J Robinson1, H Wharrad. 1. Post-graduate Division of Nursing Studies, The Medical School, University of Nottingham, England. jjarenginerow@enta.net
Abstract
AIMS: To explore the relationship between the global distribution of health professionals (physicians and nurses), gross national product per capita (GNP), female literacy and the health outcome indicators of infant, and under-5 mortality rates using available data from United Nations' (UN) sources. To consider the reliability and validity of the variables included, and the implications of the findings for health policy and practice, and for further research. DESIGN: Using a database on 155 countries, regression analyses were performed using GNP, female literacy, numbers of physicians per 1000 population and numbers of nurses per 1000 population as independent variables, and infant mortality (IMR) and under-5 mortality rates (u5MR) as dependent variables. RESULTS: Linear regression analyses give R2 values for the two mortality indicators (IMR and u5MR) of 63% and 66% for physicians and 51% and 52% for nurses. Multiple linear regression analyses reveal a more complex picture. Countries with high ratios of physicians and nurses to population relative to their GNP also tend to show low IMRs and u5MRs. However, when female literacy is included in the model, the majority of these outlying countries move back towards the regression line. Nurses disappear from the model altogether when regressed with physicians, GNP per capita and female literacy for both outcome indicators. CONCLUSIONS: Despite the acknowledged need for caution in the validity and reliability of the UN data sources used in the analyses, interesting positive relationships are identified between the input variables and mortality outputs. The implications for future health policy, practice and research are considered. These include the need for more reliable, comprehensive and up-to-date data sets.
AIMS: To explore the relationship between the global distribution of health professionals (physicians and nurses), gross national product per capita (GNP), female literacy and the health outcome indicators of infant, and under-5 mortality rates using available data from United Nations' (UN) sources. To consider the reliability and validity of the variables included, and the implications of the findings for health policy and practice, and for further research. DESIGN: Using a database on 155 countries, regression analyses were performed using GNP, female literacy, numbers of physicians per 1000 population and numbers of nurses per 1000 population as independent variables, and infant mortality (IMR) and under-5 mortality rates (u5MR) as dependent variables. RESULTS: Linear regression analyses give R2 values for the two mortality indicators (IMR and u5MR) of 63% and 66% for physicians and 51% and 52% for nurses. Multiple linear regression analyses reveal a more complex picture. Countries with high ratios of physicians and nurses to population relative to their GNP also tend to show low IMRs and u5MRs. However, when female literacy is included in the model, the majority of these outlying countries move back towards the regression line. Nurses disappear from the model altogether when regressed with physicians, GNP per capita and female literacy for both outcome indicators. CONCLUSIONS: Despite the acknowledged need for caution in the validity and reliability of the UN data sources used in the analyses, interesting positive relationships are identified between the input variables and mortality outputs. The implications for future health policy, practice and research are considered. These include the need for more reliable, comprehensive and up-to-date data sets.