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Epidemiology for public health practice:The application of spatial epidemiology

2022-07-22 02:00:52LongjianLiuGarvitaNagarOusmaneDiarraStephanieShosanyaGeetaSharmaDavidAfesumehAkshathaKrishna
World Journal of Diabetes 2022年7期

TO THE EDlTOR

Dear Editor, we read with great interest the recently published review paper, entitled “Spatial epidemiology of diabetes:Methods and Insights” by Cuadros

[1], in

2021. The investigators reviewed spatial methods used to understand the spatial structure of the disease and identify the potential geographical drivers of the spatial distribution of diabetes mellitus. Their report serves as a good review on the concepts and methods of spatial epidemiology. In this letter we aimed to briefly address few examples of the historical public health practice in the United Kingdom and the application of spatial epidemiology in the recent decades in the United States, and to address the potential limitations when applying this technique in research and in public health practice.

Then the melody of the psalm burst forth,like the sound of the waters, and Jurgen saw that his foster parentsfrom the Hunsby dunes were there, also old merchant Bronne with hiswife and their daughter Clara, who gave him her hand

The method used in “

” could be tracked back to more than 150 years ago, for example, the renowned study of cholera epidemic in London, United Kingdom In 1854. John Snow, a physician, used mapping approach to trace the source of the Broad Street cholera outbreak (or Golden Square outbreak) in central London[1]. In the United States, an example is that a “stroke belt” or “stroke alley” was identified in early 1980s using spatial analysis approach and to define a 11-state region, where the states had age-adjusted stroke mortality rates more than 10% above the national average[2,3]. In 2011, a study by Barker

[4] identified a geographically coherent region of the United States, where the prevalence of diagnosed diabetes mellitus is especially high. This area is also known as the “diabetes belt”. The “diabetes belt” consisted of 644 counties in 15 mostly southern states. A further analysis indicated that the prevalence of obesity and sedentary lifestyle (two modifiable risk factors for diabetes) was significantly higher in the diabetes belt than in the rest of the United States[5].

However, it should be noted that similar to the other analytical techniques, spatial epidemiology also has potential limitations[5,6]. First, the basic analysis approach of spatial epidemiology is based on ecological analysis design. Exposures and responses are measured only for aggregates rath than individuals. Therefore, findings from the analysis are subject to have ecological fallacy[5-8]. For example, results from an ecological analysis suggested that there was a significant correlation between increased state-level stroke prevalence and state-level stroke mortality. However, of the study states, several states that had higher state-level stroke prevalence rates did not have high stroke mortality rates, which led to a relatively weaker association than results from analyses using individual-level data[2]. Second, most spatial epidemiological studies apply age-adjusted rates to examine and map the variations in disease rates across geographic areas, such as neighborhoods, communities, districts, counties, states and countries at a global level. However, the calculation of age-adjusted rate is based on the proportion of age distributions across the geographics defined areas. If the proportions of age distributions vary widely between the comparison areas or regions, a simple weighted age-adjusted rate may be meaningless and may lead to an inappropriate comparison[5]. Third, data from disease registries, such as a small regional cancer registry, disease surveillance, or data from hospital electronic health records in a specific township is susceptible to information bias as a result of limited sources. Fourth, data protection and confidentiality should be kept in mind, specifically if mapping disease across small areas, such as small neighborhoods. It is likely that the number of persons at risk (

, denominators) and the number of cases (

, numerators) are too small to be used[8,9]. In the situation, a combined sample should be considered[10]. Lastly, confounding effects on the study association between exposures and outcomes should be considered and controlled appropriately in spatial epidemiological study.

These drums were put there so that the suitors of the princess might announce their arrival by beating on them, after which some one would come and take them to the king s presence

Here we are reminded again of the song about The King ofEngland s Son, for in it mention is made of the custom prevalent atthe time, when knights and squires plundered those who had beensaved from shipwreck. The ship had stranded some distance south ofNissum Bay, and the cruel, inhuman days, when, as we have just said,the inhabitants of Jutland treated the shipwrecked people so crudelywere past, long ago. Affectionate sympathy and self-sacrifice forthe unfortunate existed then, just as it does in our own time inmany a bright example. The dying mother and the unfortunate childwould have found kindness and help wherever they had been cast bythe winds, but nowhere would it have been more sincere than in thecottage of the poor fisherman s wife, who had stood, only the daybefore, beside her child s grave, who would have been five years oldthat day if God had spared it to her.

Longjian Liu 0000-0001-7956-7111; Garvita Nagar 0000-0002-3572-9024; Ousmane Diarra 0000-0002-0643-2598; Stephanie Shosanya 0000-0002-9089-8592; Geeta Sharma 0000-0003-2856-5663; David Afesumeh 0000-0002-5519-5939; Akshatha Krishna 0000-0002-6063-0747.

This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BYNC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is noncommercial. See:https://creativecommons.org/Licenses/by-nc/4.0/

In conclusion, the application of spatial epidemiology plays a pivotal role in advancing our understanding of the geographic distributions of specific disease and disease risk factors, which significantly contributes to disease control and prevention at population and community levels. However, the limitations of the study design and analysis approaches should be kept in mind when applying it in research and in public health practice.

The authors have no conflict of interest to disclose.

Liu L drafted the Letter; Nagar G, Diarra O, Shosanya S, Sharma G, Afesumeh D, and Krishna A critically reviewed the Letter.

United States

Chang KL

She didn t know if Eric felt the same until they left work together one evening and took a stroll out on a pier above the Pacific Ocean. He signed to her that he was in love and wanted to marry. Marianne s heart danced with joy.

A

Chang KL

1 Cuadros DF, Li J, Musuka G, Awad SF. Spatial epidemiology of diabetes:Methods and insights.

2021; 12:1042-1056 [PMID:34326953 DOI:10.4239/wjd.v12.i7.1042]

2 Bingham P, Verlander NQ, Cheal MJ. John Snow, William Farr and the 1849 outbreak of cholera that affected London:a reworking of the data highlights the importance of the water supply.

2004; 118:387-394 [PMID:15313591 DOI:10.1016/j.puhe.2004.05.007]

3 Liao Y, Greenlund KJ, Croft JB, Keenan NL, Giles WH. Factors explaining excess stroke prevalence in the US Stroke Belt.

2009; 40:3336-3341 [PMID:19679841 DOI:10.1161/STROKEAHA.109.561688]

4 Barker LE, Kirtland KA, Gregg EW, Geiss LS, Thompson TJ. Geographic distribution of diagnosed diabetes in the U.S.:a diabetes belt.

2011; 40:434-439 [PMID:21406277 DOI:10.1016/j.amepre.2010.12.019]

5 Lanska DJ, Kuller LH. The geography of stroke mortality in the United States and the concept of a stroke belt.

1995; 26:1145-1149 [PMID:7604404 DOI:10.1161/01.str.26.7.1145]

6 Elliott P, Wartenberg D. Spatial epidemiology:current approaches and future challenges.

2004; 112:998-1006 [PMID:15198920 DOI:10.1289/ehp.6735]

7 Beale L, Abellan JJ, Hodgson S, Jarup L. Methodologic issues and approaches to spatial epidemiology.

2008; 116:1105-1110 [PMID:18709139 DOI:10.1289/ehp.10816]

8 Szklo M. Epidemiology:Beyond the Basics.

2001; 153:821-822 [DOI:10.1093/aje/153.8.821]

9 Liu L, Wang F, Gracely EJ, Moore K, Melly S, Zhang F, Sato PY, Eisen HJ. Burden of Uncontrolled Hyperglycemia and Its Association with Patients Characteristics and Socioeconomic Status in Philadelphia, USA.

2020; 4:525-532 [PMID:34095699 DOI:10.1089/heq.2020.0076]

10 Liu L, Nú?ez AE. Multilevel and urban health modeling of risk factors for diabetes mellitus:a new insight into public health and preventive medicine.

2014; 2014:246049 [PMID:25431678 DOI:10.1155/2014/246049]

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