Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017
Background Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. St...
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description | Background Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation. Methodology/Principal findings Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density ([beta] = 2.844, P = 0.006), the number of health institutions per 1,000 residents ([beta] = -0.095, P = 0.007), and the net migration rate ([beta] = -0.219, P = 0.002). Conclusions/Significance Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth. |
doi_str_mv | 10.1371/journal.pntd.0009621 |
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However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation. Methodology/Principal findings Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density ([beta] = 2.844, P = 0.006), the number of health institutions per 1,000 residents ([beta] = -0.095, P = 0.007), and the net migration rate ([beta] = -0.219, P = 0.002). Conclusions/Significance Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth.</description><identifier>ISSN: 1935-2735</identifier><identifier>ISSN: 1935-2727</identifier><identifier>EISSN: 1935-2735</identifier><identifier>DOI: 10.1371/journal.pntd.0009621</identifier><identifier>PMID: 34383788</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Autocorrelation ; Biology and Life Sciences ; Data models ; Demographic aspects ; Disease prevention ; Distribution ; Earth Sciences ; Economic development ; Economic growth ; Economics ; GDP ; Gross Domestic Product ; Hypotheses ; Infectious diseases ; Information systems ; Lagrange multiplier ; Medicine and Health Sciences ; Per capita ; Population density ; Risk factors ; Sexually transmitted diseases ; Social factors ; Social Sciences ; Sociodemographics ; Socioeconomic data ; Socioeconomic factors ; Socioeconomics ; Spacetime ; Spatial data ; Spatial distribution ; STD ; Syphilis ; Temporal distribution ; Tertiary ; Tropical diseases ; Variables</subject><ispartof>PLoS neglected tropical diseases, 2021-08, Vol.15 (8), p.e0009621-e0009621</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Tang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Tang et al 2021 Tang et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c601t-362e4765110aa034325d9c0467dabd72a0f9e6129dc060c546e45629cc6ff1613</citedby><cites>FETCH-LOGICAL-c601t-362e4765110aa034325d9c0467dabd72a0f9e6129dc060c546e45629cc6ff1613</cites><orcidid>0000-0001-8000-9969 ; 0000-0003-3292-274X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407558/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407558/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids></links><search><contributor>Taylor, Graham P.</contributor><creatorcontrib>Tang, Shangqing</creatorcontrib><creatorcontrib>Shi, Lishuo</creatorcontrib><creatorcontrib>Chen, Wen</creatorcontrib><creatorcontrib>Zhao, Peizhen</creatorcontrib><creatorcontrib>Zheng, Heping</creatorcontrib><creatorcontrib>Yang, Bin</creatorcontrib><creatorcontrib>Wang, Cheng</creatorcontrib><creatorcontrib>Ling, Li</creatorcontrib><title>Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017</title><title>PLoS neglected tropical diseases</title><description>Background Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation. Methodology/Principal findings Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density ([beta] = 2.844, P = 0.006), the number of health institutions per 1,000 residents ([beta] = -0.095, P = 0.007), and the net migration rate ([beta] = -0.219, P = 0.002). Conclusions/Significance Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth.</description><subject>Autocorrelation</subject><subject>Biology and Life Sciences</subject><subject>Data models</subject><subject>Demographic aspects</subject><subject>Disease prevention</subject><subject>Distribution</subject><subject>Earth Sciences</subject><subject>Economic development</subject><subject>Economic growth</subject><subject>Economics</subject><subject>GDP</subject><subject>Gross Domestic Product</subject><subject>Hypotheses</subject><subject>Infectious diseases</subject><subject>Information systems</subject><subject>Lagrange multiplier</subject><subject>Medicine and Health Sciences</subject><subject>Per capita</subject><subject>Population density</subject><subject>Risk factors</subject><subject>Sexually transmitted diseases</subject><subject>Social factors</subject><subject>Social Sciences</subject><subject>Sociodemographics</subject><subject>Socioeconomic data</subject><subject>Socioeconomic factors</subject><subject>Socioeconomics</subject><subject>Spacetime</subject><subject>Spatial data</subject><subject>Spatial distribution</subject><subject>STD</subject><subject>Syphilis</subject><subject>Temporal distribution</subject><subject>Tertiary</subject><subject>Tropical 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distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017</title><author>Tang, Shangqing ; Shi, Lishuo ; Chen, Wen ; Zhao, Peizhen ; Zheng, Heping ; Yang, Bin ; Wang, Cheng ; Ling, Li</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c601t-362e4765110aa034325d9c0467dabd72a0f9e6129dc060c546e45629cc6ff1613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Autocorrelation</topic><topic>Biology and Life Sciences</topic><topic>Data models</topic><topic>Demographic aspects</topic><topic>Disease prevention</topic><topic>Distribution</topic><topic>Earth Sciences</topic><topic>Economic development</topic><topic>Economic growth</topic><topic>Economics</topic><topic>GDP</topic><topic>Gross Domestic Product</topic><topic>Hypotheses</topic><topic>Infectious diseases</topic><topic>Information 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Wen</au><au>Zhao, Peizhen</au><au>Zheng, Heping</au><au>Yang, Bin</au><au>Wang, Cheng</au><au>Ling, Li</au><au>Taylor, Graham P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017</atitle><jtitle>PLoS neglected tropical diseases</jtitle><date>2021-08-01</date><risdate>2021</risdate><volume>15</volume><issue>8</issue><spage>e0009621</spage><epage>e0009621</epage><pages>e0009621-e0009621</pages><issn>1935-2735</issn><issn>1935-2727</issn><eissn>1935-2735</eissn><abstract>Background Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation. Methodology/Principal findings Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density ([beta] = 2.844, P = 0.006), the number of health institutions per 1,000 residents ([beta] = -0.095, P = 0.007), and the net migration rate ([beta] = -0.219, P = 0.002). Conclusions/Significance Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>34383788</pmid><doi>10.1371/journal.pntd.0009621</doi><orcidid>https://orcid.org/0000-0001-8000-9969</orcidid><orcidid>https://orcid.org/0000-0003-3292-274X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Autocorrelation Biology and Life Sciences Data models Demographic aspects Disease prevention Distribution Earth Sciences Economic development Economic growth Economics GDP Gross Domestic Product Hypotheses Infectious diseases Information systems Lagrange multiplier Medicine and Health Sciences Per capita Population density Risk factors Sexually transmitted diseases Social factors Social Sciences Sociodemographics Socioeconomic data Socioeconomic factors Socioeconomics Spacetime Spatial data Spatial distribution STD Syphilis Temporal distribution Tertiary Tropical diseases Variables |
title | Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017 |
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