Selection and testing of variability indicators of the time series characterizing the environment and population health

Introduction: The complex of environmental factors on a single territory is spatially diverse and dynamic, but there is almost no experience in using statistical indicators of variability.

Objective: To identify the most informative criteria of variability of the indicators characterizing the environment and population health using the example of an industrial city.

Materials and methods: We have considered five criteria (median, interquartile range, standard deviation, average annual growth rate, and coefficient of variation) used to describe short variation series. The analysis of variability in the “environment – population health” system of the city of Bratsk was carried out using 25 indicators, including characteristics of ambient air pollution, climate, socio-economic status, commitment to a healthy lifestyle, and population health for the years 2011 to 2021. Correlation and regression analysis were used.

Results: We have substantiated the use of coefficients of variation and growth rates for the analysis of the “environment – population health” systems. Among the elements of the system, 56 % of the characteristics in the city of Bratsk showed minor variability; the prevalence of healthy eating, smoking, and sufficient physical activity; the cost of fixed assets and wages fell into the range of low variability; air pollution and drug use – moderate one, while the prevalence of alcohol abuse and the volume of investment in fixed assets demonstrated noticeable variability. Population health characteristics during the study period were less variable than environmental indicators, which is likely a reflection of the adaptive capabilities of the population.

Conclusion: For the practical use by specialists analyzing the relationship between risk factors and population health, it is proposed to use the average annual growth rate and the coefficient of variation. The advantages of the combined use of these indicators include the ability to identify not only the spread of the characteristics being studied, but also their trends, and no dependence on numerical representation of the characteristics considered.

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