RESUMO
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.
RESUMO
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.
OBJETIVOS: Apresentar uma metodologia para a formulação simultânea de metas quantitativas que reflitam tanto a melhoria da média nacional de um indicador do terceiro Objetivo de Desenvolvimento Sustentável (ODS3) quanto a redução das desigualdades geográfica nesse indicador. MÉTODOS: Estabelecemos um algoritmo em cinco etapas: (a) cálculo da variação percentual anual média (VPAM) em um país para um indicador do ODS3, (b) definição normativa de estratos geográficos a partir da distribuição subnacional do indicador em um ano base, (c) aplicação de um critério de progressividade proporcional da VPAM para projetar o indicador específico do estrato para o ano base, (d) estabelecimento da meta nacional como a média ponderada do indicador nas unidades territoriais subnacionais para o ano alvo e (e) estabelecimento de metas para a redução das desigualdades calculando a disparidade absoluta e relativa entre os estratos extremos para o ano alvo. RESULTADOS: Aplicamos o algoritmo ao indicador ODS 3.1.1 (razão de mortalidade materna, RMM), desagregado pelos 22 departamentos da Guatemala para o ano base de 2014 (RMM = 113 por 100.000 nascidos vivos). Se mantiver a intensidade média da VPAM observada entre 2009 e 2014 (-4,3%) e concentrar as suas ações com progressividade territorial, o país reduzirá, até 2030, a sua RMM para 53 por 100.000 e sua disparidade absoluta e relativa em 72% e 48%, respectivamente. CONCLUSÕES: A metodologia proposta permite formular simultaneamente metas para a redução das desigualdades geográficas em saúde e explicitar a primazia do princípio da equidade expresso no compromisso de não deixar ninguém para trás consagrado nos ODS, cuja urgência assume uma relevância renovada no atual cenário pós-pandêmico.
