Education, income inequality, and mortality: a multiple regression analysis
A Coggle Diagram about Data and methods (The study is based on a cross sectional analysis of US census statistics and vital statistics for the years 1989 and 1990 for all US states including the District of Columbia (n = 51). , Age adjusted mortality from all causes was the main dependent variable of the analysis., The Gini coefficient for households was the main independent variable of interest. and To control for varying income levels among states, I included the per capita income of all people in the regression model.), Results (Fig 1 shows the relation between the measure of income inequality and age adjusted mortality. , Fig 2 shows a positive, linear relation between education and age adjusted mortality. , Fig 3 presents the percentage of variation in age adjusted mortality explained by five regression specifications. and Subgroup analysis
A preliminary analysis of age specific mortality indicated that the findings might best reflect the experience of people aged >45 years.
For the 15-44 year age group, the Gini coefficient was significant and positively related to age specific death rates, whereas the education variable was only marginally significant.
Since the analysis did not restrict the age range of the independent variables to people aged 15-44, the results might be biased.
Deaths for 15-44 year olds comprised 8.3% of all US deaths in 1989-90, with accidental and violent deaths among the leading causes.), Discussion (Implications of results, This study had two main findings. and Therefore, my findings may not be applicable today. ) and Introduction (Three competing interpretations have been advanced. and Several recent studies)