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SDG Metadata / 3-1-1French

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SDG Metadata / 3-1-1French

<h1>Methodology</h1>
<h2>Computation method:</h2>
<p>The maternal mortality ratio can be calculated by dividing recorded (or estimated) maternal deaths by total recorded (or estimated) live births in the same period and multiplying by 100 000. Measurement requires information on pregnancy status, timing of death (during pregnancy, childbirth, or within 42 days of termination of pregnancy), and cause of death.</p>
<p>The maternal mortality ratio can be calculated directly from data collected through vital registration systems, household surveys or other sources. There are often data quality problems, particularly related to the underreporting and misclassification of maternal deaths. Therefore, data are often adjusted in order to take these data quality issues into account. Some countries undertake these adjustments or corrections as part of specialized/confidential enquiries or administrative efforts embedded within maternal mortality monitoring programmes.</p>
<p><strong>Bayesian maternal mortality estimation model (the BMat model):</strong></p>
<p>Estimation and projection of maternal mortality indicators are undertaken using the BMat model. This model is intended to ensure that the MMR estimation approach is consistent across all countries but remains flexible in that it is based on covariate-driven trends to inform estimates in countries or country-periods with limited information; captures observed trends in countries with longer time series of observations; and takes into account the differences in stochastic and sampling errors across observations.</p>
<p>The model is summarized as follows:</p>
<p><img src="data:image/png;base64,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"></p>
<p>where </p>
<p><em>EPM<sup>NA</sup></em>= the expected proportion of non-HIV-related deaths to women aged 15&#x2013;49 years that are due to maternal causes [NA = non-HIV; formerly it referred to &#x201C;non-AIDS&#x201D;]</p>
<p><em>GDP </em>= gross domestic product per capita (in 2011 PPP US dollars)</p>
<p><em>GFR </em>= general fertility rate (live births per woman aged 15&#x2013;49 years)</p>
<p><em>SBA </em>= proportion of births attended by skilled health personnel</p>
<p><em>&#x3B3;<sub>j</sub></em>= random intercept term for country j</p>
<p>&#x3D5;<sub>k</sub> = random intercept term for region k.</p>
<p>For countries with data available on maternal mortality, the expected proportion of non-HIV-related maternal deaths was based on country and regional random effects, whereas for countries with no data available, predictions were derived using regional random effects only. </p>
<p>The resulting estimates of the <em>EPM<sup>NA </sup></em>were used to obtain the expected non-HIV MMR through the following relationship:</p>
<p>Expected non-HIV MMR =EPM<sup>NA</sup>*(1-a)*E/B</p>
<p>where</p>
<p>a = the proportion of HIV-related deaths among all deaths to women aged 15&#x2013;49 years</p>
<p>E = the total number of deaths to women of reproductive age</p>
<p>B = the number of births.</p>
<p>Estimation of HIV-related indirect maternal deaths:</p>
<p>For countries with generalized HIV epidemics and high HIV prevalence, HIV/AIDS is a leading cause of death during pregnancy and post-delivery. There is also some evidence from community studies that women with HIV infection have a higher risk of maternal death, although this may be offset by lower fertility. If HIV is prevalent, there will also be more incidental HIV deaths among pregnant and postpartum women. When estimating maternal mortality in these countries, it is, thus, important to differentiate between incidental HIV deaths (non-maternal deaths) and HIV-related indirect maternal deaths (maternal deaths caused by the aggravating effects of pregnancy on HIV) among HIV-positive pregnant and postpartum women who have died (i.e. among all HIV-related deaths occurring during pregnancy, childbirth and puerperium).</p>
<p>The number of HIV-related indirect<strong><em> </em></strong>maternal deaths, <em>D<sup>HIV</sup>, </em>is estimated by:</p>
<p><em>D<sup>HIV </sup>= a * E * v * u</em></p>
<p>Where</p>
<p><em>a*E</em> = the total number of HIV-related deaths among all deaths to women aged 15&#x2013;49.</p>
<p><em>v = </em>is the proportion of HIV-related deaths to women aged 15&#x2013;49 that occur during pregnancy. The value of <em>v </em>can be computed as follows: <em>v&#xA0;</em>=&#xA0;<em>c k GFR / [</em>1 + <em>c</em>(<em>k-</em>1) <em>GFR] </em>where<strong> </strong>GFR is the general fertility rate, and where<em> c </em>is the average exposure time (in years) to the risk of pregnancy-related mortality per live birth (set equal to 1 for this analysis), and where <em>k </em>is the relative risk of dying from AIDS for a pregnant versus a non-pregnant woman (reflecting both the decreased fertility of HIV-positive women and the increased mortality risk of HIV-positive pregnant women). The value of k was set at 0.3.</p>
<p>u = is the fraction of pregnancy-related AIDS deaths assumed to be indirect maternal deaths. The UN&#xA0;MMEIG/TAG reviewed available study data on AIDS deaths among pregnant women and recommended using <em>u&#xA0;=&#xA0;</em>0.3.</p>
<p>For observed PMs, we assumed that the total reported maternal deaths are a combination of the proportion of reported non-HIV-related maternal deaths and the proportion of reported HIV-related (indirect) maternal deaths, where the latter is given by <em>a*v</em> for observations with a &#x201C;pregnancy-related death&#x201D; definition and <em>a*v*u</em> for observations with a &#x201C;maternal death&#x201D; definition.</p>
<h1>Méthodologie</h1>
<h2>Méthode de calcul :</h2>
<p>Le taux de mortalité maternelle peut être calculé en divisant les décès maternels enregistrés (ou estimés) par le total des naissances vivantes enregistrées (ou estimées) au cours de la même période et en multipliant par 100 000. La mesure exige de l’information sur l’état de la grossesse, le moment du décès (pendant la grossesse, l’accouchement ou dans les 42 jours suivant l’interruption de grossesse) et la cause du décès.</p>
<p> le taux de mortalité maternelle peut être calculé directement à partir des données recueillies au moyen de systèmes d’enregistrement vitaux, d’enquêtes auprès des ménages ou d’autres sources. Il y a souvent des problèmes de qualité des données, en particulier liés à la sous-déclaration et à la classification erronée des décès maternels. Par conséquent, les données sont souvent ajustées afin de tenir compte de ces problèmes de qualité des données. Certains pays entreprennent ces ajustements ou corrections dans le cadre d’enquêtes spécialisées/confidentielles ou d’efforts administratifs intégrés aux programmes de surveillance de la mortalité </p> maternelle.
<p><strong> modèle d’estimation de la mortalité maternelle bayésienne (le modèle BMat): </strong></p>
<p> Estimation et projection des indicateurs de mortalité maternelle sont entreprises à l’aide du modèle BMat. Ce modèle vise à s’assurer que l’approche d’estimation du RMM est uniforme dans tous les pays, mais qu’elle demeure souple en ce qu’elle est fondée sur des tendances axées sur la covariation afin d’éclairer les estimations dans les pays ou les pays dont l’information est limitée; capture les tendances observées dans les pays où les séries d’observations sont plus longues; et tient compte des différences dans les erreurs stochastiques et d’échantillonnage entre </p> les observations.
<p>Le modèle est résumé comme suit: </p>
<p><img
a month ago
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SDG Metadata / 3-1-1French

<p>Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births</p>
<p>Cible 3.1: D’ici à 2030, faire passer le taux mondial de mortalité maternelle au-dessous de 70 pour 100 000 naissances vivantes</p>
a month ago
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SDG Metadata / 3-1-1French

<p>Goal 3: Ensure healthy lives and promote well-being for all at all ages</p>
<p>Objectif 3: Permettre à tous de vivre en bonne santé et promouvoir le bien-être de tous à tout âge</p>
a month ago
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SDG Metadata / 3-1-1French

<h2>Comments and limitations:</h2>
<p>The extent of maternal mortality in a population is essentially the combination of two factors:</p>
<p>i. The risk of death in a single pregnancy or a single live birth.</p>
<p>ii. The fertility level (i.e. the number of pregnancies or births that are experienced by women of reproductive age).</p>
<p>The maternal mortality ratio (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.</p>
<p>By contrast, the maternal mortality rate (MMRate) is calculated as the number of maternal deaths divided by person-years lived by women of reproductive age. 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. An alternative measure of maternal mortality, the proportion of deaths among women of reproductive age that are due to maternal causes (PM), is calculated as the number of maternal deaths divided by the total deaths among women aged 15&#x2013;49 years.</p>
<p><strong>Related statistical measures of maternal mortality:</strong></p>
<p>Maternal mortality ratio (MMR): Number of maternal deaths during a given time period per 100,000 live births during the same time period.</p>
<p>Maternal mortality rate (MMRate): Number of maternal deaths divided by person-years lived by women of reproductive age.</p>
<p>Adult lifetime risk of maternal death: The probability that a 15-year-old woman will die eventually from a maternal cause.</p>
<p>The proportion of deaths among women of reproductive age that are due to maternal causes (PM): The number of maternal deaths in a given time period divided by the total deaths among women aged 15&#x2013;49 years.</p>
<h2>Commentaires et limitations : </h2>
<p> L'ampleur de la mortalité maternelle dans une population est essentiellement la combinaison de deux facteurs :</p>
<p>i. Le risque de décès lors d'une seule grossesse ou d'une seule naissance vivante. </p>
<p>ii. Le niveau de fertilité (c'est-à-dire le nombre de grossesses ou de naissances que connaissent les femmes en âge de procréer). </p>
<p>Le taux de mortalité maternelle (TMM) est défini comme le nombre de décès maternels pendant une période donnée pour 100 000 naissances vivantes au cours de la même période. Il décrit le risque de décès maternel par rapport au nombre de naissances vivantes et reprend essentiellement le point (i) ci-dessus.</p>
<p>En revanche, le taux de mortalité maternelle (MMRate) est calculé comme le nombre de décès maternels divisé par les années-personnes vécues par les femmes en âge de procréer. Le taux de mortalité maternelle saisit à la fois le risque de décès maternel par grossesse ou par naissance totale (naissance vivante ou mortinaissance) et le niveau de fertilité de la population. En plus du TMM et du taux de mortalité maternelle, il est possible de calculer le risque de mortalité maternelle des femmes de la population pendant leur vie adulte. Une autre mesure de la mortalité maternelle, la proportion de décès chez les femmes en âge de procréer qui sont dus à des causes maternelles (MP), est calculée comme le nombre de décès maternels divisé par le total des décès chez les femmes âgées de 15 &#x2013;49 ans. </p>
<p><strong>Mesures statistiques connexes de la mortalité maternelle : </strong></p>
<p>Taux de mortalité maternelle (TMM) : Nombre de décès maternels au cours d'une période donnée pour 100 000 naissances vivantes au cours de la même période. </p>
<p>Taux de mortalité maternelle (MMRate) : Nombre de décès maternels divisé par le nombre d'années-personnes vécues par les femmes en âge de procréer. </p>
<p>Risque de décès maternel au cours de la vie d'un adulte : La probabilité qu'une femme de 15 ans meure éventuellement d'une cause maternelle. </p>
<p>Proportion de décès de femmes en âge de procréer qui sont dus à des causes maternelles (PM) : Le nombre de décès maternels au cours d'une période donnée divisé par le nombre total de décès chez les femmes âgées de 15 ans &#x2013;49 ans. </p>
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SDG Metadata / 3-1-1French

<h1>Methodology</h1>
<h2>Computation method:</h2>
<p>The maternal mortality ratio can be calculated by dividing recorded (or estimated) maternal deaths by total recorded (or estimated) live births in the same period and multiplying by 100 000. Measurement requires information on pregnancy status, timing of death (during pregnancy, childbirth, or within 42 days of termination of pregnancy), and cause of death.</p>
<p>The maternal mortality ratio can be calculated directly from data collected through vital registration systems, household surveys or other sources. There are often data quality problems, particularly related to the underreporting and misclassification of maternal deaths. Therefore, data are often adjusted in order to take these data quality issues into account. Some countries undertake these adjustments or corrections as part of specialized/confidential enquiries or administrative efforts embedded within maternal mortality monitoring programmes.</p>
<p><strong>Bayesian maternal mortality estimation model (the BMat model):</strong></p>
<p>Estimation and projection of maternal mortality indicators are undertaken using the BMat model. This model is intended to ensure that the MMR estimation approach is consistent across all countries but remains flexible in that it is based on covariate-driven trends to inform estimates in countries or country-periods with limited information; captures observed trends in countries with longer time series of observations; and takes into account the differences in stochastic and sampling errors across observations.</p>
<p>The model is summarized as follows:</p>
<p><img src="data:image/png;base64,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"></p>
<p>where </p>
<p><em>EPM<sup>NA</sup></em>= the expected proportion of non-HIV-related deaths to women aged 15&#x2013;49 years that are due to maternal causes [NA = non-HIV; formerly it referred to &#x201C;non-AIDS&#x201D;]</p>
<p><em>GDP </em>= gross domestic product per capita (in 2011 PPP US dollars)</p>
<p><em>GFR </em>= general fertility rate (live births per woman aged 15&#x2013;49 years)</p>
<p><em>SBA </em>= proportion of births attended by skilled health personnel</p>
<p><em>&#x3B3;<sub>j</sub></em>= random intercept term for country j</p>
<p>&#x3D5;<sub>k</sub> = random intercept term for region k.</p>
<p>For countries with data available on maternal mortality, the expected proportion of non-HIV-related maternal deaths was based on country and regional random effects, whereas for countries with no data available, predictions were derived using regional random effects only. </p>
<p>The resulting estimates of the <em>EPM<sup>NA </sup></em>were used to obtain the expected non-HIV MMR through the following relationship:</p>
<p>Expected non-HIV MMR =EPM<sup>NA</sup>*(1-a)*E/B</p>
<p>where</p>
<p>a = the proportion of HIV-related deaths among all deaths to women aged 15&#x2013;49 years</p>
<p>E = the total number of deaths to women of reproductive age</p>
<p>B = the number of births.</p>
<p>Estimation of HIV-related indirect maternal deaths:</p>
<p>For countries with generalized HIV epidemics and high HIV prevalence, HIV/AIDS is a leading cause of death during pregnancy and post-delivery. There is also some evidence from community studies that women with HIV infection have a higher risk of maternal death, although this may be offset by lower fertility. If HIV is prevalent, there will also be more incidental HIV deaths among pregnant and postpartum women. When estimating maternal mortality in these countries, it is, thus, important to differentiate between incidental HIV deaths (non-maternal deaths) and HIV-related indirect maternal deaths (maternal deaths caused by the aggravating effects of pregnancy on HIV) among HIV-positive pregnant and postpartum women who have died (i.e. among all HIV-related deaths occurring during pregnancy, childbirth and puerperium).</p>
<p>The number of HIV-related indirect<strong><em> </em></strong>maternal deaths, <em>D<sup>HIV</sup>, </em>is estimated by:</p>
<p><em>D<sup>HIV </sup>= a * E * v * u</em></p>
<p>Where</p>
<p><em>a*E</em> = the total number of HIV-related deaths among all deaths to women aged 15&#x2013;49.</p>
<p><em>v = </em>is the proportion of HIV-related deaths to women aged 15&#x2013;49 that occur during pregnancy. The value of <em>v </em>can be computed as follows: <em>v&#xA0;</em>=&#xA0;<em>c k GFR / [</em>1 + <em>c</em>(<em>k-</em>1) <em>GFR] </em>where<strong> </strong>GFR is the general fertility rate, and where<em> c </em>is the average exposure time (in years) to the risk of pregnancy-related mortality per live birth (set equal to 1 for this analysis), and where <em>k </em>is the relative risk of dying from AIDS for a pregnant versus a non-pregnant woman (reflecting both the decreased fertility of HIV-positive women and the increased mortality risk of HIV-positive pregnant women). The value of k was set at 0.3.</p>
<p>u = is the fraction of pregnancy-related AIDS deaths assumed to be indirect maternal deaths. The UN&#xA0;MMEIG/TAG reviewed available study data on AIDS deaths among pregnant women and recommended using <em>u&#xA0;=&#xA0;</em>0.3.</p>
<p>For observed PMs, we assumed that the total reported maternal deaths are a combination of the proportion of reported non-HIV-related maternal deaths and the proportion of reported HIV-related (indirect) maternal deaths, where the latter is given by <em>a*v</em> for observations with a &#x201C;pregnancy-related death&#x201D; definition and <em>a*v*u</em> for observations with a &#x201C;maternal death&#x201D; definition.</p>
<h1>Méthodologie</h1>
<h2>Méthode de calcul :</h2>
<p>Le taux de mortalité maternelle peut être calculé en divisant les décès maternels enregistrés (ou estimés) par le total des naissances vivantes enregistrées (ou estimées) au cours de la même période et en multipliant par 100 000. La mesure exige de l’information sur l’état de la grossesse, le moment du décès (pendant la grossesse, l’accouchement ou dans les 42 jours suivant l’interruption de grossesse) et la cause du décès.</p>
<p> le taux de mortalité maternelle peut être calculé directement à partir des données recueillies au moyen de systèmes d’enregistrement vitaux, d’enquêtes auprès des ménages ou d’autres sources. Il y a souvent des problèmes de qualité des données, en particulier liés à la sous-déclaration et à la classification erronée des décès maternels. Par conséquent, les données sont souvent ajustées afin de tenir compte de ces problèmes de qualité des données. Certains pays entreprennent ces ajustements ou corrections dans le cadre d’enquêtes spécialisées/confidentielles ou d’efforts administratifs intégrés aux programmes de surveillance de la mortalité </p> maternelle.
<p><strong> modèle d’estimation de la mortalité maternelle bayésienne (le modèle BMat): </strong></p>
<p> Estimation et projection des indicateurs de mortalité maternelle sont entreprises à l’aide du modèle BMat. Ce modèle vise à s’assurer que l’approche d’estimation du RMM est uniforme dans tous les pays, mais qu’elle demeure souple en ce qu’elle est fondée sur des tendances axées sur la covariation afin d’éclairer les estimations dans les pays ou les pays dont l’information est limitée; capture les tendances observées dans les pays où les séries d’observations sont plus longues; et tient compte des différences dans les erreurs stochastiques et d’échantillonnage entre </p> les observations.
<p>Le modèle est résumé comme suit: </p>
<p><img
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je n'ai pas de suggestions automatiques de trraduction complètent pour celui-ci... seulement une section du texte est traduit avec l'option source microsoft translator

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<p>Indicator 3.1.1: Maternal mortality ratio</p>
<p>Indicateur 3.1.1: Taux de mortalité maternelle</p>
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<h1>References</h1>
<h2>URL:</h2>
<p><a href="https://www.who.int/reproductivehealth/publications/maternal-mortality-2000-2017/en/">https://www.who.int/reproductivehealth/publications/maternal-mortality-2000-2017/en/</a></p>
<h2>References:</h2>
<p>(1) World Health Organization (WHO), United Nations Children&#x2019;s Fund (UNICEF), United Nations Population Fund (UNFPA), World Bank Group, United Nations Population Division. Trends in maternal mortality: 2000 to 2017: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2019 </p>
<p>(2) Peterson E, Chou D, Gemmill A, Moller AB, Say L, Alkema L. Estimating maternal mortality using vital registration data: a Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity of reporting for population-periods without validation data. 2019 (<a href="https://arxiv.org/abs/1909.08578">https://arxiv.org/abs/1909.08578</a>).</p>
<h1>Références</h1>
<h2>URL : </h2>
<p><a href="https://www.who.int/reproductivehealth/publications/maternal-mortality-2000-2017/en/">https://www.who.int/reproductivehealth/publications/maternal-mortality-2000-2017/en/</a></p>
<h2>Références:</h2>
<p>(1) Organisation mondiale de la santé (OMS), Fonds des Nations unies pour l'enfance (UNICEF), Fonds des Nations unies pour la population (FNUAP), Groupe de la Banque mondiale, Division de la population des Nations unies. Tendances de la mortalité maternelle : 2000 à 2017 : estimations de l'OMS, de l'UNICEF, du FNUAP, du Groupe de la Banque mondiale et de la Division de la population des Nations unies. Genève : Organisation mondiale de la santé ; 2019 </p>
<p>(2) Peterson E, Chou D, Gemmill A, Moller AB, Say L, Alkema L. Estimating maternal mortality using vital registration data : a Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity of reporting for population-periods without validation data. 2019 (<a href="https://arxiv.org/abs/1909.08578">https://arxiv.org/abs/1909.08578</a>).</p>
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vérifier acronyms: MMEIG, PM, UNPD et WPP

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