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Common mental disorders, economic growth and development: Economic consequences and measurement issues
journal contributionposted on 2018-02-27, 00:00 authored by Michael DzatorMichael Dzator, F Asante, C Ahiadeke
A large number of studies have attempted to discern the causes of low productivity and slow growth in developing countries especially in Sub-Saharan Africa (SSA). The effects of global economic integration, corruption, geography, financial aid and human capital indicators such as education have been widely explored. Despite the significant contribution of common mental disorders (CMDs) to poverty and to the burden of disease, mainstream growth analyses have not yet integrated the body of scholarship that identifies the linkages between CMDs and growth. There are potential benefits of prioritising CMDs in development strategies but there are several challenges. Among the greatest challenges is patchy mental health record. Poor data hinders the conceptualisation and the analyses of the effect of common mental disorders on economic growth and development. This paper explores the theoretical and empirical macro-growth effects of CMDs in sub-Saharan Africa. Preliminary theorizing and evidence suggest that improvement in CMDs is likely to be a stimulus to growth in SSA. We explore further the performance of a non-psychometric instrument known as the K-6 as a cost-effective instrument with which to measure community mental health in household surveys across populations that have various levels of infrastructure and literacy. The K-6 instrument which is a semi-structured questionnaire includes six non-specific psychometric items measuring negative affective states or psychological distress. We also collect socioeconomic data during the survey which enabled us to study the determinants of common mental health conditions among urban and rural households in Ghana. Urban and rural communities were analysed separately because they may demonstrate different determinants of CMDs. We report the outcome of the simple non-psychometric survey as well as the results from logistic regressions showing the factors that affect common mental disorders among the survey respondents. The results show that both urban and rural groups experienced diminished mental health during the food and fuel price hikes of 2008 and 2009, and from the global financial crises over the same period, compared with those who reported no mental distress. The coefficients from the logistic regression estimated by the maximum likelihood show spatial variations in mental health indicators by age, education, and per capita income. For this study, gender did not appear to be a good predictor of any of the specific psychological distress measures assessed.