
Area-based markers of deprivation (e.g., postal codes) are commonly used to identify groups of people with low socioeconomic status (SES); the validity of this approach, however, remains unknown. In this study, we determined the accuracy of using income quintile groups calculated on the basis of the median family income of each forward sortation area (1996 Canadian census) to identify those living in poverty (i.e., annual family income of < $12,620). The sensitivity and specificity of using the lowest income quintile to capture those in poverty were 26% and 83%, respectively (likelihood ratio (LR) of 1.49; 99% CI, 1.49 to 1.50). Among those in non-metropolitan and metropolitan areas, the LRs were 1.26 (99% CI, 1.26 to 1.27) and 2.01 (99% CI, 2.01 to 2.02), respectively. The use of postal codes as the only marker to identify people with low SES may result in substantial misclassification of personal poverty, particularly in non-metropolitan areas.
Adult, Male, Rural Population, Adolescent, Urban Population, Data Collection, Censuses, Sensitivity and Specificity, Alberta, Social Class, Population Surveillance, Income, Humans, Female, Postal Service, Public Health, Child, Poverty
Adult, Male, Rural Population, Adolescent, Urban Population, Data Collection, Censuses, Sensitivity and Specificity, Alberta, Social Class, Population Surveillance, Income, Humans, Female, Postal Service, Public Health, Child, Poverty
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 34 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
