scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern issue. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition in children below five years. While considerable efforts are being made to address this challenging issue, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result: MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly discounting cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission. Conclusion: MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern issue. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition in children below five years. While considerable efforts are being made to address this challenging issue, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. Conclusion MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition among children below five years. While considerable efforts are being made to address this challenge, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result: MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. Conclusion: MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH—a more sensitive yardstick

2020 ◽  
Author(s):  
Ayushi Jain ◽  
Satish Balram Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent issue. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition in children below five years. While considerable efforts are being made to address this challenging issue, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH.Methodology: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Through the use of maps and spatial tools, we gauged the existence of neighbourhood dependency, the formation of clusters, within and across states.Result: MANUSH method succeeds over its counterparts – linear aggregation and geometric mean, by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising when, improvement in worst-off dimension is less or not proportionate to improvement in best-off dimension, or when, even with overall improvement, the gap between dimensions remain same. MANUSH scores helped in revealing the changing paradigm in the improvement of nutrition outcomes and the rising inequalities within and across states and districts in India. Significant clusters (p<0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. The usefulness of MANUSH index in context-specific planning and prioritising actions is also brought out using the case of the National Nutrition Mission.Conclusion: MANUSH indexing depicts balanced development effectively, hence finds relevance in bringing out inequality in a diverse and developing economy like India.

scholarly journals Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH – a more sensitive yardstick

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Ayushi Jain ◽  
Satish B. Agnihotri
Keyword(s):  
Child Nutrition ◽  
Geometric Mean ◽  
Composite Index ◽  
Family Health ◽  
Regional Disparities ◽  
Nutrition Survey ◽  
Balanced Development ◽  
Child Undernutrition ◽  
Linear Aggregation ◽  
Context Specific

Abstract Background India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition among children below 5 years. While considerable efforts are being made to address this challenge, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the ‘lagging’ indicators, and hence not incentivising a balanced improvement. Signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. Methodology Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005–06), NFHS-4 (2015–16) and CNNS (2106–18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. Result MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p < 0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. Conclusion MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

Child Undernutrition in the States of India: An Analysis Based on Change in Composite Index of Anthropometric Failure from 2006 to 2016

2021 ◽  
pp. 097226612110103
Author(s):  
J. R. Jith ◽  
Rajshree Bedamatta
Keyword(s):  
Child Nutrition ◽  
Composite Index ◽  
Family Health ◽  
Wealth Index ◽  
Household Wealth ◽  
Population Projections ◽  
Indian Children ◽  
Indian States ◽  
Child Undernutrition ◽  
Low Weight

Stunting, wasting and underweight—the three traditional indicators of undernourishment among children—provide mutually non-exclusive categories of anthropometric failures: low height for age, low weight for height and low weight for age. Although these indicators are essential for designing specific clinical and child nutrition policy interventions, they fall short of estimating the prevalence of overall anthropometric failure, which provides a sense of the scale of the nutrition problem. This article estimates the alternative, more comprehensive measure Composite Index of Anthropometric Failure (CIAF) for Indian states, based on data from the National Family Health surveys of 2006 and 2016, for children under five years (Ch–U5). The CIAF-based undernutrition estimates show significantly high anthropometric failure levels among Indian children compared to only stunting, wasting and underweight. Based on population projections for Ch–U5, we also show that a sizeable number of states may have seen an increase in child undernutrition between 2006 and 2016. We also correlated CIAF with household wealth index scores and found a positive relationship with children facing no anthropometric failure.

scholarly journals Stunting among Preschool Children in India: Temporal Analysis of Age-Specific Wealth Inequalities

2020 ◽  
Vol 17 (13) ◽  
pp. 4702
Author(s):  
Sunil Rajpal ◽  
Rockli Kim ◽  
William Joe ◽  
S.V. Subramanian
Keyword(s):  
Child Nutrition ◽  
Age Groups ◽  
Policy Research ◽  
Family Health ◽  
Temporal Analysis ◽  
Preschool Age ◽  
Nutritional Intake ◽  
Child Stunting ◽  
Child Undernutrition ◽  
Wealth Inequalities

Adequate nutritional intake for mothers during pregnancy and for children in the first two years of life is known to be crucial for a child’s lifelong physical and neurodevelopment. In this regard, the global nutrition community has focused on strategies for improving nutritional intake during the first 1000 day period. This is largely justified by the observed steep decline in children’s height-for-age z scores from birth to 23 months and presumed growth faltering at later ages as a reflection of earlier deprivation that is accumulated and irreversible. Empirical evidence on the age-stratified burden of child undernutrition is needed to re-evaluate the appropriate age for nutrition interventions to target among children. Using data from two successive rounds of National Family Health Surveys conducted in 2006 and 2016, the objective of this paper was to analyze intertemporal changes in the age-stratified burden of child stunting across socioeconomic groups in India. We found that child stunting in India was significantly concentrated among children entering preschool age (24 or above months). Further, the temporal reduction in stunting was relatively higher among children aged 36–47 months compared to younger groups (below 12 and 12–23 months). Greater socioeconomic inequalities persisted in stunting among children from 24 months or above age-groups, and these inequalities have increased over time. Children of preschool age (24 or above months) from economically vulnerable households experienced larger reductions in the prevalence of stunting between 2006 and 2016, suggesting that policy research and strategies beyond the first 1000 days could be critical for accelerating the pace of improvement of child nutrition in India.

scholarly journals An Intersectional Analysis of the Composite Index of Anthropometric Failures in India

2020 ◽  
Author(s):  
Sabu K Ulahannan ◽  
Yogish Channa Basappa ◽  
Sangeetha V Joice ◽  
Prashanth N Srini
Keyword(s):  
Descriptive Analysis ◽  
Economic Inequality ◽  
Group Analysis ◽  
Composite Index ◽  
Family Health ◽  
Nutritional Interventions ◽  
Child Undernutrition ◽  
Rural And Urban ◽  
Poor Households ◽  
And Gender

Abstract Background: Nutritional inequality in India has been estimated typically using stunting, wasting and underweight separately which hide the overall magnitude and severity of undernutrition. We used the Composite Index of Anthropometric Failure (CIAF) that combines all three forms of anthropometric failures to assess the severity of undernutrition and identify the most vulnerable social groups and geographical hotspots.Method: CIAF was constructed using child anthropometric data from the fourth round of the National Family Health Survey (NFHS-4, 2015-16). We considered 24 intersecting sub-groups based on intersections across four main axes of inequality i.e., caste [Scheduled Tribe (ST), Scheduled Caste (SC) and Other], economic position (poor and non-poor), place of residence (rural and urban) and gender (male and female) (eg. ST-Poor-Rural-Female). Cross-tabulation and logistic regression were done to assess the odds of CIAF among intersecting groups and to identify the most vulnerable sub-groups. Concentration curve was plotted to visualise economic inequality in child undernutrition across caste categories. Choropleth maps were constructed and descriptive analysis of the district-level prevalence of CIAF was performed to identify the geographic clustering of undernutrition.Results: Overall 55.1% of children were undernourished by CIAF and 6.7% of children have simultaneous three anthropometric failure. In sub-group analysis, children from ST and SC caste have a higher risk of undernutrition irrespective of other axis of inequality. The typical urban advantage is reversed among the children from poor SC and other-caste in most sub-groups. Compared with CIAF, socio-economic inequality was amplified for simultaneous-three-failures among all caste categories. Socio-economic inequalities within caste are more for other caste and SC categories than with ST. Based on the analysis of the high prevalence in the co-occurrence of two or three failures, 111 districts from 12 of 29 states in India were identified across four geographic clusters.Conclusions: The study shows social and eco-geographical clustering of multi-dimensional anthropometric failures and indicates the need for focused nutritional interventions among SC and ST community in general and ST children from the poor households. Furthermore, governance interventions that target entire regions across districts and states combined with decentralised planning are needed.

scholarly journals An intersectional analysis of the composite index of anthropometric failures in India

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Sabu Ulahannan Kochupurackal ◽  
Yogish Channa Basappa ◽  
Sangeetha Joice Vazhamplackal ◽  
Prashanth N Srinivas
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Descriptive Analysis ◽  
Group Analysis ◽  
Composite Index ◽  
Family Health ◽  
Nutritional Interventions ◽  
Child Undernutrition ◽  
Economic Position ◽  
And Gender

Abstract Background Nutritional inequality in India has been estimated typically using stunting, wasting and underweight separately which hide the overall magnitude and severity of undernutrition. We used the Composite Index of Anthropometric Failure (CIAF) that combines all three forms of anthropometric failures to assess the severity of undernutrition and identify the most vulnerable social groups and geographical hotspots. Method CIAF was constructed using child anthropometric data from the fourth round of the National Family Health Survey (NFHS-4, 2015–16). We considered 24 intersecting sub-groups based on intersections across four main axes of inequality i.e., caste [Scheduled Tribe (ST), Scheduled Caste (SC) and Other], economic position (poor and non-poor), place of residence (rural and urban) and gender (male and female) (eg. ST-Poor-Rural-Female). Cross-tabulation and logistic regression were done to assess the odds of CIAF among intersecting groups and to identify the most vulnerable sub-groups. Concentration curve was plotted to visualise economic position inequality in child undernutrition across caste categories. Choropleth maps were constructed and descriptive analysis of the district-level prevalence of CIAF was performed to identify the geographic clustering of undernutrition. Results Overall 55.32% of children were undernourished by CIAF and 6.62% of children have simultaneous three anthropometric failure. In sub-group analysis, children from ST and SC caste have a higher risk of undernutrition irrespective of other axis of inequality. Compared with CIAF, economic position inequality was amplified for simultaneous-three-failures among all caste categories. Economic position inequalities within caste are more for other caste and SC categories than with ST. Economic position, caste and gender based inequality in all three failures is more consistent in rural areas than with urban areas. Based on the analysis of the high prevalence in the co-occurrence of two or three failures, 111 districts from 12 of 29 states in India were identified across four geographic clusters. Conclusions The study shows social and eco-geographical clustering of multi-dimensional anthropometric failures and indicates the need for focused nutritional interventions among SC and ST community in general and ST children from the poor households. Furthermore, governance interventions that target entire regions across districts and states combined with decentralised planning are needed.

scholarly journals An Intersectional Analysis of the Composite Index of Anthropometric Failures in India

2021 ◽  
Author(s):  
Sabu K Ulahannan ◽  
Yogish Channa Basappa ◽  
Sangeetha V Joice ◽  
Prashanth N Srini
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Descriptive Analysis ◽  
Group Analysis ◽  
Composite Index ◽  
Family Health ◽  
Nutritional Interventions ◽  
Child Undernutrition ◽  
Economic Position ◽  
And Gender

Abstract Background: Nutritional inequality in India has been estimated typically using stunting, wasting and underweight separately which hide the overall magnitude and severity of undernutrition. We used the Composite Index of Anthropometric Failure (CIAF) that combines all three forms of anthropometric failures to assess the severity of undernutrition and identify the most vulnerable social groups and geographical hotspots.Method: CIAF was constructed using child anthropometric data from the fourth round of the National Family Health Survey (NFHS-4, 2015-16). We considered 24 intersecting sub-groups based on intersections across four main axes of inequality i.e., caste [Scheduled Tribe (ST), Scheduled Caste (SC) and Other], economic position (poor and non-poor), place of residence (rural and urban) and gender (male and female) (eg. ST-Poor-Rural-Female). Cross-tabulation and logistic regression were done to assess the odds of CIAF among intersecting groups and to identify the most vulnerable sub-groups. Concentration curve was plotted to visualise economic position inequality in child undernutrition across caste categories. Choropleth maps were constructed and descriptive analysis of the district-level prevalence of CIAF was performed to identify the geographic clustering of undernutrition.Results: Overall 55.32% of children were undernourished by CIAF and 6.62% of children have simultaneous three anthropometric failure. In sub-group analysis, children from ST and SC caste have a higher risk of undernutrition irrespective of other axis of inequality. Compared with CIAF, economic position inequality was amplified for simultaneous-three-failures among all caste categories. Economic position inequalities within caste are more for other caste and SC categories than with ST. Economic position, caste and gender based inequality in all three failures is more consistent in rural areas than with urban areas. Based on the analysis of the high prevalence in the co-occurrence of two or three failures, 111 districts from 12 of 29 states in India were identified across four geographic clusters.Conclusions: The study shows social and eco-geographical clustering of multi-dimensional anthropometric failures and indicates the need for focused nutritional interventions among SC and ST community in general and ST children from the poor households. Furthermore, governance interventions that target entire regions across districts and states combined with decentralised planning are needed.

scholarly journals To Weight or Not to Weight, That Is the Question: The Design of a Composite Indicator of Landscape Fragmentation

2021 ◽  
Vol 11 (7) ◽  
pp. 3208
Author(s):  
Andrea De Montis ◽  
Vittorio Serra ◽  
Giovanna Calia ◽  
Daniele Trogu ◽  
Antonio Ledda
Keyword(s):  
Principal Component Analysis ◽  
Geometric Mean ◽  
Composite Index ◽  
Weighted Average ◽  
Principal Component ◽  
Expert Judgment ◽  
Landscape Fragmentation ◽  
Composite Indicator ◽  
Per Se ◽  
Higher Sensitivity

Composite indicators (CIs), i.e., combinations of many indicators in a unique synthetizing measure, are useful for disentangling multisector phenomena. Prominent questions concern indicators’ weighting, which implies time-consuming activities and should be properly justified. Landscape fragmentation (LF), the subdivision of habitats in smaller and more isolated patches, has been studied through the composite index of landscape fragmentation (CILF). It was originally proposed by us as an unweighted combination of three LF indicators for the study of the phenomenon in Sardinia, Italy. In this paper, we aim at presenting a weighted release of the CILF and at developing the Hamletian question of whether weighting is worthwhile or not. We focus on the sensitivity of the composite to different algorithms combining three weighting patterns (equalization, extraction by principal component analysis, and expert judgment) and three indicators aggregation rules (weighted average mean, weighted geometric mean, and weighted generalized geometric mean). The exercise provides the reader with meaningful results. Higher sensitivity values signal that the effort of weighting leads to more informative composites. Otherwise, high robustness does not mean that weighting was not worthwhile. Weighting per se can be beneficial for more acceptable and viable decisional processes.

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