Large-scale monitoring in the DRC’s Ituri forest with a locally informed multidimensional well-being index

To monitor quality of life in changing landscapes and assess impacts of interventions, development scholars and practitioners continue to seek sensitive, flexible, practical means of measuring well-being. An approach that has received relatively little attention from development scholars but that is gaining traction among NGOs is the use of a well-being index derived from a list of locally defined and democratically weighted basic necessities. The Wildlife Conservation Society has been piloting a tool called the Basic Necessities Survey (BNS) in and around protected areas in Central Africa and beyond for over a decade. Adapted from consensual relative poverty metrics developed in the UK and Sweden, BNS data can be used to calculate a Well-being Index (WBI) that is locally relevant and comparable. To demonstrate its applicability in a lower-income context, we present findings from the Ituri Region of the Democratic Republic of the Congo (DRC) where over 2,000 households were surveyed using the BNS tool in 2015, 2017, and 2019. WBI scores were lower among traditionally vulnerable and marginalized groups: Indigenous and female-headed households, those with young or elderly heads, and households that were smaller or had high ratios of dependents. WBI varied with livelihood and geography and was sensitive enough to detect group-specific changes over a short time; namely an economic shock concentrated in villages along the main local highway in 2017 when the DRC experienced a major currency devaluation. Scores can be calculated to either incorporate or isolate variability in subjective expectations about what constitutes well-being; we show that expectations differed for Indigenous households and expectations rose faster than assets in this period. Findings build confidence in the utility of this type of locally informed multidimensional well-being metric in low-income regions. Those seeking practical instruments to produce flexible and regionally comparable well-being measures may wish to consider this approach.