Informe Muerte Materna
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Transcript of Informe Muerte Materna
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Trends in
Maternal Mortality:
1990 to 2015Estimates by WHO, UNICEF, UNFPA, World Bank Group
and the United Nations Population Division
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Trends in maternal mortality:
1990 to 2015
Estimates by WHO, UNICEF, UNFPA, World Bank Group
and the United Nations Population Division
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WHO Library Cataloguing-in-Publication Data
Trends in maternal mortality: 1990 to 2015: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United
Nations Population Division.
1.Maternal Mortality - trends. 2.Maternal Welfare. 3.Data Collection - methods. 4.Models, Statistical. I.World Health
Organization. II.World Bank. III.UNICEF. IV.United Nations Population Fund.
ISBN 978 92 4 156514 1 (NLM classification: WQ 16)
PRE-PUBLICATION VERSION
© World Health Organization 2015
All rights reserved. Publications of the World Health Organization are available on the WHO website (www.who.int)
or can be purchased from WHO Press, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland
(tel.: +41 22 791 3264; fax: +41 22 791 4857; e-mail: [email protected]).
Requests for permission to reproduce or translate WHO publications –whether for sale or for non-commercial
distribution– should be addressed to WHO Press through the WHO website (www.who.int/about/licensing/
copyright_form/en/index.html).
The designations employed and the presentation of the material in this publication do not imply the expression of
any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country,
territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and
dashed lines on maps represent approximate border lines for which there may not yet be full agreement.
The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or
recommended by the World Health Organization in preference to others of a similar nature that are not mentioned.
Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters.
All reasonable precautions have been taken by the World Health Organization to verify the information containedin this publication. However, the published material is being distributed without warranty of any kind, either
expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no
event shall the World Health Organization be liable for damages arising from its use.
http://www.who.int/mailto:[email protected]%20http://www.who.int/about/licensing/copyright_form/en/index.htmlhttp://www.who.int/about/licensing/copyright_form/en/index.htmlhttp://www.who.int/about/licensing/copyright_form/en/index.htmlhttp://www.who.int/about/licensing/copyright_form/en/index.htmlmailto:[email protected]%20http://www.who.int/
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Box 2Estimating trends for countries with improving data quality
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Box 2
Estimating trends for countries with improving data quality
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Categorization of VR data retrieved from CRVS systems (country-year records) based
on usability and availability
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Box 4
Accurately interpreting point-estimates and uncertainty intervals
the true value lies below 216.
• There is an 80% chance that the true 2015 global MMR lies between 207 and 249.
• There is still a 10% chance that the true 2015 global MMR lies above 249, and a 10% chance
that the true value lies below 207.
Other accurate interpretations include:
• We are 90% certain that the true 2015 global MMR is at least 207.
• We are 90% certain that the true 2015 global MMR is 249 or less.
The amount of data available for estimating an indicator and the quality of that data determine the width
of an indicator’s UI. As data availability and quality improve, the certainty increases that an indicator’s
true value lies close to the point-estimate.
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J-7?4?26258 5K45 4 :>Q8.4-Q760 `734/ `266 02. .M./5I4668 V-73 4 345.-/46 R4I1._S E5 5K./ .f432/.1
5-./01 2/ 5K.1. 2/02R457-1 12/R. :;;
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T2@,& EJ :'%1/2%&' #4 /2%&5$2, /#5%2,1%? 52%1# Q
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RS N2V.523. -21H /I3?.-1 K4M. ?../ -7I/0.0 4RR7-02/P 57 5K. V7667`2/P 1RK.3.9 u :X\ ]CE >:: 57 \>=_S ,K-.. -.P27/1 U #R.4/24 ]:[Zc CE ;>
57 W[:_B O7I5K.-/ )124 ]:Z\c CE :>W 57 =:\_ 4/0 O7I5KQ.415.-/ )124 ]:: 57 :X=_ U K4M.
370.-45. TT&S ,K. -.342/2/P V2M. -.P27/1 K4M. 67` TT&S
L.M.67J2/P -.P27/1 4RR7I/5 V7- 4JJ-7f2345.68 ;;o ]W
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:>UX; 8.4-1 ?.5`../ :;;< 4/0 =S OI?QO4K4-4/ )V-2R4 4RR7I/51 V7- 5K. 64-P.15 J-7J7-527/ ][>o_
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TL* -.P27/ TT&4 DI3?.- 7V
345.-/46
0.45K1?
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2/02-.R5 TT&R
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Latin America and the
Caribbean BDD 5>> $ D$
>#=
Latin Americai B> B >>> $ @$ >#=
Caribbeanm
$D@ $ 5>> 5 "> $#@
Oceanian $LD @>> $ 5 >#B
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[1.95& CJ =Z 57 :[ 57 ;_ U K4M. 67` TT&S
,K-.. R7I/5-2.1 7I5120. 5K. 1I?QO4K4-4/ )V-2R4/ -.P27/ K4M. K2PK TT&9 )VPK4/2154/ ]W;\c CE =>W 57\=c CE =ZX 57 >[=_ 4/0 A4252 ]W>;c CE =W\ 57 \[
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O2.--4 N.7/. `25K 4/ 4JJ-7f2345. 62V.523. -21H 7V : 2/ :ZB 4/0 "K40 `25K 4/ 4JJ-7f2345. 62V.523. -21H
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T2@,& UJ "#/;251'#$ #4 /2%&5$2, /#5%2,1%? 52%1# Q
Developed
regionsd "5 5 @>> $" $ D>> :L "#B 5#5 "#"
Developing
regions :5> @"= >>> "5= 5>" >>> :: "#: $#5 5#$
Northern Africae $D$ B :>> D> 5 $>> @= 5#B :#$ 5#"
Sub-Saharan
Africaf =LD ""5 >>> @:B ">$ >>> :@ "#: $#@ "#=
Eastern Asiag =@ "B >>> "D : L>> D" @#> :#L @#>
Eastern Asia
excluding
China @$ @=> :5 5L> $B >#D ?5#> 5#$
Southern Asia @5L "$> >>> $DB BB >>> BD :#@ 5#B @#$
Southern Asia
excluding
India :=@ @D L>> $L> "$ >>> B: :#$ "#@ @#$
South-eastern
Asiai 5"> 5= >>> $$> $5 >>> BB :#5 :#D :#>
Western Asia $B> B D>> =$ : D>> :5 "#" "#D $#=
Caucasus and
Central Asiak B= $ 5>> 55 B$> @" 5#> 5#$ "#=
Latin America
and the $5@ $B >>> BD D 5>> @> "#L 5#$ "#B
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TL* -.P27/ :;;< = o RK4/P.
2/ TT&
?.5`../
:;;< 4/0
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=> $D@ $ 5>> 5D $#L "#@ $#:
Oceanian 5=$ DL> $LD @>> @" 5#> "#= 5#>
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"#9$%5? &'%1/2%&')//.f :; J-7M20.1 2/V7-34527/ 7/ TT& 5-./01 V-73 :;;< 57 = V7- .4RK R7I/5-8S )11.113./51 7V
/4527/46Q6.M.6 J-7P-.11 57`4-01 4RK2.M2/P TL* >):W ]1.. R45.P7-2.1 .fJ642/.0 2/ G7f >_ `.-.
R7/0IR5.0 V7- 5K71. ;> R7I/5-2.1 5K45 154-5.0 5K. .M46I4527/ J.-270 2/ :;;< `25K 5K. K2PK.15 TT&
]:[ .fJ.-2./R.0 4 0.R62/. 2/ TT& ?.5`../ :;;< 4/0 =S F7- 5K. -.342/2/P
=\ R7I/5-2.1B 25 R4//75 ?. R7/V20./568 R7/R6I0.0 `K.5K.- TT& 2/R-.41.0 7- 0.R-.41.0B K7`.M.-
J72/5Q.152345.1 1IPP.15 5K45 == 7V 5K.3 62H.68 .fJ.-2./R.0 4 0.R-.41. 4/0 X 62H.68 .fJ.-2./R.0 4/
2/R-.41.S
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=>Q8.4- J.-270B 3.4/2/P 5K45 5K.8 4RK2.M.0 TL* >)S ,K.1. R7I/5-2.1 4-.9 T4602M.1 ];
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27
U (''&''1$. ;5#.5&'' 2$- '&%%1$. 2 %52\&)%#5? %#+25-' &$-1$.
;5&A&$%2@,& /2%&5$2, /#5%2,1%?
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= 7V Z>o 7- 37-. K4M. 4RK2.M.0 TL* >) U 5K.8 K4M. ?../ J64R.0 2/ 5K. V2-15 R45.P7-8S ,K.
1.R7/0 R45.P7-8B 5K71. R7I/5-2.1 5K45 4-. 34H2/P J-7P-.11B 2/R6I0.1 W; R7I/5-2.1 `25K 4/ .152345.0
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.152345.0 TT& -.0IR527/ 7V =>o 7- 37-.B 4/0 45 6.415 4 ;oB 7- 4 P-.45.- 5K4/ :) 54-P.5S
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,K. /2/. R7I/5-2.1 `K2RK 4-. R7/120.-.0 57 K4M. 4RK2.M.0 TL* >) ?41.0 7/ J72/5Q.152345.1 4-.9
GKI54/B "43?7024B "4?7 $.-0.B 5K. E16432R &.JI?62R 7V E-4/B 5K. N47 (.7J6.d1 L.37R-452R &.JI?62RB
T4602M.1B T7/P7624B &`4/04 4/0 ,237-QN.15.S n.5B 437/P 5K.1. R7I/5-2.1 5K.-. 21 1I?154/5246
M4-24527/ 2/ 5K. 6.M.6 7V R.-542/58 7V 5K21 4RK2.M.3./5S )1 2/02R45.0 ?8 I/R.-542/58 2/5.-M461 ]7/68
"43?7024 4/0 T4602M.1 K4M. 4 P-.45.- 5K4/ ;o
7- 37-.S F7- 5K. 75K.- 1.M./B 4 :o ]1.. ,4?6. X_B 466
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29
@K26. 02VV.-2/P R7/5.f51 34H. 211I2/P J-.1R-2?.0 -.0IR527/ 15-45.P2.1 23J7112?6.B .f432/2/P 5K.
15-45.P2.1 .3J678.0 ?8 1IRR.11VI6 R7I/5-2.1 R4/ 266I32/45. -7I5.1 5K45 75K.- R7I/5-2.1 348 V2/0
I1.VI6S A7`.M.-B 5K. W< R7I/5-2.1 `25K 5K. K2PK.15 TT&1 2/ = `266 K4M. 57 4RK2.M. 1I?154/524668
K2PK.- 4//I46 -45.1 7V -.0IR527/ 57 45542/ TT&1 ?.67` :X< 2/ =
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30
Box 6
Strategies driving success in reducing maternal mortality
UVWg4 0&.&2'+< 679+-4(&* '()*(+,-+. (/0*)1. +21-2, 3)+4+2(*56+ 7*(+)2*6 7/)(*6-(8
9:;(>&- >. 0%%&-- (" 0., @#02>() ": -&A#02B $&*$",#%(>C&B 90(&$.02 0.,
.&DE"$. ;&02(; %0$&
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4'07.'70/+ 9/00-&04 ') 4&N7/+O 0&60)*7.'-8&O 3/'&02/+ /2* 2&E9)02 (&/+'(O /2* /+4)
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• _-&' Y/3 *&8&+)6&* 4&N7/+ /2* 0&60)*7.'-8& (&/+'( 4&08-.&4 46&.-1-./++< 1)0 /*)+&4.&2'4
/2* 9*$"C& @#02>() ": %0$& 0., &@#>()
• %)2,)+-/ -2'0)*7.&* 60).&*70&4 /' '(& 1/.-+-'
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K.465K 1815.31 4/0 2/V-415-IR5I-.B 2/ 4002527/ 57 251 02-.R5 K.465K 23J4R51S %3.-P./5 KI34/254-24/
1.552/P1 4/0 125I4527/1 7V R7/V62R5B J715QR7/V62R5 4/0 021415.- 4617 12P/2V2R4/568 K2/0.- J-7P-.11S
E/0..0B Z\o 7V K2PK 345.-/46 37-546258 R7I/5-2.1 ]5K71. `25K TT& w W
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32
Box 7
Tools for improving data collection
H".:>,&.(>02 F.@#>$) >.(" I0(&$.02 J&0(;- KHFIJL
U-'(-2 &4'/9+-4(&* .-8-+ 0&,-4'0/'-)2 /2* 8-'/+ 4'/'-4'-.4 H;T_AI 4c 3)0& 3/'&02/+ *&/'(4O 0&46&.'-8&+220.%& 0., M&-*".-& KIJ!ML
M' '(& (&/+'(S./0& 1/.-+-'< +&8&+O %FAT 4.."C0(>".-
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4)+7'-)24 *&+-8&0&* 8-/ 3)9-+& *&8-.&4 H3V&/+'( '))+4I '(/' .)22&.' 10)2'+-2& (&/+'( E)0K&04 ')
2/'-)2/+ (&/+'( 4H@S
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02-.R568 -.V6.R5 5K. R-252R46 /..0 V7- ?.55.- 0454 7/ 345.-/46 37-546258S *7M.-/3./51 4-. R466.0 IJ7/
57 .154?621K `.66 VI/R527/2/P "&$O 1815.31 `25K 4RRI-45. 455-2?I527/ 7V R4I1. 7V 0.45KS
E3J-7M.3./51 2/ 3.41I-.3./5 3I15 ?. 0-2M./ ?8 4R527/ 45 5K. R7I/5-8 6.M.6B `25K P7M.-/3./51
R-.452/P 1815.31 57 R4J5I-. 0454 1J.R2V2R 57 5K.2- 2/V7-34527/ /..01c 1815.31 5K45 3I15 4617 3..5
5K. 154/04-01 -.aI2-.0 V7- 2/5.-/4527/46 R73J4-4?26258S *67?4668B 154/04-02Y.0 3.5K701 V7-
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J-.M./52/P I/0.--.J7-52/P 1K7I60 ?. .154?621K.0 57 ./K4/R. 2/5.-/4527/46 R73J4-4?26258S
F2/4668B 0454 5K45 R4/ ?. 0214PP-.P45.0 57 .f432/. 5-./01 4/0 3.41I-. 5K. 37-546258 ?I-0./ `25K2/
5K. 3715 MI6/.-4?6. 4/0 3715 V-.aI./568 7M.-677H.0 J7JI64527/1 4-. R-252R46 V7- 23J6.3./52/P
15-45.P2.1 57 400-.11 2/.aI252.1 4/0 4RR.6.-45. J-7P-.11 57`4-01 345.-/46 37-546258 -.0IR527/S
(7JI64527/1 -.aI2-2/P J4-52RI64- 455./527/ 2/R6I0. -.VIP..1 4/0 P-7IJ1 5K45 V4R. 021R-232/4527/ 7-152P34S G.55.- 0454 7/ 5K. 345.-/46 37-546258 ?I-0./ 437/P 4076.1R./5 P2-61 21 4617 /..0.0c
345.-/46 R4I1.1 -4/H 1.R7/0 437/P R4I1.1 7V 0.45K V7- P2-61 4P.0 :>U:; >H?@S O.M.-46 R7I/5-2.1B
J4-52RI64-68 5K71. 2/ N452/ )3.-2R4 4/0 5K. "4-2??.4/B 4/0 2/ O7I5KQ%415 )124B K4M. 46-.408 ?.PI/
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0215I-?2/P V4R5 5K45 345.-/46 0.45K1 4-. 7RRI--2/P 437/P P2-61 .M./ 87I/P.- 5K4/ :>S
UJS ( )2,, %# 2)%1#$
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0&4&5&$)&'
:S h2QT77/ GS *67?46 15-45.P8 V7- `73./d1 4/0 RK260-./d1 K.465KS D.` n7-H ]Dn_9 C/25.0
D4527/1c =;Zj:j@A#xF&AxTOTx;\S::SJ0V B 4RR.11.0 >
D7M.3?.- =_S
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=_S
:=S @26375K gB T2Y7PIRK2 DB #.15.-P44-0 TB O48 NB T45K.-1 "B bI-.2RHQG-7`/ OB .5 46S N.M.61
4/0 5-./01 7V 345.-/46 37-546258 2/ 5K. `7-609 5K. 0.M.67J3./5 7V /.` .152345.1 ?8 5K. C/25.0
D4527/1S ,.RK/2R46 -.J7-5 ]1I?3255.0 57 5K. @A#B CDE"%FB CDF()B 4/0 ,K. @7-60 G4/H_S = D7M.3?.- =_S
=
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D7M.3?.- =_S
=ZS %6 )-2V../ OB A266 hB )K14/ hbB g4326 hB D4K4- ^B O5-.45V2.60 (hS T45.-/46 37-546258 2/
G4/P640.1K9 4 "7I/507`/ 57 = R7I/5-8 R41. 15I08S N4/R.5S =:_9:W\\QZXS
=[S D.J46 T2/215-8 7V A.465K 4/0 (7JI64527/ D.J46B (4-5/.-1K2J V7- T45.-/46B D.`?7-/ { "K260
A.465KB @7-60 A.465K #-P4/2Y4527/ ]@A#_B @7-60 G4/H 4/0 )6624/R. V7- A.465K (762R8 4/0 O815.31&.1.4-RKS OIRR.11 V4R57-1 V7- `73./y1 4/0 RK260-./y1 K.465K9 D.J46S *./.M49 @A#c =
]K55J9jj```S`K7S2/5jJ3/RKjH/7`6.0P.jJI?62R4527/1j/.J46xR7I/5-8x-.J7-5SJ0VB 4RR.11.0 >
D7M.3?.- =_S
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T4602M.19 =
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J0V B 4RR.11.0 > D7M.3?.- =_S
W;S T.K6 *B N4?-2aI. )S (-27-252Y2/P 2/5.P-45.0 3A.465K 15-45.P2.1 V7- I/2M.-146 K.465K
R7M.-4P.S OR2./R.S =]\=
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($$&B&'
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Annex 1. Summary of the country consultations 2015
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Annex 2. Measuring maternal mortality
Concepts and definitions
In the International statistical classification of diseases and related health problems, 10th revision
(ICD-10),1 WHO defines maternal death as:
The death of a woman while pregnant, or within 42 days of termination of pregnancy, irrespective of
the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy
or its management (from direct or indirect obstetric death), but not from accidental or incidental
causes.
This definition allows identification of maternal deaths, based on their causes, as either direct or
indirect. Direct maternal deaths are those resulting from obstetric complications of the pregnant
state (i.e. pregnancy, delivery and postpartum), interventions, omissions, incorrect treatment, or a
chain of events resulting from any of the above. Deaths due to, for example, obstetric
haemorrhage or hypertensive disorders in pregnancy, or those due to complications ofanaesthesia or caesarean section are classified as direct maternal deaths. Indirect maternal deaths
are those resulting from previously existing diseases, or from diseases that developed during
pregnancy and that were not due to direct obstetric causes but aggravated by physiological
effects of pregnancy. For example, deaths due to aggravation of an existing cardiac or renal
disease are considered indirect maternal deaths.
The concept of death during pregnancy, childbirth and the puerperium is included in the ICD-10
and is defined as any death temporal to pregnancy, childbirth or the postpartum period, even if it
is due to accidental or incidental causes (this was formerly referred to as “pregnancy-related
death”, see Box 1). This alternative definition allows measurement of deaths that are related to
pregnancy, even though they do not strictly conform to the standard “maternal death” concept, in
settings where accurate information about causes of death based on medical certificates is
unavailable.
For instance, in population-based surveys, respondents provide information on the pregnancy
status of a reproductive-aged sibling at the time of death, but no further information is elicited on
the cause of death. These surveys – for example, the Demographic and Health Surveys and
Multiple Indicator Cluster Surveys – therefore, usually provide measures of pregnancy-related
deaths rather than maternal deaths.
Further, complications of pregnancy or childbirth can lead to death beyond the six weeks
postpartum period, and the increased availability of modern life-sustaining procedures and
technologies enables more women to survive adverse outcomes of pregnancy and delivery, and to
delay death beyond 42 days postpartum. Despite being caused by pregnancy-related events,
these deaths do not count as maternal deaths in routine civil registration systems. Specific codes
for “late maternal deaths” are included in the ICD-10 (O96 and O97) to capture delayed maternal
deaths occurring between six weeks and one year postpartum (see Box A2.1). Some countries,
particularly those with more developed civil registration systems, use this definition.
1 International statistical classification of diseases and related health problems, tenth revision. Vol. 2: Instruction manual.
Geneva: World Health Organization; 2010.
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Box A2.1
Definitions related to maternal death in ICD-10
Maternal death
The death of a woman while pregnant or within 42 days of termination ofpregnancy, irrespective of the duration and site of the pregnancy, from any cause
related to or aggravated by the pregnancy or its management (from direct or
indirect obstetric death), but not from accidental or incidental causes.
Pregnancy-related death
The death of a woman while pregnant or within 42 days of termination of
pregnancy, irrespective of the cause of death.
Late maternal deathThe death of a woman from direct or indirect obstetric causes, more than 42 days,
but less than one year after termination of pregnancy.
Coding of maternal deaths
Despite the standard definitions noted above, accurate identification of the causes of maternal
deaths is not always possible. It can be a challenge for medical certifiers to correctly attribute
cause of death to direct or indirect maternal causes, or to accidental or incidental events,
particularly in settings where most deliveries occur at home. While several countries apply the ICD-
10 in civil registration systems, the identification and classification of causes of death during
pregnancy, childbirth and the puerperium remain inconsistent across countries.
With the publication of the ICD-10, WHO recommended adding a checkbox on the death
certificate for recording a woman’s pregnancy status at the time of death.2 This was to help
identify indirect maternal deaths, but it has not been implemented in many countries. For
countries using ICD-10 coding for registered deaths, all deaths coded to the maternal chapter (O
codes) and maternal tetanus (A34) are counted as maternal deaths.
In 2012, WHO published Application of ICD-10 to deaths during pregnancy, childbirth and the
puerperium: ICD maternal mortality (ICD-MM) to guide countries to reduce errors in coding
maternal deaths and to improve the attribution of cause of maternal death.3 The ICD-MM is to beused together with the three ICD-10 volumes. For example, the ICD-MM clarifies that the coding of
maternal deaths among HIV-positive women may be due to one of the following.
• Obstetric causes: Such as haemorrhage or hypertensive disorders in pregnancy – these should
be identified as direct maternal deaths.
• The interaction between human immunodeficiency virus (HIV) and pregnancy : In these cases,
there is an aggravating effect of pregnancy on HIV and the interaction between pregnancy
2 International statistical classification of diseases and related health problems, tenth revision. Vol. 2: Instruction manual.
Geneva: World Health Organization; 2010.
3 Application of ICD-10 to deaths during pregnancy, childbirth and the puerperium: ICD maternal mortality (ICD-MM).
Geneva: World Health Organization; 2012.
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and HIV is the underlying cause of death. These deaths are considered as indirect maternal
deaths. In this report, they are referred to as “AIDS-related indirect maternal deaths”, and in the
ICD those deaths are coded to O98.7 and categorized in Group 7 (non-obstetric complications)
in the ICD-MM.
• Acquired immunodeficiency syndrome ( AIDS): In these cases, the woman’s pregnancy status is
incidental to the course of her HIV infection and her death is a result of an HIV complication, as
described by ICD-10 codes B20–24. These are not considered maternal deaths. Thus, proper
reporting of the mutual influence of HIV or AIDS and pregnancy in Part 1 of the death
certificate will facilitate the coding and identification of these deaths.
Measures of maternal mortality
The extent of maternal mortality in a population is essentially the combination of two factors:
(i) The risk of death in a single pregnancy or a single live birth.
(ii) The fertility level (i.e. the number of pregnancies or births that are experienced by women ofreproductive age).
The MMR is defined as the number of maternal deaths during a given time period per 100 000 live
births during the same time period. It depicts the risk of maternal death relative to the number of
live births and essentially captures (i) above.
By contrast, the maternal mortality rate (MMRate) is defined as the number of maternal deaths in a
population divided by the number of women aged 15–49 years (or woman-years lived at ages 15–
49 years). The MMRate captures both the risk of maternal death per pregnancy or per total birth
(live birth or stillbirth), and the level of fertility in the population. In addition to the MMR and the
MMRate, it is possible to calculate the adult lifetime risk of maternal mortality for women in the
population (see Box A2). An alternative measure of maternal mortality, the proportion of maternal
deaths among deaths of women of reproductive age (PM), is calculated as the number of maternal
deaths divided by the total deaths among women aged 15–49 years.
Box A2.2
Statistical measures of maternal mortality
Maternal mortality ratio (MMR)
Number of maternal deaths during a given time period per 100 000 live births during the
same time period.
Maternal mortality rate (MMRate)
Number of maternal deaths divided by person-years lived by women of reproductive age.4
4 Wilmoth J, Mizoguchi N, Oestergaard M, Say L, Mathers C, Zureick-Brown S, et al. A new method for deriving global
estimates of maternal mortality: supplemental report. Stat Politics Policy. 2012;3(2):1–38.
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Box A2.2
Statistical measures of maternal mortality
Adult lifetime risk of maternal death
The probability that a 15-year-old woman will die eventually from a maternal cause.
The proportion of maternal deaths among deaths of women of reproductive age (PM)
The number of maternal deaths in a given time period divided by the total deaths among
women aged 15–49 years.
Approaches for measuring maternal mortality
Ideally, civil registration systems with good attribution of cause of death provide accurate data on
the level of maternal mortality and the causes of maternal deaths. In countries with incomplete
civil registration systems, it is difficult to accurately measure levels of maternal mortality. First, it is
challenging to identify maternal deaths precisely, as the deaths of women of reproductive age
might not be recorded at all. Second, even if such deaths were recorded, the pregnancy status or
cause of death may not have been known and the deaths would therefore not have been reported
as maternal deaths. Third, in most developing-country settings where medical certification of
cause of death does not exist, accurate attribution of a female death as a maternal death is
difficult.
Even in developed countries where routine registration of deaths is in place, maternal deaths may
be underreported due to misclassification of ICD-10 coding, and identification of the true numbersof maternal deaths may require additional special investigations into the causes of death. A
specific example of such an investigation is the Confidential Enquiry into Maternal Deaths (CEMD),
a system established in England and Wales in 1928.5,6,7 The most recent report of the CEMD (for
2009–2011) identified 79% more maternal deaths than were reported in the routine civil
registration system.8 Other studies on the accuracy of the number of maternal deaths reported in
civil registration systems have shown that the true number of maternal deaths could be twice as
high as indicated by routine reports, or even more.9,10 Annex 6 summarizes the results of a
5 Lewis G, editor. Why mothers die 2000–2002: the confidential enquiries into maternal deaths in the United Kingdom.
London: RCOG Press; 2004.
6 Lewis G, editor. Saving mothers’ lives: reviewing maternal deaths to make motherhood safer 2003–2005. The seventh
report on confidential enquiries into maternal deaths in the United Kingdom. London: Confidential Enquiry into
Maternal and Child Health (CEMAH); 2007.
7 Centre for Maternal and Child Enquiries (CMACE). Saving mothers’ lives: reviewing maternal deaths to make
motherhood safer: 2006–2008. The eighth report on confidential enquiries into maternal deaths in the United Kingdom.
BJOG. 2011;118(Suppl.1):1–203. doi:10.1111/j.1471-0528.2010.02847.x.
8 Knight M, Kenyon S, Brocklehurst P, Neilson J, Shakespeare J, Kurinczuk JJ, editors (on behalf of MBRRACE-UK). Saving
lives, improving mothers’ care – lessons learned to inform future maternity care from the UK and Ireland Confidential
Enquiries into Maternal Deaths and Morbidity 2009–12. Oxford: National Perinatal Epidemiology Unit, University of
Oxford; 2014.
9 Deneux-Tharaux C et al. Underreporting of pregnancy-related mortality in the United States and Europe. Obstet
Gynecol. 2005;106:684–92.
10 Atrash HK, Alexander S, Berg CJ. Maternal mortality in developed countries: not just a concern of the past. Obstet
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literature review (updated January 2014) for such studies where misclassification on coding in civil
registration could be identified.
These studies are diverse in terms of the definition of maternal mortality used, the sources
considered (death certificates, other vital event certificates, medical records, questionnaires or
autopsy reports) and the way maternal deaths are identified (record linkage or assessment fromexperts). In addition, the system of reporting causes of death to a civil registry differs from one
country to another, depending on the death certificate forms, the type of certifiers and the coding
practice. These studies have estimated underreporting of maternal mortality due to
misclassification in death registration data, ranging from 0.85 to 5.0, with a median value of 1.5 (i.e.
a misclassification rate of 50%).
Underreporting of maternal deaths was more common among:
• early pregnancy deaths, including those not linked to a reportable birth outcome;
• deaths in the later postpartum period (these were less likely to be reported than early
postpartum deaths);
• deaths at extremes of maternal age (youngest and oldest);
• miscoding by the ICD-9 or ICD-10, most often seen in cases of deaths caused by:
o cerebrovascular diseases;
o cardiovascular diseases.
Potential reasons cited for underreporting and/or misclassification include:
• inadequate understanding of the ICD rules (either ICD-9 or ICD-10);
• death certificates completed without mention of pregnancy status;
• desire to avoid litigation;
• desire to suppress information (especially as related to abortion deaths).
The definitions of misclassification, incompleteness and underreporting of maternal deaths areshown in Box A2.3.
Box A2.3
Definitions of misclassification, incompleteness and underreporting
Misclassification
Refers to incorrect coding in civil registration, due either to error in the medical certification
of cause of death or error in applying the correct code.
Incompleteness
Refers to incomplete death registration. Includes both the identification of individual deaths
in each country and the national coverage of the register.
Gynecol. 1995;86(4 pt 2):700–5.
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Box A2.4
Approaches to measuring maternal mortality
period approximately five years prior to the survey); the analysis is more complicated.
Census14,15
A national census, with the addition of a limited number of questions, could produce estimates of
maternal mortality. This approach eliminates sampling errors (because all women are covered)
and hence allows a more detailed breakdown of the results, including trend analysis, geographic
subdivisions and social strata.
• This approach allows identification of deaths in the household in a relatively short reference
period (1–2 years), thereby providing recent maternal mortality estimates, but is conducted at
10-year intervals and therefore limits monitoring of maternal mortality.
• It identifies pregnancy-related deaths (not maternal deaths); however, if combined with
verbal autopsy, maternal deaths could be identified.
• Training of enumerators is crucial, since census activities collect information on a range of
other topics unrelated to maternal deaths.
• Results must be adjusted for characteristics such as completeness of death and birth
statistics and population structures, in order to arrive at reliable estimates.
Reproductive-age mortality studies (RAMOS)11,12
This approach involves identifying and investigating the causes of all deaths of women of
reproductive age in a defined area or population, by using multiple sources of data (e.g.
interviews of family members, civil registrations, health-care facility records, burial records,
traditional birth attendants), and has the following characteristics.
• Multiple and diverse sources of information must be used to identify deaths of women of
reproductive age; no single source identifies all the deaths.
• Interviews with household members and health-care providers and reviews of facility records
are used to classify the deaths as maternal or otherwise.
• If properly conducted, this approach provides a fairly complete estimation of maternal
mortality (in the absence of reliable routine registration systems) and could provide
subnational MMRs. However, inadequate identification of all deaths of reproductive-aged
women results in underestimation of maternal mortality levels.
• This approach can be complicated, time-consuming and expensive to undertake –
particularly on a large scale.
• The number of live births used in the computation may not be accurate, especially in settings
where most women deliver at home.
14 Stanton C et al. Every death counts: measurement of maternal mortality via a census. Bull World Health Organ.
2001;79:657–64.15 WHO guidance for measuring maternal mortality from a census. Geneva: World Health Organization; 2013.
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Box A2.4
Approaches to measuring maternal mortality
Verbal autopsy16,17,18
This approach is used to assign cause of death through interviews with family or communitymembers, where medical certification of cause of death is not available. Verbal autopsies may be
conducted as part of a demographic surveillance system maintained by research institutions that
collect records of births and deaths periodically among small populations (typically in a district).
This approach may also be combined with household surveys or censuses. In special versions,
and in combination with software that helps to identify the diagnosis, verbal autopsy is suitable
for routine use as an inexpensive method in populations where no other method of assessing the
cause of death is in place. The following limitations characterize this approach.
• Misclassification of causes of deaths in women of reproductive age is not uncommon with
this technique.
• It may fail to identify correctly a group of maternal deaths, particularly those occurring early in
pregnancy (e.g. ectopic, abortion-related) and indirect causes of maternal death (e.g.
malaria).
• The accuracy of the estimates depends on the extent of family members’ knowledge of the
events leading to the death, the skill of the interviewers, and the competence of physicians
who do the diagnosis and coding. The latter two factors are largely overcome by the use of
software.
• Detailed verbal autopsy for research purposes that aims to identify the cause of death of an
individual requires physician assessment and long interviews. Such systems are expensive
to maintain, and the findings cannot be extrapolated to obtain national MMRs. This limitation
does not exist where simplified verbal autopsy is aiming to identify causes at a population
level and where software helps to formulate the diagnoses.
16 Chandramohan D et al. The validity of verbal autopsies for assessing the causes of institutional maternal death. Stud
Fam Plann. 1998;29:414–22.
17 Chandramohan D, Stetal P, Quigley M. Misclassification error in verbal autopsy: can it be adjusted? Int J Epidemiol.
2001;30:509–14.
18 Leitao J et al. Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring. Global
Health Action. 2013;6:21518.
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Annex 3. Methods used to derive a complete series of annual
estimates for each covariate, 1985–2015
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19 GDP per capita measured in purchasing power parity (PPP) equivalent dollars, reported as constant 2011 international
dollars, based on estimates published by World Bank Group. International Comparison Program database. Washington
(DC): World Bank Group; 2014.
20 World population prospects: the 2015 revision. New York: United Nations, Department of Economic and Social Affairs,
Population Division; 2015.
21 UNICEF Data: Monitoring the Situation of Children and Women [website]. New York: United Nations Children’s Fund;
2015 (http://data.unicef.org/).
22 Making pregnancy safer: the critical role of the skilled attendant: a joint statement by WHO, ICM and FIGO. Geneva:
World Health Organization; 2014.
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Annex 4. Adjustment factor to account for misclassification of
maternal deaths in civil registration, literature review of
reports and articles
Country Period/year Adjustment factor
Australiaa 1994–1996 1.23
Australiab 1997–1999 1.80
Australiac 2000–2002 1.97
Australiad 2003–2005 2.03
Austriae 1980–1998 1.61
Brazilf 2002 1.40
Canadag 1988–1992 1.69
Canadah 1997–2000 1.52
Denmark i 1985–1994 1.94
Denmark j 2002–2006 1.04
Finlandk 1987–1994 0.94
Francel Dec 1988 to
March 1989
2.38
Francem 1999 1.29
Francen 2001–2006 1.21
Franceo 2007–2009 1.21
Guatemalap 1989 1.84
Guatemalap 1996–1998 1.84
Guatemalaq 2000 1.88
Guatemalar
2007 1.73
Irelands 2009–2011 3.40
Japant 2005 1.35
Mexicou 2008 0.99
Netherlandsv 1983–1992 1.34
Netherlandsx 1993–2005 1.48
New Zealandy 2006 1.11
New Zealandz
2007 0.85
New Zealandaa 2008 1.00
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Country Period/year Adjustment factor
New Zealandbb 2009 0.92
New Zealandcc 2010 1.00
Portugaldd 2001–2007 2.04
Serbiaee 2007–2010 1.86
Singaporeff 1990–1999 1.79
Sloveniagg 2003–2005 5.00
South Africahh 1999–2001 0.98
South Africaii 2002–2004 1.16
South Africaii 2005–2007 0.90
Sweden jj 1997–2005 1.33
Swedenkk 1988–2007 1.68
United Kingdomll 1988–1990 1.39
United Kingdomll 1991–1993 1.52
United Kingdomll 1994–1996 1.64
United Kingdomll 1997–1999 1.77
United Kingdomll 2000–2002 1.80
United Kingdomll 2003–2005 1.86
United Kingdomll 2006–2008 1.60
United Statesmm 1991–1997 1.48
United Statesnn 1995–1997 1.54
United Statesoo 1999–2002 1.59
United Statesoo 2003–2005 1.41
Median 1.5
a AIHW, NHMRC. Report on maternal deaths in Australia 1994–96. Cat. no. PER 17. Canberra: AIHW; 2001 ().
b Slaytor EK, Sullivan EA, King JF. Maternal deaths in Australia 1997–1999. Cat. No. PER 24. Sydney: AIHW National
Perinatal Statistics Unit; 2004 (Maternal Deaths Series, No. 1).
c Sullivan EA, King JF, editors. Maternal deaths in Australia 2000–2002. Cat. no. PER 32. Sydney: AIHW National
Perinatal Statistics Unit; 2006 (Maternal Deaths Series, No. 2).
d Sullivan EA, Hall B, King JF. Maternal deaths in Australia 2003–2005. Cat. no. PER 42. Sydney: AIHW National
Perinatal Statistics Unit; 2007 (Maternal Deaths Series, No. 3).
e Johnson S, Bonello MR, Li Z, Hilder L, Sullivan EA. Maternal deaths in Australia 2006–2010. Cat. no. PER 61. Canberra:
AIHW; 2014 (Maternal Deaths Series, No. 4).
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f Brasil Ministério da Saúde, Secretaria de Atenção à Saúde, Departamento de Ações Programáticas Estratégicas. Estudo da
mortalidade de mulheres de 10 a 49 anos, com ênfase na mortalidade materna: relatório final. Brasilia: Ministério da Saúde,
Secretaria de Atenção à Saúde, Departamento de Ações Programáticas Estratégicas, Editora do Ministério da Saúde; 2006.
g Turner LA et al. Underreporting of maternal mortality in Canada: a question of definition. Chronic Dis Can. 2002;23:22–
30.
h Health Canada. Special report on maternal mortality and severe morbidity in Canada – enhanced surveillance: the path to
prevention. Ottawa: Minister of Public Works and Government Services Canada; 2004.
i Andersen BR et al. Maternal mortality in Denmark 1985–1994. Eur J Obstet Gynecol Reprod Biol. 2009;42:124–8.
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k Gissler M et al. Pregnancy-associated deaths in Finland 1987–1994 definition problems and benefits of record linkage.
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Annex 5. Usability assessment of civil registration data for
selected years (1990, 1995, 2000, 2005, 2010 and latest
available year)
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