Abstract

IntroductIonIn 1990, to help public health officials, politicians and key leaders compare human wellbeing, the UN Development Programme created the Human Development Index (HDI).1 The aim was to create an index that was based on available country- specific data, whilst being transparent and suffi- ciently robust enough to withstand scientific scru- tiny. The index is now widely used to compare world countries, and government leaders pay close attention to the individual rank of each country.The HDI is based on the concept that people are the real wealth of a nation. The originators of the HDI recognised that there are three essential components required for humans to develop to their maximum ability: health, education and income. There is general agreement that if any one of these elements is absent, individual achievement will be severely limited. Currently, the composite index is obtained by first normalising each individual component to a maximum value of unity so that all are on a comparable scale. Then the overall HDI is computed by taking the geometric mean of the three individual index val- ues.2 The health component of the index is based solely on life expectancy at birth, and the wealth component is based upon the gross national income per capita. Since 2011, the education part of the HDI is calculated by combining two separate measures: mean schooling years for adults and expected school years for children entering the school system. The geometric mean of these two values comprises the education index.For countries with large numbers of guest workers, mean years of schooling is likely to be low, because the majority of guest workers are unskilled labourers with a lower educational level than the citizen population. In contrast, the expected number of school years component would be relatively unaffected by guest workers because it is based upon students currently enrolled in the educational system.The aim of this report is to determine the impact of guest worker status on the composite HDI ranking score. We focused on the 93 countries classified as high or very high human development because this group has the highest concentration of migrant guest workers.MethodWe used published HDI data from the UN Human Development Programme 2010 or the most recent year to examine country rankings for all the countries ranked in the high or very high HDI groups.2 As an estimate of the number of migrant guest workers, we used the percentage of migrant workers aged 40-45 in the total popula- tion from available data in the UN migration data- base or, if unavailable, data from the World Bank.3,4 To determine the impact of migrant sta- tus on HDI, we plotted the country-specific rank- ing of each of the three individual HDI compo- nents (education, health, income) against migrant status. We also plotted each of the three compo- nents against the overall HDI, using a marker to identify those countries with the highest propor- tion of migrant workers.We used linear least squares analyses to study the relationship between migrant status and HDI as well as the individual components of the HDI. For outcomes that appeared non- linear, we used locally weighted scatterplot smoothing (Lowess) to fit the data. For comparing continuous variables between groups of coun- tries, we used t-tests. All p-values are two-sided, with a predetermined significance level of .05.ResultsData for both HDI and migrant status were availa- ble for 89 of the 93 countries listed in the UN high or very high development group. When we plot- ted the educational component of the HD against the percentage of migrants in these countries, we noted a biphasic curve with an inflexion point when the percentage of migrant workers in the population reached 30%. After this level was reached, there was a robust negative correlation between the educational component of the HDI and percentage of migrant workers (R = 0. …

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