Characterizing multidimensional poverty in Migori County, Kenya and its association with depression

Introduction Narrow, unidimensional measures of poverty often fail to measure true poverty and inadequately capture its drivers. Multidimensional indices of poverty more accurately capture the diversity of poverty. There is little research regarding the association between multidimensional poverty and depression. Methods A cross-sectional survey was administered in five sub-locations in Migori County, Kenya. A total of 4,765 heads of household were surveyed. Multidimensional poverty indices were used to determine the association of poverty with depression using the Patient Health Questionnaire (PHQ-8) depression screening tool. Results Across the geographic areas surveyed, the overall prevalence of household poverty (deprivation headcount) was 19.4%, ranging from a low of 13.6% in Central Kamagambo to a high of 24.6% in North Kamagambo. Overall multidimensional poverty index varied from 0.053 in Central Kamagambo to 0.098 in North Kamagambo. Of the 3,939 participants with depression data available, 481 (12.2%) met the criteria for depression based on a PHQ-8 depression score ≥10. Poverty showed a dose-response association with depression. Conclusions Multidimensional poverty indices can be used to accurately capture poverty in rural Kenya and to characterize differences in poverty across areas. There is a clear association between multidimensional poverty and depressive symptoms, including a dose effect with increasing poverty intensity. This supports the importance of multifaceted poverty policies and interventions to improve wellbeing and reduce depression.

Multidimensional Indices with Data-driven Dimensional Weights: A Multidimensional Coefficient of Variation

Multidimensional indices require specification of the dimensional weights. There are two broad approaches to the task: the normative and the data-driven. The data-driven approach, however, often yields indices violating economic norms. This article asks whether a normatively acceptable index of inequality of the standard of living in an economy can be obtained from data-driven weights. It gives an affirmative answer by deriving a multidimensional coefficient of variation (MCV) from an endogenous weighting scheme and showing that the index satisfies the various economic norms suggested in the literature. The derived index does not appear in the existing literature and the literature does not seem to contain an MCV satisfying all of the economic norms discussed in the article. JEL: D60, D63

Strengths and Weaknesses of Two Empathy Measures: A Comparison of the Measurement Precision, Construct Validity, and Incremental Validity of Two Multidimensional Indices

The quality of empathy research, and clinical assessment, hinges on the validity and proper interpretation of the measures used to assess the construct. This study investigates, in an online sample of 401 adult community participants, the construct validity of the Affective and Cognitive Measure of Empathy (ACME) relative to that of the Interpersonal Reactivity Index (IRI), the most widely used multidimensional empathy research measure. We investigated the factor structures of both measures, as well as their measurement precision across varying trait levels. We also examined them both in relation to convergent and discriminant criteria, including broadband personality dimensions, general emotionality, personality disorder features, and interpersonal malignancy. Our findings suggest that the ACME possesses incremental validity beyond the IRI for most constructs related to interpersonal malignancy. Our results further indicate that the IRI Personal Distress scale is severely deficient in construct validity, raising serious concerns regarding past findings that have included it when computing total empathy scores. Finally, our results indicate that both questionnaires display poor measurement precision at high trait levels, emphasizing the need for future researchers to develop indices that can reliably measure high levels of empathy.

Strong law of large numbers for random variables with multidimensional indices

Tu wpisz tekst

A comparison of published multidimensional indices to predict outcome in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) has an unpredictable course and prognostic factors are incompletely understood. We aimed to identify prognostic factors, including multidimensional indices from a significant IPF cohort at the Bristol Interstitial Lung Disease Centre in the UK.Patients diagnosed with IPF between 2007 and 2014 were identified. Longitudinal pulmonary physiology and exercise testing results were collated, with all-cause mortality used as the primary outcome. Factors influencing overall, 12- and 24-month survival were identified using Cox proportional hazards modelling and receiver operating characteristic curve analysis.We found in this real-world cohort of 167 patients, diffusing capacity for carbon monoxide (DLCO) and initiation of long-term oxygen were independent markers of poor prognosis. Exercise testing results predicted 12-month mortality as well as DLCO, but did not perform as well for overall survival. The Composite Physiological Index was the best performing multidimensional index, but did not outperform DLCO. Our data confirmed that patients who experienced a fall in forced vital capacity (FVC) >10% had significantly worse survival after that point (p=0.024).Our data from longitudinal follow-up in IPF show that DLCO is the best individual prognostic marker, outperforming FVC. Exercise testing is important in predicting early poor outcome. Regular and complete review should be conducted to ensure appropriate care is delivered in a timely fashion.

Multidimensional Indicators of Inequality and Poverty

This chapter reviews the main features of multidimensional indices of inequality and poverty. For each of these cases, the discussion is divided into two approaches: a direct approach, where desirable properties are specified and a measure of inequality or poverty obtained; and the inclusive measure of well-being approach, where an index of individual well-being is defined in a first step, and the measure of inequality or poverty obtained in a second step. The emphasis will be on the properties that different measures satisfy and on the main justifications put forward when properties disagree. A systematic comparison between indices, whenever appropriate, is presented. Several policy applications of the indices are also discussed.