4.6 Article

Local Modelling Techniques for Assessing Micro-Level Impacts of Risk Factors in Complex Data: Understanding Health and Socioeconomic Inequalities in Childhood Educational Attainments

Journal

PLOS ONE
Volume 9, Issue 11, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0113592

Keywords

-

Funding

  1. Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer)
  2. UKCRC Public Health Research Centre of Excellence
  3. Economic and Social Research Council [MR/KO232331/1, MR/K006525/1]
  4. Medical Research Council [MR/KO232331/1, MR/K006525/1]
  5. Welsh Government [MR/KO232331/1]
  6. Wellcome Trust, under the UK Clinical Research Collaboration [MR/KO232331/1]
  7. Farr Institute of Health Informatics Research
  8. Arthritis Research UK [MR/K006525/1]
  9. British Heart Foundation [MR/KO232331/1, MR/K006525/1]
  10. Cancer Research UK [MR/KO232331/1, MR/K006525/1]
  11. Engineering and Physical Sciences Research Council [MR/K006525/1]
  12. National Institute of Health Research [MR/K006525/1]
  13. National Institute for Social Care and Health Research (Welsh Government) [MR/K006525/1]
  14. Chief Scientist Office (Scottish Government Health Directorates) [MR/K006525/1]
  15. ESRC [ES/L007444/1] Funding Source: UKRI
  16. MRC [MR/K006525/1, MR/K023233/1] Funding Source: UKRI
  17. Economic and Social Research Council [ES/L007444/1] Funding Source: researchfish
  18. Medical Research Council [MR/K023233/1, MR/K006525/1] Funding Source: researchfish

Ask authors/readers for more resources

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, Micro-impact of Domain'' and Contribution of Domain'', to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available