Incorporating geography into a new generalized theoretical and statistical framework addressing the modifiable areal unit problem

Background

All analyses of spatially aggregated data are vulnerable to the modifiable areal unit problem (MAUP), which describes the sensitivity of analytical results to the arbitrary choice of spatial aggregation unit at which data are measured. The MAUP is a serious problem endemic to analyses of spatially aggregated data in all scientific disciplines. However, the impact of the MAUP is rarely considered, perhaps partly because it is still widely considered to be unsolvable.

Results

It was originally understood that a solution to the MAUP should constitute a comprehensive statistical framework describing the regularities in estimates of association observed at different combinations of spatial scale and zonation. Additionally, it has been debated how such a solution should incorporate the geographical characteristics of areal units (e.g. shape, size, and configuration), and in particular whether this can be achieved in a purely mathematical framework (i.e. independent of areal units). We argue that the consideration of areal units must form part of a solution to the MAUP, since the MAUP only manifests in their presence. Thus, we present a theoretical and statistical framework that incorporates the characteristics of areal units by combining estimates obtained from different scales and zonations. We show that associations estimated at scales larger than a minimal geographical unit of analysis are systematically biased from a true minimal-level effect, with different zonations generating uniquely biased estimates. Therefore, it is fundamentally erroneous to infer conclusions based on data that are spatially aggregated beyond the minimal level. Instead, researchers should measure and display information, estimate effects, and infer conclusions at the smallest possible meaningful geographical scale. The framework we develop facilitates this.

Conclusions

The proposed framework represents a new minimum standard in the estimation of associations using spatially aggregated data, and a reference point against which previous findings and misconceptions related to the MAUP can be understood.

Electronic supplementary material

The online version of this article (10.1186/s12942-019-0170-3) contains supplementary material, which is available to authorized users.

Patient characteristics driving clinical utility in psychiatric pharmacogenetics: a reanalysis from the AB-GEN multicentric trial

Clinical utility of commercial multi-gene pharmacogenetic tests in depression is starting to be studied with some promising results on efficacy and tolerability. Among the next steps is the definition of the patient profile that is most likely to benefit from testing. Here we present a reanalysis of data from the AB-GEN randomized clinical trial showing that clinical utility of pharmacogenetic testing can be markedly influenced by patient characteristics such as age, baseline severity and duration of current depressive episode.Trial registration ClinicalTrials.gov NCT02529462.

Possible suppression of fetal erythropoiesis by the Kell blood group antibody anti-Kp(a)

Antibodies to antigens in the Kell blood group system are usually immunoglobulin G, and, notoriously, anti-K, anti-k, and anti-Kp(a) can cause severe hemolytic transfusion reactions, as well as severe hemolytic disease of the fetus and newborn (HDFN). It has been shown that the titer of anti-K does not correlate with the severity of HDFN because, in addition to immune destruction of red blood cells (RBCs), anti-K causes suppression of erythropoiesis in the fetus, which can result in severe anemia. We report a case involving anti-Kp(a) in which one twin was anemic and the other was not. Standard hemagglutination and polymerase chain reaction (PCR)-based tests were used. At delivery, anti-Kp(a) was identified in serum from the mother and twin A, and in the eluate prepared from the baby’s RBCs. PCR-based assays showed twin A (boy) was KEL*841T/C (KEL*03/KEL*04), which is predicted to encode Kp(a+b+). Twin B (girl) was KEL*841C/C (KEL*04/KEL*04), which is predicted to encode Kp(a–b+). We describe the first reported case of probable suppression of erythropoiesis attributable to anti-Kp(a). One twin born to a woman whose serum contained anti-Kp(a) experienced HDFN while the other did not. Based on DNA analysis, the predicted blood type of the affected twin was Kp(a+b+) and that of the unaffected twin was Kp(a–b+). The laboratory findings and clinical course of the affected twin were consistent with suppression of erythropoiesis in addition to immune RBC destruction.