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Observed patterns of genetic structure result from the interactions of demographic, physical, and historical influences on gene flow.
These differences are not unexpected given the complex interactions of demographic and selective forces, and are currently being investigated.
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Because the interaction of demographic factors with fatigue is largely a neglected area of study, we recommend greater interdisciplinary collaborations, incorporation of multiple demographic variables as independent factors, and use of within-participant analyses.
Little research has addressed how the interaction of demographic and biomedical parameters with psychosocial processes has an impact on appointment keeping.
It is crucial to understand the interaction of demographic expansion and natural selection, and in particular purifying (negative) selection, to assess whether the recent explosive growth has affected the genetic basis and architecture of complex disease.
Interestingly, empirical studies that have focused on one type of process eventually suggested the occurrence of others (e.g. Fauvergue and Hopper 2009 for the interaction of Allee effects and genetics; E. Vercken, F. Vincent, L. Mailleret, N. Ris, E. Tabone and X. Fauvergue, unpublished data, for the interaction of demographic stochasticity and genetics).
For two reasons, we have chosen not to conduct a decomposition with interactions of the demographic characteristics.
Our study, therefore, however, hopes to lay a foundation for more research into these complex interactions of socio-demographics and health issues.
However, escapes that occur at early life-history stages will also have a greater duration of demographic interactions (e.g., competition) with wild-origin fish (Hindar et al. 1991).
The etiology of elevated blood pressure is a complex process involving the interaction of genetics, demographics, comorbid disorders, and environmental influences.
Multilinear regression analysis was used to examine the possibility of interaction and confounding effects of demographic and diabetes-related variables with the HRQoL intervention and control group.
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