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Erratum to: Etman A, Kamphuis CBM, Prins R, Burdorf A, Pierik FH and Van Lenthe FJ. Characteristics of residential areas and transportational walking amongfrail and non-frail Dutch elderly: does the size of the area matter? Int J Health Geogr. 2014 Mar 4;13:7. doi: 10.1186/1476-072X-13-7. (Astrid Etman, 27 August 2015)

After publication of this paper, the authors have determined that the estimates for functional features were incorrect and that the log-transformed beta-coefficients were somewhat misinterpreted. For the corrected tables, please contact Astrid Etman ( The information provided in the text of the article is correct except for some sentences in the Abstract, Results section, and Discussion
section. In the Abstract, the first two sentences of the results paragraph should read like this: An increase in aesthetics (e.g. absence of litter and graffiti) within 800 and 1200 meter buffers, and an increase of one destination per buffer of 400 and 800 meters were associated with more transportational walking, up to a 2.83-fold... read full comment

Comment on: Etman et al. International Journal of Health Geographics, 13:7

Author correction to a citation (Matthew Shane Loop, 08 May 2015)

In the manuscript, we cited Auchincloss et al. (2012). We actually intended to cite Fritz C, Schuurman N, Robertson C, and Lear S. (2013). "A scoping review of spatial cluster analysis techniques for point-event data." Geospatial Health 7(2): 183-198. read full comment

Comment on: Loop et al. International Journal of Health Geographics, 14:4

Related slides (Maged Nabih Kamel Boulos, 28 October 2014)

Creating self-aware and smart healthy cities read full comment

Comment on: Kamel Boulos et al. International Journal of Health Geographics, 13:10

Vitamin D explains some of the findings (William B. Grant, 19 December 2011)

The epidemiology of sepsis in the United States led to an ecological study finding a role for solar UVB and vitamin D. Characteristics included in that study were racial disparities, seasonality, comorbid diseases, and geographical... read full comment

Comment on: Wang et al. International Journal of Health Geographics, 9:9

OpenNI user experience recommendations (Maged N. Kamel Boulos, 31 July 2011)

A comprehensive set of guidelines from OpenNI / PrimeSense that may help guiding future developments:

Kinect Paint offers a good example of a Kinect-optimised experience, with large interface elements and big buttons: read full comment

Comment on: Kamel Boulos et al. International Journal of Health Geographics, 10:45

Multiple Testing (Martin Kulldorff, 13 July 2010)

This is a really nice paper, and it is interesting to see how the different methods compare for this data set. The author provides a clear example of the important differences between global clustering tests and cluster detection tests.

For the hypothesis testing part of the kernel intensity function method, it seams that one statistical test is performed for each of the 40x40=1600 grid points (p8). If so, the method does not adjust for the multiple testing inherent in the many cluster locations evaluated. At the alpha=0.05 level, one would expect 0.05*1600=80 'statistically significant' grid points just by chance alone, which is slightly less than the 110 that were found according to figure 5. Whether the difference in 110 and 80 is statistically significant is hard to tell... read full comment

Comment on: Wheeler International Journal of Health Geographics, 6:13

Geographic variations in sepsis (Greg Martin, 11 May 2010)

The finding that sepsis mortality varies significantly across the U.S. is important and likely explains part of the healthcare disparities observed with this condition. A previous study using similar methodology reported similar findings regarding geographic variation, but also included analysis of incident cases and linked geographic and seasonal variations in sepsis incidence: see Danai P, et al. Critical Care Medicine 2007; 35: 410–415. read full comment

Comment on: Wang et al. International Journal of Health Geographics, 9:9

Space-time surveillance in the R package surveillance (Michael Höhle, 27 April 2010)

As the review covers software for space-time disease surveillance I would like to point out that the R package "surveillance" has a function "stcd" dedicated to space-time point referenced data not mentioned in the article.

It implements are space-time cluster detection method developed in Assuncao and Correa (2009), CSDA, 53(8):2817-2830 (see manual for details). The documentation & testing of the function reveals, that its implementation is still somewhat experimental which might be the reason for it missing in the comparison/mentioning, but I would like to make readers aware of this option.
Hopefully, the stability and documentation of stcd will improve with time.

Best regards,

Michael Höhle
-author of the R package... read full comment

Comment on: Robertson et al. International Journal of Health Geographics, 9:16

Solar ultraviolet-B doses/vitamin D and ethnic heritage play important roles in breast and prostate cancer incidence rate variations, respectively (William B. Grant, 21 April 2010)

The paper on spatial trends of breast and prostate cancer incidence rates in the United States [1] presents interesting data but overlooks a significant portion of the literature on ecological studies of cancer mortality rates in the United States related to solar ultraviolet-B (UVB) doses and other risk modifying factors. A set of such papers is provided here published prior to submission of this paper [2-5]. In addition, there have been more since that paper was submitted [6,7]. These and other ecological studies have been reviewed recently [8,9]. The role of vitamin D in reducing risk of cancer has also been reviewed recently [10,11]. Other factors included in the ecological studies of white Americans [3-7] were air pollution, alcohol consumption, dietary iron and zinc... read full comment

Comment on: Mandal et al. International Journal of Health Geographics, 8:53

ColorCode 3-D (Maged Nabih Kamel Boulos, 06 November 2009)

Another anaglyph-like system worth mentioning that promises good colour fidelity: read full comment

Comment on: Boulos et al. International Journal of Health Geographics, 8:59

Nothing's happening in Arizona (Joseph Hill, 18 December 2008)

I think I have the answer to R. C. Hunsaker's query (why so few heat deaths in Arizona). The SHELDUS database only records casualties from hazard events. Here in Arizona, we don't have heat events, we just have heat. (And occasional non-heat events.) That must be why SHELDUS records only 56 heat-event-related deaths in Arizona, compared to 951 in Illinois. <br><br>If the study looked at all hazard deaths, the picture would certainly be different. I don't know total numbers for Arizona, but I do know there have been at least 4,000 heat-related deaths of undocumented migrants along the southwest border since the 1990s. (Before changes in federal border policy, there were none -- speaking of contributing factors ...) But neither these deaths nor any other "uneventful"... read full comment

Comment on: Borden et al. International Journal of Health Geographics, 7:64

re: Heat deaths (K.C. Hunsaker, 17 December 2008)

If heat were the primary cause of death, then what explains the relatively few deaths in Arizona, for example? It has a large, vulnerable elderly population, and very high summer temperatures. Looking further, I would hazard a guess that poverty (inability to afford central air and thus nighttime cooling) and genetic predisposition to heart disease, both leading to heat deaths, would be the more likely ultimate culprits. read full comment

Comment on: Borden et al. International Journal of Health Geographics, 7:64

A valuable advance in the application of the spatial scan statistic (Francis Boscoe, 26 November 2008)

This is an important paper that engages important interpretive issues regarding the spatial scan statistic that have been generally neglected. Basically, the authors’ method involves distilling complex SaTScan output from multiple program iterations, allowing the maximum circle size to vary. A few years ago, I and three coauthors proposed a method for distilling summary information from within a single program iteration (see reference 15). The two approaches are complementary and could probably be unified.When identifying high (or low) rate clusters, the very last geographic unit in a cluster (that is, the one farthest from the center), by definition, must always have a high (or low) rate. This leads to heterogeneous clusters with a dumbbell or ring structure, where the geographic... read full comment

Comment on: Chen et al. International Journal of Health Geographics, 7:57

A relevant reference (Dale Zimmerman, 14 August 2008)

The authors did not cite, and therefore appear to be unaware of, an article (of which I am the first author) which overlaps heavily with their article. The article is "Quantifying the effects of mask metadata disclosure and multiple releases on the confidentiality of geographically masked health data," Geographical Analysis, vol. 40, pp. 52-76 (2008). In it we obtain results which are more general than those of the authors, and we obtain these results analytically rather than empirically. In particular we demonstrate what happens to confidentiality (as measured by the area of confidence regions of specified level for individuals' true locations, rather than distance from the average to the true location) as the number of anonymized released versions of the original data set increases.... read full comment

Comment on: Cassa et al. International Journal of Health Geographics, 7:45

correction to NIH grant support (Andrew Lawson, 02 May 2008)

The NIH grant support for this work was incorrect in the published paper. The correct grant that supported this work is NIH #RO1CA095979 from the National Cancer Institute. read full comment

Comment on: Puett et al. International Journal of Health Geographics, 4:8

Educating the Public (Dot Sulock, 23 March 2007)

Thanks for this valuable study! University faculty members need to teach undergraduates about issues related to WMD, such as those presented in this very educational article. There will be a summer institute at UGa July 9-12 for university faculty from any discipline to learn more about teaching nonproliferation and these authors will be speakers. The public needs to be educated in other ways also. This is a very serious matter. read full comment

Comment on: Bell et al. International Journal of Health Geographics, 6:5

Methods clarification (Eric Scott Sills, 06 August 2006)

This manuscript presents highly reliable data in a novel way, designed to facilitate congressional accountability (and funding) for a vital public health objective. This is a laudable goal and the authors are to be commended in this important effort.The authors indicate that many (n=426) congressional districts do not follow state OR county boundaries, and provide examples of congressional districts that are equivalent to state boundaries (because several states' low population only equate to one congressional representative). This warrants a minor point of clarification not presented in the article. All U.S. Congressional district delineations must repsect a state's boundary; in no case may a district include territory of more than one state. Accordingly, county level data may indeed beome... read full comment

Comment on: Hao et al. International Journal of Health Geographics, 5:28

Results of a similar analysis using New York State data (Francis Boscoe, 11 April 2005)

Research staff the New York State Cancer Registry recently completed a similar analysis as the one presented by Klassen, Kulldorff and Curriero. These results were originally presented in a poster session at the 2003 CDC Cancer Conference [1] and we briefly summarize them here.The goal of the study was to test whether socioeconomic factors might explain patterns of elevated incidence of prostate cancer in New York State as identified by the spatial scan statistic. Records were obtained for 60,556 cases of prostate cancer diagnosed among New York State men between 1995 and 1999. Adjusting for age and race alone, 24 areas or clusters of elevated incidence were identified, widely distributed throughout the state. These included some “nested” areas with varying levels of relative... read full comment

Comment on: Klassen et al. International Journal of Health Geographics, 4:1

Citation clarification (Francis Boscoe, 04 February 2005)

This article makes reference to a "forthcoming" article by Boscoe, Ward and Reynolds. In fact, this article has already been published. See International Journal of Health Geographics 2004, 3:28. read full comment

Comment on: Pickle et al. International Journal of Health Geographics, 4:3

Red-Green Color Blindness and Map Design (Francis Boscoe, 24 May 2004)

In addition to red and green, there are a variety of color pairs that tend to be difficult to distinguish by those with so-called 'red-green color blindness', such as orange and yellow. Fortunately, cartographers have thoroughly researched this problem and have designed a variety of color schemes that are discernable by nearly all with color-vision impairments (1). Examples of these color schemes are freely available at (2). The 'traffic-light' color scheme is fine so long as bluish-green is used in place of green.(1) Olson JM, Brewer CA. An evaluation of color selections to accommodate map users with color-vision impairments. Annals of the Association of American Geographers 1997; 87: 103-134.(2) Harrower M, Brewer CA. an online tool for selecting... read full comment

Comment on: Boulos et al. International Journal of Health Geographics, 3:10

Red - Green Colourblindness (Chris Ballentine, 10 May 2004)

I followed with interest the BBC web news about your paper and the distribution of dentists in the UK. I was disappointed on following the link to your 'traffic light' map that this uses a red-green extreme colour key. Like me, a significant % of your audience will be red-green colour blind. The use of the 'traffic light' analogy for a simple public message is great, but there are many other colour schemes that will not result in 10% of them seeing red (or is it green?)! read full comment

Comment on: Boulos et al. International Journal of Health Geographics, 3:10

Methods Comparisons (Martin Kulldorff, 28 February 2003)

In geographical disease surveillance it is sometimes of interest to study disease incidence and mortality in different but overlapping geographical areas. For example, if a geographical cluster is found in a particular location, it may be of interest to study the geographical distribution within that specific location. Jacquez’ and Greiling’s study of breast cancer incidence on Long Island is therefore an interesting follow-up to the state-wide analyses done by the New York State Health Department, which had found a cluster on Long Island. The comparison that the authors make between the spatial scan statistic and the local Moran method is not informative though. The former was applied to New York State as a whole and the latter only to Long Island. In order to compare methods... read full comment

Comment on: Jacquez et al. International Journal of Health Geographics, 2:3