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Objectives. To present a methodology for the simultaneous setting of quantitative targets that reflect both an improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in its geographic inequality. Methods. A five-step algorithm was developed: (a) calculate the national average annual percent change (AAPC) for an SDG3 indicator; (b) normatively define geographic strata from the subnational distribution of the indicator in a baseline year; (c) apply a proportional progressivity criterion to the AAPC to project the stratum-specific indicator value for the target year; (d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and (e) set the inequality reduction targets by calculating the absolute and relative gaps between the bottom and top strata for the target year. Results. The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala’s 22 departments at the baseline year 2014 (MMR = 113 per 100,000 live births). By sustaining the AAPC rate attained from 2009 to 2014 (-4.3%) and focalizing its actions with territorial progressivity, by 2030 the country could reduce its MMR to 53 per 100,000 and its absolute and relative inequality gaps by 72% and 48%, respectively. Conclusions. The proposed methodology allows for simultaneously setting targets for overall progress and inequality reduction in health, making explicit the primacy of the equity principle contained in the SDG commitment to leave no one behind, whose urgency takes on renewed relevance in the current pandemic scenario.

Objetivos. Presentar una metodología para la formulación simultánea de metas cuantitativas que reflejen tanto la mejoría del promedio nacional de un indicador del tercer Objetivo de Desarrollo Sostenible (ODS3) como la reducción de su desigualdad geográfica. Métodos. Se definió un algoritmo en cinco pasos: a) cálculo del cambio porcentual anual promedio (CPAP) nacional para un indicador del ODS3; b) definición normativa de estratos geográficos a partir de la distribución subnacional del indicador en un año base; c) aplicación de un criterio de progresividad proporcional del CPAP para proyectar el indicador estrato-específico al año meta; d) establecimiento de la meta nacional como el promedio ponderado del indicador en las unidades territoriales subnacionales al año meta; y e) formulación de metas de reducción de desigualdad mediante el cálculo de las brechas absoluta y relativa entre los estratos extremos al año meta. Resultados. Se aplicó el algoritmo al indicador ODS 3.1.1 (razón de mortalidad materna, RMM), desagregado por los 22 departamentos de Guatemala para el año base 2014 (RMM = 113 por 100 000 nacidos vivos). Sosteniendo la intensidad promedio de CPAP observada entre 2009 y 2014 (−4,3%) y focalizando sus acciones con progresividad territorial, el país reduciría al 2030 su RMM a 53 por 100 000 nacidos vivos y sus brechas absoluta y relativa en 72% y 48%, respectivamente. Conclusiones. La metodología propuesta permite formular simultáneamente metas de reducción de las desigualdades geográficas en salud y hacer explícita la primacía del principio de equidad expresado en el compromiso de no dejar a nadie atrás que identifica a los ODS, cuya urgencia cobra renovada relevancia en el escenario pospandémico actual.

Objectives: Present methodology for the concurrent development of quantitative targets that reflect improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in geographic inequality., Methods: A five-step algorithm was developed: a) calculate the national average annual percentage change (AAPC) for an SDG3 indicator; b) standardize the definition of geographic strata based on subnational distribution of the indicator in a base year; c) apply a criterion for proportional progress in the AAPC in order to project the stratum-specific indicator to the target year; d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and e) develop inequality reduction targets by calculating absolute and relative gaps between the top and bottom strata for the target year., Results: The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala's 22 departments for base year 2014 (MMR = 113/100,000 live births). By sustaining the average AAPC rate attained from 2009 to 2014 (-4.3%) and targeting its actions to territorial progress, the country would reduce its MMR to 53/100,000 by 2030 and its absolute and relative gaps by 72% and 48%, respectively., Conclusions: The proposed methodology makes it possible to concurrently develop targets for the reduction of geographic inequalities in health and improvements in the national average, with explicit reference to the primacy of the principle of equity expressed in the SDGs' commitment to leaving no one behind , whose urgency is newly important in the current post-pandemic scenario.