Modeling the distribution of urolithiasis prevalence under projected climate change in Iran
Although studies support a positive correlation between temperature and stone risk, the precise relationship between these factors has not been elucidated. We modeled the current distribution of urolithiasis prevalence in Iran using 26 bioclimatic, climatic and topographic variables based on two mul...
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| Veröffentlicht in: | Urolithiasis 2015-08, Vol.43 (4), p.339-347 |
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| creator | Shajari, Ahmad Sanjerehei, Mohammad Mousaei |
| description | Although studies support a positive correlation between temperature and stone risk, the precise relationship between these factors has not been elucidated. We modeled the current distribution of urolithiasis prevalence in Iran using 26 bioclimatic, climatic and topographic variables based on two multivariate linear regression models in geographical information system. The impact of climate change on the stone prevalence was predicted under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES climate models by mid-century (2050). Extraterrestrial radiation and isothermality in the first regression model and annual mean temperature, precipitation seasonality and isothermality in the second model were the significant (
P
0.9) and determined a mean urolithiasis prevalence of 6 % (range of 1.5–10.8 %) in Iran. The climate change under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES models can, respectively, lead to an average increase of 5.7, 4.3 and 9 % in the urolithiasis prevalence based on the second regression model by 2050. The highest increase of the prevalence will occur in the west, northwest and southwest provinces of the country. Predicting the impact of climate change on climate-related diseases can be useful for effective preventive measures. |
| doi_str_mv | 10.1007/s00240-015-0784-2 |
| format | Article |
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P
< 0.01) predictors of urolithiasis prevalence. Both regression models provided good estimates of the stone prevalence (
R
2
> 0.9) and determined a mean urolithiasis prevalence of 6 % (range of 1.5–10.8 %) in Iran. The climate change under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES models can, respectively, lead to an average increase of 5.7, 4.3 and 9 % in the urolithiasis prevalence based on the second regression model by 2050. The highest increase of the prevalence will occur in the west, northwest and southwest provinces of the country. Predicting the impact of climate change on climate-related diseases can be useful for effective preventive measures.</description><identifier>ISSN: 2194-7228</identifier><identifier>EISSN: 2194-7236</identifier><identifier>DOI: 10.1007/s00240-015-0784-2</identifier><identifier>PMID: 25976637</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Climate Change ; Female ; Forecasting ; Geographic Information Systems ; Geography, Medical ; Humans ; Iran - epidemiology ; Linear Models ; Male ; Medical Biochemistry ; Medicine ; Medicine & Public Health ; Nephrology ; Original Paper ; Prevalence ; Urolithiasis - epidemiology ; Urology</subject><ispartof>Urolithiasis, 2015-08, Vol.43 (4), p.339-347</ispartof><rights>Springer-Verlag Berlin Heidelberg 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-706625d50d6a88b049aed5588d9ba2558bc82ccc5176965fa4f2771c42e6f9c73</citedby><cites>FETCH-LOGICAL-c442t-706625d50d6a88b049aed5588d9ba2558bc82ccc5176965fa4f2771c42e6f9c73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00240-015-0784-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00240-015-0784-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,778,782,27907,27908,41471,42540,51302</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25976637$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Shajari, Ahmad</creatorcontrib><creatorcontrib>Sanjerehei, Mohammad Mousaei</creatorcontrib><title>Modeling the distribution of urolithiasis prevalence under projected climate change in Iran</title><title>Urolithiasis</title><addtitle>Urolithiasis</addtitle><addtitle>Urolithiasis</addtitle><description>Although studies support a positive correlation between temperature and stone risk, the precise relationship between these factors has not been elucidated. We modeled the current distribution of urolithiasis prevalence in Iran using 26 bioclimatic, climatic and topographic variables based on two multivariate linear regression models in geographical information system. The impact of climate change on the stone prevalence was predicted under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES climate models by mid-century (2050). Extraterrestrial radiation and isothermality in the first regression model and annual mean temperature, precipitation seasonality and isothermality in the second model were the significant (
P
< 0.01) predictors of urolithiasis prevalence. Both regression models provided good estimates of the stone prevalence (
R
2
> 0.9) and determined a mean urolithiasis prevalence of 6 % (range of 1.5–10.8 %) in Iran. The climate change under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES models can, respectively, lead to an average increase of 5.7, 4.3 and 9 % in the urolithiasis prevalence based on the second regression model by 2050. The highest increase of the prevalence will occur in the west, northwest and southwest provinces of the country. Predicting the impact of climate change on climate-related diseases can be useful for effective preventive measures.</description><subject>Climate Change</subject><subject>Female</subject><subject>Forecasting</subject><subject>Geographic Information Systems</subject><subject>Geography, Medical</subject><subject>Humans</subject><subject>Iran - epidemiology</subject><subject>Linear Models</subject><subject>Male</subject><subject>Medical Biochemistry</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Nephrology</subject><subject>Original Paper</subject><subject>Prevalence</subject><subject>Urolithiasis - epidemiology</subject><subject>Urology</subject><issn>2194-7228</issn><issn>2194-7236</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp1kMtOAyEUQInRWFP7AW4MiRs3o0AZGJam8ZXUuNGVC8LAnZZmylSYMfHvpWk1xkQ23FzOfXAQOqPkihIirxMhjJOC0LIgsuIFO0AnjCpeSDYVhz8xq0ZoktKK5KOU4pQcoxErlRRiKk_Q21PnoPVhgfslYOdTH3099L4LuGvwELvW90tvkk94E-HDtBAs4CE4iDnRrcD24LBt_dr0gO3ShAVgH_BjNOEUHTWmTTDZ32P0enf7Mnso5s_3j7ObeWE5Z30hiRCsdCVxwlRVTbgy4MqyqpyqDctBbStmrS2pFEqUjeENk5JazkA0ysrpGF3u-uaF3gdIvV77ZKFtTYBuSJoKlT2QPCejF3_QVTfEkLfbUkIpyacqU3RH2dilFKHRm5g_GD81JXorX-_k6yxfb-VrlmvO952Heg3up-JbdQbYDkj5KVuKv0b_2_ULhumOnA</recordid><startdate>20150801</startdate><enddate>20150801</enddate><creator>Shajari, Ahmad</creator><creator>Sanjerehei, Mohammad Mousaei</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope></search><sort><creationdate>20150801</creationdate><title>Modeling the distribution of urolithiasis prevalence under projected climate change in Iran</title><author>Shajari, Ahmad ; Sanjerehei, Mohammad Mousaei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-706625d50d6a88b049aed5588d9ba2558bc82ccc5176965fa4f2771c42e6f9c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Climate Change</topic><topic>Female</topic><topic>Forecasting</topic><topic>Geographic Information Systems</topic><topic>Geography, Medical</topic><topic>Humans</topic><topic>Iran - epidemiology</topic><topic>Linear Models</topic><topic>Male</topic><topic>Medical Biochemistry</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Nephrology</topic><topic>Original Paper</topic><topic>Prevalence</topic><topic>Urolithiasis - epidemiology</topic><topic>Urology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shajari, Ahmad</creatorcontrib><creatorcontrib>Sanjerehei, Mohammad Mousaei</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>Urolithiasis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shajari, Ahmad</au><au>Sanjerehei, Mohammad Mousaei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling the distribution of urolithiasis prevalence under projected climate change in Iran</atitle><jtitle>Urolithiasis</jtitle><stitle>Urolithiasis</stitle><addtitle>Urolithiasis</addtitle><date>2015-08-01</date><risdate>2015</risdate><volume>43</volume><issue>4</issue><spage>339</spage><epage>347</epage><pages>339-347</pages><issn>2194-7228</issn><eissn>2194-7236</eissn><abstract>Although studies support a positive correlation between temperature and stone risk, the precise relationship between these factors has not been elucidated. We modeled the current distribution of urolithiasis prevalence in Iran using 26 bioclimatic, climatic and topographic variables based on two multivariate linear regression models in geographical information system. The impact of climate change on the stone prevalence was predicted under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES climate models by mid-century (2050). Extraterrestrial radiation and isothermality in the first regression model and annual mean temperature, precipitation seasonality and isothermality in the second model were the significant (
P
< 0.01) predictors of urolithiasis prevalence. Both regression models provided good estimates of the stone prevalence (
R
2
> 0.9) and determined a mean urolithiasis prevalence of 6 % (range of 1.5–10.8 %) in Iran. The climate change under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES models can, respectively, lead to an average increase of 5.7, 4.3 and 9 % in the urolithiasis prevalence based on the second regression model by 2050. The highest increase of the prevalence will occur in the west, northwest and southwest provinces of the country. Predicting the impact of climate change on climate-related diseases can be useful for effective preventive measures.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>25976637</pmid><doi>10.1007/s00240-015-0784-2</doi><tpages>9</tpages></addata></record> |
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| subjects | Climate Change Female Forecasting Geographic Information Systems Geography, Medical Humans Iran - epidemiology Linear Models Male Medical Biochemistry Medicine Medicine & Public Health Nephrology Original Paper Prevalence Urolithiasis - epidemiology Urology |
| title | Modeling the distribution of urolithiasis prevalence under projected climate change in Iran |
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