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First, starting from the locations of central activities, a concentration index is presented to visualize the functional urban environment by means of a density surface, which is refined with network distances rather than Euclidean ones.
A concentration index approach with decomposition into contributing factors was applied.
One is a concentration index of health expenditure ranked by some measure of socioeconomic status.
We used a concentration index (CI) to assess equality in the distribution of needs and utilisation among three areas with different per-head gross domestic product (GDP).
Therefore, we propose the use of the Gini coefficient for consumption expenditure (Gc) or a concentration index for consumption expenditure (Cc), which leads us to a calculated concentration curve ranked by income instead of the Gini coefficient.
For example, Gerdtham et al. [12] investigated the effects of health rating scales, Wagstaff and Watanabe [13] investigated the relationship between malnutrition, and consumption and wealth, Gravelle [14] removed the effects of age and gender from a concentration index, and Erreygers [15] proposed a new rank-dependent measure.
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The latter was estimated based on a precipitation concentration index (PCI).
Second, we use a relative concentration index.
The concentration of minority populations in certain areas is also noticeable, presenting a higher concentration index than the Han population.
We also computed a mortality concentration index.
The opposite is true when the concentration curve lies everywhere below the diagonal, which would imply a positive concentration index.
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CEO of Professional Science Editing for Scientists @ prosciediting.com