br>0|<br>2145|<br>2062|<br>2158|<br>1747|<br>1528|<br>1215|<br>1195|905|
|1-4|2345|2421|1693|1532|736|636|612|462|
|<br>5-14|<br>473|<br>607|<br>417|<br>454|<br>315|<br>336|<br>285|293|
|15-44<br>|1147<br>|1257<br>|877<br>|992<br>|812<br>|1133<br>|755<br>|1007<br>|
|45-64|711|531|842|685|518|551|476|460|
|65+|697|781|1122|1185|1103|1249|1401|1408|
_Estimates and Projectionj of Mortality by Cause_ _46_ Table B4. Mortality rates per 100,000 (continued)

|_Region_|_197_|_0_|_198_|_5_|_200_|_0_|_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|<br>_andage_|_Male_|_Femae_|_Male_|_Femae_|_Mal_|_Female_|_Mak_|_Femae_|
|<br>Industrl|||||||||
|Total|351|305|303|255|254|192|277|162|
|0|20.|8|3|2|0|0|0|0|
|1-4|45|53|8|9|1|6|0|4|
|<br>5-14|<br>2|<br>1|<br>1|<br>0|<br>0|<br>0|<br>0|0|
|15-44|9|4|6|2|0|0|0|0|
|<br>45-64|<br>48|<br>21|<br>33|15|0|0|0|0|
|<br>65+|<br>226|<br>219|<br>253|<br>226|253|186|276|158|
|Nonmarket|||||||||
|Total|386|316|313|190|224|183|300|260|
|0|64|22|24|18|10|7|6|2|
|<br>1-4|18|5|88|83|0|4|3|5|
|5-14|15|3|5|2|1|0|0|0|
|15-44|57|16|58|4|16|0|0|0|
|45-64|87|40|69|13|67|1|56|0|
|65+|145|230|69|69|130|173|236|254|
|<br>LAC|||||||||
|Total|519|425|423|355|264|226|213|178|
|<br>0|<br>184|<br>132|<br>136|<br>113|80|63|55|39|
|<br>14|119|106|85|81|40|38|11|9|
|<br>5-14|<br>29|<br>27|<br>18|<br>17|<br>8|<br>7|<br>4|3|
|<br>15-44|<br>59|<br>55|<br>48|<br>37|<br>17|<br>19|10|14|
|<br>45-64|<br>53|<br>35|<br>50|<br>27|<br>24|<br>10|<br>14|6|
|<br>65+|<br>76|<br>71|<br>86|<br>80|<br>94|<br>90|<br>120|106|
|Sub-Sahara|||||||||
|Total|1552|1393|1838|1565|im|1552|1860|1553|
|0|506|422|613|500|595|482|536|416|
|<br>1-4|415|361|518|390|365|283|400|256|
|5-14|161|177|160|173|170|176|178|178|
|15-44|279|257|314|288|373|345|416|381|
|45-64|113|87|137|105|146|123|160|127|
|65+|78|88|97|108|123|144|170|195|
|MENA|||||||||
|Total|795|792|881|862|611|662|582|646|
|<br>0|<br>282|267|346|277|239|190|196|150|
|1-4|169|189|269|263|75|74|66|72|
|<br>5-14|<br>56|<br>71|<br>55|<br>59|40|44|36|39|
|<br>15-44|<br>132|141|78|120|9|164|84|160|
|<br>45-64|<br>85|58|57|56|63|74|66|75|
|<br>65+|<br>73|<br>66|<br>76|<br>88|<br>100|<br>117|134|151|
|Asia|||||||||
|Total|4651|5048|3967|3813|2366|2678|2067|2158|
|<br>0|<br>1174|<br>1241|<br>1064|<br>857|<br>613|<br>480|<br>407|300|
|<br>1-4|<br>1642|<br>1765|<br>821|<br>798|<br>256|241|135|125|
|<br>5-14|<br>227|<br>332|<br>184|<br>205|<br>98|108|67|73|
|<br>15-44|677|804|436|547|326|606|245|453|
|45-6|461|351|599|498|285|345|236|252|
|65+|470|555|864|909|788|898|978|956|
_Annae B. Supplmentary Tables_ _47_ Table 84. Mortality rates per 100,000 (continued)

|_Region_|_197_|_0_|_198_|_5_|_200_|_0_|201|5|
|---|---|---|---|---|---|---|---|---|
|<br>_and age_|_Mak_|_Femak_|_Mak_|_Femake_|<br>_Male_|_Female_|_Mak_|_Femak_|
||||Ne|oplasms|||||
|World|||||||||
|Total|1750|1778|2610|2293|3361|3005|4854|4245|
|0|5|4|7|5|7|6|7|6|
|1-4|34|36|50|45|25|24|26|24|
|5-14|29|28|31|30|51|52|55|54|
|15-44|134|163|220|234|247|284|291|358|
|<br>45-64|<br>615|<br>591|<br>973|<br>785|<br>1248|<br>1073|<br>1901|Uo08|
|<br>65+|<br>933|<br>956|<br>1330|<br>1193|<br>1784|<br>1565|<br>2575|2194|
|<br>Developed|||||||||
|Total|842|907|1154|1036|1121|1093|1370|1253|
|<br>0|<br>1|<br>0|<br>1|<br>1|<br>1|<br>1|<br>1|1|
|1-4|22|23|11|12|2|3|2|2|
|5-14|8|4|5|3|5|3|5|3|
|15-44|41|41|49|44|43|36|39|29|
|45-64|234|223|356|265|358|271|435|309|
|65+|535|615|732|711|712|779|888|909|
|Developing|||||||||
|Total|908|871|1456|1257|2240|1912|3484|2993|
|0|4|4|6|4|6|5|6|6|
|14|12|12|39|33|22|22|23|22|
|5-14|22|24|26|27|45|49|50|52|
|15-44|92|121|171|189|204|248|252|329|
|45-64|380|368|617|521|890|802|1466|1299|
|<br>65+|<br>398|<br>341|<br>598|<br>482|<br>1073|<br>786|<br>1686|1285|
|Industral|||||||||
|Total|620|604|885|744|775|702|963|842|
|0|1|0|0|0|0|0|0|0|
|1-4|20|21|9|10|1|2|1|1|
|<br>5-14|<br>4|<br>1|<br>2|<br>1|<br>2|<br>1|<br>2|1|
|15-44|24|17|27|17|25|14|21|11|
|45-64|161|128|241|149|242|155|289|179|
|65+|411|437|606|566|505|531|650|649|
|Nonmarket|||||||||
|Total|221|303|268|292|346|391|406|411|
|0|0|0|0|0|0|0|0|0|
|1-4|2|2|2|2|1|1|1|1|
|5-14|4|3|3|3|3|3|3|2|
|15-44|18|24|22|27|19|22|18|18|
|45-64|74|95|115|115|116|116|146|130|
|<br>65+|<br>124|<br>178|<br>126|<br>145|<br>206|<br>248|<br>238|259|
|LAC|||||||||
|Total|112|107|153|141|247|226|389|349|
|0|0|0|1|0|1|1|1|1|
|1-4|3|2|2|2|2|2|2|2|
|5-14|2|2|3|3|5|5|5|5|
|15-44|9|13|14|17|24|26|27|29|
|45-64|38|38|54|51|99|87|164|136|
|<br>65+|<br>59|<br>51|<br>79|<br>67|<br>117|<br>106|<br>190|177|
_and Projetin of Modali by Caue_ _48_ _.taes_ Table E4. Mortaity rates per 100,000 (contnued)

|_Region_|_197_|_0_|_198_|_5_|_200_|_0_|_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Femae_|_Mak_|_Femal_|_Mal_|_Femal_|_Mak_|_Female_|
|<br>Sub-Sahara|||||||||
|Total|75|84|116|126|192|200|324|325|
|0<br>|1<br>|0<br>|1<br>|1<br>|1<br>|1<br>|2<br>|2<br>|
|1-4|1|1|2|3|4|4|5|6|
|<br>5-14|<br>1|<br>2|<br>3|<br>4|<br>6|<br>8|<br>10|12|
|15-44|7|15|13|22|24|34|41|55|
|45-64|33|38|49|56|79|86|137|138|
|<br>65+|<br>33|<br>27|<br>48|<br>41|<br>78|<br>67|<br>129|113|
|MENA|||||||||
|Total|76|67|125|110|202|172|331|277|
|0|0|0|1|1|1|1|1|1|
|1-4|1|1|2|2|3|3|4|4|
|5-14|2|2|4|4|6|7|8|8|
|15-44|9|11|15|17|24|27|35|41|
|45-64|30|29|50|47|80|72|146|123|
|65+|34|24|54|39|87|63|137|99|
|_Asia_|||||||||
|Total|646|613|1063|880|1599|1313|2440|2042|
|0|3|3|4|2|3|3|3|3|
|<br>1-4|<br>7|<br>8|<br>33|<br>27|<br>13|<br>12|<br>12|10|
|5-14|17|17|16|15|28|29|27|27|
|15-44|66|83|130|133|133|161|149|205|
|45-64<br>|280<br>|263<br>|464<br>|366<br>|632<br>|558<br>|1019<br>|901<br>|
|65+|272|239|416|336|790|550|1230|896|
||<br>Circ|<br>aor<br>Sy|<br>stem and C|<br>erta Deg|<br>eneratve D|<br>iseae|||
|World|||||||||
|Total|5464|5970|6362|6846|9101|8662|12843|11714|
|0|71|64|61|48|44|30|.31|19|
|1-4|69|69|58|49|22|19|19|14|
|5-14|61|61|52|45|46|39|44|35|
|<br>15-44|<br>432|<br>352|<br>461|<br>365|<br>557|<br>429|<br>648|482|
|45-64|1475|1019|1761|1163|2461|1482|3580|2025|
|65+|3357|4404|3970|5176|5970|6664|8520|9140|
|Developed|||||||||
|Total|2339|3074|2681|3394|2990|3439|3699|3978|
|0|4|1|2|2|0|0|0|0|
|1-4|7|7|4|6|0|1|0|0|
|5-14|4|1|1|1|1|0|1|0|
|15-44|90|40|85|27|84|30|72|23|
|45-64|485|292|609|293|643|259|769|281|
|65+|1750|2732|1979|3066|2262|3150|2856|3674|
|Developing|||||||||
|Total|3124|2897|3681|3452|6111|5223|9144|7736|
|0|67|64|59|47|**44**|30|31|19|
|1-4|62|62|54|44|22|18|19|14|
|5-14|56|60|51|44|45|38|**43**|34|
|15-44<br>|342<br>|312<br>|376<br>|337<br>|473<br>|399<br>|576<br>|459<br>|
|45-64|989|727|1151|870|1818|1223|2812|1744|
|65+|<br>1608|1672|1990|2110|3709|3514|**5664**|**5466**|
_Anna B. Suppementary Tables_ _49_

|Table R4. Mor|tality rates pe|r 100,000 (|continued)||||||
|---|---|---|---|---|---|---|---|---|
|_Region_|_1970_||_1985_||200|0|_201_|_5_|
|<br>_and age_|_Mak_|_Female_|_Male_|_Female_|_Mak_|_Femak_|_Male_|_Female_|
|Industriat<br>|||||||||
|Total<br>|1665<br>|2032<br>|1702<br>|2002<br>|2033<br>|2258<br>|2514<br>|2694|
|0|2|1|2|1|0|0|0|0|
|1-4<br>|6|7|3|5|0|0|0|0|
|5-14<br>|1<br>|0<br>|1<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|43<br>|15<br>|38<br>|10<br>|37<br>|10<br>|30|7|
|45-64<br>|323|151|326|119|400|125|477|143|
|65+|1290|1858|1332|1866|1595|2123|2006|2544|
|Nonmarket|||||||||
|Total<br>|674<br>|1042<br>|979<br>|1392<br>|957<br>|1181<br>|1185<br>|1284<br>|
|0<br>|2<br>|0|1|0|0|0|0|0|
|1-4|1|0|0|1|0|0|0|0|
|5-14<br>|3<br>|1<br>|1<br>|1<br>|1<br>|0<br>|1<br>|0<br>|
|15-44|47|26|47|17|47|20|42|15|
|45-64|162|141|284|173|242|134|292|138|
|65+<br>|460|874|647|1200|666|1026|850|1130|
|LAC|||||||||
|Total|337|303|456|393|636|569|972|883|
|O<br>|4|2|5|4|2|1|1|0|
|1-4|4|3|3|3|1|1|1|0|
|5-14<br>|4<br>|3<br>|3<br>|3<br>|2<br>|2<br>|2<br>|1|
|15-44<br>|30<br>|23<br>|37<br>|24|45|25|53|27|
|45-64<br>|96<br>|65<br>|134<br>|79<br>|192<br>|102|305|147|
|65+<br>|201|207|275|231|394|438|611|707|
|Sub-Sahara|||||||||
|Total|353|336|470|439|648|609|970|881|
|0<br>|18<br>|14<br>|21|16|19|14|16|10|
|1-4|11|9|13|10|10|8|11|7|
|5-14|16|16|17|16|19|17|21|18|
|15-44|54|52|69|63|96|83|134|107|
|45-64|103|93|144|125|202|169|316|234|
|65+<br>|151|152|205|208|302|318|473|504|
|M1ENA<br>|||||||||
|Total<br>|319<br>|271|383|333|557|477|855|693|
|0<br>|9<br>|9<br>|11|8|7|4|5|3|
|1-4|5|5|7|7|2|2|2|2|
|5-14<br>|8|9|7|6|6|5|6|5|
|15-44|40|40|38|34|56|50|74|62|
|45-64|97|75|115|85|173|123|297|182|
|65+|159|134|205|193|313|293|471|439|
|Asia|||||||||
|Total|2115|1987|2373|2288|4269|3569|6348|5279|
|0<br>|36|38|22|19|17|11|10|6|
|1-4|43|45|31|24|8|7|5|4|
|5-14<br>|28<br>|33|24|19|18|15|14|11|
|15-44<br>|218<br>|197<br>|232<br>|217<br>|276<br>|241<br>|316<br>|263<br>|
|45-64|694|495|759|581|1251|829|1893|1180|
|65+|1097|1179|1306|1428|2700|2466|4109|3816|
_Estimates and Projections of Mortality by Cause_ _50_ Table 94. Mortality rates per 100,000 (continued)

|_Regin_|_197_|_0_|_1985_||_200_|_0_|_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|<br>_and age_|_Male_|_Female_|_Mak_|_Female_|_Mal_|_Female_|_Male_|_Female_|
|||C|ompliatUo|.s of Pregn|ancy||||
|World|||||||||
|Total|0|239|0|225|0|265|0|269|
|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|5-14|0|1|0|0|0|0|0|0|
|15-44|0|229|0|218|0|249|0|249|
|<br>45-64|0|10|0|7|0|16|0|20|
|<br>65+|<br>0|<br>0|0|0|0|0|0|0|
|<br>Developed|||||||||
|Total|0|10|0|8|0|7|0|5|
|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|9|0|7|0|6|0|4|
|<br>45-64|<br>0|<br>1|<br>0|<br>1|<br>0|2|0|2|
|65+|0|0|0|0|0|0|0|0|
|Developing|||||||||
|Total|0|229|0|218|0|257|0|263|
|<br>0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|<br>5-14|<br>0|<br>1|<br>0|<br>0|<br>0|<br>0|0|0|
|<br>15-44|<br>0|<br>220|<br>0|212|0|243|0|245|
|<br>45-64|<br>0|<br>9|0|6|0|14|0|18|
|<br>65+|<br>0|<br>0|0|0|0|0|0|0|
|Industrlal|||||||||
|Total|0|2|0|0|0|2|0|1|
|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|2|0|0|0|1|0|1|
|<br>45-64|<br>0|<br>0|<br>0|<br>0|<br>0|<br>1|<br>0|1|
|65+|0|0|0|0|0|0|0|0|
|Nonmarket|||||||||
|Total|0|9|0|7|0|6|0|4|
|<br>0|<br>0|<br>0|0|0|0|0|0|0|
|<br>1-4|0|0|0|0|0|0|0|0|
|<br>5-14|0|0|0|0|0|0|0|0|
|15-44|0|8|0|6|0|5|0|3|
|<br>45-64|<br>0|<br>1|<br>0|<br>1|<br>0|<br>1|<br>0|1|
|65+|0|0|0|0|0|0|0|0|
|LAC|||||||||
|Total|0|16|0|12|0|12|0|11|
|<br>0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>0|0|0|0|
|<br>15-44|<br>0|<br>16|0|12|0|11|0<br>|10<br>|
|45-64|0|1|0|1|0|1|0|1|
|65+|0|0|0|0|0|0|0|0|
_Annca B. Supplementary Tables_ _5s_ Table B4. MortalIty rates per 100,000 (continued)

|_RegIn_|_197_|_0_|_198_|_5_|_200_|_0_|_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_male_|_Feme_|_Mak_|_Female_|<br>_Mak_|_Female_|<br>_Mak_|_Femak_|
|Sub-Sahara|||||||||
|Total|0|41|0|48|0|61|0|74|
|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|1-4|0|0|0|0|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|39|0|46|0|59|0|71|
|45-64|0|1|0|2|0|2|0|3|
|65+|0|0|0|0|0|0|<br>0|0|
|MENA|||||||||
|Total|0|25|0|23|0|33|0|39|
|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|24|0|22|0|32|0|37|
|45-64|0|1|0|1|0|2|0|2|
|65+<br>|0|0|0|0|0|0|0|0|
|Asia|||||||||
|Total|0|147|0|134|0|151|0|139|
|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|141|0|131|0|142|0|127|
|45-64|0|6|0|3|0|9|0|12|
|65+|0|0|0|0|0|0|0|0|
|||<br>C|<br>ertain Peri|<br>matal Condi|<br>to_||||
|World|||||||||
|Total|1585|1292|1915|1406|1492|1102|1393|992|
|<br>0|<br>1582|<br>1290|<br>1912|<br>1404|<br>1492|<br>1102|<br>1392|991|
|1-4|2|3|3|2|1|1|1|1|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
|Developed|||||||||
|Total|133|54|86|58|83|55|83|50|
|0|133|54|84|56|83|55|83|50|
|1-4|0|0|2|1|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
|Developing|||||||||
|Total|1452|1238|1829|1349|1410|1047|1310|942|
|0|1450|1236|1828|1348|1409|1046|1309|941|
|1-4|2|2|1|1|1|1|1|1|
|5-14|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
_Estimtes and Projections of Mortality by Cause_ _52_ Table EUL Mortality rates per 100,000 (continued)

|_Region_<br>_and age_|_1970_<br>_Male_|_FemakF_|_1985_<br>_Ma_|<br>_Femal_|_2000_<br>_Mle_|<br>_Female_|2015<br>_Male_|_Femal_|
|---|---|---|---|---|---|---|---|---|
|Industrial|||||||||
|Total|70|25<br>|31<br>|20<br>|39<br>|26<br>|39<br>|22<br>|
|0|70|25|29|19<br>|39<br>|26<br>|39<br>|22<br>|
|1-4<br>|0<br>|0<br>|1<br>|1<br>|0<br>|0<br>|0<br>|0<br>|
|5-14|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
|Nonmarket|||||||||
|Total|63|29|55|37|43|29|44|28|
|0|63<br>|29<br>|55<br>|37<br>|43<br>|29<br>|44<br>|28<br>|
|1-4|0|0|0|0|0|0|0<br>|0<br>|
|5-14|0|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44|0|0|0|0<br>|0<br>|0<br>|0<br>|0<br>|
|45-64<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|65+|0|0|0|0|0|0|0|0|
|LAC|||||||||
|Total|87|59<br>|129<br>|89<br>|104<br>|75<br>|94<br>|65<br>|
|0|87<br>|59<br>|129<br>|89<br>|104<br>|75<br>|94<br>|65<br>|
|1-4|0|0|0|0|0|0|0|0<br>|
|5-14|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44|0|0|0|0|0|0|0<br>|0<br>|
|45-64|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|65+|0|0|0|0|0|0|0|0|
|Sub-Sahara|||||||||
|Total|290|233|376|296|423<br>|326<br>|442<br>|329<br>|
|0|289|233|376|296<br>|422<br>|326<br>|441<br>|329<br>|
|1-4|0|0|0|0|0<br>|0<br>|0<br>|0<br>|
|5-14|0|0|0|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|45-6|0|0|0|0|0<br>|0<br>|0<br>|0<br>|
|65+|0|0|0|0|0|0|0|0|
|MlENA|||||||||
|Total|178|153|231|177|214|159|213|154<br>|
|0|178|153|231|177|214|159<br>|213<br>|154<br>|
|1-4|0|0|0|0|0|0|0|0<br>|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
|<br>Asia|||||||||
|Total|897|793|1093|787|668|486<br>|561<br>|394<br>|
|0|896|791|1092|787|668|486|561|394|
|1-4|1|2|0|0|0|0|0|0|
|5-14|0|0|0|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44|0|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|45-64|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|
_Annex B. Supplemeniary Tables_ _53_ Table B4. Mortality rates per 100,000 (continued)

|_Region_<br>|_1970_||_198_|_5_|_2000_||_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Mak1_|_Female_|<br>_Mae_|_Femalt_|_Male_|_Female_|_Mal_|_Female_|
||||Injury an|Poisonin|8||||
|World<br>|||||||||
|Total<br>|1713<br>|734<br>|2345<br>|1349<br>|2423<br>|938<br>|2999<br>|1176<br>|
|0<br>|61<br>|52<br>|88<br>|67<br>|58<br>|45|55|41|
|1-4<br>|210<br>|171<br>|482<br>|378<br>|122<br>|90<br>|123|86|
|5-14<br>|136<br>|57<br>|174<br>|86<br>|153<br>|68|158|69|
|15-44<br>|798<br>|169|956|398|1194|282|1371|326|
|45-64<br>|316|87|398|170|540|141|786|211|
|65+<br>|191|199|247|250|35X,|313|507|443|
|Developed<br>|||||||||
|Total<br>|498<br>|286<br>|491<br>|238|473|235|513|259|
|0<br>|7|3|5|3|3|2|3|2|
|1-4|98|79|47|43|10|9|9|8|
|5-14<br>|26<br>|6<br>|15<br>|4|12|4|11|3|
|15-44<br>|177<br>|33<br>|209<br>|36<br>|171<br>|26<br>|151<br>|21<br>|
|45-64<br>|94<br>|35<br>|117<br>|36<br>|141|35|168|39|
|65+<br>|95|131|98|115|136|159|171|187|
|Developing<br>|||||||||
|Total<br>|1215<br>|448<br>|1854<br>|1110<br>|1950<br>|704<br>|2486<br>|916<br>|
|0<br>|54<br>|49<br>|83<br>|64<br>|54|42|51|39|
|1-4<br>|112<br>|92<br>|435|335|112|81|114|78|
|5-14<br>|109<br>|51|159|81|141|64|147|66|
|15-44<br>|620<br>|136<br>|747<br>|362<br>|1023<br>|256<br>|1220<br>|305<br>|
|45-64<br>|222|52|281|134|399|107|618|172|
|65+|97|68|149|135|220|153|336|257|
|Industrial<br>|||||||||
|Total<br>|326<br>|207|274|155|277|146|303|168|
|0<br>|5<br>|2<br>|2<br>|1|2|1|2|1|
|1-4<br>|90|73|34|33|5|5|3|3|
|5-14<br>|15|2|6|1|4|1|4|1|
|15-44<br>|92<br>|16<br>|101<br>|17<br>|85|11|72|9|
|45-64<br>|57<br>|21<br>|61<br>|20|85|19|101|22|
|65+<br>|69|93|71|83|96|109|121|132|
|Nonmarket<br>|||||||||
|Total<br>|171<br>|80|216|83|196|89|210|91|
|0<br>|3<br>|1<br>|3<br>|2|2|1|2|1|
|1-4<br>|8|6|13|10|5|4|5|4|
|5-14<br>|12<br>|4<br>|9|3|7|3|7|2|
|15-44<br>|86|17|109|19|86|15|79|12|
|45-64|37|14|**56**|16|56|15|67|17|
|65+|26|38|27|32|40|50|50|54|
|LAC|||||||||
|Total|139|44|181|58|199|74|247|94|
|0<br>|3<br>|2|5|4|4|3|4|3|
|14<br>|12|8|11|8|10|7|10|6|
|5-14<br>|12<br>|5<br>|13<br>|6|13|6|12|5|
|15-44<br>|70<br>|14<br>|95<br>|19<br>|107<br>|25<br>|119<br>|26<br>|
|45-64|27|6|37|8|42|11|67|18|
|65+|15|9|21|13|23|21|36|35|
_Estimates and Projections of Mortality by Cause_ _54_ Table 34. Mortality rates per 100,000 (continued)

|_Region_|_197_|_0_|_198_|_5_|_200_|_0_|_201_|_5_|
|---|---|---|---|---|---|---|---|---|
|_and age_|_Male_|_Female_|<br>_Male_|_Femtal_|_Male_|_Female_|<br>_Male_|_Female_|
|<br>Sub-Sahara|||||||||
|Total|157|58|215|79|305|109|442|154|
|0<br>|11<br>|9<br>|14<br>|12<br>|16<br>|13<br>|17<br>|13<br>|
|1-4|15|13|22|17|26|20|33|24|
|5-14|19|9|24|11|33|15|43|19|
|15-44|80|16|111|24|167|37|251|58|
|45-64|23|5|32|8|45|12|70|19|
|65+|9|6|12|8|18|13|28|21|
|MlENA|||||||||
|Total|115|44|154|58|220|77|311|108|
|0|6|6|9|7|8|6|8|6|
|1-4|9|8|15|12|16|11|19|13|
|5-14<br>|13<br>|6<br>|15|6|19|9|23<br>|10|
|15-44|58|15|78|18|120|28|167|42|
|45-64|20|5|25|6|38|10|66|17|
|65+<br>|9|5|12|8|18|12|28|19|
|Asia|||||||||
|Total|804|301|1304|916|1224|443|1486|560|
|0|34|31|55|41|26|20|22|16|
|**1-4**|75|64|388|298|59|43|52|35|
|5-14|65|32|106|58|75|35|69|31|
|15-44|412|90|463|301|629|165|684|179|
|45-64|153|36|187|112|274|74|415|119|
|65+|64|48|105|106|161|107|244|181|
||||<br>Othe|<br>CalUes|||||
|World|||||||||
|Total|5011|5320|4885|4899|5032|5108|5934|5597|
|0|1256|1105|1029|819|897|688|746|548|
|1-4|906|908|805|755|295|243|253|184|
|5-14|247|239|213|178|188|148|178|133|
|15-44|477|469|432|414|420|478|433|480|
|**45-64**|623|510|589|468|627|570|784|659|
|65+|1503|2090|1816|2263|2605|2981|3540|3593|
|Developed|||||||||
|Total|774|1000|913|929|986|976|1229|1086|
|0|77|31|52|36|18|12|15|9|
|1-4|71|73|115|115|4|7|4|5|
|5-14|16|5|9|4|5|2|4|1|
|15-44|53|27|73|22|30|11|20|7|
|45-64|114|88|154|78|104|37|113|29|
|65+|443|**778**|510|674|826|908|1072|1035|
|Developing|||||||||
|Total|4238|4320|3972|3970|4046|4132|4705|4511|
|0<br>|1178<br>|1075<br>|977<br>|783<br>|879<br>|676<br>|731<br>|539<br>|
|1-4<br>|835<br>|836<br>|690<br>|640<br>|291<br>|236<br>|249<br>|178<br>|
|5-14|231|234|205|175|183|146|174|132|
|15-4<br>|424<br>|442<br>|359<br>|393<br>|390<br>|467<br>|413<br>|473<br>|
|45-64|510|422|435|391|523|534|671|630|
|65+|1060|1312|1305|<br>1589|1779|2073|2467|2558|
_Annex B. Supplementary Tables_ _55_

|Table B4. Mor|tality rates pe|r 100,000 (|continued)||||||
|---|---|---|---|---|---|---|---|---|
|_Region_|_197_|_0_|_198_|_5_|_200_|_0_|201|5|
|<br>_and age_|_Male_|_Female_|_Maek_|_Femalk_|_Male_|_Female_|<br>_Male_|_Female_|
|Indusral<br>|||||||||
|Total<br>|414<br>|483<br>|445<br>|496<br>|609<br>|537<br>|700<br>|521<br>|
|0|36|14|28|20|5|4|4|2|
|1-4<br>|59<br>|67|32|38|2|4|1|2|
|5-14<br>|5|1|2|1|1|0|1|0|
|15-44|20|10|24|8|6|2|4|1|
|45-64|54|37|62|32|30|1|35|0|
|65+|240|354|297|399|565|525|656|515|
|Nonmarket|||||||||
|Total<br>|359<br>|517<br>|469<br>|433<br>|377<br>|439<br>|529<br>|565<br>|
|0|42|16|24|17|13|9|11|6|
|1-4|11|6|83|78|2|3|3|3|
|5-14<br>|11|3|7|3|4|1|3|1|
|15-44|32|17|50|14|24|9|17|6|
|45-64|59|51|92|46|74|35|78|29|
|65+<br>|204|424|214|276|261|382|417|520|
|LAC|||||||||
|Total|362|320|426|368|327|292|379|328|
|0|88|63|95|75|52|40|41|29|
|1-4|47|41|62|58|18|15|8|6|
|5-14<br>|18|14|15|10|10|6|7|4|
|15-44|37|36|33|23|29|21|25|19|
|45-64<br>|52<br>|40|52|31|46|28|60|32|
|65+<br>|120|128|170|171|172|183|239|239|
|Sub-Sahara|||||||||
|Total|712|652|869|766|917|840|1055|947|
|0<br>|254|206|313|248|316|248|298|225|
|14|141|120|177|131|130|98|145|92|
|5-14|66|62|69|62|77|65|85|69|
|15-44|81|76|96|89|121|113|150|137|
|45-64|64|56|81|72|96|90|125|110|
|65+<br>|105|132|133|164|176|225|253|316|
|AENA|||||||||
|Total<br>|510<br>|490|499|479|459|**464**|538|537|
|0<br>|168<br>|151<br>|181<br>|141<br>|136|105|120|89|
|1-4|68|71|94|89|32|28|30|28|
|5-14|28|28|27|23|24|19|25|19|
|15-44|51|51|37|43|51|62|**58**|71|
|45-64|61|47|45|43|58|60|83|77|
|65+|133|141|116|141|159|191|222|253|
|Asia|||||||||
|Total|2654|2858|2177|2357|2343|2536|2732|2699|
|0|668|655|389|320|375|283|273|197|
|1-4|579|603|357|362|111|95|66|53|
|5-14<br>|119<br>|130<br>|94<br>|80<br>|73|56|**57**|41|
|15-44<br>|254<br>|280<br>|194<br>|237<br>|189<br>|272<br>|181<br>|246<br>|
|45-64|332|278|257|245|324|356|403|411|
|65+|701|912|<br>887|<br>1113|<br>1271|<br>1474|<br>1752|1751|
_EelbWe$ and Protai of MoMt4I1y by Caus_ _56_

|Table DS. M<br>_Ri d_|moHtay r|ats_per_|100,000|<sup>from sp</sup>|<sup>ecific ca</sup>|<sup>uses by a</sup>|<sup>pe, sex,</sup>|<sup>and reg</sup>|<sup>ion, 19</sup>|<sup>85</sup>|
|---|---|---|---|---|---|---|---|---|---|---|
|_ego an_<br>_age group_|_Makl_|_Feml_|_Mal_<br>|_Female_|_Mal_|_Femal_|_Makl_|_Femake_|_Mak_|_Femakl_|
||Dioah|ea|Tliberulo|<br>dss|Acute res<br>qy Infec|pito-<br>tion|Measl|es|COP|D|
|World|||||||||||
|Tota|61|63|21<br>|14<br>|122<br>|108<br>|7<br>|10<br>|43<br>|38<br>|
|0<br>|1136<br>|962<br>|9<br>|6<br>|1160<br>|966<br>|105<br>|91<br>|288<br>|262<br>|
|1-4|71|140|6|8|550|365|30|43|9|26|
|5-14|32|25|2|4|17<br>|24<br>|7<br>|14<br>|2<br>|3<br>|
|15-44|24|27|16|13|21|28|1|2|3|3|
|<br>45-64|32|32|55|28|59|52|0|0|53<br>|35<br>|
|65+|55|60|81|35|376|365|0|0|514|322|
|Developed|||||||||||
|Total|2|2|6|1|37|35|0|0|37|20|
|<br>0|70|**58**|1|1|118<br>|91<br>|2<br>|2<br>|13<br>|10<br>|
|1-4|6|8|1|3<br>|121<br>|90<br>|1<br>|2<br>|3<br>|9<br>|
|5-14|0|0|0|0|2<br>|1<br>|0<br>|0<br>|0<br>|0<br>|
|15-44|0|0|4|0|5|1|0|0|2|1|
|45-64|0|0|10|1|18|5|0|0|29<br>|11<br>|
|65+|2|2|17|6|254|201|0|0|351|126|
|Developing|||||||||||
|Total|80|84<br>|25<br>|19<br>|148<br>|132<br>|10<br>|13<br>|45<br>|43<br>|
|0|1316<br>|1115<br>|10<br>|7<br>|1336<br>|1115<br>|122<br>|106<br>|334<br>|305<br>|
|1-4|83|164|7|9|626|414|35|51<br>|10<br>|29<br>|
|-14|39|30|2|4<br>|20<br>|28<br>|9<br>|17<br>|3<br>|4<br>|
|15-4|32|35|20|18<br>|26<br>|37<br>|1<br>|2<br>|4<br>|4<br>|
|45-64|48|51|77|44|80|80|0|1|65|49|
|<br>65+|91|118|126|65|462|534|0|1|630|523|
|Industril|||||||||||
|Totd|1|1|2|1|33|38|0|0|43|23|
|0|5|3|0|0|29<br>|21<br>|0<br>|0<br>|2<br>|1<br>|
|1-4|2|3|0|1|16|20|1|1<br>|3<br>|3<br>|
|5-14|0|0|0|0|0|0|0<br>|0<br>|0<br>|0<br>|
|15-44|0|0|0|0|1|0|0|0<br>|1<br>|0<br>|
|45-64|0|0|3|1<br>|12<br>|5<br>|0<br>|0<br>|25<br>|11<br>|
|65+|3|3|17|6|297|251|0|0|378|143|
|Nonmarket|||||||||||
|Total|4|3|11|1|45|29|0|0<br>|27<br>|15<br>|
|0|164|136|2|1|246|189|5|4|28<br>|22<br>|
|1-4|11|14|3|5|270|187|2|2|4|18|
|<br>5-14|0|0|0|0|4|2|0|0|0<br>|0<br>|
|15-44|0|0|11|0|12|1|0|0|3<br>|1<br>|
|45-64|0|0|23|1|28|5|0|0|35<br>|10<br>|
|65+|1|1|18|5|132|96|0|0|272|91|
|LAC|||||||||||
|Total|51|49|15|9|80|63<br>|4<br>|4<br>|31<br>|25<br>|
|0|931|807|7|5|821|693<br>|45<br>|38<br>|225<br>|213<br>|
|1-4|71|113|4|5|252|164|19|19<br>|6<br>|19<br>|
|5-4|13|12|2|2|11<br>|11<br>|2<br>|2<br>|1<br>|2<br>|
|15-44|12<br>|9<br>|13<br>|9<br>|14<br>|11<br>|0<br>|0<br>|4<br>|3<br>|
|45-64|32|19|43|16|49|27|0|0|46|24|
|<br>65+|<br>103|<br>106|75|37|339|330|0|0|411|252|
_57_ _Atnae B. Suppknanty Tablu_

|Table BS. Mo<br>|rtality rat|es per 10|0,000 fro|m specifi|c<sup>causes (</sup>|<sup>continu</sup>|<sup>ed)</sup>||||
|---|---|---|---|---|---|---|---|---|---|---|
|_Region and_<br>_age group_|_Mal_|_Femal_|_k Ma_|_Femae_|_Maed_|_Femal_|<br>_Mak_|_Femae_|_Male_|_Female_|
|<br>Sub-Sahara|||||||||||
|Total|272|238|28|24|361|260|38|49|51|49|
|<br>0|<br>2699|<br>2227|12|13|2280|1869|322|275|624<br>|552<br>|
|1-4|141|310|11|16|1243|574|86|106|23|54|
|5-14|146|96|3|10|47|77|36|71|7|11|
|15-44|169|126|33|25|91|110|4|7|1|1|
|<br>45-64|<br>223|<br>154|<br>87|<br>55|<br>168|<br>139|<br>0|<br>1|<br>46|40|
|<br>65+|254|307|129|74|604|684|1|1|544|373|
|<br>MElNA|||||||||||
|Total|122|150|20|20|212|184|18|29|43|42|
|<br>0|<br>2073|<br>1727|<br>12|<br>10<br>|1m<br>|1465<br>|204<br>|177<br>|478<br>|427<br>|
|1 4|101|291|8|15|847|538|58|114|16|51|
|<br>5-14|<br>52|<br>42|<br>3|<br>5|24|34|12|24|3|5|
|<br>15-44|<br>27|51|20|23|26|50|1|3|5|5|
|<br>45-64|<br>48|<br>79|62|41|71|83|0|0|53|39|
|65+|125|241|93|65|460|614|0|1|499|364|
|<br>Asia|||||||||||
|Total|43|49|27|19|111|111|4|6|46|46|
|0|793|677|10|4|1045|874|56|49|233|215|
|1-4|65|102|6|6|473|388|18|26|5|18|
|<br>5-14|18|17|2|3|1s|19|3|6|2|3|
|15-44|14|21|19|17|18|28|1|1|4|4|
|45-64|28|37|82|47|74|79|0|1|71|56|
|<br>65|67|84|138|68|466|541|0|1|690|605|
|+|||||||||<br>Jatea|tal|
|Wld|Pol|o|Yefow|fever|Mal|ria|||para|sites|
|or<br>Totd|1|0|0|0|3|3|0|0|2|3|
|<br>0|<br>8|<br>3|<br>0|<br>0|44|35|0|0|27|21|
|<br>1-4|<br>3|<br>2|0|1|4|3|0|0|4|15|
|<br>5-14|<br>0|0|0|0|2|2|0|0|3|4|
|15-44|0|0|0|0|1|1|0|0|1|0|
|45-64|0|0|0|0|3|3|1|0|2|1|
|<br>65+|0|0|0|0|6|5|2|1|1|1|
|Develoed|||||||||||
|p<br>Total|0|0|0|0|0|0|0|0|0|0|
|<br>0|<br>0|<br>0|0|0|0|0|0|0|1|1|
|1-4|0|1|0|0|0|0|0|0|1|4|
|5-14|0|0|0|0|0|0|0|0<br>|0<br>|0<br>|
|15-44|0|0|0|0|0|0|0|0|0|0|
|<br>45-64|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|<br>65+|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|0|0|0|
|<br>Developing|||||||||||
|Total|_1_|_1_|0|0|4|4|0|0|3|4|
|<br>0|<br>9|<br>3|<br>0|<br>0|<br>52|<br>41|0|0|31|24|
|1-4|4|3|0|2|5|3<br>|0<br>|0<br>|5<br>|17<br>|
|5-14|0|0|0|0|2|2|0|0|4|4|
|<br>15-44|<br>0|<br>0|<br>0|<br>0|<br>2|<br>2|<br>0|<br>0|<br>1|1|
|<br>45-64|<br>0|<br>0|0|0|5|4|1|1|3|1|
|<br>65+.|<br>1|<br>1|<br>0|0|11|10|3|2|1|1|
_58_ _Estiades and Projecwtims ofMortality by Cus_ Table D5. Mortality rates per 100,000 from specific causes (continued)

|_Region and_<br>_age group_|_Male_|_Femkle_|<br>_Male_|_Female_|_Male_|_Femal_|_Male_|_Female_|_Male_|_Female_|
|---|---|---|---|---|---|---|---|---|---|---|
|Industd|||||||||||
|Total|0|0|0|0|0|0|0|0|0|0|
|0|0|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|Nonmarket|||||||||||
|Total|0|0|0|0|0|0|0|0|1|1|
|0|1|0|0|0|0|0|0|0|2|1|
|1-4|0|1|0|1|0|0|0|0|2|9|
|5-14|0|0|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|0|0|
|<br>45-6|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>1|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|LAC|||||||||||
|Total|1|0|0|0|1|1|0|0|2|2|
|0|5|3|0|0|4|5|0|0|15|12|
|1-4|3|2|0|1|1|1|0|0|4|9|
|5-14|0|0|0|0|1|1|0|0|1|1|
|15-44|0|0|0|0|1|1|0|0|0|0|
|45-64|0|0|0|0|2|1|0|0|2|0|
|<br>65+|<br>0|<br>0|<br>0|<br>0|<br>3|<br>3|<br>0|<br>0|<br>1|1|
|Sub-Sahara|||||||||||
|Totad|1|1|1|0|5|4|0|0|9|9|
|0|7|3|0|<br>0|<br>94|<br>69|<br>0|<br>0|<br>56|43|
|14|2|3|0|2|1|1|0|J|8|20|
|5-14|0|0|0|0|1|0|0|0|14|12|
|15-44|0|0|1|0|0|0|0|0|3|2|
|45-64|0|0|0|0|5|<br>4|<br>1|<br>0|<br>6|2|
|65+|0|0|0|0|7|7|1|0|1|2|
|MENA|||||||||||
|Total|1|1|0|0|4|4|0|0|4|5|
|0|6|3|0|0|50|40|0|0|43|33|
|<br>1-4|<br>2|<br>2|<br>0|<br>1|<br>1|<br>1|<br>0|<br>0|<br>6|16|
|5-14|0|0|0|0|3|3|0|0|5|5|
|<br>15-44|<br>0|<br>0|<br>0|<br>0|<br>2|<br>3|<br>1|<br>C|<br>1|1|
|45-64|0|0|0|<br>0|4|<br>3|<br>1|<br>0|<br>3|1|
|65+|0|0|0|0|5|6|1|0|1|1|
|Asia|||||||||||
|Totad|1|1|0|0|5|4|1|0|2|3|
|0|11|3|0|0|48|40|0|0|24|19|
|<br>1-4|<br>4|<br>3|<br>0|<br>2|<br>8|<br>5|<br>0|<br>0|<br>4|18|
|5-14|0|0|0|0|2|2|0|0|2|3|
|15-44|0|0|0|0|2|2|0|0|1|0|
|45-64|1|0|0|0|6|5|2|1|3|1|
|65+|1|1|0|0|13|12|4|3|1|1|
_Annex D. Supplementary Tables_ _59_ Table B5. Mortality rates per 100,000 from specific causes (continued)

|**_Reglon_**_and_<br>_age group_|_Male_|_Femal_|_e Male_|_Femae_|_Male_|_Female_|_Male_|_Fema_|_k Mak_|_Femak_|
|---|---|---|---|---|---|---|---|---|---|---|
||lschemi<br>dise|c heart<br>ase|Cerebro<br>dise|vascular<br>ase|Otier c<br>vasc|rdio-<br>ular|Diab|etes|Certain<br>erat|dege-<br>ive|
|World|||||||||||
|Total|83|80|66|92|76|78|8|13|29|22|
|0|2|1|17|13|63|S0|3|4|14|14|
|1-4|0|0|4|4|13|15|1|1|7|3|
|5-14|0|0|1|1|6|5|0|0|2|2|
|15-44|9|3|6|9|13|13|1|2|12|7|
|45-64|178|71|107|100|111|79|17|25|75|44|
|65+<br>|1076|1025|957|1080|1009|847|96|122|227|172|
|Developed|||||||||||
|Total|207|208|103|160|118|155|10|17|34|24|
|0|0|0|3|2|18|14|0|0|5|3|
|1-4|0|0|1|2|7|12|0|1|2|2|
|5-14|0|0|0|0|1|1|0|0|0|0|
|15-44<br>|12<br>|2<br>|4<br>|2<br>|8<br>|4<br>|1<br>|1<br>|7<br>|2<br>|
|45-64|249|72|87|61|95|50|11|9|64|25|
|65+<br>|1726|1425|961|1080|1085|1052|87|107|206|129|
|Developing|||||||||||
|Total|45|38|55|69|63|52|7|12|27|22|
|0<br>|2<br>|2|20|15|70|56|4|5|15|16|
|1-4|0|0|5|4|14|15|2|1|.8|3|
|5-14|0|0|2|2|7|6|0|0|2|2|
|15-44|9|4|6|11|14|16|2|2|13|9|
|45-64|142|70|117|123|119|96|20|34|80|55|
|65+<br>|619|614|954|1080|956|635|101|138|242|215|
|Induswtral|||||||||||
|Total|199|174|93|137|122|161|13|21|34|25|
|0|0|0|4|3|23|17|0|0|6|5|
|1-4|0|0|2|3|12|19|0|1|2|3|
|5-14|0|0|0|0|1|0|0|0|0|0|
|15-44|7|1|3|1|6|2|1|0|4|1|
|45-64|208|47|55|30|88|37|12|9|54|19|
|65+<br>|1544|1151|816|910|1022|1062|101|132|205|139|
|Nonmarket|||||||||||
|Total|222|268|122|200|110|144|5|9|36|23|
|0|0|0|2|1|10|9|0|0|2|1|
|1-4<br>|0<br>|0<br>|0<br>|0<br>|1<br>|3<br>|0<br>|0<br>|1<br>|0<br>|
|5-14|0|0|0|0|1|1|0|0|1|0|
|<br>15-44|<br>21|<br>3|<br>7|<br>4|<br>12|<br>7|<br>1|<br>1|<br>11|4|
|<br>45-64|325|<br>113|<br>146|<br>110|<br>109|<br>70|<br>9|<br>10|<br>81|35|
|65+|2246|2007|1375|1441|1265|1032|46|53|208|110|
|LAC|||||||||||
|Total|65|41|43|45|75|76|14|17|31|17|
|0<br>|1<br>|1<br>|10<br>|6<br>|53<br>|43<br>|1|1|14|12|
|1-4|0|0|1|2|8|10|0|0|4|2|
|5-14|0|0|1|1|4|3|0|0|1|1|
|15-44<br>|8<br>|3<br>|6|6|12|10|2|2|12|5|
|45-64|179|60|89|72|140|98|41|41|105|41|
|<br>65+|<br>994|<br>682|<br>727|<br>690|<br>1230|<br>1184|<br>200|<br>232|<br>299|172|
_Estimates and Projections of Mortality by Cause_ _60_ Table B5. Mortality rates per 100,000 from specific causes (continued)

|_Region and_<br>_age group_|_Male_|_Female_|_Mak_|_Female_|_Male_|_Female_|_Male_|_Female_|_Male_|_Femae_|
|---|---|---|---|---|---|---|---|---|---|---|
|<br>Sub-Sahara|||||||||||
|Total|60|35|41|44|73|80|10|15|26|17|
|<br>0|<br>4|<br>3|<br>42|<br>28|<br>149|<br>111|<br>4|<br>6<br>|<br>22<br>|25<br>|
|14|0|0|10<br>|5<br>|22<br>|23<br>|0<br>|0<br>|8<br>|2<br>|
|5-14|0|0|3|3|18|18|0|0|5|4|
|<br>15-44|<br>16|<br>5|<br>10|<br>11|27|34|3|4|19|12|
|<br>45-64|<br>243|<br>96|<br>114|<br>122|<br>169|<br>188|38|64|85|53|
|65+|1129|765|833|813|1193|1131|168|195|239|143|
|MENA|||||||||||
|Total|63|38|40|45|65|n|9|13|23|15|
|<br>0|<br>3|<br>2|<br>31|<br>19|<br>108|81|<br>3|4|22|22|
|1-4|0|0|7|5|15|22|0|0|6|2|
|<br>5-14|<br>0|<br>0|<br>2|<br>2|<br>9|8|0|0|2|2|
|<br>15-44|<br>11|4|6|9|15|19|2|3|12|8|
|45-64|222|82|92|102|142|143|31|49|77|44|
|<br>65+|1128|797|816|821|1167|1134|166|194|240|144|
|Asia|||||||||||
|Total|37|37|62|82|59|40|6|10|27|25|
|<br>0|<br>1|1|12|11|41|36|5|5|12|12|
|1-4|0|0|3|4|12|12|3|1|9|5|
|5-14|0|0|1|1|5|4|0|0|1|2|
|1544|7|3|6|12|13|13|1|2|13|9|
|-<br>45-64|<br>115|<br>66|<br>125|<br>134|<br>107|<br>76|<br>14|<br>26|<br>77|59|
|65+|441|564|1020|1207|860|427|71|109|233|239|
||<br>Men|<br>tal|<br>Oral h|<br>ealth|<br>Micron|<br>utrient|||||
||disor|ders|dise|ases|disor|ders|Mainti|on|||
|world|||||||||||
|Total|1|3|0|0|4|7|11|5|||
|0|0|0|0|0|13|10|75|60|||
|1-4|0|0|0|1|4|16|77|22|||
|5-14|0|0|0|0|2|2|2|2|||
|15-44|0|1|0|0|1|4|0|0|||
|<br>45-64|2|1|0|0|5|6|2|0|||
|65+|17|33|0|0|27|26|12|12|||
|Developed|||||||||||
|Total|2|5|0|0|3|4|3|1|||
|<br>0|0|0|0|0|2|1|3|1|||
|1-4|0|0|0|1|3|5|38|5|||
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>1|<br>0|<br>0|0|||
|<br>15-44|<br>0|<br>0|<br>0|<br>0|<br>1|<br>0|0|0|||
|<br>45-64|<br>1|1|0|0|3|3|1|0|||
|<br>65+|<br>25|<br>38|<br>0|<br>0|21|21|7|7|||
|Developing|||||||||||
|Total|1|2|0|0|4|8|13|6|||
|<br>0|<br>0|<br>0|<br>O|<br>0|<br>15|<br>12|<br>87|70|||
|1-4|0|0|0|1|4|18|84|25|||
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>3|<br>2|<br>2|2|||
|<br>15-4|<br>1|<br>1|<br>0|<br>0|2|5|0|0|||
|45-64|2|1|0|0|. 5|9|2|0|||
|<br>65+|<br>11|<br>28|<br>0|<br>0|<br>30|32|15|18|||
Annax _B. Supplmlan Table_ _61_ Table B5. Mortality rates per 100,000 from specific causes (continued)

|_Reglon and_<br>_aSe 8P_|_Mak_|_Female_|_Mad_|_Female_|_Mak_|_Female_|_Mal_|_Femae_|
|---|---|---|---|---|---|---|---|---|
|Industrwal|||||||||
|Total|3|6|0|0|2|3|1|1|
|o<br>|0<br>|0<br>|0<br>|0<br>|1<br>|0<br>|1<br>|0<br>|
|14<br>|0<br>|0<br>|0<br>|0<br>|3<br>|4<br>|0'<br>|0|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-4|0|0|0|0|0|0|0|0|
|45-64<br>|1<br>|0<br>|0<br>|0<br>|1<br>|1|0|0|
|65+<br>|29|44|0|0|14|20|5|7|
|Nonmarket<br>|||||||||
|Totda<br>|2<br>|3<br>|0<br>|0<br>|6<br>|5<br>|8|2<br>|
|0<br>|0<br>|0<br>|0<br>|0<br>|3<br>|2<br>|7|2|
|1-4<br>|0<br>|.0<br>|0<br>|3<br>|3<br>|8<br>|90<br>|11|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|1<br>|0<br>|0|0|
|15-4<br>|0<br>|0<br>|0|0|2|1|0|0|
|45-<br>|2<br>|.1<br>|0<br>|0<br>|8<br>|5<br>|2|0|
|65+<br>|17|25|0|0|42|24|11|7|
|LAC<br>|||||||||
|Total<br>|1<br>|2<br>|0<br>|1<br>|6<br>|6|6|5|
|0<br>|0<br>|0<br>|0<br>|0<br>|15<br>|12<br>|85<br>|68|
|1-4<br>|0<br>|0<br>|0<br>|6<br>|2|3|15|9|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|3<br>|1|1|1|
|15-4<br>|0<br>|0<br>|0<br>|0|2|2|0|0|
|45-64<br>|2<br>|1<br>|0<br>|0|9|9|4|2|
|65+<br>|11|29|0|0|68|51|36|37|
|Sub-Sahara<br>|||||||||
|Total<br>|1<br>|1|0|0|9|11|22|8|
|0<br>|0<br>|0<br>|0<br>|0<br>|22<br>|18<br>|142<br>|108<br>|
|1-4|0|0|0|0|3|7|87|8|
|5-14<br>|0<br>|0<br>|0<br>|0|7|7|5|4|
|15-44<br>|0<br>|0<br>|0<br>|0|5|d|1|1|
|45-64<br>|3<br>|1<br>|0|0|17|20|5|1|
|65+<br>|11|26|0|0|73|64|20|27|
|MENA<br>|||||||||
|Total|I|1|0|0|6|8|13|6|
|0<br>|0<br>|0<br>|0<br>|0<br>|21<br>|17<br>|134|98|
|1-4<br>|0<br>|0<br>|0<br>|0<br>|2|6|55|8|
|5-14<br>|0<br>|0<br>|0<br>|0|4|3|2|3|
|15-44|0|0|0|0|2|5|0|0|
|45-64|2|1|0|0|9|15|2|0|
|65+|11|26|0|0|64|62|V|26|
|_Asia_|||||||||
|Total<br>|1|2|0|0|3|7|12|6|
|0|0|0|0|0|12|9|59|51|
|1-4|0|0|0|0|4|27|103|36|
|5-14<br>|0<br>|1|0|0|2|1|1|2|
|15-44<br>|1<br>|1<br>|0<br>|0|1|5|0|0|
|45-64|2|1|0|0|3|6|1|0|
|65+|11|28|0|0|16|21|11|13|
_62_ _Estimates and Projections of Mortality by Cause_

> Table B6. Deaths in thousands from specific causes by age, sex, and region, 1985

|_Region_<br>_and_<br>_age g.oup_|_Mate_|_Female_|_Mak_|_Femal_|_k Male_|_Female_|_Male_|_Female_|_Male_|_Female_|
|---|---|---|---|---|---|---|---|---|---|---|
||Diar|rhea|Tuber|culosis|_Acute_r<br>ry Inf|espirato-<br>ection|Me|asles|CO|PD|
|World|||||||||||
|Total|1490|1508|502|342|2970|<br>2579|181|241|1042|<br>901|
|0|702|569|6|3|717|571|65|54|178|<br>155|
|1-4|164|310|13|18|1269|<br>807|68|96|20|57|
|5-14|175|131|10|18|91|122|39|72|12|17|
|15-44|268|285|179|144|235|306|8|17|35|31|
|45-64|116|117|197|103|214|191|0|1|190|<br>127|
|65+|65|95|96|55|444|582|0|0|607|514|
|Developed|||||||||||
|Total|10|10|31|7|212|210|1|1|212|122|
|0|6|5|0|0|11|8|0|0|1|1|
|1-4|2|3|0|1|42|30|0|1|1|3|
|5-14|0.|0|0|0|1|1|0|0|0|0|
|15-44|0|0|10|0|13|2|<br>0|<br>0|<br>4|1|
|45-64|0|0|12|1|21|7|0|0|35|14|
|65+|1|2|8|5|124|163|0|0|171|102|
|Developing|||||||||||
|Total|1480|1498|470|334|2758|2369|180|240|829|779|
|0|695|564|5|3|706|563|64|54|176|154|
|1-4|162|307|13|17|1227|777|68|95|19|54|
|5-14|175|131|10|18|90|121|39|72|12|17|
|15-44|268|285|169|144|222|304|8|17|30|30|
|45-64|116|<br>117|<br>185|<br>102|<br>193|<br>184|<br>0|<br>1|<br>155|113|
|<br>65+|<br>63|<br>93|<br>88|<br>51|<br>320|<br>420|<br>0|<br>0|<br>436|412|
|Industrial|||||||||||
|Total|2|3|9|4|124|148|0|0|159|89|
|0|0|0|0|0|2|1|0|0|0|0|
|1-4|0|1|0|0|3|4|0|0|1|1|
|5-14|0|0|0|0|0|0|0|0|0|0|
|15-4|0|0|0|0|2|1|<br>0|<br>0|<br>1|1|
|45-64|0|0|3|1|9|4|0|0|20|9|
|<br>65+|<br>1|<br>2|<br>6|<br>3|<br>107|<br>138|<br>0|<br>0|<br>136|79|
|Nonmarket|||||||||||
|Total|8|7|22|3|89|62|0|0|54|33|
|0|6|5|0|0|9|7|0|<br>0|<br>1|1|
|1-4|2|2|0|1|39|26|0|0|1|2|
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>1|<br>1|<br>0|<br>0|<br>0|0|
|15-44|0|0|10|0|11|1|0|0|<br>3|1|
|<br>45-64|<br>0|<br>0|<br>10|<br>1|<br>12|<br>3|<br>0|<br>0|<br>15|5|
|65+|0|0|2|1|17|<br>25|<br>0|<br>0|<br>34|23|
|LAC|||||||||||
|Total|102|98|31|18|159|127|8|8|63|50|
|<br>0|<br>54|<br>46|<br>0|<br>0|<br>48|<br>39|<br>3|<br>2|<br>13|12|
|1-4|15|24|1|1|55|35|4|4|1|4|
|5-14|6|6|1|1|5|<br>5|<br>1|<br>1|<br>1|1|
|15-44|11|9|12|8|13|10|0|0|4|3|
|45-64|8|5|10|4|12|7|0|0|11|6|
|65+|8|10|6|3|27|31|0|0|33|24|
_Annex B. Supplmentary Tables_ _63_ Table 86. Deaths In thousands from specific causes (condnued)

|_Region and_<br>_age group_|_Male_|_Femal_|_Male_|_Female_|_Male_|_Femal_|_e Mak_|_Female_|_Make_|_Female_|
|---|---|---|---|---|---|---|---|---|---|---|
|<br>Sub-Sahara|||||||||||
|Total|613|545|64|55|812|595|<br>85|111|114|<br>113|
|0|255|208|1|1|216|175|<br>30|26|59|52|
|1-4|47|102|4|5|411|189|<br>28|35|8|18|
|5-14|91|59|2|6|29|48|22|44|5|7|
|15-44<br>|15C<br>|<br>118|31|24|84|104|<br>4|7|1|1|
|45-64|50|37|19|13|37|33|0|0|10|<br>10|
|65+|15|21|7|5|35|47|0|0|31|26|
|MENA|||||||||||
|Total|233|274|39|37|407|334|35|52|83|77|
|0|142|114|1|1|122|97|14|12|33|28|
|1-4|25|69|2|4|211|127|14|27|4|12|
|5-14|26|20|1|2|12|16|6|11|2|2|
|15-44|23|40|17|18|21|39|0|2|4|4|
|45-64|10|16|13|8|14|17|0|0|11|8|
|65+|7|15|5|4|27|38|0|0|29|23|
|Asia|||||||||||
|Total|532|580|337|225|1379|1313|<br>52|69|570|540|
|0|243|196|3|1|321|253|17|14|72|62|
|1-4|75|112|7|7|550|426|21|29|6|20|
|514|52|4|||||||||
|-||7|6|9|44|52|10|16|5|7|
|15-44|79|118|110|94|104|152|4|8|22|22|
|45-64|49|60|143|77|129|127|0|1|123|90|
|65+|33|47|69|38|232|303|0|0|343|339|
||||||||||<br>LUt|estlnal|
||**Po**|**lio**|Ye11o|w fever|Mal|aria|Schisto|somlasis|para|sites|
|World|||||||||||
|Total|15|10|4|4|79|67|8|4|60|73|
|o|5|2|0|0|27|21|0|0|16|12|
|1-4|7|5|0|3|10|6|0|0|10|34|
|5-14|1|2|0|0|8|9|0|0|18|18|
|15-44|0|1|4|0|14|14|3|0|7|5|
|45-64|1|0|0|0|12|10|3|2|7|3|
|65+|0|0|0|0|8|8|2|2|1|1|
|Developed|||||||||||
|Total|0|0|0|0|0|0|0|0|1|1|
|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|1-4|0|0|0|0|0|0|0|0|0|1|
|5-14|0|0|0|0|0|0|C|0|0|0|
|<br>15-44|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|45-64|0|0|0|0|0|0|0|0|0|0|
|65+|0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|Developing|||||||||||
|Total|15|10|4|4|79|67|8|4|59|72|
|0|5|2|0|0|27|21|0|0|16|12|
|1-4|7|5|0|3|10|6|0|0|10|32|
|5-14|1|2|0|0|8|9|0|0|18|18|
|15-44|0|1|3|0|14|14|3|0|7|5|
|45-64|1|0|0|0|12|10|3|2|7|3|
|65+|0|<br>0|<br>0|<br>0|8|<br>8|<br>2|<br>2|<br>1|1|
_Emate awd PVwjtion of Motalty by ause_ _64_ Table 36. Deaths in thousands from specific causes (continued)

|_Region_<br>_and_<br>_age gronp_|_MAlk_|_Fema_|_Mak_|_Female_|_Male_|_Femal_|_Male_|_Female_|_Mate_|_Female_|
|---|---|---|---|---|---|---|---|---|---|---|
|Industrial|||||||||||
|Total|0|0|0|0|0|0|0|0|0|0|
|o|o|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|0|0|
|<br>5-14|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|15-44|0|0|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|0|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|Nonmarket|||||||||||
|Total|0|0|0|0|0|0|0|0|1|1|
|o|o|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|0|0|0|0|1|
|5-14|0|0|0|0|0|0|0|0|0|0|
|15-44|0|0|0|0|0|0|0|0|0|0|
|<br>45-64|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|LAC|||||||||||
|Total|1|1|0|0|3|3|0|0|3|4|
|O|O|0|0|0|0|0|0|0|1|1|
|1-4|1|0|0|0|0|0|0|0|1|2|
|5-14|0|0|0|0|1|1|0|0|1|1|
|15-4|0|0|0|0|1|1|0|0|0|0|
|45-64|0|0|0|0|1|0|0|0|0|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|Sub-Sahara|||||||||||
|Total|2|1|1|1|11|9|0|0|21|20|
|0|1|0|0|0|9|6|0|0|5|4|
|1-4|1|1|0|1|0|0|0|0|3|7|
|5-14|0|0|0|0|0|0|0|0|9|7|
|15-44|0|0|1|0|0|0|0|0|2|2|
|45-64|0|0|0|0|1|1|0|0|1|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|MENA|||||||||||
|Total|1|1|0|0|8|7|1|0|8|9|
|o|0|0|0|0|3|3|0|0|3|2|
|1-4<br>|1|1|0|0|0|0|0|0|2|4|
|5-14|0|0|0|0|2|1|0|0|3|2|
|<br>15-44|<br>0|<br>0|<br>0|<br>0|<br>2|<br>2|<br>0|<br>0|<br>1|1|
|45-64|0|0|0|0|1|1|0|0|1|0|
|65+|0|0|0|0|0|0|0|0|0|0|
|Asia|||||||||||
|Total|11|7|2|3|57|48|7|3|26|38|
|0|3|1|0|0|15|12|0|0|7|5|
|<br>1-4|<br>5|<br>3|<br>0|<br>2|<br>9|<br>5|<br>0|<br>0|<br>4|20|
|<br>5-14|<br>1|<br>1|<br>0|<br>0|<br>5|<br>7|<br>0|<br>0|<br>6|8|
|15-4|0|1|2|0|10|10|2|0|3|3|
|45-64|1|0|0|0|10|8|3|1|5|2|
|65+|0|<br>0|<br>0|<br>0|<br>7|<br>7|<br>2|<br>2|<br>0|1|
_Annxa B. Suppkmenlary Tables_ _65_ Table B6. Deaths In thousands from specific causes (continued)

|_Region and_<br>_age group_|_Male_|_Femal_|_e Make_|_Female_|_Mate_|_Female_|_Mal_|_Femal_|_e Mak_|_Female_|
|---|---|---|---|---|---|---|---|---|---|---|
||Ischem<br>dise|ic heart<br>ase|Cerebro<br>dise|vascuar<br>ase|Othr<br>vasc|cadio-<br>ular|Dia|betes|Cerlal<br>exa|n degen-<br>tive|
|World|||||||||||
|Total|2019|1929|<br>1608|2205|1838|1867|197|309|<br>700|<br>536|
|0<br>|1<br>|1<br>|11<br>|8<br>|39|30|2|2|9|8|
|1-4|1|0|9|9|29|32|3|2|16|7|
|5-14|1|1|8|7|34|28|1|1|<br>8|9|
|15-44|105|34|65|95|144|139|16|19|130|78|
|45-64<br>|642|259|386|365|400|288|62|90|270|160|
|65+<br>|1270|1634|1129|1722|1191|1350|113|195|268|274|
|Developed|||||||||||
|Total|1173|1254|585|962|669|933|58|100|196|145|
|0<br>|0|0|0|0|2|1|0|0|0|0|
|1-4|0|0|0|1|3|4|0|0|1|1|
|5-14|0|0|0|0|1|0|0|0|0|0|
|15-44<br>|32<br>|5<br>|11<br>|6<br>|21<br>|10<br>|2|1|17|5|
|45-64|300|97|105|82|115|67|13|12|77|34|
|65+<br>|841|1151|468|873|528|851|42|86|100|105|
|Developing|||||||||||
|Total<br>|847<br>|675<br>|1022<br>|1243<br>|1169<br>|934<br>|139<br>|209<br>|504<br>|391|
|0<br>|1|1|10|7|37|28|2|2|8|8|
|1-4|1|0|9|8|27|28|3|1|15|6|
|5-14<br>|1<br>|1<br>|7<br>|<br>7<br>|<br>34<br>|<br>27|<br>1|<br>1|<br>8|8|
|15-44<br>|73<br>|29|53|89|123|129|14|18|113|72|
|45-64|342|161|282|283|286|221|49|78|193|127|
|65+<br>|429|483|661|849|662|500|70|109|167|169|
|Industrial|||||||||||
|Total|733|674|344|529|452|623|48|81|125|95|
|0<br>|0<br>|0<br>|0<br>|0|1|1|0|0|0|0|
|14|0|0|0|1|2|4|0|0|0|0|
|5-14|0|0|0|0|0|0|0|0|0|0|
|15-44<br>|13<br>|2<br>|5<br>|3<br>|11<br>|3<br>|2<br>|1|8|2|
|45-64|162|40|43|25|68|31|10|7|43|16|
|65+<br>|558|633|295|500|369|584|37|73|74|76|
|Nonmarket<br>|||||||||||
|Total|440|580|241|433|217|310|11|20|71|50|
|0|0|0|0|0|0|0|0|0|0|0|
|14|0|0|0|0|0|0|0|0|<br>0|0|
|5-14<br>|0|0|0|0|0|0|0|0|0|0|
|15-44<br>|19|3|6|4|11|6|1|1|10|3|
|45-64|138|58|62|56|46|36|4|5|34|18|
|65+|283|519|173|372|159|267|6|14|26|28|
|LAC|||||||||||
|Total|130|83|86|90|150|153|28|34|62|33|
|0<br>|0|0|1|0|3|2|0|0|1|1|
|1-4|0|0|0|0|2|2|0|0|1|0|
|5-14|0|0|1|0|2|1|<br>0|<br>0|<br>0|1|
|15-44|7|3|5|5|11|10|2|2|11|5|
|**45-64**|43|15|21|18|34|25|10|10|25|10|
|65+|79|65|**58**|65|98|112|16|22|24|16|
_Estimates and Projections of Mortality by Cause_ _66_ Table B6. Deaths In thousands from specific causes (continued)

|_Region and_<br>_age grvup_|_Mak_|_Female_|_Mal_|_Female_|_Mate_|_Female_|_Make_|_Female_|_Male_|_Femal_|
|---|---|---|---|---|---|---|---|---|---|---|
|<br>Sub-Sahara|||||||||||
|Total|135|81|92|101|164|184|22|34|58|<br>39|
|0|0|0|4|3|14|10|0|1|2|2|
|1-4|0|0|3|2|7|8|0|0|3|1|
|5-14|0|0|2|2|11|11|0|0|3|2|
|15-44|15|5|9|11|25|32|3|4|18|<br>12|
|45-64|54|23|25|29|37|45|8|15|19|<br>13|
|65+|65|52|48|56|69|77|10|13|14|10|
|MENA|||||||||||
|Total|120|70|76|82|125|129|18|25|43|27|
|0|0|0|2|1|7|5|0|0|1|1|
|14|0|0|2|1|4|5|0|0|1|0|
|5-14|0|0|1|1|5|4|0|0|1|1|
|15-44|9|3|5|7|12|15|1|2|10|6|
|45-64|45|17|19|21|29|29|6|10|16|9|
|65+|66|50|48|51|68|71|10|12|14|9|
|Asia|||||||||||
|Total|462|442|768|970|730|468|72|117|340|291|
|0|0|0|4|3|13|10|1|2|4|3|
|1-4|0|0|3|5|14|13|3|1|10|5|
|5-14|0|0|4|4|16|10|0|0|3|4|
|15-44|<br>42|<br>19|33|<br>66|<br>75|<br>72|<br>8|<br>10|<br>74|49|
|45-64|200|106|216|215|186|123|25|42|133|95|
|65+|219|316|508|677|428|239|35|61|116|134|
||Me|nal|Oral h|ealth|Miomn|utrient|||||
||disor|ders|dise|ase|disor|ders|Malnu|trition|||
|World|||||||||||
|Total|31|64|0|3|94|158|255|117|||
|0|0|0|0|0|8|6|46|35|||
|1-4|0|0|0|2|8|36|178|48|||
|5-14|1|2|0|0|13|10|8|10|||
|15-44|5|6|0|0|16|41|2|2|||
|<br>45-64|<br>6|<br>3|<br>0|<br>0|<br>17|<br>24|<br>6|1|||
|65+|20|53|0|0|32|42|14|20|||
|Developed|||||||||||
|Total|14|32|0|0|19|24|18|8|||
|0|0|<br>0|<br>0|<br>0|<br>0|<br>0|<br>0|0|||
|1-4|0|0|0|0|1|2|13|2|||
|5-14|0|0|0|0|1|0|0|0|||
|15-44|0|0|0|0|3|1|0|0|||
|45-64|1|1|0|0|4|3|1|0|||
|<br>65+|<br>12|<br>31|<br>0|<br>0|<br>10|<br>17|<br>3|6|||
|Developing|||||||||||
|Total|17|32|0|2|75|135|237|109|||
|0|0|0|0|0|8|6|46|35|||
|1-4|0|0|0|2|7|34|165|47|||
|<br>5-14|<br>1|<br>2|<br>0|<br>0|<br>13|<br>10|<br>8|10|||
|15-44|5|6|0|0|14|40|2|2|||
|45-64|4|2|0|0|13|20|5|1|||
|65+|7|22|0|0|21|25|11|14|||
Annea _B. Supplmenlay Tabls_ _67_ Table 86. Deaths in thousands from specific causes (continued)

|_Region and_<br>_ag group_|_Mak_|_Female_|_Male_|_Femal_|_Mal_|_Femae_|_Mal_|_Femae_|
|---|---|---|---|---|---|---|---|---|
|Industrda|||||||||
|Total|11|25|0|0|7|13|2|4|
|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|1-4<br>|0<br>|0<br>|0<br>|0<br>|1<br>|1<br>|0|0|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44|0|0|0|0|0|0|0|0|
|45-64|0|0|0|0|1|1|0|0|
|65+|10|24|0|0|5|11|2|4|
|Nonmarket|||||||||
|Total|3|7|0|0|12|11|16|4|
|0|0|0|0|0|0|0|0|0|
|1-4|0|0|0|0|0|1|13|2|
|5-14<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0|0|
|15-44<br>|0|0|0|0|2|1|0|0|
|45-64|1|0|0|0|3|3|1|0|
|65+<br>|2|6|0|0|5|6|1|2|
|LAC|||||||||
|Total|2|3|0|1|12|11|13|11|
|0|0|0|0|0|1|1|5|4|
|1-4<br>|0|0|0|1|0|1|3|2|
|5-14|0|0|0|0|1|1|1|1|
|15-44<br>|0<br>|0<br>|0<br>|0<br>|2<br>|2<br>|0<br>|0<br>|
|45;-64|0|0|0|0|2|2|1|0|
|<br>65+|1|3|0|0|5|5|3|4|
|Sub-Sahara|||||||||
|Total|2|2|0|0|20|25|49|18|
|0|0|0|0|0|2|2|13|10|
|1-4|0|0|0|0|1|2|29|3|
|5-14|0|0|0|0|4|4|3|2|
|15-44|0|0|0|0|5|8|1|1|
|45-64|1|0|0|0|4|5|1|0|
|65+|1|2|0|0|4|4|1|2|
|AENA|||||||||
|Total|1|2|0|0|12|15|26|11|
|0|0|0|0|0|1|1|9|7|
|1-4|0|0|0|0|1|1|14|2|
|5-14|0|0|0|0|2|2|1|1|
|15-44<br>|0|0|0|0|2|4|0|0|
|45-64|0|0|0|0|2|3|0|0|
|65+|1|2|0|0|4|4|1|2|
|Asia|||||||||
|Total|13|25|0|1|32|83|149|69|
|0|0|0|0|0|4|3|18|15|
|1-4|0|0|0|0|5|30|120|40|
|5-14|1|2|0|0|5|4|3|6|
|15-44|4|6|0|0|5|26|0|1|
|45-64|3|2|0|0|5|10|2|0|
|65+|5|16|0|0|8|12|6|7|
_68_ _E8atOim 4nd Pwjctim of MOdali by QUe_

# Annex C. Expert Assessments

This annex provides expert assessments of mortality in 1985 from some specific causes by age, sex, and region and explains how they were obtained. The basic procedure was to show the regression estimates based on WHO data and regression models to individual experts on specific diseases, with a request for corrections and supporting evidence, and to calculate alternative rates and numbers of deaths on the basis of plausible recommendations.

Those specific causes of death on which alternative assessments were made are discussed in the same order as in preceding tables. Comments were also received on neoplasms and injury and poison, but no revisions were suggested. For specific causes not covered, no comments were received.

Those causes of death left out are not necessarily less controversial. For instance, West and Sommer (1987:4) estimate 420,000 deaths annually among preschool children from vitamin A deficiency, but the regression estimates for deaths under five due to micronutrient disorders are only 58,000. More generally, a comparison in Table Cl with figures compiled by Walsh (1988:15) shows that some estimates in the literature are considerably higher than the regression estimates here. The comparisons in this table cannot be examined in detail because information on Walsh's procedures is not available. The comparisons do suggest that the regression estimates substantially understate deaths from malaria and schistosomiasis, and these discrepancies are among those examined below.

Table Cl. Comparison of esdmated deaths from certain specific causes in developing countries around 1985 with Walsh assessment

||||_Ratio_<br>_Walshl_|_:_<br> <br>_Pe_|_rcent_|
|---|---|---|---|---|---|
|_Dise_|_iRegrv_<br>_sion_|_-_<br>_Walsh_|_Regres-_<br>_sion_|_Regres-_<br>_sion_|_Walsh_|
|Diarrhea|2978|4300|144|30.6|21.9|
|Tuberculosis|804|900|112|8.3|4.6|
|Acute respiratory infection|5127|10000|195|52.6|51.0|
|Measles|420|2000|476|4.3|102|
|Polio|25|2|8|0.3|0.0|
|Yellow fever, dengue, encephalitis|<br>8|31|388|0.1|**0.2**|
|<br>Malaria|<br>146|1500|1027|<br>1.5|7.6|
|Schistosomnasis, filarlasis|12|375|3125|0.1|1.9|
|Pregnancy|218|500|229|2.2|2.5|
|<br>Malnutrition, micronutrdent|556|2000|360|a|a|

Sources: Estimates reported above and Walsh (1988:15).

'Walsh lists malnutrition as an associated cause, with deaths presumed to be also counted elsewhere. Therefore, this cause is not included in the calculation of percentages. These percentages are over causes included In the table only, not over all causes.
_69_ __bme_ Anna C _Expet A_ Some expert assessments differ substantially from the regression esimates. Consideration of one particular discrepancy-that for diarrhea in the 65 and over age group in Latin America and the Caribbean-is instructive. The regression estimate of the mortality rate was 105 per 100,000, intermediate among developing countries, and the expert assessment was that this should be reduced to 10 for each developing country region. For the reporting countries in Latin America as a group, the rate is actually 85. Since these countries have 53 percent of the regional population, even if no one dies from this cause in the nonreporting countries-e.g., Colomia, Bolivia, Haiti, Jamaica, and Nicaragua-a regional average of 10 is impossible. The regional rate for tiis age group, if the data reported to WHO are credited, cannot be lower than 45 per 100,000.

# At least four explanations can be advanced for such discrepancies.

First, nonreporting countries may in fact be so different that projecting contrasts among reporting countries does not come close to capturing their variation. This explanation may suffice where contrasts are less extreme than in this case, but is insufficient here. No matter how different the nonreporting countries are assumed to be, the recommended regional average cannot be attained.

* Second, the data reported to WHO may be poor, as is certainly the case for some countries, at least with respect to leaving some causes unspedfied. In this case, reports of diarrhea deaths at older ages may also include deaffis for which the underlying cause was different.

* Third, the morbidity surveys on which several of the expert assessments are based may also be inaccurate: through their focused nature they may encourage reports on the particular causes being investigated, they may incorporate associated with underlying causes, they may focus on such groups as the young with inadequate attention to others such as the elderly, or they may be somewhat dated and give earlier rather than current levels.

v Fourth, case-fatality rates, when these are used to convert cases to deaths, may be problematic. They often have a weaker basis tan morbidity estimates, may well be inaccurate, and are generally broad averages that fagl to reflect substantial variability by age, region, severithr of disease, and so on. They are also easy to misapply, since they may have been calculated to cover periods other tan a year (or without a reference period at all) or may relate only to hospitalized cases rather than the entire spectrum of disease, which survey data would attempt to cover.

We cannot assess these possibilities in every case. However, in giving the expert assessments below (Table C2), we do indicate the contrasts with the regression estimates and adjust the assessments to be consistent with estimated mortality levels and in some particulars where they appear dearly too extreme.

## _Diarrhea_

Alternative rates were recommended for the four developing-country regions, based on a substantial number of country surveys and a report from the U.S. nstitute
_70_ _Estimates and Projections of Mortality by Cause_ Table C2L. Expert assessnents of mortality rates (per 100,000) and deaths (in thousands) for some specific causes, by age, sex, and region, 1985

|_Region and_|_Rate_|_s_|_Dea_|_ths_|_Rat_|_e_|_Dea_|_ths_|
|---|---|---|---|---|---|---|---|---|
|_age group_|_A4k_|_Female_|_Mak_|_Femak_|_Male_|_Female_|_Male_|_Female_|
|||Diarr|hea|||Polio|||
|World|||||||||
|Totd|59|61|1439|1457|1.7|1.5|42|35|
|0<br>|1582<br>|1342<br>|977<br>|793<br>|19.4<br>|16.9<br>|12<br>|10<br>|
|1-4|100|193|233|429|12.5|10.8|29|24|
|5-14<br>|23<br>|20<br>|126<br>|105<br>|0.2<br>|0.2<br>|1<br>|1<br>|
|15-44|6|9|72|95|0.0|0.0|0|0|
|45-64|6|7|23|25|0.0|0.0|0|0|
|65+|6|7|7|11|0.0|0.0|0|0|
|Developed|||||||||
|Total|2|2|10|10|0.0|0.0|0|0|
|0|70|58|6|5|0.0|0.0|0|0|
|14|6|8|2|3|0.0|0.0|0|0|
|5-14|0|0|0|0|0.0|0.0|0|0|
|15-44|0|0|0|0|0.0|0.0|0|0|
|45-64|0|0|0|0|0.0|<br>0.0|<br>0|0|
|65+|2|<br>2|<br>1|<br>2|<br>0.0|<br>0.0|<br>0|0|
|Developing|||||||||
|Total|76|80|1429|1447|2.2|1.9|42|35|
|0|1838|1559|971|788|22.7|19.8|12|10|
|1-4|117|226|231|426|14.7|12.7|29|24|
|5-14<br>|28<br>|24<br>|126<br>|105<br>|0.2<br>|0.2|1|1|
|15-4|8|12|72|95|0.0|0.0|0|0|
|45-64|9|11|22|25|0.0|0.0|0|0|
|65+|9|11|6|9|0.0|0.0|0|0|
|Industrial|||||||||
|Total|1|1|2|3|0.0|0.0|0|0|
|0|5|3|0|0|0.0|0.0|0|0|
|1-4|2|3|0|1|0.0|0.0|0|0|
|5-14|0|0|0|0|0.0|0.0|0|0|
|15-4<br>|0<br>|0<br>|0|0|0.0|0.0|0|0|
|45-64|0|0|0|0|0.0|0.0|0|0|
|65+|3|3|1|2|0.0|0.0|0|0|
|Nonmarket|||||||||
|Total|4|3|8|7|0.0|0.0|0|0|
|0|164|136|6|5|0.0|0.0|0|0|
|1-4|11|14|2|2|0.0|0.0|0|0|
|5-14|0|0|0|0|0.0|0.0|0|0|
|15-44|0|0|0|0|0.0|0.0|0|0|
|45-64|0|0|0|0|0.0|0.0|0|0|
|65+|1|1|<br>0|<br>0|<br>0.0|<br>0.0|<br>0|0|
|LAC|||||||||
|Total|77|74|154|148|0.0|0.0|0|0|
|0|1536|1330|89|75|0.0|0.0|0|0|
|14|117|185|25|39|0.0|0.0|0|0|
|5-14|52|48|25|23|0.0|0.0|<br>0|0|
|154|11|9|10|8|0.0|0.0|0|0|
|**45-6**|13|8|3|2|0.0|0.0|0|0|
|65+|10|10|1|1|0.0|0.0|0|0|
_71_ _Reft once_ Table C2. Expert assessments of mortallty rates and deafts (continued)

|_Region and_|_Rat_|_es_|_Dea_|_ths_|_Rat_|_es_|_Pela_|_tha_|
|---|---|---|---|---|---|---|---|---|
|<br>_age group_|_Male_|_Femal_|_Ma_|_Female_|_Mak_|_Femak_|_Mal_|_Femtak_|
|<br>Sub-Sahara|||||||||
|Total|217|212|491|489|5.7|5.2|13|12|
|0|3993|3294|378|308|42.3|42.8|4|4<br>|
|1-4|206|455|69|151|26.9|24.1|9|8|
|5-14|48|32|30|20|0.0|0.0|0|0|
|15-44|11|9|11|8|0.0|0.0|0|0|
|45-64|12|8|3|2|0.0|0.0|0|0|
|<br>65+|<br>9|<br>11|<br>1|<br>1|<br>0.0|<br>0.0|<br>0|0|
|MENA|||||||||
|Total|100|115|192|211|3.1|2.7|6|5|
|0|2141|1783|147|118|29.1|30.3|2<br>|2<br>|
|1-4|104|298|26|71|15.9|12.6|4|3|
|5-14|22|18|11|8|0.0|0.0|0|0|
|15-44|7|13|6|10|0.0|0.0|0|0|
|45-64|8,|12|2|3|0.0|0.0|0|0|
|65+|<br>7|13|0|1|0.0|0.0|0|0|
|Asia|||||||||
|Total|47|50|592|599|1.8|1.5|23|18|
|0|1163|993|357|287|19.5|13.8|6|4|
|1-4|94|149|110|165|13.7|11.8|16|13|
|<br>5-14|<br>21|<br>19|<br>60|<br>53|0.3|0.4|1|1|
|15-44|8|12|45|68|0.0|0.0|0|0|
|45...64|9|11|15|19|0.0|0.0|0|0|
|65+|9|11|5|6|0.0|0.0|0|0|
||<br>Y|<br>ellow fever,|<br>deague|||<br>Malri|||
|World|||||||||
|Total|0.5|0.5|13|13|12|10|299|238|
|<br>0|<br>1.3|<br>1.3|<br>1|<br>1|<br>318|<br>244|<br>197|144|
|14|1.2|1.3|3|3|7|6|15|13|
|5-14|1.0|1.1|6|5|3|3|17|13|
|15-44|03|03|3|3|2|2|19|24|
|<br>45-64|.<br>0.2|.<br>0.2|<br>1|<br>1|<br>10|<br>7|<br>36|27|
|65+|0.2|0.2|0|0|12|10|15|17|
|Developed|||||||||
|Total|0.0|0.0|0|0|0|0|0|0|
|0|0.1|0.1|0|0|0|0|0|0|
|1-4|0.1|0.1|0|0|0|0|0|0|
|5-14|0.1|0.1|0|0|0|0|0|0|
|15-44|0.0|0.0|0|0|0|0|0|0|
|45-64|0.0|0.0|0|0|0|0|0|0|
|<br>65+|<br>0.0|<br>0.0|<br>0|<br>0|<br>0|<br>0|<br>0|0|
|Developing|||||||||
|Total|0.7|0.7|13|13|16|13|299|238|
|0|1.5|1.5|1|1|372|285|197|144|
|<br>1-4|<br>1.4|<br>1.5|3|3|8|7|15|13|
|<br>5-14|<br>1.2|<br>1.2|<br>5|<br>5|<br>4|<br>3|<br>17|13|
|15-44|0.3|0.4|3|3|2|3|19|24|
|45-64|0.3|0.3|1|1|15|12|36|27|
|65+|0.3|0.3|0|0|21|21|15|17|
_72_ _Etmtes and Projedions of Mortality by Cause_ Table C2. Expert assessments of mortalit' rates and deafts (continued)

|_Regio and_|_Rate_||_Deot_|_h_|_Rate_|_s_|_Dea_|_ths_|
|---|---|---|---|---|---|---|---|---|
|_a group_|_MAde_|_Femalk_|_Mak_|_Femae_|_Mak_|_Fcmale_|_Male_|_Female_|
|Industrala<br>|||||||||
|Total<br>|0.0|0.0|0|0|0|0|0|0|
|0<br>|0.0<br>|0.0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|1-4<br>|0.0<br>|0.0<br>|0<br>|0<br>|0<br>|0|0|0|
|5-14<br>|0.0<br>|0.0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|0.0<br>|0.0<br>|0|0|0|0|0|0|
|45-64|0.0|0.0|0|0|0|0|0|0|
|65+|0.0|0.0|0|0|0|0|0|0|
|Nonmarket<br>|||||||||
|Total|0.1|0.1|0|0|0|0|0|0|
|0<br>|0.1<br>|0.1<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0|
|1-4<br>|0.1<br>|0.1<br>|0<br>|0<br>|0<br>|0|0|0|
|5-14<br>|0.1<br>|0.1<br>|0<br>|0<br>|0<br>|0<br>|0<br>|0<br>|
|15-44<br>|0.1<br>|0.1<br>|0<br>|0<br>|0<br>|0<br>|0|0|
|45-64<br>|0.1<br>|0.1<br>|0<br>|0|0|0|0|0|
|65+<br>|0.1|0.1|0|0|0|0|0|0|
|LAC<br>|||||||||
|Total<br>|0.1<br>|0.1<br>|0|0|3|3|6|5|
|0<br>|0.1<br>|0.1<br>|0<br>|0<br>|9<br>|9|1|1|
|1-4<br>|0.1<br>|0.1<br>|0<br>|0<br>|1|1|0|0|
|5-14<br>|0.1<br>|0.1<br>|0<br>|0<br>|3|2|1|1|
|15-44<br>|0.1<br>|0.1|0|0|3|3|2|2|
|s-64<br>|0.1<br>|0.1<br>|0<br>|0|5|2|1|1|
|65+<br>|0.1|0.1|0|0|5|5|0|0|
|Sub-Sahara<br>|||||||||
|Total<br>|4.4<br>|4A<br>|10<br>|10<br>|101<br>|77<br>|228|177|
|0<br>|7.2<br>|7.2|1|1|1882|1386|178|130|
|1-4<br>|7.2<br>|7.2<br>|2|2|16|20|5|7|
|5-14|7.2|7.2|4|4|14|6|9|4|
|_i5-44_<br>|2.0<br>|2.0<br>|2|2|5|10|5|9|
|45-64<br>|2.0|2.0|0|0|107|76|24|18|
|65+<br>|2.0|2.0|0|0|125|130|8|9|
|MiENA<br>|||||||||
|Total|0.2|0.2|0|0|4|4|8|7|
|0<br>|0.2|0.2|0|0|50|40|3|3|
|1-4<br>|0.2<br>|0.2<br>|0<br>|0|1|1|0|0|
|5-14<br>|0.2<br>|0.2<br>|0<br>|0<br>|3<br>|3<br>|2|1|
|15-44<br>|0.2<br>|0.2<br>|0<br>|0<br>|2<br>|3<br>|2<br>|2<br>|
|45-64<br>|0.2|0.2|0|0|4|3|1|1|
|65+|0.2|0.2|0|0|4|6|0|0|
|Asia|||||||||
|Total<br>|0.2<br>|0.2|2|2|5|4|57|48|
|0<br>|0.3<br>|0.3|0|0|48|40|15|12|
|1-4|0.3|0.3|0|0|8|5|9|5|
|5-14<br>|0.3<br>|0.3<br>|1<br>|1<br>|2<br>|2|5|7|
|15-44<br>|0.1<br>|0.1<br>|1<br>|1<br>|2<br>|2<br>|10<br>|10|
|45-64|0.1|0.1|0|0|6|5|10|8|
|65+|0.1|0.1|0|0|13|12|7|7|
R¢61efWs _m73_ Table C2. Expert assessments of mortality rates and deaths (continued)

|_Region and_|_Rat_|_es_|_Dct_|_dhs_|_Rates_|_Deaths_|
|---|---|---|---|---|---|---|
|_age group_|_Male_|_Female_|_Male_|_Femake_|_Mal_<br>_Female_|_Male_<br>_Female_|
|||Schistoso|mfasl||CompHatilons o|f pregnancy|
|World<br>|||||||
|Total<br>|1.0<br>|0.4|25.4|9.0|20.8|499.5|
|0<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|
|14<br>|0.0|0.0|0.1|0.0|0.0|0.0|
|5-14<br>|0.1<br>|0.0<br>|0.4<br>|0.2<br>|0.1<br>|0.8|
|15-44<br>|1.1<br>|0.2<br>|12.1<br>|2.5<br>|45.0<br>|484.8<br>|
|45-64<br>|2.5|1.0|9.0|3.8|3.8|14.0|
|65+<br>|3.2|1.5|3.9|2.5|0.0|0.0|
|Developed<br>|||||||
|Total<br>|0.0|0.0|0.3|0.0|1.2|7.5|
|0<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|1-4|0.0|0.0|0.0|0.0|0.0|0.0|
|5-14<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|15-44<br>|0.1.|0.0|0.3|0.0|2.5|6.6|
|45-64|0.0|0.0|0.0|0.0|0.7|0.9|
|65+<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|Developing<br>|||||||
|Total<br>|1.3<br>|0.5<br>|25.2<br>|9.0<br>|27.3|492.0|
|0<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|
|1-4<br>|0.0<br>|0.0<br>|0.1<br>|0.0<br>|0.0|0.0|
|5-14<br>|0.1<br>|0.0<br>|0.4<br>|0.2<br>|0.2<br>|0.8|
|15-44<br>|1.4<br>|0.3<br>|11.9<br>|2.5<br>|58.6<br>|478.2<br>|
|45-64<br>|3.7<br>|1.6<br>|9.0<br>|3.8|5.6|13.1|
|65+|5.4|3.1|3.9|2.5|0.0|0.0|
|Industrlal<br>|||||||
|Total|0.0|0.0|0.0|0.0|0.1|0.4|
|0<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|1-4<br>|0.0<br>|0.0<br>|0.0|0.0|0.0|0.0|
|5-14<br>|0.0<br>|0.0<br>|0.0|0.0|0.0|0.0|
|15-44<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|0.2|0.4|
|45-64<br>|0.0<br>|0.0<br>|0.0<br>|0.0<br>|0.0|0.0|
|65+<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|Nonmarket<br>|||||||
|Total|0.1|0.0|0.3|0.0|3.3|7.1|
|0<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|1-4<br>|0.0<br>|0.0<br>|0.0<br>|0.0|0.0|0.0|
|S-14<br>|0.0<br>|0.0|0.0|0.0|0.0|0.0|
|15-44<br>|0.3|0.0|0.3|0.0|7.0|6.2|
|45-64|0.0|0.0|0.0|0.0|1.8|0.9|
|65+|0.0|0.0|0.0|0.0|0.0|0.0|
|LAC|||||||
|Total|4.6|0.9|9.3|1.9|16.9|34.0|
|0<br>|0.0|0.0|0.0|0.0|0.0|0.0|
|1-4<br>|0.1|0.0|0.0|0.0|0.0|0.0|
|5-14<br>|0.2<br>|0.1<br>|0.1<br>|0.1|0.2|0.1|
|15-44<br>|7.0<br>|0.7<br>|6.4|0.6|35.4|32.3|
|45-64|7.8|2.9|1.9|0.7|6.3|1.6|
|65+|10.3|4.5|0.9|0.4|0.0|0.0|
_Eshnales and Projetions of Mortality by Cause_ _74_ Table C2. Expert assessments of mortality rates and deaths (contlnued)

|**_Rcion_**_and_|_Raks_||_Dea_|_ths_|_Rate_|_Deaths_|
|---|---|---|---|---|---|---|
|_age grmup_|_Malt_|_Femal_|_Male_|_Femak_|_Male_<br>_Femake_|_MA_<br>_Female_|
|Sub-Sahara|||||||
|Total|2.4|1.4|5.4|3.3|54.7|126.0|
|0|0.0|0.0|0.0|0.0|0.0|0.0|
|1-4|0.1|0.0|0.0|0.0|0.0|0.0|
|5-14|0.3|0.2|0.2<br>|0.1<br>|0.6<br>|0.4<br>|
|15-44|0.6|1.3|0.6|1.2|128.6|121.5|
|45-64|15.2|5.9|3.4|1.4|17.3|4.2|
|65+|19.5|7.9|1.2|0.6|0.0|0.0|
|MENA|||||||
|Total|2.3|0.5|4.4|0.9|20.8|38.0|
|0|0.0|0.0|0.0|0.0|0.0|0.0|
|<br>1-4|<br>0.0|<br>0.0|<br>0.0|0.0|0.0|0.0|
|5-14|0.1|0.0|0.1|0.0|0.2|0.1|
|15-4|3.7|0.4|3.1|0.3|46.3|36.2|
|45-64|4.6|1.8|0.9|0.4|8.4|1.7|
|65+|5.9|2.5|0.4|0.2|0.0|0.0|
|Asia|||||||
|Total|0.5|0.2|6.1|2.9|24.8|294.0|
|0|0.0|0.0|0.0|0.0|0.0|0.0|
|1-4|0.0|0.0|0.0|0.0|0.0|0.0|
|5-14|0.0|0.0|0.0|0.0|0.1|0.2|
|15-44|0.3|0.1|1.8|0.3|52.2|288.2|
|45-64|1.6|0.8|2.7|1.2|3.4|5.6|
|65+|3.0|2.3|1.5|1.4|0.0|0.0|
|||Diabe|bs||||
|World|||||||
|Total|8|12|188|290|||
|0|3|3|2|2|||
|1-4|1|1|3|2|||
|5-14|0|0|1|1|||
|15-4|1|1|15|16|||
|45-64|16|21|56|78|||
|65+|90|117|110|192|||
|Developed|||||||
|Total|10|17|58|100|||
|o|0|0|0|0|||
|1-4|0|1|0|0|||
|5-14|0|0|0|0|||
|15-44|1|1|2|1|||
|45-64|11|9|13|12|||
|65+|87|107|42|86|||
|Developing|||||||
|Total|7|11|130|189|||
|0|3|4|2|2|||
|1-4|2|1|3|1|||
|<br>5-14|<br>0|<br>0|<br>1|1|||
|15-44|2|2|13|14|||
|45-64|18|28|43|65|||
|65+|95|130|68|106|||
**_Rfrences_**

_75_ Table C2. Expert assessments of mortality rates and deaths (continued)

|_Region and_|_Rat_|_es_|_Deat_|_hs_|
|---|---|---|---|---|
|_age group_|_Male_|_Female_|_Male_|_Female_|
|Industrial|||||
|Total|13|21|48|81|
|0|0|0|0|0|
|1-4|0|1|0|0|
|5-14|0|0|0|0|
|15-44|1|0|2|1|
|45-64|12|9|10|7|
|65+|101|132|37|73|
|Nonmarket|||||
|Total|5|9|11|20|
|o|0|0|0|0|
|1-4|0|0|0|0|
|5-14|0|0|0|0|
|15-44|1|1|1|1|
|45-64|9|10|4|5|
|65+|46|53|6|14|
|LAC|||||
|Total|14|17|28|34|
|o|1|1|0|0|
|1-4|0|0|0|0|
|5-14|0|0|0|0|
|15-44|2|2|2|2|
|45-64|41|41|10|10|
|65+|200|232|16|22|
|Sub-Sahara|||||
|Total|5|5|10|11|
|o|o|0|0|0|
|1-4|0|0|0|0|
|5-14|0|0|0|0|
|15-44|2|0|2|0|
|45-64|10|10|2|2|
|65+|100|120|6|9|
|MENA|||||
|Total|9|13|18|25|
|o|3|4|0|0|
|14|0|0|0|0|
|5-14|0|0|0|0|
|15-44|2|3|1|2|
|45-64|31|49|6|10|
|65+|166|194|10|12|
|Asia|||||
|Total|6|10|74|119|
|0|5|5|1|2|
|<br>1-4|<br>3|<br>1|<br>3|1|
|5-14|0|0|0|0|
|15-44|1|2|8|10|
|45-64|14|26|25|43|
|65+|71|109|36|63|
_Estimates and Projections of Mortality by Cause_ _76_ of Medicine (1986:159-162) for case-fatality rates. The recommendations<sup>were age- but</sup> niot sex-specific, with age groups 0 and 1-4 combined. Older ages<sup>were separated into</sup> 15-59 and 59 and over, but the rates were identical.

The ratios of the rates from the expert assessment to the regression<sup>estimates,</sup> by age group and region, were as follows:

|||Sub-<br>Saharan<br>|||
|---|---|---|---|---|
||LAC|Africa<br>|MENA<br>|Asia<br>|
|0-4|1.65|1.48<br>|1.03<br>|1.47<br>|
|5-14|4.05<br>|0.33<br>|0.43<br>|1.15<br>|
|15-44|0.95<br>|0.07<br>|0.26<br>|0.58<br>|
|45-64|0.40|0.05<br>|0.16<br>|0.31<br>|
|65+|0.10|0.04|0.06|0.14|

The inconsistency between the expert assessment for age 65<sup>and over and reported</sup> figures for Latin America has already been noted. Either<sup>the reported deaths are grossly</sup> exc;issive or the expert assessment for this age group and region<sup>is wrong. The 5-14 age</sup> group for Latin America also presents a problem: the rate for<sup>reporting countries is 6.9</sup> per 100,000, and the expert assessment of 50 could be reached<sup>(assuming the reports</sup> are accurate) only if nonreporting countries have a rate 14<sup>times that of reporting</sup> countries. In general, the pattern of expert assessments across<sup>age groups is so different</sup> from that of the regres'k'n rates that no attempt was<sup>made to reconcile them.</sup> Using the rates from the expert assessment, we calcula*td deaths<sup>within each</sup> age group and allocated these between the sexes (and, in the<sup>cc.-. of the youngest age</sup> gr'ups, between 0 and 1-4) in proportion to numbers of<sup>deai' s in the regression</sup> e.timates. For all ages combined, the regression estimates<sup>and expert assessment</sup> actually produce similar results: the developing-country<sup>mortality rate is reduced</sup> marginally following the recommendations from 62 to 60 per<sup>100,000, and developing-</sup> country deaths reduced from 3.0 to 2.9 million. However, deaths<sup>among those 0-4 are</sup> increased 40 percent and among those 5 and older decreased<sup>63 percent.</sup>

# _Polio_

Detailed altemative numbers of deaths were recommended based<sup>on lameness</sup> prevalence surveys reported in several publications, including<sup>a summary article by</sup> Bernier (1984). The surveys suggest that new cases worldwide<sup>are half a million, and</sup> a case-fatality rate of 15 percent (the literature suggests rates between<sup>10 and 20 percent)</sup> was applied to obtain the expert assessment.

For industrial market and nonmarket economies and for Latin<sup>America and the</sup> Caribbean, the recommended figures were uniformly zero. However,<sup>some deaths</sup> actually were reported to WHO (e.g., 9 deaths in Sweden<sup>in 1985, and 34 in the United</sup> Kingdom), so that the expert assessment was modified to incorporate<sup>the very low</sup> regression estimates in these cases.
Annex C _Epert AssesementB_ _77_ Adopting the recommended rates in full for the other regions leads to a substantial rise in the world mortality rate from polio from .5 to 1.6 per 100,000, and an increase in the number of deaths worldwide from 25 to 77 thousand.

The inaease involves three regions with little data: Sub-Saharan Africa, the Middle East and North Africa, and Asia. Recommended rates at ages 0 and 14, the age groups most affected, range from 12 to 43 in these regions. Most of the reported rates for 1970 (most countries reported some deaths) are at or below the bottom of this range. For 1985, there are virtually no useful data-this cause is missing for all the Latin American countries due to reporting procedures adopted in the region for TCD-9, and includes no deaths everywhere else except in three countries, for which rates per 100,000 are as follows:

||Age 0|Age 14|
|---|---|---|
|Korea, Rep. of|15.2|15.9|
|Sri Lanka|1.3|1.6|
|Thailand|0.8|0.2|

Therefore, reports of deaths to WHO are well below the expert assessments.

_Yellow fever, dengue, and encephalitis_ The recommendations on this category, largely judgmental, were these: (a) that yellow fever deaths in Sub-Saharan Africa be estimated at 15,000 under age 15 and 5,000 at age 15 and over, out of total numbers of cases of 75,000 and 25,000 respectively; (b) that deaths in Latin America and the Caribbean be estimated at 10 under 15 and 70 at 15 and over, out of total cases of 11,000 and 7,000 respectively; and (c) that malefemale ratios equal one, and cases at 0 and 14 be proportional to dte size of the age groups.

The equations for yellow fever were not satisfactory, and produced an irregular age pattern (not visible in preceding tables because rates are so low). The first step in revision was to smooth the rates, redistributing deaths across age-sex groups without altering the total, to give the same rate for all those under 15 and a second rate for all those 15 and over.

Next, rates were adjusted for Sub-Saharan Africa to give the recommended number of deaths, which is nine times the regression estimate. A rate of 7.2 per 100,000 for those under 15 resulted. Rates of this order were in fact reported to WHO for children under five in 1970 (for Portugal and Uruguay); in 1985, however, virtually no deaths from this cause were reported.

Rates for Latin America were nzt adjusted, because they would have to be lower than those for developed countries to give the recommended numbers of deaths. The regression estimates were intermediate between developed countries, on one hand, and all other developing regions, on the other, and these were maintained.
_78_ _Estimates and Projections of Mortality by Cause_ Because of the adjustment for Sub-Saharan Africa, the world mortality rate rises from .17 to .54 per 100,000, and deaths rise from 8,000 to 26,000, with Sub-Saharan Africa accounting for 75 percent of the total.

# _Malaria_

Numbers of malaria cases were provided by region, and rough estimates of deaths for Sub-Saharan Africa and Brazil were recommended by disease experts. The prevalence estimates, on the basis of 1985 data reported to WHO, are given below, together with ratios of the regression estimate of deaths to these cases.

||Reported cases<br>|Ratio of deaths<br>to 1000 cases|
|---|---|---|
|Industrial market economies<br>|7,353<br>|10.7|
|Industrial nonmarket economies<br>|<br>631<br>|12.7|
|Latin America and Caribbean<br>|883,451<br>|6.4|
|Middle East and North Africa<br>|394,969|39.3|
|Asia|3,560,432|29.5|

No 1984 or 1985 Sub-Saharan Africa reports were available, but cases were 4.8 to 7.8 million annually between 1976 and 1983. Since case-fatality rates may be anywhere from under 1 to 50 per thousand, the regression estimates of deaths appear broadly consistent with the case reports. The rate for Latin America, though lower than the others, is consistent with an analysis of deaths in 1977-82 in the Amazon and CenterWestern regions in Brazil, which gave a case-fatality rate of 5.8 (Fiusa Lima, n.d.).

Nevertheless, an increase was recommended for Latin America, based on an informal estimate of 6,000 to 10,000 malaria deaths in Amazonia. (Brazil reports almost half the cases in the America 3.) With no more precise guidance, we simply doubled the number of deaths in each age-sex group for Latin America, effectively assuming that case-fatality rates are comparable to those in developed countries. Deaths in Amazonia would then be 50 to 90 percent of the revised regional total. The resulting age-specific rates are in the upper range for reporting Latin American countries. At age 0, the revised rate is 9 per 100,000; by contrast, the highest reported rates in the region are El Salvador 7.2 per 100,000 Guatemala 5.7 per 100,000 Ecuador 4.7 per 100,000.

For Sub-Saharan Africa. estimates of deaths between 405,000 and 952,000 were recommended. If 1985 cases were in the range of 4.8-7.8 million, these expert assessments would give deaths per thousand cases between 50 and 200-ratios that are probably too high, particularly if malaria is overall less lethal in this region than in other regions. (Malaria is believed to be most lethal among migrants moving into an area where it is endemic. Lower fatality rates in settled areas of fixed endemicity may be expected.) We therefore chose the lower expert assessment of 405 thousand and adjusted deaths in each age-sex group proportionally to reach this total. This implies a mortality rate 20 times the regression estimate.
_Annex_ C _Expet Assessments_ _79_ For the world as a whole, the revised mortality rate rises from the original estimate of 3 to 11 and the number of deaths from 146,000 to 537,000, with 75 percent of them in Africa.

# _Schistosomiasis and filariasis_

Two sets of age- and sex-specific morbidity estimates were provided for each developing country region, one based on Pike (1987:204-205) and another on Walsh (1988:15), and various case-fatality rates ranging from 2.5 to 5 percent, and averaging 3.5 percent, were recommended.

First we observed that multiplying the average of the morbidity estimates by a constant case-fatality rate would produce an age distribution of deaths similar to that of the regression estimates (though very different in total) only if one assumed a tenyear lag, i.e., that average duration from initial infection to death is 10 years plus the average current duration of infection. Making the bold inference from this that those who die of schistosomiasis do so on average ten years after infection, we adopted ratios of deaths in the current year to current cases that are a tenth of the recommended casefatality rates. (Note that these ratios are not strictly case-fatality rates, and depend on complicated assumptions about whether numbers of cases have been rising or falling and how long a case stays active if death does not occur.) We did allow these ratios to vary by region, assumning a simplified distribution of the three principal species: we chose a high ratio of .0050 for Asia, assuming _Schistosomiasis japonicum is_ more lethal than other spedes; .0035 for Latin America and the Middle East, where S. _mansoni_ may have intermediate lethality; and .0025 for Sub-Saharan Africa where S. _hamatobium is_ the least lethal. The last parameter is consistent with a reported estimate of a causespecific mortality rate of 2 per thousand per year among heavily infected men in Zanzibar (Morrow n.d.:Table 4). The parameter choices were made to minimize deaths from this cause. Similarly, we took the lower set of morbidity estimates, based on Walsh (1988:15), with the additional argument that the other set used mid-1970s data. Total deaths by region calculated using these assumptions were distributed among agesex groups, using the distribution in the regression estimates.

Even with the choice of mdnimizing parameters, the resultng revision raises the world mortality rate from 0.25 to 0.70 per 100,000 and increases deaths from 12,000 to 34,400. The revision gives rates for Latin American males 45-64 of 7.8 per 100,000, and for males 65 and over of 10.3. For comparison, the highest reported rates for males in Latin America and the Caribbean in 1985 are these: Age 45-64 Age 65 + Suriname 4.4 15.9 Guyana 2.2 8.6 No other reporting country in the region has rates dose to these. Even with minimizing assumptions, therefore, the revised mortality rates are still high in comparison, with reported rates.
_80_ _Estimates and Projetions of Mortality by Cause_ The revised Asian rates are lower and more reasonable-and possibly even too low, since we estimate Chinese rates per 100,000, from survey data, at 4.1 for males 45-64 and 9.0 for males 65 and over.

# _Complications of pregnancy_

WHO compiled maternal mortality rates from a variety of sources for around 1983, and these provide our expert assessment. The compilation is based on information available at the headquarters of the World Health Organization-in the library, in the documentation centres and in the possession of individual members of the staff. All relevant data bases-e.g. MEDLINE, POPLINE-were searched, as were national yearbooks, the reports of consultants, needs assessment missions, evaluation studies, etc. Helpful colleagues around the world who know of our interest also provided information (WHO 1986:4).

With this type of search, a possible upward bias in the results, unless a rigorous standard of data quality is imposed, cannot be excluded. Such a bias could occur because of selective reporting of higher (and therefore more 'interesting') figures, selective dismissal of reports including no maternal deaths (e.g., because of lack of evidence whether the category was used), and the utilization of somewhat older data where nothing else is available. No attempt to minimize this bias is evident in the report, which in fact goes out of its way to citP- exceptionally high figures in a brief overview.

Mateinal deaths are more commonly expressed in relation to live births rather than to population. Reexpressing the regression estimates as a rate per 100,000 livebirths gives this comparison with the WHO report (where the Middle East and North Afica region is made up by combining Northern Africa and Western Asia from the WHO report):

||Regression estimates|WHO (1986)|
|---|---|---|
|Developing countries|191|450|
|Latin America and Caribbean|103|270|
|Sub-Saharan Africa|229|680|
|Middle East and North Africa|<br>153|430|
|Asia|204|420|

The WHO (1986) figures, it should be noted, do not appear to be simple averages of those collected in the report. Though they are probably based on these data, their specific derivation is not explained. The differences between these figures and our regression estimates are substantial. In mining the WHO report for statistics to include in the World Development Report, the World Bank (1988:286) rejected some of the higher numbers as inconsistent among 3hemselves, ending up with reduced average maternal mortality rates of 329 in low-income economies and 381 in middle-income economies. A further reduction would be necessary to agree with the regression estimates, as well as with deaths reported to WHO. For Latin America and the Caribbean, for instance, reporting countries have a matemal mortality rate of 75. If this
_81_ _Annex C Expert Assesments_ rate is credited, the nonreportng countries would need a rate of 540-somewhat too high to accept-to produce the WHO (1986) figure. Similarly, for Asia, reporting countries (among which we count China and rural India) have a rate of 202, and a rate of 1048 would be needed in the nonreporting countries to produce the WHO (1986) figure.

Adopting the WHO (1986) estimates, and applying age distributions from the regression estimates, would raise deaths due to complications of pregnancy from 218 to 492 thousand in developing countries, an increase of 130 percent.

## _Diabetes_

For diabetes, the recommendations were essentially subjective: to replace SubSaharan African rates with rates lower than developed country rates; to reduce Asian rates to reported levels for Korea, Singapore, Thailand, and Hong Kong, treating these as setting an upper bound; to reduce rates for Latin America somewhat; to eliminate deaths at age 0; and to allow a nominal number of deaths, say 1 in 100,000, at age 5-14.

The revised African rates were adopted. The Asian rates were not changed because calculations subsequent to those provided to the expert had already reduced them. Latin American rates were not changed for various reasons, including the suspicion that there may be higher rates in the Caibbean. Deaths at age 0 were not eliminated because such deaths were in fact reported. And increasing the rate at 5-14 was not thought necessary because the regression estimates are in fact nonzero, though quite small.

The result of changing the Afdcan rates is to reduce world mortality rates slightly from 10.5 to 9.9 and deaths from 507,000 to 477,000.

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