Literature DB >> 28302356

Correlates of county-level nonviral sexually transmitted infection hot spots in the US: application of hot spot analysis and spatial logistic regression.

Brian A Chang1, William S Pearson2, Kwame Owusu-Edusei3.   

Abstract

PURPOSE: We used a combination of hot spot analysis (HSA) and spatial regression to examine county-level hot spot correlates for the most commonly reported nonviral sexually transmitted infections (STIs) in the 48 contiguous states in the United States (US).
METHODS: We obtained reported county-level total case rates of chlamydia, gonorrhea, and primary and secondary (P&S) syphilis in all counties in the 48 contiguous states from national surveillance data and computed temporally smoothed rates using 2008-2012 data. Covariates were obtained from county-level multiyear (2008-2012) American Community Surveys from the US census. We conducted HSA to identify hot spot counties for all three STIs. We then applied spatial logistic regression with the spatial error model to determine the association between the identified hot spots and the covariates.
RESULTS: HSA indicated that ≥84% of hot spots for each STI were in the South. Spatial regression results indicated that, a 10-unit increase in the percentage of Black non-Hispanics was associated with ≈42% (P < 0.01) [≈22% (P < 0.01), for Hispanics] increase in the odds of being a hot spot county for chlamydia and gonorrhea, and ≈27% (P < 0.01) [≈11% (P < 0.01) for Hispanics] for P&amp;S syphilis. Compared with the other regions (West, Midwest, and Northeast), counties in the South were 6.5 (P < 0.01; chlamydia), 9.6 (P < 0.01; gonorrhea), and 4.7 (P < 0.01; P&amp;S syphilis) times more likely to be hot spots.
CONCLUSION: Our study provides important information on hot spot clusters of nonviral STIs in the entire United States, including associations between hot spot counties and sociodemographic factors. Published by Elsevier Inc.

Entities:  

Keywords:  Hot spots; Metro; Nonmetro; Sexually transmitted infections; Spatial logistic regression

Mesh:

Year:  2017        PMID: 28302356     DOI: 10.1016/j.annepidem.2017.02.004

Source DB:  PubMed          Journal:  Ann Epidemiol        ISSN: 1047-2797            Impact factor:   3.797


  6 in total

1.  The Spatial Association Between Federally Qualified Health Centers and County-Level Reported Sexually Transmitted Infections: A Spatial Regression Approach.

Authors:  Kwame Owusu-Edusei; Thomas L Gift; Jami S Leichliter; Raul A Romaguera
Journal:  Sex Transm Dis       Date:  2018-02       Impact factor: 2.830

2.  Identifying Infectious Diarrhea Hot spots and Associated Socioeconomic Factors in Anhui Province, China.

Authors:  Yanbin Hao; Na Zhang; Jiabing Wu; Bin Su; Lei Gong; Wanwan Ma; Sai Hou; Jin Zhang; Dandan Song; Wenmin Liao; Shuang Zhong; Lianping Yang; Cunrui Huang
Journal:  Am J Trop Med Hyg       Date:  2019-09       Impact factor: 2.345

3.  Assessing inequities underlying racial disparities of COVID-19 mortality in Louisiana parishes.

Authors:  Guangxiao Hu; Nora Hamovit; Kristen Croft; Jennifer D Roberts; Deb Niemeier
Journal:  Proc Natl Acad Sci U S A       Date:  2022-06-27       Impact factor: 12.779

4.  Mapping hot spots of breast cancer mortality in the United States: place matters for Blacks and Hispanics.

Authors:  Justin Xavier Moore; Kendra J Royston; Marvin E Langston; Russell Griffin; Bertha Hidalgo; Henry E Wang; Graham Colditz; Tomi Akinyemiju
Journal:  Cancer Causes Control       Date:  2018-06-19       Impact factor: 2.506

5.  County-Level Social Capital and Bacterial Sexually Transmitted Infections in the United States.

Authors:  Kwame Owusu-Edusei; Bryttany McClendon-Weary; Lara Bull; Thomas L Gift; Sevgi O Aral
Journal:  Sex Transm Dis       Date:  2020-03       Impact factor: 3.868

6.  Maternal HIV and syphilis are not syndemic in Brazil: Hot spot analysis of the two epidemics.

Authors:  Mary Catherine Cambou; Eduardo Saad; Kaitlyn McBride; Trevon Fuller; Emma Swayze; Karin Nielsen-Saines
Journal:  PLoS One       Date:  2021-08-03       Impact factor: 3.240

  6 in total

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