Adjusting for spatial variation when assessing individual-level risk: A case-study in the epidemiology of snake-bite in Sri Lanka
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Dileepa Senajith Ediriweera aff001; Anuradhani Kasthuriratne aff002; Arunasalam Pathmeswaran aff002; Nipul Kithsiri Gunawardene aff003; Shaluka Francis Jayamanne aff004; Kris Murray aff005; Takuya Iwamura aff007; David Griffith Lalloo aff008; Hithanadura Janaka de Silva aff004; Peter John Diggle aff009
Působiště autorů:
Centre for Health Informatics, Biostatistics and Epidemiology, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
aff001; Department of Public Health, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
aff002; Department of Parasitology, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
aff003; Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
aff004; Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, St Mary’s Campus, London, United Kingdom
aff005; Grantham Institute—Climate Change and the Environment, Imperial College London, South Kensington, London, United Kingdom
aff006; Faculty of Life Sciences, School of Zoology, Tel Aviv University, Tel Aviv, Israel
aff007; Liverpool School of Tropical Medicine, Liverpool, United Kingdom
aff008; CHICAS, Lancaster University Medical School, Lancaster, United Kingdom
aff009
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223021
Souhrn
Background
Health outcomes and causality are usually assessed with individual level sociodemographic variables. Studies that consider only individual-level variables can suffer from residual confounding. This can result in individual variables that are unrelated to risk behaving as proxies for uncaptured information. There is a scarcity of literature on risk factors for snakebite. In this study, we evaluate the individual-level risk factors of snakebite in Sri Lanka and highlight the impact of spatial confounding on determining the individual-level risk effects.
Methods
Data was obtained from the National Snakebite Survey of Sri Lanka. This was an Island-wide community-based survey. The survey sampled 165,665 individuals from all 25 districts of the country. We used generalized linear models to identify individual-level factors that contribute to an individual’s risk of experiencing a snakebite event. We fitted separate models to assess risk factors with and without considering spatial variation in snakebite incidence in the country.
Results
Both spatially adjusted and non-adjusted models revealed that middle-aged people, males, field workers and individuals with low level of education have high risk of snakebites. The model without spatial adjustment showed an interaction between ethnicity and income levels. When the model included a spatial adjustment for the overall snakebite incidence, this interaction disappeared and income level appeared as an independent risk factor. Both models showed similar effect sizes for gender and age. HEmployment and education showed lower effect sizes in the spatially adjusted model.
Conclusions
Both individual-level characteristics and local snakebite incidence are important to determine snakebite risk at a given location. Individual level variables could act as proxies for underling residual spatial variation when environmental information is not considered. This can lead to misinterpretation of risk factors and biased estimates of effect sizes. Both individual-level and environmental variables are important in assessing causality in epidemiological studies.
Klíčová slova:
Employment – Ethnic epidemiology – Ethnicities – Medical risk factors – Snakebite – Snakes – Sri Lanka – Sinhalese people
Zdroje
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PLOS One
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