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Summarizing, presenting, and interpreting epidemiological data: Building on incidence and prevalence 

Summarizing, presenting, and interpreting epidemiological data: Building on incidence and prevalence
Chapter:
Summarizing, presenting, and interpreting epidemiological data: Building on incidence and prevalence
Author(s):

Raj S. Bhopal

DOI:
10.1093/med/9780198739685.003.0008
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date: 21 October 2020

Basic epidemiological data on disease occurrence and population structure can be manipulated and presented in many ways. Epidemiological summary measures, broadly, estimate absolute or relative frequency of outcomes. Usually, relative measures are more useful in causal enquiry while absolute measures are better in health planning and policy. These measures, usually in association with risk factor prevalence data, allow estimation of the risk attributable to a risk factor in those exposed and in the entire population. Avoidable mortality (and morbidity) refers to the potential to avoid death (or morbidity) from a number of specified causes if the best possible health care actions were taken. Years of life saved measures help to measure the impact of avoidable mortality in the population. Epidemiological data on diseases can be combined with other information, such as socio-economic circumstances, social values and attitudes, and behaviours relevant to health, to build up a community health profile.

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